Integrated Planning and Operation Dispatching of Source–Grid–Load–Storage in a New Power System: A Coupled Socio–Cyber–Physical Perspective

Abstract

The coupling between modern electric power physical and cyber systems is deepening. An increasing number of users are gradually participating in power operation and control, engaging in bidirectional interactions with the grid. The evolving new power system is transforming into a highly intelligent socio–cyber–physical system, featuring increasingly intricate and expansive architectures. Demands for stable system operation are becoming more specific and rigorous. The new power system confronts significant challenges in areas like planning, dispatching, and operational maintenance. Hence, this paper aims to comprehensively explore potential synergies among various power system components from multiple viewpoints. It analyzes numerous core elements and key technologies to fully unlock the efficiency of this coupling. Our objective is to establish a solid theoretical foundation and practical strategies for the precise implementation of integrated planning and operation dispatching of source–grid–load–storage systems. Based on this, the paper first delves into the theoretical concepts of source, grid, load, and storage, comprehensively exploring new developments and emerging changes in each domain within the new power system context. Secondly, it summarizes pivotal technologies such as data acquisition, collaborative planning, and security measures, while presenting reasonable prospects for their future advancement. Finally, the paper extensively discusses the immense value and potential applications of the integrated planning and operation dispatching concept in source–grid–load–storage systems. This includes its assistance in regards to large-scale engineering projects such as extreme disaster management, facilitating green energy development in desertification regions, and promoting the construction of zero-carbon parks.

1. Introduction

There is a dual pursuit regarding the provision of electrical power: high-efficiency and convenient service quality, coupled with an increasing emphasis on harmonious coexistence with nature. However, the traditional power system not only fails to meet the growing demand for intelligent services, but also struggles to effectively implement the concept of green environmental protection. Given this context, the emergence of a new power system is justified.

The new power system boasts a broader range of energy supply forms and incorporates highly intelligent and automated operational features compared to those of traditional power system. Nevertheless, its architectural complexity has increased [1], notably with the integration of storage into the traditional three-element structure of source–grid–load, thereby shaping the current framework of source–grid–load–storage [2,3].

Moreover, the human–social aspect gains increasing prominence in the new power system [4,5,6,7]. With the continuous advancement of energy storage technology and the growth of the energy trading market [8,9], the traditional users are transformed from pure electricity consumers into active participants who can sell electricity to the grid, thus becoming prosumers [10,11,12]. By proactively strategizing their electricity consumption, sales, and energy storage, prosumers facilitate bidirectional energy flow. Advanced information communication technology significantly enhances communication between users and power system. Data regarding users’ daily electricity usage habits and demand feedback can be collected via the electric power information network and transmitted to the control center, enabling large-scale data analysis to aid management personnel in formulating suitable electricity pricing implementation schemes and operational dispatching strategies. Hence, in the daily planning and operation dispatching of the new power system, the role of humans is indispensable. Despite individual limitations, collectively, even unintentional electricity usage behaviors can impact the system’s normal operation. Conversely, if the vast majority of users can be guided to reasonably adjust their electricity consumption behaviors, human groups, such as residential communities, can evolve into flexible resources with significant regulatory potential. This is crucial for aiding in the operation management of the power system and for achieving peak shaving and valley filling.

The increasing penetration of renewable energy sources, like wind power and photovoltaics, intensifies the volatility and uncertainty of power generation [13,14,15,16], resulting in the significant challenge of an inadequate supply of flexible resources and a power supply–demand imbalance within the power system [17,18]. Hence, improving the flexibility of the new power system is essential for addressing these current challenges [19,20,21,22,23]. However, flexible resources, including thermal power units and energy storage devices, are not only distributed discretely, but also operate independently, posing challenges in achieving efficient and unified deployment and control. Therefore, to fully harness the flexible regulation potential of the new power system, it is essential to utilize advanced sensing devices and information communication technologies to break down the barriers regarding the source, grid, load, and storage elements [24], efficiently integrate diverse flexible resources, and achieve scalable regulation and management. Furthermore, the significance and influence of human involvement should be underscored, involving a thorough exploration of the potential for flexibilities on the user side, as well as the active promotion of widespread user engagement in system operation and dispatch [25]. Ultimately, a comprehensive, multi-level mechanism for collaborative planning and operation dispatching of the new power system, integrating source, grid, load, and storage, should be established to ensure the secure and efficient operation of the power system.

Although numerous review and survey papers have explored the source–grid–load–storage aspects of new power systems, this paper distinguishes itself with several unique features. Firstly, it employs a comprehensive socio–cyber–physical perspective to explore the integrated planning and operation of source–grid–load–storage in new power systems. This approach emphasizes the impact of social factors, focusing on the interactions between users and the power system. It also incorporates the coupled characteristics of the informational and physical components for a comprehensive analysis. The objective is to offer a comprehensive, multidimensional perspective to better understand the complex interrelations among the source, grid, load, and storage components in new power systems. Secondly, in addition to optimizing the internal operations of the power system, this paper thoroughly examines the seamless integration and expansion of multi-energy elements, extending the exploration background from power systems to the integrated energy system. By exploring specific applications for multi-energy complementarity and comprehensive utilization, it provides a feasible theoretical foundation for the integrated and coordinated operation of the power system with other energy systems. Finally, particular emphasis is placed on integrating theory with practice. This paper actively discusses the implementation methods and application value of the theoretical models for integrated planning and operational dispatching of source–grid–load–storage systems in various large-scale engineering projects, providing reference and inspiration for future research and applications.

The tasks to be discussed in this review paper include the following:

• Comprehensive exploration of theoretical concepts and frameworks: a comprehensive study of the theoretical foundations related to source, grid, load, and storage, aiming to establish a solid conceptual framework. Subsequently, an in-depth analysis of their interactions and coupled relationships within the new power system will be conducted.
• Introduction and analysis of key technologies: a detailed elucidation of the key technologies for achieving integrated planning and operation dispatching in the new power system.
• Technological limitations and research prospects: a critical evaluation of the inherent limitations and shortcomings of the aforementioned technologies and provision of a reasonable outlook regarding the future research and development prospects for these technologies.
• Analysis of engineering application value: through rigorous analysis and empirical evidence, we will explore and confirm the practical value and potential of integrated planning and operation dispatching in large-scale engineering projects.

2. Methodology

In this paper, we conducted a comprehensive literature search using multiple reputable indexed databases, including Web of Science, CNKI, ScienceDirect, and IEEE Xplore. This approach ensures comprehensive coverage of significant research achievements in the field of power systems and integrated energy systems, thereby facilitating access to a wealth of high-quality academic resources.

In accordance with the logical structure planned for this paper, we utilized various terms and search queries during the literature retrieval process. These included, but were not limited to, terms like power system, source–grid–load–storage, power cyber–physical system, social system, collaborative planning, optimal dispatching, extreme disaster response, smart energy ecosystem, zero-carbon development, and integrated energy system. By strategically combining and utilizing these search terms, we effectively filtered out irrelevant documents from the vast academic databases. This not only narrowed down our search scope, but also allowed us to accurately identify and select the most pertinent academic literature related to our research topic, significantly enhancing search efficiency and meeting the specific research needs of this paper.

During the literature review, we employed rigorous selection criteria to ensure the quality, relevance, and applicability of the chosen literature. Firstly, we restricted our search to the past decade, focusing on the last three years’ scientific achievements, to reflect the latest developments and trends in the field. Secondly, to assess relevance, we conducted an initial screening based on titles and abstracts, focusing on whether they directly addressed the core of integrated planning and operation dispatching discussed. Furthermore, we analyzed the literature’s keywords, matching them with our core terms to determine whether they had high relevance to our research topic. Lastly, we performed a content review, emphasizing theories, methods, technologies, or practical applications directly linked to our research. This meticulous process enabled us to pinpoint the most relevant literature, avoiding unnecessary reading and analysis, and conserving time and resources. It also ensured the selection of highly pertinent literature, bolstering the theoretical foundation and empirical support for our review study.

To provide a more intuitive visualization of the research trends and scientific progression related to our paper’s theme, we gathered relevant literature data from Web of Science, spanning from 2014 to 2023, regarding certain research topics covered in this paper. By organizing this data, we constructed publication trend charts for the research topics, as illustrated in Figure 1. This chart visually represents the yearly distribution of relevant research literature in our field of study.

From Figure 1, it is evident that the research trends of the topics selected in this paper have exhibited an overall upward trajectory over the past decade. This upward shift may be attributed to multiple factors. Primarily, technological advancements stand out as a significant catalyst. The continual evolution of new technologies, notably the swift progress and extensive application of renewable energy, the smart grid, and energy storage technologies, has propelled relevant research regarding the coordinated planning and dispatching of emerging power systems. Furthermore, policy support has been pivotal. In recent years, numerous countries have implemented policies and regulations to foster the development of renewable energy and integrated energy systems. These include subsidies and tax incentives for renewable energy, carbon emission trading schemes, and investment promotions for smart grid infrastructure. Such policies not only bolster related research, but also facilitate the practical application and industrialization of scientific inquiries. Lastly, evolving social demands play a notable role. With the rising emphasis on sustainable development and environmental conservation in modern society, there is a growing momentum for research and implementation of green engineering projects, such as zero-carbon parks. Additionally, as public environmental consciousness escalates and the aspiration for a green lifestyle intensifies, energy companies are proactively investing in research and development for efficient, low-carbon energy solutions to align with society’s green energy aspirations.

3. Source–Grid–Load–Storage

Fossil fuels traditionally serve as the primary power source in the power system, offering stable and controllable output characteristics. During this fossil fuel period, energy storage technology was in its nascent stage, and the associated equipment had not been extensively deployed, consequently hindering the establishment of a scalable energy storage system. The components of source–grid–load form the three essential elements of traditional power systems [26], which are specifically evident in the processes of power generation, transmission, transformation, distribution, and utilization, as illustrated in Figure 2.

The power system demonstrates the “double-high” characteristics [27,28,29] due to the high penetration of renewable energy sources and a high proportion of electronic power devices. However, the flexibility of the power system is diminishing gradually [3]. Consequently, there is a growing emphasis on energy storage technologies capable of enhancing system flexibility, leading to the development of increasingly sophisticated energy storage systems. A novel architecture for power systems, termed the “source–grid–load–storage” framework, is gradually emerging, as illustrated in Figure 3.

3.1. The Source–Grid–Load–Storage Architecture of the New Power System

The continuous advancement and rapid progress of science, technology, and society have led to significant innovations in theoretical concepts and technological methods within the electricity sector. In the power system industry, the focus is on the changes and advancements in source, grid, load, and storage [30], as illustrated in Figure 4. Going forward, we will begin with fundamental concepts and proceed to explore in-depth the application functionalities and value manifestation of the aforementioned aspects.

The term “source” denotes the initial point of power supply and the origin of energy flow within the power system. This process involves the conversion of various forms of energy, including fossil fuels, solar energy, and wind energy, into electricity, which is subsequently transmitted into the grid to fulfill the electricity demands of society. Currently, the power generation sector is transitioning towards diverse and cleaner production methods [31,32]. However, the substantial rise in the proportion of new energy sources has led to increased generation fluctuations on the source side, significantly impacting the stable operation of the system [33]. Hence, effective resource planning and configuration are vital for achieving coordinated operation among multiple energy sources, ensuring the security and stability of the power system [34,35].

The term “grid” denotes the electricity transmission and distribution network, comprising substations, transmission lines, and other components. It serves to tightly interconnect the power source side with user loads, forming a complex network of “power bridges” to guarantee stable electricity supply. Due to the continuous enhancement of digitalization and intelligence within the power system [36,37,38], the grid has gained a high level of adaptability and adjustability. The development and implementation of ultra-high voltage transmission technology enables smart grids to achieve cross-regional, long-distance integration and optimal utilization of various power generation sources [39,40]. This facilitates more efficient and cost-effective electricity transmission, satisfying the energy demands of large regions.

The term “load” denotes the electricity consumption segment within the power system, covering industrial, commercial, and residential usage, which includes a variety of electrical appliances and facilities. In the traditional power system framework, individuals function solely as electricity consumers, passively accepting the consumption pattern of one-way flow of energy. However, with the continuous development and deployment of energy storage technology, demand response mechanisms, and electric vehicles [41,42], among other technological advancements, the energy flow between the power source and the load is progressively transitioning from unidirectional transmission to bidirectional interaction. It is anticipated that in the future, prosumers who actively manage their consumption, production, and storage of energy will become commonplace [43,44]. During this period, user groups can serve as flexible resources actively employed in the operation and regulation of the power system, aiding in achieving peak shaving and valley filling.

The term “storage” denotes energy storage, encompassing various technologies and devices, including electrochemical energy storage, pumped storage, and electromagnetic storage [45,46]. By flexibly utilizing energy storage technology, excess electricity can be stored and discharged during peak demand periods to fulfill electricity demands. This is crucial for maintaining the balance between electricity supply and demand, while enhancing the flexibility and reliability of power system operation. Thus, centralized management and coordinated allocation are essential for the dispersed energy storage resources in the power system to establish a shared energy storage management platform. This ensures that energy storage systems can promptly respond to regulatory directives, thereby ensuring the stable operation of the power system.

3.2. The Coupling Relationship among Source, Grid, Load, and Storage

With the ongoing development and construction of new power systems, the coupling relationship among the source, grid, load, and storage will become increasingly interconnected. Today, electricity no longer flows unidirectionally from the source to the load but can flow bidirectionally between them. The power operation mode is gradually transitioning towards “source–load interaction” [30,47], where changes in user-side status can also influence source-side operation. For example, by conducting a thorough analysis of user demand feedback, a deeper understanding of public expectations can be obtained, which assists in optimizing operational decisions, consequently affecting the output of source-side units [48]. Furthermore, the participation of numerous users in electricity market transactions [49,50] indirectly influences the system’s capacity planning. The coupling relationship between the power source and load is strengthened by the operational mode of source–load interaction, thereby enhancing the efficient utilization of energy.

During the developmental planning of the new power system, the grid is evolving from a simple transmission channel to an intelligent control hub. Advanced information and communication technologies, together with digital automation devices, enable precise control of electricity flow. For instance, real-time monitoring and data analysis allow for prompt detection of abnormal generation fluctuations in the power source, facilitating quick adjustments to grid operation efficiency. Additionally, integrating energy storage facilities into grid operations ensures stable electricity output [51]. Moreover, with the utilization of technologies like artificial intelligence, it becomes feasible to reasonably forecast future trends in generation and load changes [52,53,54,55]. Targeted adjustments in power distribution are enabled, flexibly adapting to changes in user-side demands, thus effectively mitigating operational risks in the system. Furthermore, concerning flexible resources like distributed energy storage, electric vehicles, and air conditioning systems of intelligent buildings [56,57,58], they can be coordinated and integrated into the grid to effectively enhance the flexibility and regulation capability of the power system. The implementation of intelligent grid control mechanisms is essential for establishing a coupled system integrating source, grid, load, and storage, providing a critical guarantee for ensuring the safe and stable operation of the new power system.

As the proportion of new energy sources continues to increase, the new power system faces challenges due to diminishing flexible resources. In this context, the importance of energy storage becomes increasingly prominent. Diversified energy storage technologies can enhance the coupling among source, grid, and load, thereby improving the overall synergy of the energy supply chain. Firstly, conducting integrated planning between energy storage systems and generation units is essential for achieving coordinated stable operation. This alleviates fluctuations in new energy generation and enhances proactive support capability during grid integration [3]. Secondly, precise control of energy storage devices is necessary to flexibly support grid dispatch management, optimizing energy distribution and utilization. Finally, on the user side, besides conventional power supply methods, household energy storage devices can be utilized to supply electricity [59]. With the ongoing development of the electricity market, users will be able to freely select electricity transactions in the future, considering their demands and storage capacity. This will enable them to meet their electricity needs, while also yielding economic benefits. In conclusion, the comprehensive deployment of energy storage not only provides a solid foundation for the stable operation of the new power system, but also significantly enhances the interaction among all components of the source–grid–load–storage framework, further tightening their coupling relationship.

Currently, as the interaction among the source, grid, load, and storage has deepened in the new power system, these four components have become integral parts of the complete system architecture, interdependent on each other, as illustrated in Figure 5.

Establishing an integrated associative framework based on source–grid–load–storage could facilitate the coordination and planning of distributed power sources, storage devices, and user groups in the same spacetime dimension to optimize resource allocation [60]. Coordination and cooperation across various aspects of the power system are promoted, leading to the integrated planning and operation dispatching of source–grid–load–storage in the new power system.

4. Key Technologies

Coordinated interaction among the components of source, grid, load, and storage to enhance system flexibility and adjustment capability is crucial for the future development of the new power system. However, the construction of an integrated framework pattern of source–grid–load–storage should progress gradually, requiring the implementation of various advanced technologies for support.

4.1. Data Acquisition

The vast amount of data covers various aspects of power system operations [61], providing abundant information resources with significant application value, which can help managers gain a better understanding of the overall operation of the power system [62,63]. The swift adjustment of operational strategies, the issuance of timely and accurate control instructions, and ensuring the efficient and stable operation of the power system are facilitated by the real-time acquisition of information data, including generator power generation, load consumption, and energy storage capacity, as depicted in Figure 6.

To address the challenge of achieving the comprehensive coverage of operation and maintenance (O&M) data for distributed photovoltaic (PV) power plants, a method for virtual acquisition of O&M data is proposed in Ref. [64]. Leveraging gray relational theory, the virtual acquisition of O&M data for entire regions of PV power plants has been successfully achieved using only a small number of deployed data acquisition devices. Investment costs are significantly reduced by this approach, while maintaining a high level of data acquisition accuracy. When facing issues like missing data, the method proposed in Ref. [65] employs local outlier factors to identify and eliminate outliers. Subsequently, missing data are predicted and filled using Bayesian probabilistic matrix factorization to maintain the integrity and accuracy of the dataset. Furthermore, to improve the efficiency of data acquisition, the method proposed in Ref. [66] utilizes compressed sensing for sparsity and process the monitoring data for transmission. Compared to traditional approaches, this method demonstrates superior performance in regards to both data transmission volume and accuracy. However, ensuring real-time, reliable data acquisition in today’s increasingly complex network environments is becoming more challenging.

Comprehensive and accurate data support is provided to decision makers through the utilization of data acquisition technology, enabling a deeper understanding of the real-time operation status of the source, grid, load, and storage, thereby facilitating the formulation of more scientific and efficient operational planning strategies.

4.2. Multi-Source Heterogeneous Data Fusion

Compared to the traditional power system, the operational data of the new power system has not only exploded in quantity, but also varies significantly in type and format [67,68]. Significant pressure is placed on the state monitoring and operation management of the power system. Therefore, efficiently integrating heterogeneous data from multiple sources and extracting useful information from these sources has become a current research hotspot.

In the new power system, source, grid, load, and storage belong to different domains, each with its own operational mechanisms and business types. Hence, the structural characteristics of their respective data also vary. However, multi-source heterogeneous data fusion technology enables efficient integration of operational data from different sources, facilitating the exploration of potential connections among them [24]. Subsequently, comprehensive, detailed, and effective feature information can be extracted from a holistic perspective and applied accordingly, as illustrated in Figure 7.

Multi-source heterogeneous data fusion technology shows promising application prospects. The Bayesian optimization prediction model proposed in Ref. [69] was used to train historical data, aiming to deeply explore the key factors influencing the output of wind turbines. Ultimately, a joint mapping from multidimensional fused data to wind power output is achieved. Higher predictive accuracy is demonstrated by this approach compared to models using only wind speed input. In the literature [70], fault diagnosis for transmission and distribution networks was achieved by integrating the characteristics of variations in fault status data, electrical parameters, and other external factors like meteorology. The results indicate that the redundancy information of multi-source data can be used to achieve the smart fault diagnosis more quickly and accurately. The joint safety control system and model analysis of the substation, designed in Ref. [71] based on multi-source heterogeneous data fusion, primarily target substations as electric power workplaces, with significant potential applications for energy equipment. It is evident that, compared to analysis utilizing a single data source, the utilization of multiple data sources can yield superior application outcomes. However, it is also important to note that the consideration for data security and privacy protection in the mentioned study is still incomplete, and more scientifically standardized processing methods are lacking.

Key feature information is extracted from complex datasets by comprehensively analyzing the interrelationships among diverse data using multi-source heterogeneous data fusion technology. Enhanced operational performance of various optimization models and algorithms is achieved by providing more effective data support, facilitating the breakdown of data barriers between source, grid, load, and storage in the new power system, thereby further boosting the synergistic application efficiency among different components.

4.3. Collaborative Planning

Traditional power system planning methods often concentrate on individual components without fully considering their interconnections, leading to a lack of comprehensive consideration of correlated information [72]. In contrast, integrating multiple factors and conducting in-depth analyses of the coupling relationships and interaction mechanisms among different components of the power system [73,74] are emphasized in collaborative planning. Such planning fully considers the mutual influence between components and aims to maximize the overall economic benefits and synergistic operational efficiency of the system, as illustrated in Figure 8.

To effectively achieve collaborative planning among the source, grid, load, and storage in the new power system, it is necessary to conduct in-depth research and analysis of the intricate interactions among these different system components. This process involves developing scientifically rigorous mathematical models and conducting comprehensive evaluations and making optimization adjustments to the decision-making solutions to ensure the overall optimization of the planning schemes. These elements collectively constitute the core framework of collaborative planning technology. The subsections below further elaborate on the connotations and significance of these critical elements:

• Research and Analysis: Delving deeply into the complex interactions among the various components of the new power system is vital. The focus should extend beyond superficial connections, uncovering the underlying causal relationships and influencing mechanisms between each component. For example, the demand for load is influenced by fluctuations in energy supply. Strategically siting energy storage contributes to the stability of the power system. Load variations provide guidance for energy storage operation strategies. This thorough understanding provides rigorous and accurate theoretical support for subsequent modeling and analysis.
• Mathematical Modeling: Employing precise mathematical expressions to articulate the intricate coupling relationships between source, grid, load, and storage within the new power system is essential. These models encompass multiple constraints and objective functions, including power balance, cost considerations, capacity allocation, demand response, and maximization of economic efficiency [75,76]. By applying suitable mathematical model-solving algorithms, we can derive scientifically valid planning solutions.
• Comprehensive Assessment: Conducting a comprehensive assessment of decision-making schemes based on a multi-dimensional indicator system is crucial. This system includes operational performance, economic benefits, environmental indicators, and social impact [77,78]. Following the assessment, appropriate adjustments to the planning scheme are made to ensure the optimal overall outcome.

The constituent elements of collaborative planning technology are summarized in

Table 1. The constituent elements of collaborative planning technology.

Content	Overview	Key Components	Value Demonstration	Related Literature
Objective	Multiple entities coordinate resources and interests for collaborative system planning optimization.	Collaborative planning involves distributed generation, flexible loads, energy storage, and electricity market transactions.	Implementing multi-energy synergy, fostering inter-departmental and inter-regional cooperation are employed for coordinated interest development.	[73,79,80,81,82,83,84]
Model	A complex planning model considers regional resources, diverse energy production, network characteristics, and load forecasts comprehensively.	New energy integration planning, optimized transmission line design, electricity market transaction considerations are included.	Accurate planning solutions are provided to guide decision-making.	[75,76,82,83,84]
Algorithm	The planning model is solved with mathematical optimization algorithms like linear, integer, and dynamic programming.	Objective function design, constraint definition, algorithm parameter tuning, and real-time dynamic optimization are considered.	The optimal solution of the model is sought to achieve maximized benefits.	[73,79,82,83,84]
Evaluation	The power system’s operational status, risks, and efficiency are comprehensively evaluated from economic, environmental, and reliability perspectives.	Economic benefit, environmental impact, and social acceptance are assessed.	All relevant influences are considered to create scientifically practical planning solutions, promoting sustainability.	[77,78,79,82,83,85]

, providing a clear framework for implementing collaborative planning technology in the new power system.

The judicious application of collaborative planning technology holds significant importance for the new power system. By thoroughly analyzing the distribution and output characteristics of diverse energy resources, effective collaborative operation schemes can be devised among fossil and renewable energy sources, along with energy storage devices [86,87]. The coordinated and complementary operation of multiple energy sources is enabled, as depicted in Figure 9, and overall energy utilization efficiency is enhanced and the capacity for renewable energy consumption is bolstered [88]. Besides ensuring a stable power supply, it also contributes to mitigating environmental impacts [85,89], thereby fostering the development of a cleaner, more efficient, and sustainable power system.

The synergistic planning model for new energy and multi-temporal scale energy storage, which considers environmental benefits, was constructed as documented in Ref. [79]. By enhancing the capacity for integrating new energy sources, significant reductions in carbon emissions have been accomplished within the system, yielding substantial environmental benefits. Furthermore, from a global standpoint, comprehensive planning schemes have been formulated, covering a wide range of factors and considering all aspects. These plans aim to maximize the coupling and complementary effects among source, grid, load, and storage, consequently enhancing the operational reliability of the power system [80,81]. A collaborative planning method for the source and grid that considers improving power supply capacity and reliability through the coordination of multiple planning factors was proposed in Ref. [90]; the results show that the method significantly reduces the planning risks and increases the economic benefits. The operational constraints of various flexible resources and the uncertainties of the power system at multiple time scales were comprehensively considered in [82], in which a collaborative planning model for source, grid, and storage was established. Not only were total costs effectively reduced, but the system’s efficient and reliable regulatory capacity was also ensured. The impacts of increasing wind power penetration on supply–demand characteristics and the influence of energy storage deployment on transmission network planning were deeply analyzed in Ref. [83]. A unified planning model integrating source, storage, and grid, considering the balance of flexible supply and demand, was established. The resulting planning solutions achieved optimal performance and economy.

However, the aforementioned studies failed to comprehensively consider the coordinated relationship among source, grid, load, and storage. A collaborative planning model constructed in Ref. [73] for power distribution networks integrates source–grid–load–storage with the aim of minimizing the total cost. Numerical examples demonstrate that adopting the source–grid–load–storage collaborative planning scheme further reduces the total planning cost of the power system compared to that of source–grid–load collaborative planning. Additionally, the method proposed in Ref. [84] introduces a sophisticated collaborative planning approach for integrating source–grid–load–storage in distribution networks, considering the bounded rationality of stakeholders. Multi-agent game theory is used to develop the optimal planning scheme for the distribution network, effectively coordinating grid operations, distributed energy resources, and energy storage planning, while considering user demand response. Through simulation verification, the planning results obtained considering the benefits of multiple parties are closer to the actual outcomes. However, the planning model mentioned above incorporates fewer constraints and lacks comprehensive consideration of the interconnections among various stages, suggesting room for further development. Moreover, the evaluation of the planning schemes primarily focuses on socio-economic aspects, with limited consideration given to the environmental value.

Collaborative planning technology can integrate operational configuration strategies across different segments of the power system, manage energy flow efficiently, minimize energy wastage, and enhance the overall operational performance and economic benefits of the power system.

4.4. Optimal Dispatching

Traditional power dispatching techniques struggle to adapt to the increasingly complex operational characteristics of the new power system and the diverse demands of user loads [91,92]. Therefore, it is imperative to research and implement more efficient and flexible dispatching technology to effectively allocate system resources, improve energy utilization efficiency, reduce operational costs, and enhance the system’s flexibility and reliability, ultimately achieving operational optimization [93,94].

• In the context of power system dispatch decision making, multiple optimization objectives are commonly considered [95], including economic efficiency, safety, and carbon emissions [96,97,98]. By thoroughly balancing these indicators and reasonably formulating operation dispatch plans, multi-objective optimization can be achieved, synergistically amplifying comprehensive benefits and ensuring optimal overall performance of the power system.
• Building a dispatch model involves integrating various considerations, including operational requirements, technical characteristics, environmental protection criteria, and market dynamics, to construct a rigorous and rational mathematical model that accurately depicts the complex operating conditions of the power system, upon which subsequent analyses are based.
• Utilizing artificial intelligence techniques, like reinforcement learning [99], take into consideration multiple objective functions and constraints. Iterative computation is employed to obtain the global optimal solution, deriving the optimal dispatch plan aimed at maximizing the overall operational performance of the power system.
• The constituent elements of optimal dispatching technology are summarized in Table 2, offering a coherent structure for the implementation of optimal dispatching technology in the new power system.

Table 2. The constituent elements of optimal dispatching.

Content	Detailed Examples	Related Literature
Optimization objectives	Economic efficiency, safety, flexibility, environmental friendliness	[95,96,97,98,100,101,102]
Decision constraints	Energy balance constraints, equipment operation limits, demand response protocols	[100,103,104,105,106,107]
Solving algorithm	Deterministic optimization, stochastic optimization, robust optimization, reinforcement learning	[74,85,106,108]

Table 2. The constituent elements of optimal dispatching.

Content	Detailed Examples	Related Literature
Optimization objectives	Economic efficiency, safety, flexibility, environmental friendliness	[95,96,97,98,100,101,102]
Decision constraints	Energy balance constraints, equipment operation limits, demand response protocols	[100,103,104,105,106,107]
Solving algorithm	Deterministic optimization, stochastic optimization, robust optimization, reinforcement learning	[74,85,106,108]

With the increasing demand for electricity, the power system is under significant supply pressure. Therefore, to maintain supply–demand equilibrium, it is essential to coordinate the dispatch of diverse energy resources and adjust output power from both new and conventional energy sources [103], proactively mobilizing flexible resources like energy storage [104,105,106]. The optimization scheduling model, which incorporates the resources of source, load, and storage, was proposed in Ref. [109], with the optimization objective of minimizing operational costs and risk losses. Subsequently, a rational scheduling plan was formulated. Validation confirmed that this approach not only decreased overall operational costs, but also notably bolstered the system’s flexibility. Furthermore, there is a push for broader user engagement in system operation scheduling, with the integration of various societal groups into the scheduling framework aimed at collectively maintaining the balance and stability of the power system [110]. By incentivizing electricity prices and implementing preferential policies, general users are encouraged to adjust their electricity consumption behavior during peak demand periods, thus reducing peak load and alleviating operational pressure on the power system. In the literature [107], a comprehensive optimization model for community residential load scheduling was established under the incentivized demand response mode, considering both electricity prices and residential electricity demand. Verification through simulation examples demonstrated that this model could effectively reduce residential electricity costs and ensure the stable operation of the power system.

The aforementioned research primarily focuses on dispatching and configuring resources and equipment within individual regional systems, without considering the energy characteristics and demands of different regions, or fully recognizing the significant application value of interconnection and mutual assistance across regions. In practical operation, coordinating dispatch across regions is crucial for maintaining wide-area power balance [108], as depicted in Figure 10.

By establishing cross-regional multi-energy complementary mechanisms, it is possible to fully utilize the energy advantages of different regions, conduct cross-regional resource scheduling and optimization configuration, achieve energy sharing and efficient flow, thereby improving the overall operational efficiency and supply stability of wide-area power systems. The proposed dual-level dispatch model for an inter-provincial interconnected DC power grid, which considers the uncertainty of photovoltaic-load forecasting, was introduced in Ref. [100]. It effectively addressed the issue of large-scale photovoltaic inter-provincial transmission and significantly enhanced the economic operation of the power system.

Improvements to the electricity trading mechanism, the establishment of a fair and transparent trading platform, and the implementation of market-based pricing mechanisms [111,112,113] can effectively facilitate resource flow [101] and enhance the capacity of renewable energy consumption. An optimization dispatch method for wind-storage systems oriented towards the electricity market was proposed in Ref. [102]. The uncertainties of wind power and the electricity market are comprehensively considered, with the objectives of smoothing power fluctuations and maximizing operational benefits. This system effectively improves the grid connection quality of wind-storage systems and enhances the economic benefits.

Efficiently integrating various aspects of the power system for joint dispatching and the optimization of flexible resources can significantly improve the operational performance and economic benefits, as depicted in Figure 11.

4.5. Security Protection

The modern power system has evolved into collections of large-scale and structurally complex systems, flooded with massive amounts of multi-source data [24]. There are also coupling characteristics among different business segments. The interconnected and coupled system architecture complicates the effective isolation of fault propagation during abnormal occurrences, significantly escalating the risk of cascading faults. Furthermore, with the growing prevalence of digital intelligent technology, the exposure surface of the power system is expanded, resulting in severe network security vulnerabilities [114,115,116]. Therefore, actively developing and deploying security protection technology is essential to promptly identify and appropriately address threats, including malicious intrusions, network attacks, and equipment failures, thereby ensuring the normal and stable operation of the power system.

Security protection technology encompasses numerous measures aimed at defending against various potential threats and vulnerabilities, ensuring the secure operation of power systems. The key elements of this technology are illustrated in Figure 12 and detailed in

Table 3. The constituent elements of security protection.

Safety Measures and Precautions	Risks and Hazards	Safety Mechanisms	Application Methods	Related Literature
Threat analysis and risk assessment	Emerging power systems face various security threats like environmental impacts, malicious software, hacker intrusions, or equipment failures, posing serious risks to system reliability and stability.	We conduct comprehensive analyses to identify power system vulnerabilities, allowing us to develop preventive strategies.	Threat modeling analysis, vulnerability scanning technology, quantitative security assessment	[117,118,119,120]
Intrusion detection and privacy protection	Malicious intruders may use network attacks, phishing emails, or identity theft, undermining power system stability, accessing sensitive data, and compromising user privacy.	The operational status and network traffic of the power system are analyzed separately to detect abnormal activities, while privacy measures ensure data security.	Anomaly detection methods, encrypted communication of data, federated learning	[121,122,123,124,125,126]
Access control and identity authentication	Unauthorized visitors gaining system privileges could lead to serious consequences like data tampering, crashes, and other adverse outcomes.	Access to the system is restricted to authorized users, with various identity verification methods in place.	Establishing access control lists, enhancing access auditing, implementing multi-factor authentication	[127,128,129,130]
Intelligent monitoring and emergency response	Failure to promptly monitor and address power system abnormalities may escalate security incidents, resulting in system crashes or collapse.	Real-time monitoring detects anomalies and implements emergency responses to minimize losses from security risks.	Deploying intelligent monitoring systems, developing emergency response plans, conducting regular training exercises	[118,131,132,133,134,135,136]

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• Threat analysis and risk assessment are essential steps for ensuring security protection in the power system [117]. This includes conducting in-depth analysis of various abnormal factors that may affect the stability of the power system, such as supply–demand fluctuations and external environmental influences [118]. Revealing hidden attack surfaces and vulnerabilities, as well as assessing threat levels, are crucial for the timely implementation of security measures. The evaluation of wind turbine conditions using machine learning models, as demonstrated in Ref. [119], demonstrated higher fault detection accuracy compared to conventional assessment models. Cyber-net state transition diagrams were constructed, and intrusion probability models were optimized, as depicted in the literature [120], facilitating a comprehensive risk assessment for power system network security. Strong support is provided for the identification and screening of potential “high-risk” events and anomalous nodes in the support of the secure operation and maintenance of power networks.
• Intrusion detection and privacy protection are critical for ensuring information network security in power systems. Hence, it is crucial to monitor real-time changes in the power network, to detect abnormal traffic information [121,122], and to promptly identify anomalous activities, including malicious software propagation, data theft, and other network attacks. Utilizing edge node technology, as demonstrated in [123], enabled the distributed deployment of power system data. A power system network intrusion detection model was constructed using the multi-grained cascade forest model, significantly improving data processing speed and real-time decision-making efficiency. Additionally, it is important to prioritize privacy protection by employing security measures such as encrypted communication to safeguard the confidentiality of critical information data [124,125]. The intrusion detection model was collaboratively trained within a federated learning framework, as detailed in Ref. [126], aiming to safeguard local data. The Paillier encryption scheme was employed to secure the model parameters, mitigating the risk of critical information leakage. It was verified that this approach not only achieves a notable increase in intrusion detection accuracy, but also effectively reduces communication overhead, thereby ensuring data privacy.
• Access control and identity authentication are vital for ensuring the normal operation of the power system [127]. Therefore, it is essential to strengthen access permission management and review, enhance the security of user identity authentication, and ensure that only authorized personnel can access the system’s web interfaces [128], thereby rejecting unauthorized access attempts. The authentication method for power terminals based on radio frequency fingerprints was proposed in Ref. [129], with recognition authentication performed using a BP neural network. It was verified that this method can significantly improve the speed of transient detection, thereby ensuring the wireless communication security of the power system. An identity authentication model and access control method based on blockchain were designed in [130], combined with practical application scenarios. Cross-domain distributed identity authentication and access control are enabled by this, effectively mitigating the risk of centralization.
• Intelligent monitoring involves securing infrastructure and critical equipment, deploying intelligent monitoring devices for real-time operational status monitoring of the power system [131], and analyzing operational data to promptly identify potential security issues [132]. A dynamic analysis model for discrete events in the power grid, based on log information, was established in Ref. [133]. By conducting in-depth analysis of the operational logs of the power grid, characteristic patterns of fault events were discovered, effectively identifying various types of abnormal operational events, as well as allowing for the timely detection of potential threats. Additionally, it is important to establish an emergency response mechanism and develop effective contingency plans [134,135] to ensure that the power system can respond promptly to various emergencies, thereby reducing the impact of accidents, minimizing losses, and ensuring the rapid restoration of system performance. Threat assessment for low-frequency oscillations was conducted in Ref. [118]. When the criteria are met, emergency control strategies are triggered, including measures such as disconnecting generator units and rapidly adjusting DC power. A post-fault emergency response strategy for distribution networks was proposed in Ref. [136], achieving maximal rapid recovery of distribution network loads by adjusting energy outputs and subdividing multiple microgrids. Subsequently, the shortest mobility paths were planned based on a dynamic traffic network model to facilitate swift power restoration.

Security protection technology aims to assist power systems in defending against various threats, vulnerabilities, and emergencies, while prioritizing the protection of critical information and user privacy. The widespread application of intelligent digital technology devices will further advance the development pace of power system. Concurrently, security protection technology will continue to evolve and progress to meet the evolving needs of the electricity industry, providing a solid guarantee for the safe and reliable operation of the power system.

4.6. Electricity Market

The electricity market is an economic system where electricity production and distribution are traded. It optimizes the allocation of electricity resources through the introduction of market competition mechanisms. The electricity market typically involves multiple participants, including power generators, distribution companies, electricity traders, and numerous users, as illustrated in Figure 13. Within the electricity market, multiple participants engage in buying and selling electricity transactions, regulated by relevant institutions to ensure fair competition and maintain trading order.

Pricing is crucial in the electricity market [137]. The market electricity price is determined based on a comprehensive consideration of factors including electricity demand, investment cost, weather conditions, and government policies, as illustrated in Figure 14.

Energy suppliers can optimize resource allocation, efficiently meet user demands, and minimize energy wastage based on users’ responses to different electricity price periods. Moreover, market competition incentivizes electricity suppliers to offer higher-quality services. A bi-level optimization model for power generator bidding under three marginal electricity pricing mechanisms, including system marginal price, locational marginal price, and zonal marginal price, was constructed in Ref. [138]. A multi-agent reinforcement learning approach was employed to iteratively update the model and obtain the optimal pricing strategy for power generators. A multi-agent game model considering the quality of electrical energy was proposed from the perspectives of both power generation and consumption in Ref. [139]. This model incentivizes power producers to generate high-quality electricity, facilitating efficient and high-quality bilateral transactions between power companies and users. It provides a reference for promoting quality-based pricing of future electrical energy.

The electricity market is a vital energy trading platform capable of adjusting prices based on market demand, thus optimizing the supply of various resources and promoting diversified energy production. The reliance of the electricity industry on traditional energy sources is reduced, and the development and application of new energy sources are promoted [140,141]. A distributed adjustable load resource settlement model was proposed in Ref. [142], enhancing the payment capability of the electricity spot market bidding system. A comprehensive evaluation and analysis of the market-oriented application of flexible resources and the transaction arrangements of a renewable energy system were conducted. The issue of the mismatch between renewable energy distribution and load in China was studied in Ref. [111]. A cross-regional inter-provincial incremental spot market for renewable energy was designed to promote the integration of renewable energy through economic leverage and market mechanisms, achieving satisfactory results.

Consumer transactional behavior is influenced by various factors, such as social relationships, personal preferences, and habits. Their trading demands also vary in terms of benefits, comfort level, and environmental awareness. Therefore, when describing actual transaction behaviors, it is important to consider consumers’ risk attitudes and subjective values and quantitatively analyze consumers’ actual intentions and psychological factors [143]. Appropriate transaction decision-making methods are constructed to attract consumers to actively participate in market transactions, aiming to improve market efficiency and power system stability. A pricing and optimization strategy for time-of-use electricity tariffs for electricity retailers, considering user-side demand response, was proposed in Ref. [144]. Active responses to peak and off-peak electricity prices by users is encouraged, thereby guiding users to adjust their production activities and electricity consumption demands, facilitating peak shaving and valley filling. The study in Ref. [145] considered the enhancement of users’ environmental awareness and their preference for energy use. Consequently, a game theory model for the electricity retail market, with renewable energy units, was formulated. It was verified that this electricity market model promotes the integration of renewable energy, while ensuring the balance of power supply and demand.

The continuous development and application of energy storage technology have significantly impacted aspects of the electricity market such as price formulation and market arrangements [146,147,148,149]. A two-stage demand response scheme applicable to energy retailers with energy storage systems in decentralized electricity markets was proposed in Ref. [150]. Adjusting the charge and discharge behaviors of energy storage facilities to respond to the outputs of different power sources can effectively mitigate the fluctuation of wind and solar power generation, thereby facilitating the integration of renewable energy and reducing consumer costs. The coordination mechanism for integrating energy storage resources into the electricity spot market to optimize the flexibility allocation of the power system and promote the integration of renewable energy was investigated in Ref. [151]. It also explored the unique issues and solution approaches for independent energy storage participation in the market, analyzing the practicality and effectiveness of different mechanisms, with significant implications for advancing the commercial application of energy storage resources.

The electricity market serves as a fair trading platform for numerous participants and plays a vital role in facilitating efficient interaction among source, grid, load, and storage in the power system [152,153]. The architecture and trading mechanisms of a tradable energy system were designed in Ref. [154] to accommodate distributed entities, including users, power sources, and energy storage providers. Trading is guided by real-time electricity prices to achieve coordinated development between each distributed entity and the interests of the overall system. Furthermore, the complex game in the scenario of demand response for electric vehicle dispatching was investigated in Ref. [155]. Electric vehicle aggregators are encouraged to participate in the electricity market, guiding the charging and discharging of electric vehicles to achieve optimized dispatch. The results indicate not only the facilitation of peak shaving and valley filling, but also the effective balance of economic interests among electric vehicle users, aggregators, and distribution grid operators.

In conclusion, the electricity market facilitates the integration of new energy sources and efficient resource utilization, while optimizing energy production, transmission, and consumption processes. It promotes deep interaction among various aspects of the power system, thereby advancing the establishment of an integrated pattern of source–grid–load–storage.

5. Challenges and Prospects of Key Technologies

5.1. Challenges and Prospects of Data Acquisition

The vast amount of real-time data stored in the power system can provide support for planning and scheduling decisions. However, the real-time, reliable data acquisition faces severe challenges in the face of complex dynamic operating scenarios such as distributed energy generation and diversified load management [64,65]. Therefore, in the future, we should actively explore low-latency, high-efficiency data acquisition technologies. For instance, leveraging the high bandwidth and low latency transmission characteristics of 5G networks, combined with techniques such as virtual data acquisition and digital twins [156], can enable the rapid acquisition and efficient utilization of system data. Additionally, consideration can be given to the application of satellite networks and quantum communication technology to construct secure and reliable real-time data transmission channels. This enables the comprehensive coverage and flexible networking of wide-area data, facilitating data exchange across distant regions, thereby providing strong support for the intelligent operation of the power system.

Special attention must be paid to data security and privacy protection during data acquisition. Quantum information encryption technology [157] and federated learning frameworks can be combined to construct a highly secure data ecosystem. Encrypting sensitive data, such as customer energy usage information, ensures data security during the acquisition and transmission processes, preventing various types of sensitive private data from being maliciously exploited.

Ensuring high data integrity during the data acquisition process is essential to prevent data loss or corruption [65]. Therefore, artificial intelligence techniques can be employed to construct an intelligent data error correction system, enabling the timely detection and correction of potential abnormal data, thereby achieving the self-repair and dynamic optimization of the data. Furthermore, utilizing technologies such as distributed storage databases and a blockchain to design a robust data backup mechanism can assist the system in flexibly addressing data loss issues. Additionally, integrating fault-tolerant techniques, such as lossless data compression and error correction coding, can reduce the risk of data transmission failures and enhance the reliability of large-scale datasets.

5.2. Challenges and Prospects of Multi-Source Heterogeneous Data Fusion

With the data environment of the new power system becoming increasingly complex, data heterogeneity is manifested not only in various types of data, but also in variations in data format, structure, and quality accuracy [68]. Significant challenges are posed for integrating and analyzing data. Thus, new data fusion technology should focus on developing adaptive data integration algorithms. Combining self-organization principles with artificial intelligence techniques to design dynamic weight mechanisms [158] allows for the automatic adjustment of weight distribution during the data integration process, based on data quality, variability, and the trustworthiness of data sources, thereby enhancing the accuracy and reliability of the final processing results. Additionally, leveraging technologies like graph databases and knowledge graphs enables the exploration and analysis of associative characteristics among heterogeneous data from multiple sources, uncovering potential interaction mechanisms between different datasets.

In order to ensure the stable operation of the power system, it is necessary to promptly formulate reasonable operation dispatching strategies based on the real-time operating conditions of the system and comprehensive consideration of various factors [51]. Therefore, it is imperative to efficiently integrate artificial intelligence and quantum computing technology to develop data fusion techniques with powerful parallel computing capabilities, thereby effectively reducing processing time and achieving faster data analysis and decision-making responses.

Given that the operational status of the future power system will become increasingly complex, it is necessary to expand the coverage of multi-source heterogeneous data fusion technology. In addition to the internal data of the power system, incorporating external information such as electric vehicle charging networks [159], meteorological data, urban geography, and other pertinent factors is essential for achieving comprehensive and multidimensional data integration. Additionally, integrating advanced theoretical knowledge from fields such as economic principles, meteorology, and psychological factor analysis ensures a comprehensive analysis of various data information, facilitating a precise understanding of key insights and thereby enhancing the effectiveness of comprehensive planning decisions.

5.3. Challenges and Prospects of Collaborative Planning

The integration of a substantial amount of renewable energy into the power generation mix has provided new momentum for energy transformation in the power industry, yet it also introduces significant risks and challenges. Hence, there is a need to move beyond traditional single-energy planning and adopt diversified energy management and coordinated operations [86,89]. By fully leveraging big data analysis and artificial intelligence technologies, it is crucial to consider the scale and spatial-temporal distribution differences of distributed energy sources when planning the location and capacity of various energy power plants. Establishing a multi-energy coordinated complementary operation mode to efficiently integrate source-side electric energy resources is imperative. Moreover, during the planning and design phase, it is important to actively enhance communication and connectivity among the power generation side, energy storage systems, and the electricity market [50,59,140]. Establishing robust cooperation mechanisms and devising collaborative planning and development strategies are essential to improving the overall operational efficiency of the power system.

The power system comprises various sectors, including energy production, transmission, distribution, and consumption. Significant differences exist in the technological means and management methods of its various subsystems, posing challenges to efficient information flow and coordinated operation. Planning schemes are frequently restricted by local optimum [72]. Hence, collaborative planning technology should prioritize the development of intelligent integration algorithms and the enhancement of collaborative decision-making mechanisms. Exploring and analyzing the higher-order correlation features among the source, grid, load, and storage in the power system and elucidating the mechanisms of mutual influence among various aspects of the power system [73,82], would facilitate the establishment of a more accurate and reliable multi-agent collaborative planning model for source–grid–load–storage by constructing more appropriate constraint variable conditions and correlation mechanisms.

The intricate dynamic operational characteristics of the new power system present significant challenges for modeling and characterization. Therefore, achieving breakthroughs in complex system modeling requires cross-disciplinary integration and the establishment of a collaboration framework. Models should consider not only factors like generation capacity, grid architecture, user demand response [84], and energy storage facility conditions within the system [75,76], but also external factors including environmental protection requirements [79], meteorological and geographical conditions, and policy regulations. Developing a comprehensive blueprint for the future development and construction of the power system from a multi-dimensional perspective and devising an optimal planning scheme that includes optimizing encompassing energy transmission paths, control strategies for energy storage devices, and other aspects in order to ensure the coordinated and stable operation across various components of the power system and to enhance overall energy efficiency.

The focus should extend beyond achieving coordinated operation among internal power system components to emphasize multi-domain joint development. Establishing a highly interconnected digital platform with unified data standards and formats facilitates information sharing and operational compatibility between the power system and other infrastructure systems, such as transportation, smart buildings, and environmental monitoring [159,160]. Additionally, establishing a smart city joint development planning system involves coordinating and integrating urban planning, transportation flow, and energy distribution information to formulate feasible planning schemes for urban development, ensuring that cities can better adapt to future social development needs.

5.4. Challenges and Prospects of Optimal Dispatching

Operation dispatching in new power systems often involves multi-energy aggregation and encompasses various factors, significantly increasing the complexity of dispatching tasks [94]. Hence, the limitations of current algorithm models must be overcome. Firstly, multiscale modeling can be employed to break down the power system into subsystems at different levels for hierarchical scheduling. Next, organic integration of the multidimensional scheduling can be achieved through collaborative optimization. Moreover, optimal dispatching should focus on dynamically modeling and optimizing the power system. By integrating deep learning, reinforcement learning [99], and adaptive algorithms, the scheduling decision-making system can possess the capability for trial-and-error learning. The system’s adaptability is enhanced by enabling scheduling plans to be flexibly adjusted based on feedback information. Furthermore, an emphasis should be placed on interdisciplinary integration, leveraging expertise from fields like meteorology, economics, and sociology to rigorously analyze system data. The comprehension of the power system’s complex operational characteristics is enhanced, providing a more reliable theoretical basis for designing optimized scheduling schemes.

The new power system comprises diverse fuzzy information, encompassing complex interrelations among different factors and probabilistic knowledge of future states [94,96], posing challenges for precise management. Consequently, optimal dispatching should incorporate theoretical methods from fuzzy logic [161] and probabilistic reasoning to develop a comprehensive model encompassing various uncertainty factors. Through probabilistic reasoning, a thorough analysis of historical data and the employment of statistical techniques can be used to quantify the uncertainty of the fuzzy logic model to create probability distributions, thus offering probabilistic insights into predicting the future state of the power system. Subsequently, by integrating fuzzy logic and probabilistic reasoning, effectively amalgamating fuzzy and probabilistic information from various factors, a mathematical model is constructed to enhance the precision predictions of potential future system operational states, thereby facilitating optimized scheduling decisions.

Under the requirement for real-time operation, the power system must respond swiftly and precisely. Therefore, achieving seamless integration from planning and decision making to actual operations is paramount. The future trajectory of optimization scheduling technology will favor distributed collaborative processing. The development of real-time optimization algorithms and edge processing technology is emphasized, involving partial data processing and decision making on edge devices. Such an approach effectively distributes the computational load, diminishes transmission delays, boosts the operational processing speed of the system, and enhances its capability to rapidly respond to unforeseen events.

5.5. Challenges and Prospects of Security Protection

Ensuring the safety and stability of the physical system is paramount for maintaining the normal operation of the entire power system. Nevertheless, sudden events like natural disasters and equipment failures can inflict severe damage on the physical power system. Hence, there should be a focus on innovative advancements in materials science and mechanical manufacturing, emphasizing the development of safer and more reliable power equipment. Such an approach can bolster the disaster resistance and long-term stability of the power system. Moreover, attention should be directed towards the development and application of intelligent sensing systems. Integrating advanced sensing devices with IoT and digital twin technologies [162] enables the establishment of a wide-area monitoring system. Real-time changes in the operational state of the power system are monitored, promptly identifying potential threats and hazards. Furthermore, the combined use of virtual reality and augmented reality technology can establish a more comprehensive and intuitive power monitoring and emergency response system [163]. Such an approach enables maintenance personnel to undergo simulated training and emergency drills in highly realistic virtual environments, thereby reducing the likelihood of human errors. It also facilitates data visualization to simulate equipment failures in virtual environments, thereby enhancing the maintenance staff’s ability to accurately locate issues. Moreover, guiding information can be overlaid in real-world scenarios to offer real-time guidance for maintenance operations. The precise identification and rapid repair of system failures are thus enabled.

The modern power system faces severe network risks and security vulnerabilities [116]. Malicious attacks, phishing, ransomware, and other threats seriously jeopardize the stable operation of the power system. Hence, real-time analysis, such as network traffic and measurement perception evaluation, should be conducted on data to automatically identify abnormal operational states by learning the behavioral characteristics of the system [118,122], since the adoption of preventive measures can be facilitated proactively. However, with the deepening coupling between the cyber and physical aspects of the power system, comprehensive coverage and precise extraction of abnormal state characteristics cannot be achieved solely by relying on single-sided data detection methods [123]. Thus, from a cyber–physical integration perspective, technologies like deep learning should be utilized to focus on developing collaborative detection methods based on bilateral features. By thoroughly exploring and analyzing the patterns of change in bilateral features data and their potential correlations with abnormal states in the power system, the precise detection and classification of abnormal states can be achieved.

With the significant increase in the intelligence level of power systems and the widespread application of big data, the transmission and interaction of information become more frequent. While enhancing the system’s operational efficiency, this also introduces significant challenges related to information security and privacy protection [124,125]. Hence, there is a need for preventive measures to mitigate adverse events such as information leakage and data tampering. Firstly, utilizing blockchain technology should be considered to establish a decentralized and tamper-proof data storage and interaction platform [164], effectively preventing data forgery and malicious attacks. Secondly, in combination with the utilization of new encryption algorithms, transmission data should be dynamically encrypted to make it highly resistant to eavesdropping, thus providing robust protection for the secure transmission of information data. Additionally, it is important to emphasize data access permission management because passwords carry the risk of being leaked or guessed. Therefore, techniques such as iris recognition and other biometric technologies can be introduced to establish a multi-layer authentication mechanism for the precise identification of visitors, ensuring that only authorized personnel can access and interact with data. Even in environments with frequent information exchange, illegal user intrusion and sensitive information leakage can be effectively prevented.

Transcending traditional thinking frameworks and boundaries is crucial to establish a comprehensive, multi-level security defense system. Creating a unified security management platform that integrates data from various stages, such as source, grid, load, and storage, enables unified monitoring and management of the entire power system. Leveraging artificial intelligence, big data analysis, and other technologies enables the in-depth analysis of system data [54,119] to promptly identify security risks. Simultaneously, improving information exchange mechanisms ensures real-time data sharing, strengthens communication among different components of the power system, and establishes a collaborative defense mechanism. By comprehensively considering various security requirements and planning protective scheduling measures, joint monitoring and coordinated defense can be truly achieved.

5.6. Challenges and Prospects of Electricity Market

The current level of intelligence in the electricity market is limited, which constrains market transaction efficiency. Consequently, the focus should be on developing an intelligent market control system. Accurately predicting new energy generation, user demand response, and the status of energy storage facilities, as well as conducting in-depth analysis of market transaction data [154], allow for the prompt identification of potential market opportunities and risks. Improved market operational efficiency and the provision of more precise and detailed information for decision making are achieved.

Electricity markets in different regions typically operate independently, lacking effective communication and interconnection mechanisms, thereby resulting in fragmentation and isolation within the energy markets. Therefore, future efforts should focus on integrating advanced communication technology and intelligent control systems to establish a unified cross-regional energy market management system [111]. Strengthened interaction and communication between distributed trading platforms and promoted cross-regional energy trading development would be facilitated. As a result, the efficient flow and optimized allocation [140] of multi-energy resources across large areas would be facilitated.

In the future, the electricity market is anticipated to witness the emergence of more participants [154], resulting in increasingly complex trading conditions. Hence, the focus should be on the complex evolutionary trends in the market structure. Targeted studies on trading mechanisms [113,155] involving multiple participants should be conducted, and the innovative development of diversified trading mechanisms, including competitive bidding and win–win cooperation, should be actively promoted. Establishment of comprehensive trading mechanisms aligned with market development trends will be aided.

6. Engineering Potential and Application Value

The integrated planning and operation dispatching of source–grid–load–storage is an important development direction for the new power system [60]. Combining power sources, transmission networks, loads, and energy storage facilities, various factors are comprehensively considered, as shown in

Table 4. Comprehensive factor consideration.

	Source	Grid	Load	Storage
Cyber	Analysis of energy market demand trends, assessment of potential energy resources, analysis of clean energy development trends, analysis of weather factor impacts	Analysis of energy flow, grid topology analysis, evaluation of grid capacity, security analysis of communication and control system	Consumer behavior analysis, analysis of load types and characteristics, development of load response models, analysis of user feedback information	Monitoring and evaluation of energy storage device status, charge and discharge control algorithm, strategy for energy storage capacity and power allocation
Socio	Research on new energy subsidy policies, analysis of energy market regulation policies, carbon emission quotas, emission standards for pollutants	Network architecture construction planning, investment in operation and maintenance costs, analysis of policies for renewable energy integration, energy market access capability assessment	Assessment of social acceptance, policies on energy conservation and management, trends in energy industry development, regional economic development planning	Assessment of environmental impact of energy storage technologies, assessment of safety for energy storage system, investment cost of energy storage projects, recycling and disposal of energy storage equipment
Physical	Analysis of renewable energy generation fluctuations, analysis of power generation equipment reliability, consideration of operating costs for power generation equipment, analysis of energy conversion efficiency, power balance constraints	Transmission capacity assessment, line loss constraint, voltage stability constraints, frequency stability constraints	Analysis of load distribution characteristics, fitting and prediction of load curves, load variation rate constraint, analysis of load period classification	Energy storage system capacity and power balance, consideration of energy storage charge and discharge efficiency, analysis of energy storage power response time, evaluation of energy storage cycle life, requirements for energy storage system response speed

.

Subsequently, unified planning is conducted to achieve coordinated operation in each link, as illustrated in Figure 15.

Integrated planning and operation dispatching can significantly improve the operational efficiency of the power system, ensuring high stability and reliability while creating substantial economic benefits. Therefore, applying the concept of integrated planning and operation dispatching of source–grid–load–storage to large-scale engineering projects is highly advantageous.

6.1. Promoting the Development of the Power System for Extreme Disaster Governance

In modern society, the power system has evolved into a complex cyber–physical mega-system that is highly integrated with human society. However, this high level of integration also implies high dependence, and complexity often introduces vulnerabilities. Despite the precise and meticulous operational characteristics of the power system, even a minor fault can trigger a chain reaction that may lead to the collapse of the entire system, putting human society at risk of a major shutdown event.

In recent years, global climate change has led to an increase in extreme weather events which adversely affect the normal operation of human society. Under conditions of high temperatures and severe cold, the failure rate of power equipment rises sharply, while power load increases dramatically, exacerbating the burden on energy supply. Under such internal and external challenges, power lines are prone to disconnection due to severe overload. As faults rapidly spread, the power grid quickly becomes unstable, resulting in widespread power outages [165]. For example, in 2016, typhoons and heavy rain caused a major power outage in the southern Australian grid, where renewable energy generation accounted for 48.36% of the total generation. The power supply was not restored for 50 h [166]. In 2021, extreme cold weather hit Texas, damaging wind power equipment and causing gas turbines to shut down, ultimately triggering a major power outage [167]. In 2022, Sichuan experienced extreme drought and high temperatures, leading to a significant reduction in hydropower and a rapid increase in cooling demand among residents. This created a substantial gap between power supply and demand, resulting in emergency power restrictions [168].

The incidents described above highlight the vulnerability of new power systems that include high proportions of renewable energy when they are faced with extreme disasters. This vulnerability is primarily evident in significant supply pressures and limited system flexibility. These issues culminate in the summary of factors influencing power outages in new power systems under extreme weather conditions, as shown in Figure 16.

Extreme disasters can paralyze power system, leading to major power outages that significantly disrupt normal functioning and result in substantial economic losses. However, traditional power system operation and dispatching models are not equipped to handle the challenges posed by extreme disasters and lack adequate disaster resistance capabilities. Ensuring a stable power supply requires coordinated planning of source, grid, load, and storage in the new power system to facilitate collaborative scheduling and operation across all components, as illustrated in Figure 17.

• Mitigating the impact of extreme disasters on energy supply and significantly enhancing the disaster resilience of power system operations can be achieved by reducing the system’s dependence on a single energy source and implementing coordinated [169], complementary multi-energy operations. Therefore, it is crucial to plan and deploy new energy generation stations according to local climate, geographical conditions, and resource distribution, while maintaining traditional thermal power as a reliable backup regulation resource on the generation side. By flexibly leveraging the complementary characteristics of multi-energy coupling, a diversified power generation system can be established to improve the flexibility and reliability of power system operations.
• Establishing an intelligent grid architecture and employing advanced monitoring technology for continuous real-time monitoring of energy supply and demand support system analysis and decision-making facilitates the advanced planning of grid scheduling and operations [170], allowing for the flexible adjustment of electricity transmission and distribution to ensure a stable power supply. Additionally, the implementation of microgrid technology enables localized isolation during emergencies, preventing the spread of disaster impacts across the entire power network. Moreover, utilizing ultra-high voltage transmission technology enhances the efficiency of the existing grid architecture, establishing an efficient cross-regional energy transmission network that facilitates energy sharing between different regions [171]. In the event of extreme disasters affecting one area, other regions can provide a timely energy supply to meet the electricity needs of the affected area.
• Promoting the large-scale development and coordinating the application of diverse energy storage technologies enables the storage of surplus electricity during normal operations for future use [172,173], facilitating multi-time-and-space energy scheduling. Furthermore, the strengthening of source–storage interaction and the establishment of a coordinated scheduling mechanism are crucial. In case of disruptions in generation on the source side and the inability to maintain a normal power supply, the energy storage system should promptly respond and operate efficiently to ensure a stable power supply to critical facilities.
• Optimizing adjustments are applied to the load side for ensuring the safe and stable operation of the power system under adverse environmental conditions. It is crucial to conduct an in-depth analysis of load demand characteristics and accurately predict the trends of the load curves. Subsequently, methods such as time-of-use electricity price and policy directives are employed to guide users in orderly electricity consumption [174], thereby alleviating the supply pressure on the power system. Simultaneously, energy storage regulation is supplemented to achieve a stable balance between energy supply and demand.
• All sectors of society should strengthen cooperation and establish a joint governance team. Collaboratively, they should devise response plans for extreme disasters, clearly defining the responsibilities and response measures for each party to ensure an organized response during disasters. Furthermore, regular drills should be conducted to simulate disaster scenarios, evaluate the coordination and flexibility of emergency plans, and make continuous improvements based on drill results. It is also essential to train staff for effective disaster response so that, in the event of an actual incident, they can handle the situation calmly and efficiently.

Maximizing the flexible regulation potential of the source, grid, load, and storage components in the power system facilitates coordinated resource allocation and efficient utilization, minimizing the adverse effects of disasters on system operations. This strategy enhances the adaptability and robustness of the power system, enabling it to effectively handle various natural disasters.

6.2. Promoting the Development of a Smart Energy Ecosystem in the Desertification Regions

Traditional energy industries have met human production and living needs, but they have also caused serious environmental pollution and ecological damage. Hence, a development model reliant on fossil fuels is unsustainable, necessitating a new energy revolution for human society. Emphasis should be placed on developing and utilizing green, low-carbon, and renewable energy sources to replace traditional fossil fuels [175,176,177], providing environmentally friendly power for social development. Energy requirements are fulfilled while simultaneously safeguarding the ecological environment.

The desertification region boasts unique natural environments abundant in sunlight and wind resources, making it an ideal location for renewable energy development. Hence, prioritizing the construction of large-scale wind and solar power generation bases in desertification regions is crucial for fostering high-quality renewable energy development [178]. However, desertification regions are characterized by harsh geographical conditions and fragile ecosystems, which have long grappled with water scarcity and poor soil quality. Without meticulous planning, hasty actions could impede local resource development and exacerbate the degradation of the already fragile ecological environment, resulting in adverse outcomes. Therefore, it is essential to adhere to the principles of sustainable development and prioritize the development and construction of a smart energy ecosystem in desertification regions [179].

The application of integrated planning and operation strategies for source–grid–load–storage to the development and construction of desert energy bases can yield significant benefits. Integrating ecological restoration measures into the planning and operational processes facilitates the establishment of a coordinated development model, termed “energy development and ecological management”. The groundwork for constructing a smart energy ecosystem in the desertification regions is laid. It offers a feasible solution for achieving a win–win relationship between energy development and environmental protection, opening up new possibilities for the future of the desertification regions. The implementation plan based on these concepts is depicted in Figure 18.

• During the site selection and design of energy bases in desertification regions, it is crucial to consider local climate, terrain, resource distribution, ecological and environmental factors, comprehensive ecological impact assessments, and the scientific prediction of potential ecological hazards, and the proposal of mitigation measures is essential. Moreover, wind turbines and photovoltaic facilities should be designed and selected based on local climate characteristics. These facilities should also be equipped with structures capable of withstanding wind and stabilizing sand. The proper arrangement of these facilities can effectively slow the movement of sand resulting from storms, preventing soil erosion and desertification. Furthermore, the extensive surface area of photovoltaic panels can effectively reduce ground-level solar radiation, thereby decreasing water evaporation and increasing soil moisture. Consequently, vegetation restoration zones can be established in suitable areas beneath the photovoltaic panels, maximizing land resource utilization and promoting the growth of surface vegetation.
• Because of the limited renewable energy consumption capacity in desertification regions, power transmission corridors should be strategically planned to connect desert energy bases to high energy-consuming regions. Utilizing ultra-high voltage transmission technology enables the long-distance transmission of renewable energy generation [180] and supports the large-scale integration of renewable energy. It can also promote cross-regional energy trade by serving as a foundation for integration with energy trading markets, thereby engendering economic dividends that propel local economic development. Moreover, the generation of real-time environmental data to support ecological restoration efforts is enabled by utilizing the smart grids’ distributed data monitoring systems. For example, monitoring sunlight intensity and temperature changes can assist underground drip irrigation systems in determining optimal watering times. Moisture retention is maximized, and favorable conditions for plant growth are created, thereby facilitating local environmental restoration.
• Besides exporting electricity, boosting the local utilization of renewable energy, which involves satisfying the daily electricity needs of local residents and fostering the growth of green industries, is crucial. Local initiatives, such as the integration of agriculture and photovoltaic systems, can provide both economic and ecological benefits. For example, integrating wind and solar power with agriculture and livestock can supply electricity for irrigation, greenhouse facilities, and farms. Furthermore, integrating photovoltaic panels with local industries can facilitate a comprehensive development model involving power generation from panels, planting beneath panels, grazing between panels, and ultimately, ecological restoration. Converting local ecological restoration areas into eco-tourism destinations can attract visitors and bolster the growth of the green tourism industry. Residents can engage in building a green ecological community, while reaping the benefits of sustainable development.
• The intermittent nature of wind and solar power generation poses challenges to system stability. Addressing this challenge requires allocating adequate flexible resources to mitigate output fluctuations and ensure a stable power supply. Utilizing energy storage technologies, such as batteries and hydrogen storage, aids in constructing a comprehensive storage system that efficiently stores surplus energy for future use. Real-time monitoring of the power system’s operational status and adapting to dynamic changes in wind and solar output and electricity demand are crucial for formulating coordinated dispatch strategies. The smooth coordination between wind and solar power generators and the storage system can be ensured by properly controlling the charging and discharging operations of the energy storage facilities, thereby enhancing the efficiency and stability of the power system. Moreover, future research should focus on promoting innovation in energy storage technology and developing energy storage systems tailored to the environmental characteristics of desertification regions [181], with an emphasis on environmental and sustainable objectives.

By leveraging advanced communication technologies, efficient interactions between energy bases, consumers, and energy storage systems can be established. These interactions allow for the optimization of operational strategies, considering various factors to ensure efficient and stable system operation. Furthermore, careful planning and implementation of ecological protection measures facilitate the harmonization of renewable energy development with ecological restoration. The consistent operation of the energy system is supported, while ecological projects are promoted. The proposed comprehensive planning and operational strategy offers a promising path toward sustainable development in desertification regions.

6.3. Promoting the Development of Integrated Energy System in Zero-Carbon Parks

In response to the increasingly severe energy crisis and environmental pollution issues, the energy industry is bound to undergo radical reforms, and the concept of zero-carbon development should be vigorously promoted [182,183], with a focus on exploring pathways of complementary multiple energies and conducting in-depth research on energy cascade utilization. The aim is to construct a comprehensive energy system operation framework for zero-carbon parks [184,185].

The integrated energy system within the park operates in three stages: energy collection and input, production and conversion, and transmission and storage. Initially, various energy sources, including natural gas, solar energy, and wind energy, are collected to provide a diversified energy input and to ensure sufficient energy supply for the park. During the production and conversion stage, modern equipment such as gas turbines, photovoltaic panels, and wind turbines convert natural energy into usable forms, i.e., electrical and thermal energy. Furthermore, devices such as electric boilers and electric chillers further transform secondary energy sources into the specific forms of energy required by the residents. Finally, energy is efficiently transmitted and precisely distributed throughout the park’s energy transmission network to meet users’ needs. Surplus energy is stored in various facilities to balance supply and demand and provide reserve capacity for future use. A diagram of the integrated energy system within the zero-carbon park is presented in Figure 19.

A zero-carbon park does not necessarily achieve absolute zero carbon emissions; instead, it involves establishing an effective carbon-neutral operation mechanism through the careful application of diverse technologies and scientific management methods. Comprehensive carbon monitoring is conducted at all stages of the energy system in the zero-carbon park, including production, transmission, and usage. Carbon emissions at each stage are precisely controlled according to relevant standards and regulations. Additionally, techniques such as carbon capture and storage are used to capture atmospheric carbon dioxide, creating a zero-carbon cycle and minimizing carbon emissions within the park.

In the future development and construction of zero-carbon parks, innovative approaches for coupling and complementing multiple energy sources requires further exploration to achieve the multi-level utilization of energy resources [186]. Therefore, the concept of integrated planning and operation dispatching of source–grid–load–storage can be applied. The efficient integration of energy production, transmission, consumption, and storage processes within the park is involved [187], enabling the organic combination of different energy sources and establishing a comprehensive energy network that operates synergistically. Energy utilization efficiency in the park is enhanced while effectively reducing carbon emissions, thereby advancing the development of the integrated energy system in the park towards the goal of achieving “zero carbon” emissions.

• The primary objective of implementing a comprehensive plan for zero-carbon parks is to facilitate scientific planning and construction by considering multiple factors. The orderly distribution and coordinated development of diverse energy sources, including electricity, gas, heat, and cooling, within the park are essential to maintain the residents’ quality of life. Achieving this requires collaboration among professionals such as urban planners, energy experts, and community representatives in the planning process. By thoroughly evaluating factors like park layout, transportation systems, infrastructure construction, energy conditions, and residents’ demands, we can execute rational planning for production base construction, network and pipeline design, and residential areas. This ensures the establishment of a diversified energy production model, achieves efficient integration of multiple energy sources, and meets the daily needs of community residents in all aspects of their lives.
• In accordance with the coupling relationships and conversion methods among different forms of energy, we reasonably utilize various energy conversion technologies and equipment to establish a comprehensive energy network featuring multi-energy interconnection and coupling integration within the zero-carbon park.
• Efforts are being made to vigorously promote the utilization of energy storage devices and facilitate the establishment of a more extensive energy reserve network, ensuring an adequate energy supply. Additionally, electric vehicles (EVs) can be integrated into the dispatching process as controllable loads and mobile energy storage units. We can increase the level of renewable energy consumption and reduce carbon emissions by guiding EVs in adjusting their charging and discharging schedules and optimizing their load profiles [188].
• The successful implementation of zero-carbon parks requires the active involvement of the government, businesses, and community residents. The government can promote the development of clean energy by formulating and implementing targeted policies, offering incentives to clean energy companies, and imposing penalties for excessive corporate carbon emissions. Additionally, clear regulations for corporate carbon management can be established. Businesses can utilize carbon trading market mechanisms to optimize their carbon management and adjust their emissions based on market conditions, allowing for a flexible and efficient approach to meeting emissions targets. Community residents can contribute to green energy production by participating in government-organized training programs and installing renewable energy equipment such as solar panels and small wind turbines in their homes.
• The establishment of an intelligent monitoring system lays the groundwork for the efficient and flexible operation of zero-carbon parks. By deploying a wide range of intelligent sensors and monitoring devices, along with cutting-edge perception technology, we can achieve real-time monitoring of the park’s comprehensive energy system. This, in turn, enables rapid understanding and effective management of the supply and demand dynamics of various energy types within the park. It also provides comprehensive and precise data to support scheduling plans, allowing for meticulous regulation of energy production, conversion efficiency, and storage operations. As a result, this ensures the coordinated and stable operation of the integrated energy system [189], meeting the energy demands of users.
• In developing and constructing zero-carbon parks, it is essential to stimulate social motivation and establish mechanisms for public participation. The first step is to create communication channels between the community and the energy system. By utilizing advanced smart metering and big data analysis technologies, we can collect real-time data for users’ energy consumption and feedback. This provides insights into user energy needs and preferences, enabling precise predictions of user-side load demand. By proactively adjusting the operational mode of the energy system in response to demand fluctuations, we can maintain stability. Furthermore, government incentives can encourage community residents to engage in the multi-energy market within the park [190], This leverages user-side flexibility in system dispatch and operations. Additionally, awareness and education campaigns should be conducted to promote low-carbon development concepts and emphasize social responsibilities. These efforts will enhance user understanding and support for sustainable development.

To fully leverage the interactive impacts and synergistic benefits across all aspects of the zero-carbon park’s energy system, it is essential to utilize the coupling relationships and complementary characteristics of different energy sources. This requires an integrated approach to planning and operating the park’s energy system, including source, grid, load, and storage components. A comprehensive management strategy can provide a robust operational framework for the zero-carbon park, enabling coordinated multi-energy production and optimizing energy transmission and distribution. Energy balance and stable supply are ensured, while significantly contributing to carbon reduction and sustainable development goals.

7. Conclusions

Due to the increasing coupling and interaction among the source, grid, load, and storage in the power system, traditional planning and dispatching methods are unable to effectively address the complex dynamic characteristics within the new power system, thereby compromising operational efficiency. Therefore, it is necessary to conduct comprehensive research and analysis on the new concept of integrated planning and operation dispatching of source–grid–load–storage. In this paper, based on the perspective of socio–cyber–physical coupling, we delve into theoretical concepts, key technologies, challenges and prospects, and practical applications. The research summary is provided below, along with future research prospects.

(1) Research Summary

• Theoretical Concepts and Trends: This review began by providing a comprehensive overview of the theoretical concepts related to the source, grid, load, and storage elements within the new power system. By deeply exploring the new changes and emerging trends in each area, particularly under the current development context, the study elucidated the complex coupling relationships among these components. This foundational understanding is crucial for developing integrated models that accurately reflect the dynamics of modern power systems, thereby enabling more effective planning and operation strategies.
• Key Technologies: Implementing integrated planning and operation for the new power system requires several key technologies. These include data collection, heterogeneous data integration, collaborative planning, optimization, security protection, and electricity market mechanisms. Each technology addresses specific challenges within the power system, contributing to a more cohesive and efficient operation. For instance, advanced data collection and integration techniques enable the comprehensive monitoring and analysis of system performance, while optimization algorithms facilitate better resource allocation and scheduling.
• Challenges and Future Prospects: The study also delved into the limitations of these technologies, providing a critical assessment of their current capabilities and identifying areas for future research. By addressing these challenges, such as data integration complexities, security vulnerabilities, and optimization inefficiencies, future advancements can significantly enhance the robustness and reliability of the power system. This prospective outlook guides ongoing research efforts towards addressing critical gaps and improving the overall performance of integrated power systems.
• Practical Applications: The potential value and applications of the integrated planning and operation model in large-scale engineering projects were thoroughly discussed. This includes the model’s role in advancing smart energy ecosystems in desertification areas and other significant engineering practices. By applying these integrated models in real-world scenarios, the study demonstrated how theoretical advancements can translate into practical benefits such as improved energy efficiency, reduced reliance on fossil fuels, and enhanced sustainability. These applications underscore the practical relevance and transformative potential of integrated planning and operation strategies in addressing contemporary energy challenges.

(2) Research Prospects

• Enhanced Analytical Methods: Future research should focus on developing enhanced analytical methods to better understand the complex interactions and causal relationships within power system components. This will provide more accurate theoretical support for modeling and analysis, enabling more precise and effective planning strategies.
• Advanced Data Analytics: Leveraging advanced data analytics and machine learning techniques to manage and interpret vast amounts of operational data will be crucial. This can significantly improve decision-making processes in planning and operations, leading to more responsive and adaptive power systems.
• Collaborative Technologies: Developing and refining technologies that facilitate collaborative planning and optimization across source–grid–load–storage components will be essential. Emphasis should be placed on integrated solutions that can adapt to evolving power system dynamics, fostering greater resilience and efficiency.
• Regulatory and Market Frameworks: It is crucial to encourage the establishment of supportive policies and regulatory frameworks that foster innovation in integrated planning and operation models. Furthermore, to create a more conducive environment for integrated power systems, additional research into electricity market mechanisms that promote efficiency and sustainability is warranted.
• Sustainability and Renewable Integration: Prioritizing research aimed at enhancing the integration of renewable energy sources, minimizing reliance on fossil fuels, and advancing sustainable practices within the power system is pivotal. This entails promoting technologies that facilitate the efficient use of renewable resources, aligning with global sustainability objectives.
• Practical Implementation: Future studies should also concentrate on the practical application of integrated planning and operation models in real-world scenarios. Pilot projects and case studies offer invaluable insights, validating theoretical models and bridging the divide between theory and practice.

In conclusion, the integrated planning and operation of source–grid–load–storage represents not only an inevitable trend in the evolution of power systems, but also a key strategic imperative for propelling the advancement of future power systems and the broader energy landscape. Through continuous innovation and refinement of this model, we are confident in our ability to tackle future energy challenges, accomplish sustainable energy development goals, and make significant contributions to socio-economic progress.