A Review of Distributed Energy Systems: Technologies, Classification, and Applications

Abstract

Climate change is worsening across the region, exacerbating the energy crisis, while traditional centralized energy systems struggle to meet people’s needs. Globally, countries are actively responding to this dual challenge of climate change and energy demand. In September 2020, China introduced a dual carbon target of “Carbon peak and carbon neutrality”. Since then, it has consistently encouraged and supported innovative research on carbon reduction and energy conservation through its resource policies. Distributed energy systems (DESs) are gaining favor in various countries due to their promising applications in energy and environmental realms, particularly in light of current imperatives for energy conservation, emission reduction, and relevant policies. This paper provides a retrospective analysis of recent research and applications of DESs, conducts a systematic classification and statistical overview of DES implementations, and offers insightful recommendations and future prospects for the advancement of DESs.

1. Introduction

With rapid economic growth, energy and environmental issues have become major challenges for the world, and the use of fossil fuels is recognized as a major source of greenhouse gas emissions [1]. In 2022, carbon dioxide emissions from energy use, industrial processes, vent combustion, and methane emissions grew by a record 0.8%, while emissions from energy use grew by 0.9%, as shown in Figure 1, which illustrates carbon emissions from 2013 to 2023 [2]. Primary energy consumption grew in the world, as shown in Figure 2 and Figure 3, which illustrate world primary energy consumption and the structure of world energy consumption in 2023. Global primary energy consumption has achieved a record high for the second consecutive year. Fossil fuels continue to underpin their development, accounting for 84% of their energy mix. The year 2023 saw a second consecutive record year for global primary energy consumption, as it grew by 2%, reaching 620 EJ. Its growth rate was 0.6% above its ten-year average and over 5% above its 2019 pre-COVID-19 level. A new record in the consumption of fossil fuels (in absolute terms) was recorded. In 2023, it fell to 81.5% compared to almost 81.9% in 2022.

In order to cope with the crisis of energy shortage and environmental pollution, all over the world people are actively promoting the research and application of renewable energy. There have been many studies and research on solar energy and wind energy [3,4]. The EU has introduced a series of policy measures to strengthen support for the clean energy transition. In May 2022, the EU issued the “European Joint Action Plan for Cheap, Secure and Sustainable Energy”, which proposed to increase the EU’s energy efficiency target from 9% to 13% by 2030 and provide an additional EUR 210 billion to breakthrough key clean energy technologies by 2027. By 2030, the share of renewable energy in the EU’s energy consumption will strive to increase to 45%.

China published a white paper titled “China’s Energy Transition” in August 2024, which aims to comprehensively introduce the historic achievements made in Chinese energy transition over the past decade and share the practices of China’s energy transition. China’s energy transformation is focused on ecological progress, accelerating the formation of a new model of energy consumption that is efficient, green, and inclusive and promotes coordinated carbon reduction, pollution reduction, and green growth so as to achieve harmonious coexistence between man and nature.

The DES is an important way to solve the global energy crisis and promote energy transformation. The DES usually refers to the establishment of energy systems around the user, including prime movers, waste heat recovery, energy storage, heat pumps (HPs), solar photovoltaics (PVs), small wind turbines (WTs), and other equipment that use renewable energy sources [5]. It can be used not only for power generation but also for co-generation and individual heating.

The DES offers a wide range of advantages over traditional centralized energy systems [6]. Renewable energy technologies contribute to much of the world’s electricity distribution and generation, becoming efficient, flexible in deployment, and economically competitive with traditional energy systems.

Renewable energy sources play a very important role in the new governance of the energy system, facilitating participation, providing resilience, and unlocking significant generation potential and flexibility. Their combination promotes diversification of ownership of energy assets and empowerment of demand, contributing to the goals of decarbonization, energy security, and market price efficiency [7].

Researchers have made many studies on the prospects of distributed energy applications as well as system optimized and system performance evaluation [8,9,10].

Through the statistics of the core journals of the “Web of Science” database, the following data information related to the DES research content is obtained. As shown in Figure 4, research on DESs from 2015 to 2024 has centered on various aspects, including energy systems, energy storage, control technologies, energy efficiency, energy consumption, optimization algorithms, and energy markets. Figure 5 depicts the interconnections among these popular research topics.

Figure 6 illustrates the evolution of research content over time. Initially, the focus was on elements, such as distributed generation in 2015, progressing to research on the impacts of energy systems, control technologies, and policy aspects. Subsequently, there was a shift towards investigating system energy efficiency and consumption, culminating in research on energy markets and energy trading by 2020.

The research on energy storage technology and economic analysis emphasizes the economic viability of various energy storage solutions. Zakeri employs Monte Carlo methods to assess the life cycle and equilibrium costs of these technologies, providing a crucial foundation for evaluating return on investment in energy storage applications [11]. This highlights the importance of thorough economic analysis when considering the deployment of energy storage systems.

In the realm of distributed generation and microgrid optimization, Liu et al. focus on battery energy storage systems (BESSs) and create optimization models using particle swarm optimization and interior point methods [12]. Their work underlines the significance of optimizing resource allocation within microgrids, presenting practical strategies for enhancing energy management. Similarly, Zhang proposes a layered system architecture model to improve the balance between local energy production and consumption, particularly in peer-to-peer (P2P) energy trading, thereby facilitating direct interactions among users [13].

Addressing uncertainty and planning methods in distributed energy systems, Fu reviews planning strategies that incorporate statistical machine learning and advanced AI techniques to manage the unpredictability of renewable energy sources [14]. Yan introduces a multi-microgrid trading strategy utilizing distributed robust optimization to tackle forecasting uncertainties while ensuring privacy protection [15]. Additionally, Brown’s case study in Victoria emphasizes the necessity for consumer-oriented policies in distributed energy systems, revealing a gap in current regulations [16]. Moura further explores innovative concepts, like virtual metering and P2P energy trading, analyzing their implications for policy development to better serve the interests of consumers [17].

The preceding research augments the contemporary comprehension of distributed energy systems (DESs) by delineating a plethora of challenges and potential resolutions in relation to technological constraints, national policies, and deployment tactics. This review study aspires to contribute further to this undertaking. Additionally, it is conspicuous from the literature that there exists a dearth of more extensive and meticulous studies on DESs. From the studies discussed above, it can be asserted that existing inquiries have concentrated on relatively specific scopes, particularly in terms of technology and applications, yet they have failed to furnish information regarding the concomitant challenges associated with DESs. This study endeavors to present a comprehensive scrutiny of DESs, mainly taking into account the technical, application, and other facets, as well as the challenges confronted and feasible solutions.

It details DESs from the following aspects:

• The application of different renewable energy technologies in DESs and their methods and research analysis;
• DES applications at different scale levels;
• DES challenges and their potential solutions.

In terms of this paper’s structure, Section 2 introduces the detailed research on DESs in recent years. Section 3 reviews the development and application of DESs in China, as well as the application of DESs at different scale levels in the world. Section 4 discusses the achievements of DESs in terms of technology, goals, etc., as well as the challenges faced by DESs and possible solutions. Section 5 classifies and summarizes the full text.

2. Research on Distributed Energy Systems

2.1. System Optimization

Researchers have proposed models and algorithms to optimize DESs from different perspectives such as design, operation, and planning [18,19,20]. In the design phase, the focus is on creating efficient system structures that can scale with demand. During operation, real-time optimization of resource allocation, scheduling, and event handling aims to maximize efficiency. In the planning phase, long-term objectives, such as capacity expansion and maintenance, are prioritized to ensure system sustainability. Recent advancements in computational methods and machine learning have significantly improved the ability to tackle complex DES optimization challenges, leading to more efficient systems across various industries.

2.1.1. System Design Optimization

Researchers have conducted extensive studies on the optimal design of DESs [21,22,23]. The design of DESs directly affects their energy efficiency, economic efficiency, and environmental efficiency.

The optimization of system aspects within distributed energy systems involves several key aspects, including system architecture design, power electronics matching, optimization of energy management and control strategies, integration of communication technologies, construction of intelligent monitoring and control systems, security enhancement, research on multi-energy scheduling algorithms, dynamic stability enhancement, and integration with conventional power systems.

In the field of modern energy management, researchers have proposed a variety of innovative methods and systems to improve the efficiency of energy storage and management. For example, Goebel and Jacobsen designed a system that enables aggregators to deliver controlled energy storage devices to multiple markets simultaneously [24]. In addition, Liu et al. improve energy management through the optimization of storage strategies, adopting robust game theory methods and distributed algorithms, taking into account the costs of generation and trading [25]. These studies demonstrate the possibilities of flexible management in complex energy markets.

In terms of renewable energy systems, Li et al. have developed a low-starting wind speed electro-electromagnetic hybrid collector, which can effectively use urban medium and low-speed wind for power generation [26]. At the same time, geothermal power plants designed by Martinez and others are combined with wind and photovoltaic sources to improve the stability of renewable energy generation [27]. In view of the uncertainty of photovoltaic output, Lu et al. put forward an economic operation strategy to mitigate its impact on the economy of the energy system [28]. In addition, Liu et al. have developed distributed energy systems that combine solar and hybrid storage, thereby reducing annual costs while optimizing energy savings and reducing CO₂ emissions [29].

In the study of optimization and algorithms, Zhang et al. proposed the enhanced dynamic reverse learning Jaya method, which was successfully applied to the mixed integer optimization of plate-fin heat exchangers, demonstrating its efficiency in solving complex nonlinear problems [30]. Ding et al. used graph theory to propose a dynamic programming method aimed at optimizing the location of energy stations and pipeline network layout to reduce load fluctuations and hydraulic imbalances [31]. Further, Specht et al. combined a heuristic model and a linear optimization model to develop a method to determine the electricity demand of homes and electric vehicles [32].

In terms of multi-energy systems and scheduling, Ye et al. proposed a multi-distributed energy system (MDES), which uses dual-objective optimization for capacity planning and scheduling and realizes benefit distribution through the Nash bargaining method [33]. At the same time, Wang et al. provide a tree structure describing various systems for the multi-level structure of Heating, Ventilation, and Air Conditioning (HAVC) systems, which improves the flexibility and adaptability of energy management [34].

Then, Zhang et al.‘s study integrated microchannel heat pipe arrays and thermoelectric generators into photovoltaic systems, using three-way valves to optimize heat flow, thereby improving power efficiency [35]. Yang et al. explore ways to improve wind power prediction accuracy, including power prediction strategies that take into account wind speed error tolerance, wind speed correction methods weighted by dynamic features of multi-source information, and key mathematical formulas and logical relationships in wind power generation prediction [36,37,38].

In addition, there are also studies focusing on the performance of energy storage systems, aiming to improve new energy consumption rates, reduce costs, and optimize energy storage capacity and system economics by developing distributed energy storage optimization models and scheduling strategies. Shao et al. built a distributed phase change material unit model and a photovoltaic energy storage system model and analyzed the actual capacity of the distributed energy system participating in scheduling [39]. Yang et al. proposed a double-layer optimization method for distributed shared energy storage with source network co-operation, achieving a 100% new energy consumption rate and reducing the peak–valley load difference by 61% [40]. Li et al. developed a distributed robust model for multi-microgrid systems, optimizing the energy storage capacity with electro-hydrogen hybrid energy storage. They also analyzed the economic costs of the systems under different energy storage configurations [41]. Rao et al. established a distributed energy storage optimization distribution model with multiple costs as the objective function and proposed an operation strategy of linkage between energy storage and demand response. This strategy effectively reduced the total annual cost of the distribution network and increased the new energy consumption rate [42].

These innovations not only provide new ideas for the sustainable development of energy systems but also point the way for future research.

2.1.2. System Operational Optimization

There has also been a great deal of research into the optimization of DES operation [43,44,45]. Inappropriate operating strategies may hinder the good benefits of DESs. Therefore, it is also important to choose a reasonable operation strategy. Operational optimization of DESs offers a number of advantages, including increased energy efficiency, reduced energy waste, increased system flexibility and robustness, reduced dependence on traditional energy sources, reduced environmental impact, promotion of energy diversification and renewable energy use, and improved power supply quality and reliability.

Energy management optimization of distributed energy systems can improve energy efficiency, balance supply and demand, reduce energy costs, enhance system flexibility, and promote the use of renewable energy, but it also faces challenges such as the characteristics of different energy types, the accuracy of demand forecasting, and the management of energy storage devices.

• Local energy market

Local energy markets are reshaping distributed energy systems by optimizing operations and boosting efficiency. They enable peer-to-peer trading, allowing consumers and producers to interact directly and maximize local renewable resources. With smart meters and advanced analytics, these markets facilitate real-time pricing and demand response, ensuring optimal energy allocation.

This decentralized approach enhances grid resilience and empowers communities to effectively manage their energy needs, creating a more sustainable energy ecosystem. Ge et al. developed a joint energy market for the procurement of local integrated energy system services, taking into account the flexibility of demand [46]. Zhang et al. introduced a peer-to-peer energy-sharing approach in decentralized energy systems (DESs) to promote carbon neutrality, enhancing self-sufficiency and reducing emissions. Their multi-energy sharing model maximizes social welfare, yielding a fully decentralized solution [47]. Khorasany et al. present a complete proposal for a trading energy market (TEM) as a framework for the design, implementation, and deployment of interactive energy solutions for microgrid energy management [48]. Zhang et al. investigated the distributed economic dispatch of microgrids with high renewable energy penetration and demand-side management in grid-connected mode [49]. Tao et al. proposed a market-based approach for allocating computing resources in distributed cloud computing services. This method reduces energy consumption costs while increasing revenue from cloud computing services [50].

• Microgrids and community energy management

Microgrids are critical for optimizing community energy management and distributed energy systems. They provide localized control over energy generation and consumption, enhancing efficiency and reliability.

By integrating renewable sources, like solar and wind, along with energy storage and demand response, microgrids enable communities to meet their specific energy needs. As the demand for sustainable solutions grows, effective microgrid management is essential for maximizing the performance of distributed energy systems. Karystinos et al. propose the interconnection of autonomous solar home systems to create an off-grid community microgrid that brings economic benefits to the community, which is a win–win solution for the community [51]. Liu et al. proposed a distributed robust energy management scheme for multiple interconnected energy microgrids (MGs) [52]. Fattaheian et al. propose an interaction-based energy management framework to operate a multi-microgrid distribution system (MMDS), presenting a new approach to determine tradable coordinator signals in a distributed manner to address energy prices as well as power loss and grid congestion issues [53].

• Smart grid and control strategy

Smart grids transform energy management for distributed energy systems by integrating advanced communication technologies and data analytics. They enable real-time monitoring and control, optimizing supply and demand while seamlessly incorporating renewable energy sources, storage, and demand response.

Effective control strategies are essential to maximize the potential of these systems, ensuring a sustainable and efficient energy future. Lefebure et al. compared different model predictive control (MPC) strategies for energy management in buildings and energy centers, proposing a distributed control approach based on pairwise decomposition to maximize energy-saving potential [54]. Yin designed a real-time distributed voltage control method for smart grids to replace traditional centralized approaches. In this method, controllers in neighboring regions communicate with one another, enabling global optimal voltage control across the entire smart grid without relying on a central controller [55]. Chang proposed a distributed energy system that combines a dynamic game model (DGM) with weather data from the Central Weather Bureau and verified its feasibility [56].

• Flexibility management and risk optimization

Flexibility management and risk optimization are crucial for optimizing distributed energy systems. With the rise of renewable energy and fluctuating demand, these systems face significant challenges. Flexibility management enhances responsiveness to emergencies and demand shifts, ensuring a reliable energy supply. Meanwhile, risk optimization helps identify and mitigate potential risks, improving resource allocation and operational strategies.

By integrating these approaches, organizations can enhance efficiency and support sustainable development in a dynamic market. Bhattacharya et al. propose a mathematical framework that takes into account the interplay of energy flexibility and renewable generation in a traded power system, mathematically linking system operating costs to available flexibility capacity [57]. Almeida et al. proposed an optimization approach for centralized day-ahead decisions, incorporating risk considerations for extreme events. They implemented both risk-neutral and risk-averse methods to address this challenge [58]. Kong et al. proposed a two-tier framework for optimizing energy community scheduling and sizing of shared energy storage systems. This framework incorporates a dynamic tariff strategy to address supply–demand imbalances, guiding community dispatch to reduce peak-to-valley differences while ensuring economic efficiency [59].

2.1.3. System Integration Optimization

Many researchers have also considered both design and operation to optimize DESs [60,61,62]. Due to the interplay of system configurations and operational strategies, integration optimization is essential to improve the performance of DESs, and the optimal design and operation of DESs is a complex and popular research topic.

Incorporating different influencing factors into the design of the entire distributed energy system is a complex and comprehensive task. In the process of system design, it is necessary to fully consider the influence of various factors such as technology, economy, environment, society, and policy.

• Energy sharing and management model

The integration and optimization of distributed energy systems are essential for enhancing energy sharing and management models. By leveraging diverse renewable energy sources and advanced technologies, these models facilitate more efficient energy use and promote sustainability. This approach enables communities to collaboratively manage their energy resources, balancing supply and demand while reducing reliance on traditional power grids.

Effective energy sharing not only maximizes the potential of distributed energy systems but also fosters resilience and innovation in energy management practices. Balakumar et al. proposed a distributed energy sharing program (DESP) to enable energy sharing among PV producers in a Smart Hybrid Microgrid (SHM) to enable PV producers to efficiently use energy [63]. Boudoudouh et al. proposed a multi-intelligentsia system for energy management of microgrids based on distributed hybrid renewable energy generation and distributed electricity consumption [64]. Gomes et al. explored community-owned renewable energy distribution among members’ buildings. Their no-cost model enhances the consumption–generation balance through individual demand response participation [65]. Si et al. proposed a multi-energy management strategy using demand complementarity, developing local optimization models for residential and industrial consumers to minimize global operating costs [66].

• Energy planning and dispatching

Energy planning and dispatching play a crucial role in the effective integration and optimization of distributed energy systems. As the energy landscape evolves, leveraging a variety of renewable sources becomes imperative for achieving reliability and sustainability. Effective planning ensures that these diverse energy resources are utilized efficiently, balancing supply and demand while minimizing costs.

By employing advanced dispatch strategies, communities can optimize energy flows, reduce emissions, and enhance grid resilience. This holistic approach not only supports the transition to a more decentralized energy model but also empowers consumers to participate actively in energy management. Xu et al. proposed a distributed multi-energy management framework for biogas–solar–wind interconnected microgrid co-operation for energy scheduling of multi-source microgrids [67]. Martínez et al. developed an energy planning model that incorporates geothermal energy as a dispatchable renewable source. The model determines the required power based on various scenario assumptions [68]. Xu et al. proposed a community multi-energy supply hub that integrates geothermal, solar, and wind energy. The framework utilizes geothermal hydrogen production and multi-energy conversion and storage devices to achieve a comprehensive energy supply [69]. Zhou et al. proposed a demand response model with day-ahead real-time pricing to address energy imbalances. They developed an optimal configuration method for multi-energy supply systems in industrial parks using a hybrid genetic and pattern search algorithm, analyzing the link between energy source complementarity and planning costs [70].

• Control method and optimization model

Control methods and optimization models are essential for effectively integrating and optimizing distributed energy systems. As the complexity of these systems increases, advanced control strategies are necessary to manage the variability of renewable energy sources. These methods enable precise coordination of energy generation, storage, and consumption, ensuring efficient resource utilization.

Optimization models further enhance the performance and reliability of distributed energy systems by facilitating communication among various energy technologies. This integration supports a smoother transition to sustainable energy solutions and empowers users to engage in responsive energy management practices. Moradi proposes a planning framework for active buildings as energy nanogrids [71]. Mori et al. proposed a process for the integration and optimization of renewable energy sources in a mountain hut power generation system [72]. Lin et al. critically analyzed and compared control methods for hybrid energy storage systems (HESSs) in microgrids and identified shortcomings of existing control methods [73]. Brusco et al. created a day-ahead optimization model for local energy storage communities to enhance self-consumption and ancillary services, increasing renewable energy penetration and customer flexibility through metered systems [74]. Zheng et al. propose a distributed multi-energy demand response approach with a layered building aggregator framework for smart building clusters. Their Caps Net-based forecasting models leverage load flexibility and energy complementarity to reduce costs [75].

2.2. System Performance Evaluation

With the development of DES technology, the evaluation of the system has increasingly become a hot research topic of concern. Many researchers have carried out a lot of research on this and proposed many new evaluation criteria and methods [76,77,78]. Reasonable and effective performance evaluation of the system is an important means of reducing costs and improving operational efficiency.

However, the criteria for evaluating DESs are still mainly in the three areas of average costs and benefits, energy saving rate, and carbon emission reduction rate.

Table 1. Evaluation of DESs in different aspects.

Evaluation Object	Evaluation Purpose	System Structure
Campus	Energy integration [79]	Multi-energy complementary system
	Reliability of energy supply [80]	Battery energy storage system
Office building	System comprehensive evaluation [81]	Multi-energy complementary system
Community	Network elasticity of power system [82]	Grid
	Flexible system for residential areas [83]	Distributed generation system
	Optimize microgrids for residential areas [84]	Independent microgrid
	System comprehensive evaluation [85]	Integrated energy system
Island	Meet the electricity needs [86]	Island energy system
	Distributed generation credible capacity [87]	Distributed generation system
State grid	Assess the value of regional systems [88]	Grid
Industrial park	Economic benefit evaluation [89]	Power storage system
	Determine the optimal operation strategy [90]	Integrated energy system
City-level grid	Assess the reliability of the grid [91]	Grid

shows the empirical research on distributed energy system evaluation in recent years.

Table 1 shows the evaluation of DESs. The contents emphasize significant advancements in the planning and design of hybrid renewable energy systems, emphasizing both economic and environmental aspects. They underscore the integration of renewable energy technologies and the resilience needed for future distributed energy power systems. Key components such as heat pumps and smart electric vehicle charging play crucial roles in enhancing self-consumption and reducing costs. The analysis of independent microgrids includes a techno-economic feasibility assessment, while the evaluation of battery BESSs focuses on their effectiveness during power outages. Methods for assessing distributed generation and storage capacity address uncertainties, improving overall reliability. Additionally, models that guide investments in distributed solar and wind systems, along with evaluations of energy storage’s economic efficiency, optimize returns. The reliability evaluation further reduces load-shedding costs, and the multi-energy system framework employs genetic algorithms and multi-criteria evaluation methods. Overall, these studies reflect a trend toward more sophisticated approaches in renewable energy planning, providing valuable insights into sustainable energy solutions.

2.3. Multi-Energy Complementary Energy System

While conventional DESs face limitations in practical engineering applications, MECESs typically combine renewable energy sources (such as solar, wind, biomass, and geothermal) with gas-fired CCHP systems. This hybrid approach may offer advantages over single-source systems in terms of cost, reliability, and efficiency. The general structure of a hybrid energy system is shown in Figure 7.

In recent years, HESs have garnered significant interest and attention from researchers both domestically and internationally.

As shown in Figure 8, in rural regions, MECESs are strategically designed to optimize the utilization of renewable resources such as solar, wind, and biomass energy. Solar power harnesses sunlight through photovoltaic panels to generate electricity for residential and agricultural use, particularly during peak sunny seasons. Wind energy is captured by small-scale wind turbines, which enhance the power supply in areas characterized by higher wind velocities. Furthermore, biomass energy leverages local agricultural residues and organic waste to produce usable energy via gasification or fermentation processes; this approach not only addresses waste management challenges but also delivers consistent heat and electricity for rural communities. This MECES can significantly bolster energy self-sufficiency while fostering sustainable economic development in rural areas.

Table 2. Research contents of the multi-energy system.

Refs.	Target	Key Point
[92]	Meet the energy needs of rural households	Multi-dimensional evaluation system
[93]	Integrating regional clean energy	Clustering regional energy systems
[94]	Meet the cold and hot needs of large solar areas	Low-temperature district heating
[95]	Distributed energy capacity planning	Economic cost minimization
[96]	The analysis quantifies the complementarity of multi-energy net load	Multi-objective energy model
[97]	Quantitative analysis of complementary effects of energy	Multi-energy net load correlation
[98]	Increase the penetration rate of renewable energy	Transmission loss optimization
[99]	Improve the efficient use of renewable energy	Game-theoretic framework Energy trading
[100]	Energy interaction and co-operative operation of energy stations	Joint demand response

shows the research contents of MECESs. MECESs are gaining attention for their role in enhancing energy efficiency and sustainability. Researchers have created models to maximize renewable energy use and reduce costs through effective integration. This includes co-operative operation models that consider transmission losses and employ advanced multi-energy management strategies. Game-theoretic frameworks have been introduced for optimizing interactions between renewable energy suppliers and consumers, boosting profits and welfare. Additionally, two-tier scheduling optimization improves co-operation among power stations, integrating demand response to alleviate peak pressures and lower emissions. Stochastic programming methods address the complexities of renewable energy and multi-energy loads, emphasizing the significance of energy source complementarity for achieving economic efficiency and effective risk management.

2.4. The Effect of Parameters on DESs

Several parameters significantly influence the performance and optimal outcomes of DESs. To demonstrate the impact of these factors, researchers have conducted sensitivity analyses focusing on economic indicators, energy demand, and system parameters within DESs.

2.4.1. Economy

Sensitivity analyses of economic parameters include mainly fuel prices and electricity prices. Typically, energy prices are a key economic factor affecting system performance, and a wealth of results have been achieved in energy price sensitivity analyses [101,102,103,104]. Among these studies, this study analyzes the relationship between energy costs and market transactions.

Table 3. Economic evaluation of DESs.

Scale	Application Scenario	Main Evaluation Parameters
Urban	Energy market	Total cost of generating electricity [105]
		Total costs, carbon emissions [106]
Community	Energy market	Energy pricing [107]
		Transaction price [21]
		Energy retail pricing [108]
	DESs	Maximum and average economic loss [109]
Rural	Distributed photovoltaic	Carbon emissions, average electricity prices [110]
Industrial building	Water resource recovery	Net present value [111]

shows the economic evaluation of DESs. Fluctuations in energy costs have a significant impact on market trading prices, further affecting the supply and demand balance of the energy market and the decision making of market participants. They will also integrate consumers’ willingness to participate in the energy trading market. The optimal balance of system energy cost is found in the form of a multi-objective optimization decision.

2.4.2. Technology

The technical analysis of distributed energy encompasses several key aspects. It begins with studying various types of distributed energy sources, such as solar, wind, and bioenergy, to grasp their technical characteristics and application scenarios. System integration is crucial, focusing on effectively connecting distributed energy with traditional power grids and microgrids through established technical standards and interface protocols. Additionally, designing and optimizing energy management systems (EMSs) is vital, incorporating demand response and energy storage solutions. Economic analysis evaluates the project’s viability by assessing the return on investment, operating costs, and the impact of policy incentives, while also considering environmental effects, including greenhouse gas emissions. Evaluating technological maturity helps gauge market acceptance and development progress. Furthermore, safety and reliability analyses ensure operational stability, and policies and standards influence the adoption of these technologies. A comprehensive examination of these elements reveals the technical characteristics of distributed energy and its significant role in the future energy landscape.

Table 4. Technical evaluation of DESs.

System Scale	Application Scenario	Main Evaluation Parameters
Building	Energy demand balance	Consumption of heat and cold [112]
	Building heating	Average cost of heating [113]
	Energy supply	Satisfaction rate [114]
Community	Distributed generation	Satisfaction rate [115]
		The optimum size [116]
		Pressure drop of gas pipe network [117]
	Multi-energy microgrid	Energy load dispatching [118]
Industrial Park	Multi-energy microgrid	Daily energy storage, short dynamic payback period [119]

shows the technical evaluation of DESs.

The above studies aim to strengthen innovative approaches to multi-energy systems by emphasizing the concept of multi-energy complementarity, with a special focus on parametric analysis. The key mechanism identified is a hybrid pricing structure that combines real-time incentives with distributed energy purchase prices designed to minimize total costs and optimize thermal power generation. This study also proposes a two-stage optimal planning framework for distributed energy networks powered by solar, geothermal, and natural gas, aiming to improve economic, energy, and environmental performance through integrated parameter analysis. Other advancements include an optimized two-story retail pricing scheme that facilitates demand response in multi-energy buildings and a real-time approach that aligns planned and actual energy needs. Practical application shows that the combination of solar collectors and heat storage systems can significantly improve the energy efficiency of buildings. There are also studies that use a meta-heuristic approach to determine the optimal configuration of distributed generator sets while simulating community models to assess environmental sustainability and economic viability. Overall, these studies highlight the critical importance of multi-energy complementarity in achieving efficient energy management and addressing challenges, such as uncertainties in renewable generation and limitations of existing reliability indicators, in evaluating distributed energy sources.

3. DES Applications

Information Regarding the Application of DESs in China

Global electricity generation increased by 2.5% in 2023 to reach a record level of 29,925 TWh. Figure 9 illustrates renewable energy generation from 2013 to 2023. Recording a growth rate that was 25% faster than total global primary energy consumption suggests that the world’s energy system is increasingly electrifying. Coal retained its position as the dominant fuel for power generation, with fossil fuels overall forming 60% of global electricity generation. Renewables’ share of total power generation rose from 29% to 30%. In 2023, grid-scale battery electricity storage system (BESS) capacity stood at 56 GW, nearly 50% of which was installed in China.

Figure 10 and Figure 11 show the installed capacity of solar and wind power, respectively, over the past 10 years. Solar and wind capacity continued to grow rapidly in 2023, beating the previous year’s record of 276 GW by around 186 GW, a 67% increase. Solar accounted for 75% (346 GW) of the capacity additions, with China responsible for around a quarter of the growth. Wind achieved a record year for new builds with over 115 GW coming online. Nearly 66% of capacity additions were in China, and its total installed capacity is now equal to North America and Europe combined.

Green energy investments and RE consumption reduce carbon emissions, while non-renewable energy consumption and economic growth increase carbon emissions in both the short and long term. Long-term reductions in carbon emissions could imply a transition to carbon neutrality. China should encourage green energy investment and increase the share of RE to ensure long-term carbon neutrality [120]. Heating areas in China are divided into northern urban areas, northern urban areas, northern rural areas, and southern areas. Energy-efficient and affordable distributed heating technologies are promoted in rural and southern areas. In addition, energy-efficient retrofitting of buildings is critical to reducing heating energy demand and should be prioritized [121].

Table 5. Application of DESs in different regions of China.

Region	Research Focus	Application Scenario
National	Analyze the Chinese present situation of the application of distributed generation and description [122]	—
National	Explore the application of blockchain in distributed transactions [123]	—
Lianyungang (City)	Optimization of distributed power generation systems [124]	Hospital
Eastern coastal area	Flexible management of DES power, cooling, heating, and steam energy [125]	Community
Northern Shandong region	Straw burning has a significant impact on the environment [126]	Rural area
Tianjin (City)	Align daily economic objectives with temporary demand response and environmental benefits [127]	Office building
North China	Evaluate the capacity expansion potential of photovoltaic systems [128]	Comprehensive energy park

shows the applications of DESs in different regions of China. These applications have focused on the application and optimization of distributed energy systems, with a focus on various renewable energy sources such as natural gas, photovoltaics, and wind. This study identifies policy deficiencies and development barriers while proposing countermeasures to promote the growth of distributed energy. Innovations such as blockchain integration for energy trading and interval optimization models that address energy price and demand uncertainty have emerged, providing a new framework for efficient operations. In addition, multi-objective mathematical planning models have been developed to minimize costs, emissions, and energy biases and to assess environmental impacts through life cycle assessments. The common goal of these efforts is to improve the flexibility, sustainability, and economic viability of distributed energy systems across the country.

There are also studies analyzing the prospects and potential for distributed energy in China [129,130]. In these research contents, the impacts of regional characteristics and local policies on the application and implementation of distributed energy systems in different regions are analyzed and compared. These research contents have certain reference values for the large-scale application of distributed energy systems or regional energy utilization and management.

Table 6. Application of DESs on different scales.

Level	Grid Type	Load Type	DES Technology
Neighborhood level	Grid Tied	Stable	Integration of wind, photovoltaic, and biomass generation systems [131]
	Off-Grid	Intermittent	PV system [132]
	Grid Tied Grid Tied Off-Grid	Intermittent Intermittent Off-grid microgrid system	A multi-energy complementary CCHP system [133] PV system and wind turbines [134] A CCHP system with a two-way connection to the grid [135]
Community level	Grid Tied	Stable	Solar and biogas generator energy systems [136]
	Grid Tied Off-Grid Grid Tied Grid Tied Grid Tied Off-Grid Grid Tied	Intermittent Stable Intermittent Stable Stable Off-grid microgrid system Stable	PV system containing energy storage [137] Hydrogen, heat, and electricity co-generation system based on solar energy [138] Regionally distributed hydrogen energy systems [139] PV system and wind turbine [140] Hybrid PV, wind, and battery system [141] Hybrid wind, solar, and battery microgrids [142] RES-CCHP-MG [143]
Urban level	Grid Tied	Intermittent	CCHP with hybrid centralized energy storage [144]
		Stable	Geothermal with ORC [145]
		Intermittent	Geothermal driven CCHP [146]
		Stable Stable	Low-temperature geothermal power system [147] DES-CCHP [148]

further elucidates the diversity of DES technologies employed in both off-grid and grid-connected configurations across various scales, along with optimal selections for different load profiles. In off-grid systems, particularly at neighborhood and community levels, prevalent technologies encompass PV systems and hybrid renewable energy systems, which primarily address intermittent loads. These systems often necessitate flexible energy management solutions for storage and scheduling to ensure a reliable energy supply. For grid-connected systems, especially at community and city levels, integrated energy systems that combine PV and geothermal resources are frequently utilized, as well as CCHP systems incorporating wind and PV. Such configurations effectively mitigate the volatility associated with renewable energy sources and cater to stable load requirements. Additionally, hybrid renewable energy systems and geothermal-powered Organic Rankine Cycle (ORC) systems are increasingly promoted in regional and city-level applications to provide stable, intermittent, or integrated energy supplies tailored to diverse load types. Overall, these DES technologies demonstrate adaptability and flexibility in addressing stable, intermittent, and isolated off-grid load demands, thereby meeting the energy needs of various environments and regions.

4. Discussion and Prospects

The DES as an important driving force of energy transformation, and its future development will profoundly affect the change in the global energy structure. With the continuous progress of technology and the gradual strengthening of policy support, the application of DESs in the world will be further expanded. In 2023, global electricity generation increased by 2.5% to a record 29,925 TWh (data from BP Statistical Review of World Energy, 2024) [2], with renewables accounting for 30% of the total. Solar and wind installations are growing rapidly, with solar accounting for 75% of new installations, and China is playing a key role in both areas, accounting for a large portion of the global growth. In order to fully understand the future development trend of DESs, we can explore it from multiple dimensions such as technological innovation, market dynamics, policy drivers, challenges, and solutions.

As shown in Figure 12, in the future, distributed energy will form a close information and energy interaction network between urban and rural areas, improving the resilience of the energy system. Rural areas with abundant renewable energy resources, such as solar and wind energy, can enhance the reliability of energy supply through smart grid interconnection with the city. In times of extreme weather or natural disasters, rural distributed energy systems can serve as an important “backup force” to ensure the continuity of energy supplies. At the same time, rural energy can provide green support for cities and promote low-carbon development. Through the integration of information technology and smart grids, urban and rural energy connectivity will be more efficient, promoting the optimization of energy use and system stability and improving overall energy security and sustainability.

4.1. The DES Develops in the Direction of Intelligence and Integration

In the future, distributed energy systems will not be limited to a single energy production and storage device but a highly integrated and intelligent ecosystem. This transformation will depend on technological advances in several areas.

• Smart grid and demand response

With the rapid development of smart grid technology, distributed energy systems will achieve more accurate energy management. Smart grids can monitor and adjust the power supply and demand balance in real time to ensure the stable operation of the power system. Through demand response technology, consumers can participate in the adjustment of electricity demand, and smart devices will automatically adjust electricity consumption behavior based on real-time electricity price, load demand, and other information. In spot market conditions, we analyzed the interactions between microgrids, demand response, PV investment, and pricing mechanisms and found that market transactions and economic incentives can significantly promote investment in solar and battery storage [149].

• Energy Internet and distributed collaboration

The distributed energy system of the future will no longer rely on a single energy supply but through the energy Internet, through digital technology to connect multiple distributed power sources (such as solar, wind, biomass) and energy storage systems (such as batteries, hydrogen storage). By integrating advanced sensing, communication, and control technologies, the energy Internet has the potential to reshape power generation, distribution, and consumption. Smart grids, such as dynamic pricing, distributed generation, and demand management, have far-reaching implications for ICT in the energy Internet. The synergy between the smart grid and the energy Internet not only improves energy efficiency but also helps reduce the operating costs of communication networks and data centers [150]. This energy co-operation mode can effectively solve the instability of single energy and realize energy complementarity.

• Energy storage technology breakthrough and cost reduction

Energy storage technology is one of the cores of the future development of DESs, and at present, battery energy storage, hydrogen energy storage, compressed air energy storage, and other technologies are developing rapidly. With the advancement of materials science and the expansion of production scale, energy storage technology will further reduce costs and improve energy efficiency. In particular, the emergence of new energy storage technologies, such as solid-state batteries and flow batteries, may be applied on a large scale in the future, helping to solve the intermittency problem of renewable energy generation. Combining thermal energy storage with power storage technologies, such as supercapacitors and lithium batteries, improves energy efficiency within distributed energy systems by integrating hybrid energy storage, focusing on the synergy of different energy storage systems while optimizing system configuration and operational strategies to improve performance and reduce costs [151].

• Microgrid of distributed energy systems

As a typical application of distributed energy systems, microgrids will be widely promoted in the future. Microgrids can operate independently and interact with the main power grid to achieve independent energy supply in local areas. Power networks are vulnerable to various hazards, especially in remote areas or disaster and emergency situations, and microgrids can ensure the continuity and stability of the power supply [152]. With a network microgrid centered on production and consumption, Coco integrates distributed energy resources, mobile energy storage devices, and demand response strategies to improve the resilience and emergency recovery ability of the system in bad weather and evaluates its performance in natural disasters through simulations and experiments.

4.2. Growth and Diversification of Distributed Energy Markets

As renewable energy technologies continue to mature and costs fall, the distributed energy market will grow rapidly on several levels.

• The scale of the distributed generation market

Distributed generation is expected to account for a larger market share of global energy supply by 2030. Residential and commercial buildings, industrial facilities, and other types of users will increasingly choose distributed photovoltaic, wind power, geothermal energy, and other technologies as the main sources of energy. Especially, in the rapidly urbanized areas, distributed energy systems will become an important means to solve the contradiction between energy supply and demand. In this regard, power system flexibility is particularly important, especially on the demand side, for providing an acceptable level of power quality for the needs of consumers [153]. Due to the uncertainty and capacity variation of distributed energy resource-rich systems, various power quality problems may be caused. Therefore, without sacrificing user comfort and utility, it is essential to establish an energy balance between generation and demand, improve the reliability and stability of the power system, and minimize energy costs.

• Energy as a service

As consumer demand for personalized and flexible energy services grows, the energy-as-a-service (EaaS) model will emerge in the distributed energy market. With EaaS, users do not need to invest in expensive energy equipment but obtain an on-demand energy supply through leasing or subscription. The company will provide end-to-end energy management services, including energy production, storage, supply, dispatch, and more, to help consumers reduce energy costs and achieve sustainable development goals.

However, there are serious frequency regulation problems in high renewable permeable power systems. In order to solve the frequency regulation problem in high renewable permeable power systems, the researchers propose an optimized distributed resource scheduling method to improve frequency modulation efficiency and reduce communication delay [154]. By dynamically adjusting the resource allocation of communication equipment and the wireless spectrum, the frequency adjustment accuracy can be guaranteed and the system instability caused by communication delay can be reduced. In addition, collaborative optimization based on intelligent algorithms and real-time monitoring systems can more effectively coordinate the participation of distributed resources and improve the response speed and reliability of the overall system. Future research will further explore how to optimize the application of distributed resources in frequency regulation under different communication technologies, network architectures, and spectrum resources to ensure the stable operation of high renewable energy power systems.

• Driving carbon markets and green finance

In the future, with the gradual improvement of the global carbon market, distributed energy systems will become an important part of the carbon trading market. Through carbon credit trading, businesses and individuals can benefit from the use of renewable energy, further promoting the development of green finance. Peer-to-peer (P2P) energy trading offers a promising way for producers and consumers to conduct bilateral and multilateral transactions, further helping to integrate distributed energy into the distribution grid and promote the low-carbon operation of the system [155]. But, realizing this potential requires overcoming challenges in model formulation and distributed optimization. This will provide more financial support for distributed energy investments and facilitate their rapid deployment.

4.3. Challenges and Solutions

Despite the promise of distributed energy systems, there are still some challenges to their development, and addressing these challenges is key to future success.

• Intermittency and instability of renewable energy

Energy storage systems (ESSs) are indispensable in modern energy infrastructure, addressing critical issues such as efficiency, power quality, and reliability in both DC and AC power systems. ESSs play a pivotal role in maintaining grid stability and facilitating the seamless integration of renewable energy sources into the grid. These systems are essential for various applications, including aviation, shipboard systems, and electric vehicles, offering cost-effective solutions for managing peak load demands while enhancing overall system reliability and efficiency [156]. Recent advancements in research have led to the development of high-power energy storage technologies, such as supercapacitors, superconducting magnetic energy storage (SMES), and flywheels, which feature high power density and rapid response capabilities, making them particularly suitable for scenarios requiring swift charge and discharge cycles. Moreover, the integration of hybrid energy storage systems with diverse energy storage devices provides enhanced flexibility, demonstrating increasing appeal across a wide range of applications, especially in supporting critical loads. Despite significant progress in energy storage technology, the inherent volatility of renewable energy continues to pose challenges to the stability of distributed energy systems.

Future efforts should focus on optimizing power systems, improving system flexibility, and reinforcing the synergy between energy storage and demand response mechanisms to ensure continuous and stable power supply.

• Technical standards and interoperability issues

With the application of different types of distributed energy technologies, how to ensure the interoperability of equipment and systems will be the key to achieving the large-scale promotion of distributed energy. Developing unified technical standards and protocols to promote the seamless connection of smart grids, energy storage systems, sensor networks, and other devices will be an important task in the future.

• Social cognition and user engagement

Despite the significant economic and environmental benefits of distributed energy systems, some users still lack awareness or active participation.

At present, the existing market participation mechanism has some shortcomings in ensuring the balance of interests of all parties, protecting the rights and interests of vulnerable participants, and improving the autonomous participation mechanism of market entities. These problems lead to the long-term infringement of the interests of some participants and then affect their participation enthusiasm [157]. In the multi-entity market environment, there is a lack of effective tools and programs to balance the interests of all parties. Therefore, there is an urgent need to design a new market participation approach to build multi-level integrated community energy systems that include multiple independent energy entities such as sources, loads, and energy storage facilities.

In the future, governments, enterprises, and scientific research institutions need to strengthen public education and publicity, improve consumer awareness and acceptance of distributed energy technologies, and promote more users to participate in the energy transition.

5. Conclusions

DESs are pivotal in the energy transition, providing enhanced efficiency, flexibility, and economic advantages compared to traditional centralized power generation. A defining characteristic of DESs is their capacity to localize energy production near end users, thereby minimizing carbon emissions and advancing the objective of achieving low or near-zero carbon emissions. In this context, renewable energy sources such as solar, wind, and geothermal play a vital role in enhancing the sustainability of DESs and are integral to global initiatives aimed at reducing carbon emissions.

DESs can be categorized from various perspectives. Firstly, they may be classified into grid-connected systems and off-grid systems based on their connection mode with the power grid; secondly, they can also be further subdivided according to application priority and load type. For smaller-scale buildings, like residential homes and small commercial establishments, the DES typically integrates multiple energy technologies, including solar photovoltaics, wind power, and energy storage solutions (such as solid oxide fuel cells and proton exchange membrane fuel cells), along with biomass for electricity generation and heating purposes. In these compact applications, combining waste heat recovery systems with renewable energies significantly reduces fossil fuel dependency while lowering CO₂ emissions.

At broader urban or regional scales, implementing the DES necessitates the consideration of the overall environmental development within the locality. Large-scale distributed energy systems demand sophisticated network management frameworks to maintain equilibrium between energy supply and demand dynamics. For instance, in urban applications, it is crucial not only to facilitate access to renewable resources but also to implement intelligent grid management strategies that address varying load demands alongside fluctuating energy availability. Furthermore, depending on user requirements, different types of distributed grids can be delineated into stable versus intermittent supply systems; intermittent configurations often depend heavily on renewables whose output is susceptible to meteorological conditions—hence, effective energy storage technologies must be employed for ensuring system stability and reliability.

Regarding renewable energy-driven DESs, solar power, wind generation methods (including offshore installations), hydropower, and biomass combustion processes are the primary contributors. To enhance the efficiency and penetration of solar technology, several targeted improvements should be considered. Firstly, for photovoltaic panels, it is essential to develop more efficient materials, such as perovskite solar cells, to improve photovoltaic conversion efficiency. Additionally, reducing production costs, particularly in raw material procurement and manufacturing processes, can facilitate the widespread adoption of solar panels. Moreover, enhancing the heat exchange efficiency of solar water heaters and optimizing the heat storage system can minimize energy loss and extend their service life. For thermoelectric generators, improving their thermoelectric conversion efficiency and reducing costs will enable broader applications in various fields, including remote areas and specialized applications.

In addition to solar energy, wind, hydropower, and biomass are essential pillars in the global energy transition. To enhance the efficiency of these technologies, the wind power sector can focus on developing lighter and stronger turbine blades while leveraging artificial intelligence and big data analytics to improve wind resource forecasting and optimize wind farm operations. Offshore wind development will prioritize innovations in floating wind platforms and foster better integration with oil and gas platforms through advanced load sharing and dynamic management strategies, leading to reduced operating costs, lower wind curtailment, and decreased carbon emissions [158]. Hydropower remains a cornerstone of renewable energy worldwide, and its efficiency can be further boosted by optimizing dam designs and turbine technologies. Advanced turbine designs and water flow management techniques can increase power generation and reduce ecological impact. Small hydropower plants in remote areas can provide clean, localized electricity, broadening the scope of hydropower applications. Biomass energy, another vital renewable resource, stands to gain from advancements in combustion, gasification, and pyrolysis technologies, further improving efficiency and lowering emissions. Additionally, converting agricultural and municipal waste into biogas not only produces clean energy but also offers an effective solution to waste disposal, providing sustainable energy options for local communities.

To achieve efficient integration of these energy technologies, it is imperative to develop cross-cutting smart grid systems. Smart grids can optimize the output of various types of renewable energy based on real-time supply and demand, avoid energy waste, and ensure stable power supply. Meanwhile, the development of energy storage technologies, such as lithium batteries and large-scale energy storage systems, will help mitigate the instability of renewable energy, thereby increasing its penetration in the energy system. By integrating solar, wind, hydro, and biomass energy with smart grids and energy storage technology innovations, we can effectively promote the global energy structure’s transformation towards a low-carbon and sustainable direction.

Notably, among these technologies are solar innovations encompassing photovoltaic panels and thermoelectric generators alongside solar water heaters, which have seen widespread adoption globally while continuing an upward growth trajectory. As an illustration for 2023, the total global capacity for BESSs is projected at 55.7 GW, with nearly half installed within China alone; concurrently, worldwide installed capacities for both solar arrays/wind turbines continue ascending—with an additional 186 GW added during 2023, a remarkable increase by 67% year on year where approximately three-quarters stemmed from solar contributions (346 GW), with China accounting roughly one-fourth thereof. The wind sector has similarly experienced unprecedented expansion, adding over 115 GW of new capacity—two-thirds originating from Chinese developments specifically. It is noteworthy that Europe retains its leadership position regarding offshore wind share, comprising about twelve percent of its total generated output; however, China’s offshore capabilities have surged, reaching around thirty-seven gigawatts and surpassing Europe’s thirty-two gigawatt benchmark, respectively. Moreover, more than fifty-six gigawatts of fresh installation occurred across European territories throughout 2023, representing sixteen percent of the newly established global totals.

Overall, the future of DESs is both promising and challenging. With the combined forces of technological innovation, policy support, and growing market demand, distributed energy will be widely deployed across the globe, emerging as a key pillar in the transformation of the global energy landscape. From enhancing energy autonomy and enabling intelligent management to driving the achievement of carbon neutrality, distributed energy systems will play a pivotal role in advancing the sustainable development of the world’s energy sector.