Search Results (256)

The weak grid strength in regions with large-scale renewable energy integration has emerged as a universal challenge, limiting the further expansion of renewable energy development. Currently, the short-circuit ratio (SCR) is widely used to quantify the relative strength between AC systems and renewable energy. To address this issue, this study first analyzes and compares how different reactive power compensation methods enhance the SCR. It then proposes calculation frameworks for both the SCR and critical short-circuit ratio (CSCR) in renewable energy grid-connected systems integrated with reactive power compensation. Furthermore, based on these formulations, a quantitative evaluation methodology for voltage support strength is developed to systematically assess the improvement effects of various compensation approaches on grid strength. Finally, case studies verify that reactive power compensation provided by synchronous condensers effectively strengthens grid strength and facilitates the safe expansion of the renewable energy integration scale. Full article

Today’s power grids are being modernized with the integration of new technologies, making them increasingly efficient, secure, and flexible. One of these technologies, which is beginning to make great contributions to distribution systems, is solid-state transformers (SSTs), motivating the present technical and economic study of local level 2 distribution systems in Colombia. Taking into account Resolution 015 of 2018 issued by the Energy and Gas Regulatory Commission (CREG), which establishes the economic and quality parameters for the remuneration of electricity operators, the possibility of using these new technologies in electricity networks, particularly distribution networks, was studied. The methodology for developing this study consisted of creating a reference framework describing the topologies implemented in local distribution systems (LDSs), followed by a technical and economic evaluation based on demand management and asset remuneration through special construction units, providing alternatives for the digitization and modernization of the Colombian electricity market. The research revealed the advantages of SST technologies, such as reactive power compensation, surge protection, bidirectional flow, voltage drops, harmonic mitigation, voltage regulation, size reduction, and decreased short-circuit currents. These benefits can be leveraged by distribution network operators to properly manage these types of technologies, allowing them to be better prepared for the transition to smart grids. Full article

This study presents a practical and scalable framework for the mid- to long-term distribution network planning that reflects real-world infrastructure constraints and investment requirements. While traditional methods often rely on simplified network models or reactive reinforcement strategies, the proposed approach introduces an investment-oriented planning model that explicitly incorporates physical elements such as duct capacity, pole availability, and installation feasibility. A linear programming (LP) formulation is adopted to determine the optimal routing and sizing of new facilities under technical constraints including voltage regulation, power balance, and substation capacity limits. To validate the model’s effectiveness, actual infrastructure and load data were used. The results show that the model can derive cost-efficient expansion strategies over a five-year horizon by prioritizing existing infrastructure use and flexibly adapting to spatial limitations. The proposed approach enables utility planners to make realistic, data-driven decisions and supports diverse scenario analyses through a modular structure. By embedding investment logic directly into the network model, this framework bridges the gap between high-level planning strategies and the engineering realities of distribution system expansion. Full article

With the deterioration of the global climate, the losses caused by distribution network failures during natural disasters such as typhoons have become increasingly serious. In the whole process of disaster resistance, it is very important to effectively identify the weak links in distribution networks during typhoon disasters. In this paper, the weak links in distribution networks during typhoons are identified dynamically from four indexes: real-time failure rate, load loss caused by line disconnection, line degree, and line betweenness. First, the Batts typhoon model is established to simulate the whole process of the typhoon and obtain the real-time failure rate of the distribution network. Secondly, the distribution network is powered by distributed generators when there are line disconnections, and a mixed integer linear programming model is established to solve the problem. Then, the line degrees and the line betweenness are calculated to obtain the structure indexes of the line, both of which are dynamically related to the power flow and the loads of the distribution network. Finally, the four indexes are comprehensively analyzed, and the dynamic identification of the weak links in the distribution network are realized by the analytic hierarchy process (AHP)—entropy weight (EW)—technique for order preference by similarity to an ideal solution (TOPSIS) method. The results of the case study show that the proposed method can effectively identify the weak links in a distribution network during a typhoon and provide a reference to resist extreme disasters. Full article

Off-grid and isolated rural communities in developing countries with limited resources require energy supplies for daily residential use and social, economic, and commercial activities. The use of data from space assets and space-based solar power is a feasible solution for addressing ground-based energy insecurity when harnessed in a hybrid manner. Advances in space solar power systems are recognized to be feasible sources of renewable energy. Their usefulness arises due to advances in satellite and space technology, making valuable space data available for smart grid design in these remote areas. In this case study, an isolated village in Namibia, characterized by high levels of solar irradiation and limited wind availability, is identified. Using NASA data, an autonomous hybrid system incorporating a solar photovoltaic array, a wind turbine, storage batteries, and a backup generator is designed. The local load profile, solar irradiation, and wind speed data were employed to ensure an accurate system model. Using HOMER Pro software V 3.14.2 for system simulation, a more advanced AI optimization was performed utilizing Grey Wolf Optimization and Harris Hawks Optimization, which are two metaheuristic algorithms. The results obtained show that the best performance was obtained with the Grey Wolf Optimization algorithm. This method achieved a minimum energy cost of USD 0.268/kWh. This paper presents the results obtained and demonstrates that advanced optimization techniques can enhance both the hybrid system’s financial cost and energy production efficiency, contributing to a sustainable electricity supply regime in this isolated rural community. Full article

With the increasing deployment of DC power systems, particularly in DC distribution systems, there is a growing demand for rapid and effective fault current limiting solutions. Conventional fault current limiters (FCLs) often suffer from limitations in terms of response time, size, and operational complexity. As a solution to these challenges, this paper proposes a hybrid FCL based on a pyro conductor switch (PCS), which combines passive limiting elements with an active switching mechanism. The proposed PCS FCL consists of a pyro fuse, an IGBT switch, a limiting inductor, and a damping resistor. Upon fault detection, the IGBT switch is first turned off to initiate current transfer into the limiting branch. Subsequently, the pyro fuse operates by explosively severing the embedded conductor using a pyrotechnic charge, thereby providing galvanic isolation and reinforcing current commutation into a high-impedance path. This operational characteristic enables effective fault current suppression without requiring complex control or real-time sensing. A detailed analysis using PSCAD/EMTDC simulations was conducted to evaluate the current limiting characteristics under fault conditions, and a prototype was subsequently developed to validate its performance. The simulation results were verified through experimental testing, indicating the limiter’s ability to reduce peak fault current. Furthermore, the results demonstrated that the degree of current limitation can be effectively designed through the selection of appropriate current limiting parameters. This demonstrates that the proposed PCS-based FCL provides a practical and scalable solution for improving protection in DC power distribution systems. Full article

Distributed generation (DG) within the electrical distribution network (DN) has witnessed significant expansion globally, attributed to both technological advancements and environmental benefits. However, uncoordinated integration of DG in suboptimal locations can negatively influence the operational efficacy through issues such as increased power losses, voltage fluctuations, and protection coordination issues of the DN. Consequently, the optimal allocation of DG represents a critical element of consideration. Furthermore, the integration of network reconfiguration (NR) alongside DG units has the potential to significantly enhance system performance with only the existing infrastructure. Therefore, this work focuses on improving DN performance with optimal DG integration along with NR. The considered objectives are minimization of active power loss (APL) and cost of annual energy loss (CAEL). CAEL minimization by DG allocation and NR under multiple load models is addressed for the first time in this study. The efficacy of the employed hiking optimization algorithm (HOA) is illustrated through its application to the IEEE 33-Bus DN under various scenarios of DG operational power factors (PFs). A comparative analysis between the HOA and other reported methodologies is presented. Additionally, the results obtained for CAEL in case 6 (DG allocation with NR) are approximately 22.3% better that the best reported results of CAEL without NR, thereby affirming the usefulness of integrating the NR during DG allocation. Full article

Within the context of global warming, the frequent occurrence of extreme weather may lead to problems, such as a sharp decrease in new energy output, insufficient system backups, and an increase in the amount of energy consumed by users, resulting in large-scale power shortages within the grid for a short period of time. With the increase in the numbers of electric vehicles (EVs) and microgrids (MGs), which are resilient resources, the ability of a system to participate in demand response (DR) is further improved, which may make up for short-term power shortages. In this paper, we first propose a charging and discharging model for EVs during the onset of a cold wave, and then perform load forecasting for EVs during cold wave weather based on user behavioral characteristics. Secondly, in order to accurately portray the flexible regulation capability of microgrids with massively flexible resource access, this paper adopts the convex packet fitting expression based on MGFOR to characterize the flexible regulation capability of MGs. Then, the Conditional Value at Risk (CVaR) is used to quantify the uncertainty of wind and solar power generation, and a two-layer model with the objective of minimizing the operation cost in the upper layer and maximizing the rate of new energy consumption in the lower layer is proposed and solved using Karush–Kuhn–Tucker (KKT) conditions. Finally, the proposed method is verified through examples to ensure the economic operation of the system and improve the new energy consumption rate of the system. Full article

Hybrid renewable energy systems (HRESs) play a key role in the decarbonization of many sectors of the economy and, thus, in achieving ambitious climate goals. Due to the complexity of the issues and the impact of many factors on the efficiency of these systems, it is necessary to ensure that they are properly designed, managed, and optimized. Many techniques and methods are used to achieve an optimal multi-source energy system. In recent years, there has been a growing interest in HRESs. Taking this into account, a comprehensive review of scientific literature was carried out, based on bibliometric analysis. Professional software was used for the research: Bibliometrix and VOSviewer. The bibliographic database was created using the international scientific platform Web of Science. The evolution of research trends and the dynamic development of research on the management and optimization of HRESs in the years 2010–2024 were presented. The results of the analysis confirmed the growing importance of integrated energy management systems and optimization strategies in the context of the global energy transformation. The analysis also indicated that, despite the growing interest in this topic, further development of advanced energy management strategies and optimization methods is necessary to effectively use renewable energy sources and enhance the stability of HRESs. Full article

With the increasing liberalization of energy markets, the penetration of renewable clean energy sources, such as photovoltaics and wind power, has gradually increased, providing more sustainable energy solutions for energy-intensive industrial sectors or parks, such as iron and steel production. However, the issues of the intermittency and volatility of renewable energy have become increasingly evident in practical applications, and the economic performance and operational efficiency of localized microgrid systems also demand thorough consideration, posing significant challenges to the decision and management of power system operation. A smart microgrid can effectively enhance the flexibility, reliability, and resilience of the grid, through the frequent interaction of generation–grid–load. Therefore, this paper will provide a comprehensive summary of existing knowledge and a review of the research progress on the methodologies and strategies of modeling technologies for intelligent power systems integrating renewable energy in industrial production. Full article

The quantity of wind and photovoltaic power-based distributed generators (DGs) is continually rising within the distribution network, presenting obstacles to its safe, steady, and cost-effective functioning. Active distribution network dynamic reconfiguration (ADNDR) improves the consumption rate of renewable energy, reduces line losses, and optimizes voltage quality by optimizing the distribution network structure. Despite being formulated as a highly dimensional and combinatorial nonconvex stochastic programming task, conventional model-based solvers often suffer from computational inefficiency and approximation errors, whereas population-based search methods frequently exhibit premature convergence to suboptimal solutions. Moreover, when dealing with high-dimensional ADNDR problems, these algorithms often face modeling difficulties due to their large scale. Deep reinforcement learning algorithms can effectively solve the problems above. Therefore, by combining the graph attention network (GAT) with the deep deterministic policy gradient (DDPG) algorithm, a method based on the graph attention network deep deterministic policy gradient (GATDDPG) algorithm is proposed to online solve the ADNDR problem with the uncertain outputs of DGs and loads. Firstly, considering the uncertainty in distributed power generation outputs and loads, a nonlinear stochastic optimization mathematical model for ADNDR is constructed. Secondly, to mitigate the dimensionality of the decision space in ADNDR, a cyclic topology encoding mechanism is implemented, which leverages graph-theoretic principles to reformulate the grid infrastructure as an adaptive structural mapping characterized by time-varying node–edge interactions Furthermore, the GATDDPG method proposed in this paper is used to solve the ADNDR problem. The GAT is employed to extract characteristics pertaining to the distribution network state, while the DDPG serves the purpose of enhancing the process of reconfiguration decision-making. This collaboration aims to ensure the safe, stable, and cost-effective operation of the distribution network. Finally, we verified the effectiveness of our method using an enhanced IEEE 33-bus power system model. The outcomes of the simulations demonstrate its capacity to significantly enhance the economic performance and stability of the distribution network, thereby affirming the proposed method’s effectiveness in this study. Full article

To address the challenges of inefficiency, vulnerability to attacks, and the lack of transparency and fairness in distributed power trading, a distributed power trading mechanism based on blockchain smart contracts is proposed. Firstly, a strategy for matching distributed power trading orders is designed, and a model for managing user credit is constructed using the entropy weight method and deviation cost. Secondly, a smart contract for distributed power trading is compiled using the Solidity language. Finally, the designed smart contract is deployed, tested, and a distributed power trading network is simulated. The security analysis indicates that the Merkle Tree structure and PoW consensus mechanism effectively ensure the data and system security of distributed power transactions. Simulation test results demonstrate that the transaction mechanism can reliably complete transaction settlements, safeguard the interests of trustworthy users, and enhance the economic benefits of both parties involved in the transaction. Full article

With recent technological advancements, advanced communication technology, sensors and distributed generation (DG), it is an undeniable fact that modern power systems are flooded with massive amounts of data. These vast amount of generated data are difficult to interpret and comprehend, and are slow to sort through and explain. With ever increasing renewable power generation, grid operators should gain insights on identifying the vulnerabilities, behaviour and interactions of various power system components and anticipate challenges to enhance power system resiliency. Visualisation offers a means to reveal patterns, trends and connections in data that speed up and present information to a power system operator in a way that can be well understood topographically and provide an ability to accommodate increasing DG resources. Hence, this paper presents a comprehensive literature review of several visualisation techniques that can be embedded for improving operational efficiency and resiliency in modern power grids embedded with distributed and renewable energy resources. Full article

At present, the Colombian government is faced with the challenge of guaranteeing access to energy services for all its inhabitants. However, as there are isolated populations or populations with difficult access to conventional electricity grids in the country, it is necessary to seek innovative and appropriate solutions to the conditions and needs of the so-called non-interconnected zones (NIZs), which allow the generation and consumption of energy in a local, efficient, and safe way for all users. For this reason, this research consisted of studying and proposing technological solutions that use distributed energy resources, making the most of the energy potential in each area, as a proposed solution to the problems faced by NIZs with energy shortages. As a result, a series of proposals with microgrids are obtained, taking advantage of their flexible characteristics and using NRES as energy sources, mitigating pollution and contributing to the energy transition sought by the Colombian government. Full article

In the present article, the impacts that arise in electrical grids due to the integration of distributed energy resources (DER) are identified and analyzed, aiming to provide a basis from which the effects of these new technologies can be considered. To conduct this research, information was collected and analyzed, which was classified according to each of the impacts evidenced in the literature, such as technical, economic, social, environmental, sectoral, and political. Considering the classification of impacts by category, the corresponding advantages and disadvantages were highlighted, and based on this, a qualitative evaluation of the information found was conducted along with respective analyses. Thus, based on the development of this article, it can be concluded that DER influences many aspects, and according to the qualitative evaluation, clarity is provided regarding the contribution of each impact within electrical grids. It was found that, out of 100% of the impacts identified, those with the highest percentage of contribution are the technical impacts. Full article