Sustainable Energy Grids & Networks最新文献

{"title":"A generalized Nash-in-Nash bargaining solution to allocating energy loss and network usage cost of buildings in peer-to-peer trading market","authors":"Yuanxing Xia ,&nbsp;Yu Huang ,&nbsp;Jicheng Fang","doi":"10.1016/j.segan.2025.101628","DOIUrl":"10.1016/j.segan.2025.101628","url":null,"abstract":"<div><div>Although the peer-to-peer (P2P) energy market has emerged as a promising method to accommodate the distributed energy resources (DERs) on the demand side, the different stakeholders in the market make the energy loss allocation and network usage cost problems hard to solve. Considering the inconsistent interests of various market entities, we propose a generalized Nash-in-Nash bargaining (GNNB) model for the trading result, network usage cost, and energy loss allocation in the P2P market among buildings. We first establish the profit maximization models of distribution system operators (DSO) and building managers in P2P markets. A tripartite Nash bargaining model is developed to depict the negotiation among these entities. We then equivalently transform the Nash bargaining problem into two subproblems. A nested market-clearing algorithm based on the alternating direction method of multipliers (ADMM) is developed to solve the P2P energy market equilibrium with these bargaining results. We finally import two cases to verify the effectiveness of the GNNB solution. The heterogeneous network usage prices in the GNNB solution balance the interests of DSO and building managers. It can be concluded from the numerical results that the energy losses are allocated according to market participants’ trading amounts. Therefore, the negotiation result is fair. Our proposed model presents a fair framework to determine the network cost and energy loss allocation for the P2P energy market. It can be applied to optimize the trading result and energy loss in the local energy market project. All three parties will be satisfied with this welfare distribution.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"42 ","pages":"Article 101628"},"PeriodicalIF":4.8,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143328124","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Distributed energy management coordinating energy scheduling and trading in transactive energy market","authors":"Dewen Liu ,&nbsp;Zhao Luo ,&nbsp;Junkai Liang ,&nbsp;Hua Wang ,&nbsp;Jiahao Li ,&nbsp;Yujun Yin ,&nbsp;Yang Yu ,&nbsp;Hesen Liang","doi":"10.1016/j.segan.2025.101629","DOIUrl":"10.1016/j.segan.2025.101629","url":null,"abstract":"<div><div>The emergence of prosumers that is capable of both generating and consuming energy, coupled with advancements in communication technology, is driving the traditional energy market towards decentralization. Consequently, a novel transactive energy market (TEM) has evolved, enabling prosumers to trade energy in a distributed manner. The TEM allows prosumers to trade transactive energy in a distributed manner. To address the challenges associated with TEM, this study proposes a distributed energy management framework that coordinates energy scheduling and trading. In this model, energy scheduling and energy trading were coordinated in TEM. Specifically, a consensus-based energy supply and demand matching algorithm is proposed to balance local energy trading. Next, based on the matching results of the energy supply and demand in the TEM, a bilateral peer-to-peer energy trading algorithm based on the alternating direction method of multipliers (ADMM) is proposed to support sellers in selecting trading partners independently according to the bilateral location. This measure reduced TEM operating costs. To improve ADMM convergence, an iteration-based adaptive penalty parameter ADMM (IAPP-ADMM) algorithm is proposed. Numerical simulations based on a 14-node test system prove the effectiveness and rationality of the proposed framework.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"41 ","pages":"Article 101629"},"PeriodicalIF":4.8,"publicationDate":"2025-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143177822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Increasing hosting capacity of low-voltage distribution network using smart charging based on local and dynamic capacity limits","authors":"Marc Cañigueral ,&nbsp;Rick Wolbertus ,&nbsp;Joaquim Meléndez","doi":"10.1016/j.segan.2025.101626","DOIUrl":"10.1016/j.segan.2025.101626","url":null,"abstract":"<div><div>While the Municipality of Amsterdam wants to expand the electric vehicle public charging infrastructure to reach carbon-neutral objectives, the Distribution System Operator cannot allow new charging stations where low-voltage transformers are reaching their maximum capacity. To solve this situation, a smart charging project called Flexpower is being tested in some districts. Charging power is limited during peak times to avoid grid congestion and, therefore, enable the expansion of charging infrastructure while deferring grid investments. This work simulates the implementation of the Flexpower strategy with high penetration of electric vehicles, considering dynamic and local power limits, to assess the impact on both the satisfaction of electric vehicle users and the business model of the Charging Point Operator. A stochastic approach, based on Gaussian Mixture Models, has been used to model different profiles of electric vehicle users using data from the Amsterdam public electric vehicle charging infrastructure. Several key performance indicators have been defined to assess the impact of such charging limitations on the different stakeholders. The results show that, while Amsterdam’s existing public charging infrastructure can host just twice the current electric vehicle demand, the application of Flexpower will enable the growth in charging stations without requiring grid upgrades. Even with 7 times more charging sessions, Flexpower could provide a power peak reduction of 57% while supplying 98% of the total energy required by electric vehicle users.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"41 ","pages":"Article 101626"},"PeriodicalIF":4.8,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143177817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-agent reinforcement learning for decentralized control of shared battery energy storage system in residential community","authors":"Amit Joshi ,&nbsp;Massimo Tipaldi ,&nbsp;Luigi Glielmo","doi":"10.1016/j.segan.2025.101627","DOIUrl":"10.1016/j.segan.2025.101627","url":null,"abstract":"<div><div>This article proposes a data-driven decentralized control scheme for a battery energy storage system, shared among residential PV households characterized by their respective uncontrollable demand and PV generation. The households are connected to the grid via the point of common coupling and are accordingly billed by the utility company. We firstly translate the decentralized control objective into a multi-agent reinforcement learning (MARL) problem by modelling the interaction between the agents and their environment as a Markov Game. Thereafter, we present the novel Distributed Subgradient <span><math><mrow><mi>Q</mi><mo>−</mo></mrow></math></span>learners (DSQL) algorithm based on the localization of the Hyper<span><math><mrow><mo>−</mo><mi>Q</mi></mrow></math></span> function and the coordination among the learning agents connected via a communication network. The proposed algorithm holds merit in addressing the typical key-aspects of MARL algorithms, i.e., scalability, privacy and fairness. Finally, we perform numerical simulations by using real historical demand, PV generation and electricity tariff data and highlight the key advantages of the proposed algorithm w.r.t. the state-of-art, in terms of economic savings and key-performance indicators, such as peak-to-average ratio, valley-to-average ratio and root-mean-squared-deviation.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"41 ","pages":"Article 101627"},"PeriodicalIF":4.8,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143177812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficient coordinated VAR planning for enhancing voltage stability of wind-penetrated power system using hybrid surrogate technique","authors":"Qianggang Wang,&nbsp;Xinying Zheng,&nbsp;Yuan Chi,&nbsp;Jinsheng Guo,&nbsp;Xin Zhou","doi":"10.1016/j.segan.2025.101620","DOIUrl":"10.1016/j.segan.2025.101620","url":null,"abstract":"<div><div>The rising integration of renewable power generation and the corresponding complex dynamics of the system pose challenges to the dynamic analysis of modern power systems. To reduce computational costs and enhance efficiency, a cost-effective hybrid surrogate model is adopted to approximate complex electromechanical transient (EMT) models for the improvement of voltage stability in a coordinated VAR planning problem. Firstly, the framework of an efficient planning model based on hybrid surrogate model is introduced. The hybrid model integrates the advantages of Polynomial Chaos Expansion and Kriging techniques. To further reduce the size of training samples required by the data-driven hybrid-surrogate-model-based approach without a compromise in the accuracy, and to improve the efficiency of solving the optimization problem, an efficient input selection strategy is proposed for the surrogate model and outputs are also designed to reduce the complexity. Finally, the proposed method is verified in a reactive power source deployment problem of wind-penetrated power systems to verify the effectiveness on an IEEE 39-bus system with wind farms.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"41 ","pages":"Article 101620"},"PeriodicalIF":4.8,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143177818","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"On synergies between congestion management instruments: The Dutch case-study","authors":"Bart van der Holst ,&nbsp;Gijs Verhoeven ,&nbsp;Leo van Schooten ,&nbsp;Irena Dukovska ,&nbsp;Phuong Nguyen ,&nbsp;Johan Morren ,&nbsp;Koen Kok","doi":"10.1016/j.segan.2025.101623","DOIUrl":"10.1016/j.segan.2025.101623","url":null,"abstract":"<div><div>To address grid congestion in distribution networks, Distribution System Operators (DSOs) are exploring new congestion management instruments. Since 2022, market parties in The Netherlands can provide congestion management through capacity- and energy-based bilateral contracts. Additionally, new grid tariffs are being explored that incentivize peak shaving for small end-users. However, the interactions between these instruments are not well understood. This paper presents an integrated modeling approach to analyze the interplay between three grid tariff candidates and the two bilateral contract types in a low-voltage setting. Prosumers and congestion service providers (CSPs) are modeled using economic moving-horizon control, and a novel mixed-integer second-order cone programming formulation is introduced for day-ahead bilateral contract activation by the DSO. Results show that a seasonal peak tariff is the most effective tariff, particularly in mitigating load synchronization issues due to low market prices. Combining grid tariffs with bilateral contracts effectively managed congestion in summer. In winter, when congestion was caused by electric vehicles, adding active congestion management to the grid tariffs through contracts proved only beneficial if CSP portfolios contained sufficient flexibility. These findings highlight the need to carefully consider asset types, available flexibility, and market conditions for effective congestion management.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"41 ","pages":"Article 101623"},"PeriodicalIF":4.8,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143177821","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improving computational performance for estimating voltage stability margin in large power systems via a penalized second-order cone programming","authors":"Long Fu ,&nbsp;Yaran Li ,&nbsp;Wei Wang ,&nbsp;Tongming Liu ,&nbsp;Zhao Yang Dong ,&nbsp;Keren Yu","doi":"10.1016/j.segan.2025.101621","DOIUrl":"10.1016/j.segan.2025.101621","url":null,"abstract":"<div><div>Precisely estimating voltage stability margin (VSM) in large power systems is challenging due to problem size and complexity. In this paper, a penalized second-order cone programming (SOCP) for estimating VSM is proposed based on a phase angle approximation and sufficient cycle condition which are effective in tightening angle relaxations whilst avoiding increased computational burden. An appropriate trade-off between accuracy and efficiency can be achieved by the proposed SOCP which improves the computational performance for estimating VSM in large power systems.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"42 ","pages":"Article 101621"},"PeriodicalIF":4.8,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143428037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Collaborative planning and optimal scheduling for a specific distribution network area containing multiple microgrids based on a Game-theoretic approach","authors":"Yi Yang ,&nbsp;Jingang Wang ,&nbsp;Pengcheng Zhao ,&nbsp;Yiran Dong ,&nbsp;Xiaowei Fan","doi":"10.1016/j.segan.2025.101625","DOIUrl":"10.1016/j.segan.2025.101625","url":null,"abstract":"<div><div>In the context of sustainable development, microgrids, as carriers of renewable energy consumption, can realize energy saving and emission reduction and multi-energy complementarity, but the uncertainty of demand and fluctuation of renewable energy output will seriously threaten the reliability of grid operation. However, the interconnection between neighboring microgrids in a specific region can realize stable system operation and flexible scheduling in a larger spatial and temporal range. Therefore, this paper investigates the planning and operation strategies for the interconnection of multiple microgrids in a specific distribution network area. First, the distribution system is divided into multiple subjects of interest including centralized wind farms and shared energy storage plants. Second, an integrated demand response strategy that takes into account load differences is proposed, and a one-master-multiple-slave two-layer hybrid game optimization model with the system operator as the leader is established to play the game of interests and solve the optimal operation strategy. Finally, the results of example analysis show that the proposed strategy and model can realize the cooperative interconnection of multi-microgrid areas, promote the investment and construction and participation in system scheduling of each subject under the distribution network area, and improve the economic and environmental benefits of the system.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"41 ","pages":"Article 101625"},"PeriodicalIF":4.8,"publicationDate":"2025-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143177820","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Explainable representative-days clustering on low-voltage grid meters and feeders, with noise-aware multi-objective Bayesian optimization, applied to grid-congestion events","authors":"Konstantinos Theodorakos ,&nbsp;Oscar Mauricio Agudelo ,&nbsp;Thijs Becker ,&nbsp;Koen Vanthournout ,&nbsp;Reinhilde D’hulst ,&nbsp;Bart De Moor","doi":"10.1016/j.segan.2025.101622","DOIUrl":"10.1016/j.segan.2025.101622","url":null,"abstract":"<div><div>Low-voltage grid (LVG) state estimations help in expansion planning and preventing congestion events. However, country-scale simulations pose high computational burdens. A solution that reduces calculation time is to cluster similar days, and only simulate the most representative day of each cluster. Using real-world, quarter-hour residential consumption time series from 925 meters, congestion event probabilities from 146 real feeders, 51 daily meteorological and 12 calendar features, we propose a novel end-to-end representative-days clustering framework. Along with <span><math><mi>k</mi></math></span>-medoids clustering, we use dimensionality reduction (kernel principal component analysis, factor analysis, …) and pre/post-processing. To emphasize quarter-hour extremes, we apply dynamic data squeezing/expansion, based on the LVG consumption median. Our approach is scalable because dimensionality reduction compresses thousands of daily variables into up to 300 components, regardless of the amount of meters and exogenous features (weather, calendar, …). Multi-objective Bayesian optimization for noisy functions, along with Sobol sampling, finds the hyperparameters that minimize the <span><math><mi>k</mi></math></span> representative-day reconstruction error compared to the full-year simulation. Explainability is achieved via tree ensemble classification on the decided clusters: ranking of the most important meteorological and calendar features, along with rule induction for future clustering decisions. We applied these techniques to successfully cluster all days of 2016 of the Flemish LVG (in Belgium). Our approach works well on both meter consumptions and feeder congestion event approximations. Photosynthetic radiation (visible spectrum and solar panel absorption wavelengths), water temperature, soil water volume/temperature (variables with a recent weather memory effect) and albedo were the most important meteorological factors, along with calendar features.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"41 ","pages":"Article 101622"},"PeriodicalIF":4.8,"publicationDate":"2025-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143177810","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimal energy management with discomfort calculation in residential buildings considering load shifting and home battery storage system","authors":"Ricardo Faia,&nbsp;Pedro Faria,&nbsp;Zita Vale","doi":"10.1016/j.segan.2025.101624","DOIUrl":"10.1016/j.segan.2025.101624","url":null,"abstract":"<div><div>This paper introduces an innovative approach to residential energy management by integrating load shifting options and battery storage systems. It is considered a linear model along with various levels of user discomfort associated with shifts in appliance schedules. The study examines how optimized load shifting can synchronize energy-intensive activities with periods of low demand, resulting in reduced costs and user discomfort. The objective function minimizes the weighted sum of energy costs and discomfort calculations derived from appliance shifts. Different weighting factors in the objective function yield varying levels of inconvenience for end-users, allowing them to tailor the approach to their preferences. This comprehensive strategy offers valuable insights into optimizing residential energy management while addressing user comfort concerns. Additionally, the case study contributes a dataset of shiftable home appliances, serving as a valuable resource for evaluating the effectiveness of novel approaches to this problem.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"41 ","pages":"Article 101624"},"PeriodicalIF":4.8,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143177811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}