Sustainable Energy Grids & Networks最新文献

{"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}

{"title":"Power system dynamic analysis in future energy scenarios with high penetration of renewable energy sources — case study: Sicilian electrical grid","authors":"Rossano Musca ,&nbsp;Eleonora Riva Sanseverino ,&nbsp;Gaetano Zizzo ,&nbsp;Antony Vasile ,&nbsp;Adriano Iaria ,&nbsp;Angelo L’Abbate ,&nbsp;Lorenzo Vitulano","doi":"10.1016/j.segan.2024.101616","DOIUrl":"10.1016/j.segan.2024.101616","url":null,"abstract":"<div><div>In the near future, Sicily will undergo an unprecedented penetration of renewable sources in its electricity generation mix. In response to these developments, several grid enhancement initiatives have been planned, including HVDC infrastructure and interconnections with foreign systems. This paper presents the results of dynamic studies on 2030 energy scenarios developed by the Italian institute Ricerca Sistema Energetico (RSE). These studies consider severe contingencies and evaluate various combinations of regulating resources, both traditional and innovative, including Grid Forming control. The results indicate that relying solely on traditional regulation during contingencies leads to instability, emphasizing the urgent need to involve all available resources in the power system’s regulation mechanisms. Among the most interesting findings is the case of the Grid Forming control applied to the Tyrrhenian Link: even in the absence of regulation from the renewable sources present on the island, this approach successfully keeps the frequency drift within the permissible 1.5 Hz range. This demonstrates the significant strategic value of the infrastructure when deployed to provide dynamic support to the power system.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"41 ","pages":"Article 101616"},"PeriodicalIF":4.8,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143177815","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":"Enhancing voltage optimization in distribution networks through flexible operation of EV parking lots","authors":"Michele De Santis ,&nbsp;Tohid Harighi ,&nbsp;Anna Rita Di Fazio ,&nbsp;Alberto Borghetti ,&nbsp;Mario Russo","doi":"10.1016/j.segan.2024.101601","DOIUrl":"10.1016/j.segan.2024.101601","url":null,"abstract":"<div><div>This study focuses on the use of consumption flexibility provided by a parking lot (PL) equipped with charging stations for electric vehicles to improve the voltage control in distribution networks. A methodology is presented in which PL offers both upward and downward flexibility of power consumption, provided that energy recovery is guaranteed in subsequent time intervals. To define the flexibility offered by the PL, the proposed approach uses a stochastic optimization model that computes the day-ahead absorption profiles and the maximum allowable flexibility for each 15-minute interval, expressed in terms of the power adjustment capability of the PL in response to the distribution system operator (DSO) request. The DSO then optimizes the voltage profile of the distribution network using the power flexibility offered by the PLs, as well as by other distributed energy resources (DERs). A multiperiod horizon is used in the voltage optimization problem to account for the effects of energy recovery in subsequent intervals. The results are presented for simulations of 24-hour operation of the IEEE 123-node test feeder with four flexible PLs and 15 DERs, whose reactive powers can be varied. The results for two days show an improvement of approximately 70% in terms of voltage profiles in comparison with the case without any voltage optimization, with 30% of the specific contribution of PLs compared to only DERs optimization. The full recovery in terms of the energy provided by each PL is verified, and a cost analysis from the DSO perspective is presented.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"41 ","pages":"Article 101601"},"PeriodicalIF":4.8,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143178600","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":"Generation of low-voltage synthetic grid data for energy system modeling with the pylovo tool","authors":"Beneharo Reveron Baecker ,&nbsp;Soner Candas ,&nbsp;Deniz Tepe ,&nbsp;Anurag Mohapatra","doi":"10.1016/j.segan.2024.101617","DOIUrl":"10.1016/j.segan.2024.101617","url":null,"abstract":"<div><div>The ongoing energy transition introduces challenges in designing energy systems, particularly at the low-voltage level, where additional loads like electric vehicle charging points and heat pumps are predominantly connected. Obtaining accurate grid data for modeling and analysis is hindered by availability and confidentiality concerns, especially for low-voltage distribution grids. Unlike high voltage grids, low-voltage grids lack standardized handling due to their large size and heterogeneity. This research addresses an essential gap in the availability of grid data, offering a methodological base to generate synthetic low-voltage grids based on geospatial data. This includes the consideration of multiple feeders per transformer, greenfield and brownfield transformer positioning, and variable dimensioning of equipment components. Based on data clustering methods and an algorithmic graph-based approach, the tool provides a scalable solution that is applicable to large areas such as cities, states, or even countries with hundreds of thousands of grids. The tool is designed for Germany but can be adapted to other countries with similar low voltage grid structures, provided the necessary geospatial data are available. The derived representative synthetic grid topologies support the development of more resilient and efficient future energy systems by enabling research on specific issues like grid planning and reinforcement while considering regional constraints, such as grid congestion or voltage violations. This supports a comprehensive understanding of low-voltage energy systems in the context of the energy transition.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"41 ","pages":"Article 101617"},"PeriodicalIF":4.8,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143177816","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":"Bi-level programming model of electric vehicle charging station based on orderly charging scheduling","authors":"Jiyong Li,&nbsp;Zeyi Hua,&nbsp;Chengye Liu","doi":"10.1016/j.segan.2025.101619","DOIUrl":"10.1016/j.segan.2025.101619","url":null,"abstract":"<div><div>The escalating global energy crisis and severe environmental challenges have led to increased attention on energy-saving, clean, and zero-emission electric vehicles (EVs) from countries worldwide. Effective planning of electric vehicle charging stations (EVCSs) can enhance user satisfaction with charging services and be integrated with an orderly charging strategy. This integration improves the spatial-temporal distribution of charging loads through vehicle-to-grid interaction, thereby reducing the peak-to-valley load difference and enhancing the operational efficiency of public EVCSs. This paper presents a bi-level programming model. The upper model focuses on optimizing the combination of slow and fast charging stations to achieve the best economic return. The lower model predicts and schedules the charging loads of EV users in an orderly manner to minimize user charging costs and the peak-to-valley difference in charging loads. The proposed model is applied to a case study in a region of Beijing, with planning results compared and analyzed. The results indicate that the proposed bi-level planning model for EVCSs demonstrates advantages in enhancing overall economic benefits and reducing peak charging loads when compared to scenarios with incomplete considerations. Specifically, total investment is decreased by 1.621 million yuan, user charging costs are reduced by 46 %, global economic benefits increase by 2.7933 million yuan, the peak value of charging load is reduced by 22.19 %, and the peak-to-valley difference of load throughout the day is reduced by 25.08 %. This study provides objective decision-making recommendations for optimal location and sizing setting of EVCSs, thereby contributing to the sustainable development of the electric vehicle industry.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"41 ","pages":"Article 101619"},"PeriodicalIF":4.8,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143177814","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":"Radial partitioning with spectral penalty parameter selection in distributed optimization for power systems","authors":"Mehdi Karimi","doi":"10.1016/j.segan.2024.101613","DOIUrl":"10.1016/j.segan.2024.101613","url":null,"abstract":"<div><div>This paper introduces a novel concept of intelligent partitioning for group-based distributed optimization (DO) algorithms applied to optimal power flow (OPF) problems. Radial partitioning of the graph of a network is introduced as a systematic way to split a large-scale problem into more tractable sub-problems, which can potentially be solved efficiently with methods such as convex relaxations. Spectral parameter selection is introduced for group-based DO as a crucial hyper-parameter selection step in DO. A software package DiCARP is created, which is implemented in Python using the Pyomo optimization package. Through several numerical examples, we compare the proposed group-based algorithm to component-based approaches, evaluate our radial partitioning method against other partitioning strategies, and assess adaptive parameter selection in comparison to non-adaptive methods. The results highlight the critical role of effective partitioning and parameter selection in solving large-scale network optimization problems.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"41 ","pages":"Article 101613"},"PeriodicalIF":4.8,"publicationDate":"2024-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143177813","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}