Sustainable Energy Grids & Networks最新文献

{"title":"Cooperative price-based demand response program for multiple aggregators based on multi-agent reinforcement learning and Shapley-value","authors":"Alejandro Fraija ,&nbsp;Nilson Henao ,&nbsp;Kodjo Agbossou ,&nbsp;Sousso Kelouwani ,&nbsp;Michaël Fournier","doi":"10.1016/j.segan.2024.101560","DOIUrl":"10.1016/j.segan.2024.101560","url":null,"abstract":"<div><div>Demand response (DR) plays an essential role in power system management. To facilitate the implementation of these techniques, many aggregators have appeared in response as new mediating entities in the electricity market. These actors exploit the technologies to engage customers in DR programs, offering grid services like load scheduling. However, the growing number of aggregators has become a new challenge, making it difficult for utilities to manage the load scheduling problem. This paper presents a multi-agent reinforcement Learning (MARL) approach to a price-based DR program for multiple aggregators. A dynamic pricing scheme based on discounts is proposed to encourage residential customers to change their consumption patterns. This strategy is based on a cooperative framework for a set of DR Aggregators (DRAs). The DRAs take advantage of a reward offered by a Distribution System Operator (DSO) for performing a peak-shaving over the total system aggregated demand. Furthermore, a Shapley-Value-based reward sharing mechanism is implemented to fairly determine the individual contribution and calculate the individual reward for each DRA. Simulation results verify the merits of the proposed model for a multi-aggregator system, improving DRAs’ pricing strategies considering the overall objectives of the system. Consumption peaks were managed by reducing the Peak-to-Average Ratio (PAR) by 15%, and the MARL mechanism’s performance was improved in terms of reward function maximization and convergence time, the latter being reduced by 29%.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"40 ","pages":"Article 101560"},"PeriodicalIF":4.8,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142654683","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-parametric analysis for mixed integer linear programming: An application to transmission upgrade and congestion management","authors":"Jian Liu ,&nbsp;Donald C. Wunsch II ,&nbsp;Siyuan Wang ,&nbsp;Rui Bo","doi":"10.1016/j.segan.2024.101563","DOIUrl":"10.1016/j.segan.2024.101563","url":null,"abstract":"<div><div>Upgrading the capacity of existing transmission lines is essential for meeting the growing energy demands, facilitating the integration of renewable energy, and ensuring the security of the transmission system. This study focuses on the selection of lines whose capacities and by how much should be expanded from the perspective of the Independent System Operators (ISOs) to minimize the total system cost. We employ advanced multi-parametric programming and an enhanced branch-and-bound algorithm to address complex mixed-integer linear programming (MILP) problems, considering multi-period time constraints and physical limitations of generators and transmission lines. To characterize the various decisions in transmission expansion, we model the increased capacity of existing lines as parameters within a specified range. This study first relaxes the binary variables to continuous variables and applies the Lagrange method and Karush-Kuhn-Tucker (KKT) conditions to obtain optimal solutions and identify critical regions associated with active and inactive constraints. Moreover, we extend the traditional branch-and-bound (B&amp;B) method by determining the problem’s upper and lower bounds at each node of the B&amp;B decision tree, helping to manage computational challenges in large-scale MILP problems. We compare the difference between the upper and lower bounds to obtain an approximate optimal solution within the decision-makers’ tolerable error range. In addition, the first derivative of the objective function on the parameters of each line is used to inform the selection of lines for easing congestion and maximizing social welfare. Finally, the capacity upgrades are selected by weighing the reductions in system costs against the expense of upgrading line capacities. The findings are supported by numerical simulations and provide transmission-line planners with decision-making guidance.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"40 ","pages":"Article 101563"},"PeriodicalIF":4.8,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142698386","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":"A two-stage online inertia estimation: Identification of primary frequency control parameters and regression-based inertia tracking","authors":"Juan Diego Rios-Peñaloza ,&nbsp;Andrea Prevedi ,&nbsp;Fabio Napolitano ,&nbsp;Fabio Tossani ,&nbsp;Alberto Borghetti ,&nbsp;Milan Prodanovic","doi":"10.1016/j.segan.2024.101561","DOIUrl":"10.1016/j.segan.2024.101561","url":null,"abstract":"<div><div>In recent years, power system inertia has significantly decreased and has become more variable due to the massive integration of converter-interfaced renewable energy sources. Real-time awareness of the inertia present in the system is essential for operators to take preventive actions and mitigate potential instability risks. Online inertia tracking methods based on field data have been used to accomplish this task. However, most existing methods are disturbance-based and few have proven effective under normal operating conditions. In addition, some methods require prior knowledge of the primary frequency control dynamics, which are usually unknown, especially in presence of power converters. To overcome these limitations, this paper proposes a two-stage online inertia estimation method. The first stage estimates the primary frequency control parameters. The second stage uses a regression-based approach to track the inertia in real time. A sensitivity analysis of the parameters of the regression model is used to determine the conditions under which the primary frequency control parameters must be updated. The performance of the method is validated using the IEEE 39-bus benchmark network under normal operating conditions and under the occurrence of large disturbances. The algorithm is also tested in the presence of converter-interfaced sources controlled in both grid-following and grid-forming modes. Real-time tests validate the applicability of the method.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"40 ","pages":"Article 101561"},"PeriodicalIF":4.8,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142654198","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":"Temporal asynchrony analysis for dynamic operation of hydraulic-thermal-electricity multiple energy networks based on holomorphic embedding method","authors":"Weijia Yang ,&nbsp;Yuping Huang ,&nbsp;Suliang Liao ,&nbsp;Daiqing Zhao ,&nbsp;Duan Yao","doi":"10.1016/j.segan.2024.101559","DOIUrl":"10.1016/j.segan.2024.101559","url":null,"abstract":"<div><div>Analyzing the operational states of multiple energy networks (MEN) in multi-energy systems is crucial for ensuring system stability. The dynamic operational characteristics of different energy flows pose challenges for computational analysis. Traditional steady-state methods are inadequate for addressing the dynamics of MEN, especially when dealing with temporal discrepancies between hydraulic and thermal flows in thermal networks (TN) and the heterogeneity between TN and electrical networks. Therefore, this paper proposes a novel holomorphic embedding method (HEM) based on multi-stage decomposition method. The developed HEM constructs a time coefficient matrix and utilize inner-outer loop recursion to handle the time lag between thermal flow and hydraulic flow in the TN. Additionally, we reconstruct a holomorphic matrix, integrating hydraulic flow to bridge thermal and electric power flows, thereby improving the operational heterogeneity among different networks. Real-case simulations show that when the Taylor expansion order in HEM is equal to 4, the proposed method achieves a mere 1 % discrepancy from actual operational data, enhancing computational efficiency by 60 % compared to the Newton-Raphson method. Moreover, in this real-case scenario, the TN exhibits a maximum delay response time of 180 seconds compared to electrical networks. Exploiting this delay time effectively increases renewable energy generation within multi-energy systems by 961.58 kW per day.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"40 ","pages":"Article 101559"},"PeriodicalIF":4.8,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142654682","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":"Secured energy data transaction for prosumers under diverse cyberattack scenarios","authors":"Fariya Tabassum ,&nbsp;Md. Rashidul Islam ,&nbsp;M. Imran Azim ,&nbsp;M.A. Rahman ,&nbsp;Md. Omer Faruque ,&nbsp;Sk.A. Shezan ,&nbsp;M.J. Hossain","doi":"10.1016/j.segan.2024.101555","DOIUrl":"10.1016/j.segan.2024.101555","url":null,"abstract":"<div><div>Due to the increasing use of renewable energy sources and the advancement of smart grid technology, bilateral energy transactions between prosumers have attracted significant interest as a potential solution for efficient and decentralized energy distribution. Prosumers can establish direct energy exchanges by utilizing internet of things (IoT) technologies and arrangements with smart metering capabilities, eliminating the need for middlemen and allowing for more effective use of renewable energy sources. However, these direct energy exchanges between prosumers can be susceptible to cyber-threats, which hinder secure and effective energy transactions while protecting privacy. To enable safe and seamless energy transactions among prosumers and the grid, the cyber-security of IoT devices should be of paramount significance as a possible solution. Therefore, this paper focuses on securing the energy transactions among prosumers facilitated by smart meters. It aims to address potential threats against data integrity, confidentiality, and availability from the prosumers’ point of view and develop a comprehensive framework for securing energy transactions based on artificial intelligence (AI). The proposed structured roadmap not only identifies compromised trading data but also prevents prosumers from reacting to it by replacing the contaminated as well as missing trading data. A comparative analysis on AI-based algorithms indicates that decision tree (DT) outperforms support vector machine (SVM) and multi-layer perceptron (MLP) for the proposed framework to profile the corrupted trading data identification and categorization in order to provide effective outcomes. Additionally, the proposed framework adopts a deep learning (DL)-based model for the replacement of compromised trading data. All the numerical analyses, along with extensive simulation results, justify, the efficacy of the proposed framework.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"40 ","pages":"Article 101555"},"PeriodicalIF":4.8,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142572249","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":"Investigating the long-term benefits of EU electricity highways: The case of the Green Aegean Interconnector","authors":"Christos K. Simoglou ,&nbsp;Pandelis N. Biskas","doi":"10.1016/j.segan.2024.101558","DOIUrl":"10.1016/j.segan.2024.101558","url":null,"abstract":"<div><div>This paper investigates the potential long-term benefits that could be arisen by the construction and operation of the envisioned “Green Aegean Interconnector”. This will be a pioneering 9-GW direct interconnection line connecting Greece with Germany to facilitate the transfer of massive amounts of RES generation from South-East to Central-North Europe. The ultimate goal of this analysis is to estimate the total electricity supply cost to be undertaken by the end-consumers in Greece with and without the said interconnector along with the cost/benefit of the Greek national economy associated with the foreseen cross-border electricity exchange. Detailed simulations of the Greek electricity market using a specialized electricity market simulation software on the basis of the main provisions of the revised Greek National Energy and Climate Plan are performed under realistic market evolution scenarios for a future 30-year study horizon (2026–2055). Simulation results and the associated cost-benefit analysis indicate that such a project would enable the operation of additional RES projects in Greece. This would, in turn, decrease the overall Greek end-consumers’ electricity cost and create a significant surplus for the Greek economy through the increased exporting activity, whereas at EU-level it would assist towards further achieving the European energy market integration.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"40 ","pages":"Article 101558"},"PeriodicalIF":4.8,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142577462","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":"Blockchain-enabled transformation: Decentralized planning and secure peer-to-peer trading in local energy networks","authors":"Bingkun Wang ,&nbsp;Xiaolin Guo","doi":"10.1016/j.segan.2024.101556","DOIUrl":"10.1016/j.segan.2024.101556","url":null,"abstract":"<div><div>This paper introduces a novel blockchain-based automatic load response architecture for local energy networks, focusing on secure peer-to-peer (P2P) energy trading and decentralized planning. Departing from traditional centralized methods, the proposed system leverages non-cooperative game theory for pricing-based decentralized planning, enabling efficient resource distribution without a central authority. A key contribution is the integration of a machine-governed smart contract mechanism, which ensures secure, transparent, and consistent transactions in P2P energy trading. Additionally, an adaptive evaluation system for transaction nodes enhances the system’s responsiveness to dynamic energy demands. A distributed algorithm is developed to optimize the implementation of this architecture, ensuring practical efficiency. Case studies confirm significant improvements in operational efficiency, security, and economic outcomes, marking a substantial advancement in decentralized energy management. Key findings demonstrate that the proposed automatic load response strategy significantly enhances load curve stability, achieving a 99.16 % reduction in net load fluctuations and an 8.24 % reduction in operational costs compared to traditional methods. Additionally, the framework improves the self-consumption rate of renewable energy by up to 14.62 % and reduces the average cost for electric vehicle (EV) users by 26.12 %. These results highlight the framework's effectiveness in fostering a more balanced supply-demand relationship within local energy networks while ensuring economic and computational efficiency. The study underscores the potential to revolutionize decentralized energy management, offering a sustainable and cost-effective solution for future energy systems.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"40 ","pages":"Article 101556"},"PeriodicalIF":4.8,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142554274","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":"Integrated real-time dispatch of power and gas systems","authors":"Nikolaos Kanelakis,&nbsp;Ilias G. Marneris,&nbsp;Pandelis N. Biskas","doi":"10.1016/j.segan.2024.101554","DOIUrl":"10.1016/j.segan.2024.101554","url":null,"abstract":"<div><div>The integrated operation of the electricity and gas systems has attracted the attention of many researchers due to the ever-increasing interdependency between the two systems. In this paper, a novel framework for the real-time rolling dispatch of the integrated system is presented, targeting to attain the economically optimal and technically secure gas system real-time operation through the control of the available flexibility procured by various resources. A decoupled day-ahead scheduling is initially executed to determine unit commitment and gas linepack target decisions, which are then utilized as inputs to the proposed integrated real-time dispatch model. Intra-day gas system control is executed in a hierarchical procedure through the deployment of four control actions from various inter-system flexibility providers. The presented analysis illustrates that, based on the selection of control parameters, the activation of flexibility resources from both systems can be steered in such a way as to alleviate linepack deviations, even in cases of severely limited scheduled gas supply. The proposed control framework is tested on the Greek power and gas systems, providing significant insights regarding the activation of the control actions for the real-time gas system balancing in different look-ahead horizons.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"40 ","pages":"Article 101554"},"PeriodicalIF":4.8,"publicationDate":"2024-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142572245","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":"A machine learning based fault location method for power distribution systems using wavelet scattering networks","authors":"Charalampos G. Arsoniadis ,&nbsp;Vassilis C. Nikolaidis","doi":"10.1016/j.segan.2024.101551","DOIUrl":"10.1016/j.segan.2024.101551","url":null,"abstract":"<div><div>This paper proposes a novel machine learning based method for localizing single-line-to-ground faults in modern power distribution systems using single-end measurements. The challenge of identifying the faulty lateral is formulated as a support vector machine model-based classification problem, where a class represents a different part of the distribution network. The challenge of finding the exact fault distance is formulated as an ensemble model-based regression problem. Both models are trained with scattering coefficients extracted from the application of a wavelet scattering network on the captured faulty phase voltage signal. The performance of the proposed fault location method is evaluated with a comprehensive simulation study, conducted for the IEEE 34-bus test distribution system. The results demonstrate the efficacy of the proposed method in terms of fault location accuracy, as well as its sufficient insensitivity against several influencing factors, such as load, DG, external system strength, and network topology variations. Comparison of the proposed method with other well-established machine learning based fault location methods for power distribution systems reveals its great performance.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"40 ","pages":"Article 101551"},"PeriodicalIF":4.8,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142532469","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":"Two-stage low-carbon economic dispatch of an integrated energy system considering flexible decoupling of electricity and heat on sides of source and load","authors":"Lijun Yang ,&nbsp;Yejin Gao ,&nbsp;Pei Zhang ,&nbsp;Xiaolin Tan ,&nbsp;Jiakun An","doi":"10.1016/j.segan.2024.101552","DOIUrl":"10.1016/j.segan.2024.101552","url":null,"abstract":"<div><div>Under the goal of \"double carbon\", in order to further enhance the level of new energy consumption and solve the problem of restricting the flexibility of the system by \"ordering power by heat\" of combined heat and power (CHP) units, a low-carbon economic planning strategy with flexible decoupling of electricity and heat is proposed, by introducing a new type of electric-thermal coupling equipment on both sides of the source and load. Firstly, Consideration of the low-carbon and environmentally friendly characteristics of green ammonia production and ammonia-doped combustion technologies, a wind power(WT) – power to ammonia(P2A) - CHP units - thermal power (TH) units joint operation strategy is proposed on the source side. This strategy realizes the conversion of abandoned wind to green ammonia to ammonia coal hybrid generation, the decoupled operation of CHP units and promotes the consumption of wind power and the low-carbon operation of the system. Secondly, A dynamic incentive demand response model is developed to meet the demand of high proportion distributed PV in situ consumption on the load side. The dynamic incentive price guides the distributed power-to-heat load to change the response capacity, tracks the abandonment of wind and light, realizes the flexible conversion of power and heat load, and cooperates with the source side to promote the coupling operation of electric pyrolysis. On this basis, consider the flexible decoupling capability of electric-heat coupling equipment on both sides of the source and load to establish a two-phase low-carbon scheduling model for the day-before and day-after phases. In the day-ahead phase, the source-side electric-thermal-ammonia joint operation strategy is considered, and the electric and thermal energy supply plans are adjusted centrally; In the intra-day phase, the flexible adjustment range of power-to-heat devices and the heat load inertia on the load side are taken into account, and the electricity and heat planning strategies are adjusted in a distributed-centralised manner in conjunction with the source side. Finally, through the simulation of different cases, the results show that compared with the traditional electric heating system, the total cost of the system considering the scheduling strategy proposed in this paper decreases by ￥826,900, the carbon emission decreases by 1.2 t, and basically realises the consumption of wind power and distributed photovoltaic power output. The proposed scheme reduces carbon emissions, promotes the consumption of wind power and distributed photovoltaic output, and is able to reach the goal of low-carbon economic dispatch.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"40 ","pages":"Article 101552"},"PeriodicalIF":4.8,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142531786","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}