Sustainable Energy Grids & Networks最新文献

{"title":"A reinforcement learning-based energy management strategy for fuel cell electric vehicle considering coupled-energy sources degradations","authors":"Weiwei Huo ,&nbsp;Teng Liu ,&nbsp;Bing Lu","doi":"10.1016/j.segan.2024.101548","DOIUrl":"10.1016/j.segan.2024.101548","url":null,"abstract":"<div><div>An effective energy management strategy (EMS) is crucial for fuel cell electric vehicles (FCEVs) to optimize fuel consumption and mitigate fuel cell (FC) aging by efficiently distributing power from multiple energy sources during vehicle operation. The Proton Exchange Membrane Fuel Cell (PEMFC) is a preferred main power source for fuel cell vehicles due to its high power density, near-zero emissions, and low corrosivity. However, it is expensive, and its lifespan is significantly affected by rapid power fluctuations. To address this issue, the proposed method of minimizing instantaneous cost (MIC) reduces the frequency of abrupt changes in the FC load. Additionally, by analyzing driving condition characteristics, the Ensemble Bagging Tree (EBT) facilitates real-time recognition (WCI) of composite conditions, thereby enhancing the EMS's adaptability to various operating conditions. This paper introduces an advanced EMS based on double-delay deep deterministic policy gradient (TD3) deep reinforcement learning, which considers energy degradation, economic efficiency, and driving conditions. Training results indicate that the TD3-based policy, when integrated with WCI and MIC, not only achieves a 32.6 % reduction in FC system degradation but also lowers overall operational costs and significantly accelerates algorithm convergence.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"40 ","pages":"Article 101548"},"PeriodicalIF":4.8,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142432145","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":"Optimization of the electric vehicle charging strategy problem for sustainable intercity travels with multiple refueling stops","authors":"Hilal Yılmaz ,&nbsp;Betul Yagmahan","doi":"10.1016/j.segan.2024.101546","DOIUrl":"10.1016/j.segan.2024.101546","url":null,"abstract":"<div><div>Electric vehicle (EV) drivers considering long-distance trips still face range anxiety due to the limited range of EVs and the scarcity of charging stations. Thus, it becomes important to ensure the feasibility of the selected route and determine an optimal charging strategy. As a crucial aspect of decision support for EV drivers, this study proposes a mixed integer linear programming (MILP) approach for the EV charging strategy problem (EVCSP), incorporating a piecewise linear approximation technique to address the challenges posed by nonlinear charging times. The proposed optimization model, namely CSPM determines where, when, and how much to charge an EV for a specified route to minimize travel time and cost. The solution time of large-scale test problems and a case study on Türkiye reveal the robustness and reliability of the CSPM. Furthermore, two multi-objective optimization methods (the weighted sum and the lexicographic method) are applied to the case study, and the results are analyzed. The results indicate that the travel cost is more sensitive to the selected charging strategy, with a range of 46.09 % across the applied charging strategies, whereas travel time remains more resilient, with a maximum fluctuation of 19.77 %. A comparative analysis with a full charging strategy reveals that the CSPM reduces the travel time by 60.1 % and improves the cost efficiency by 105.72 %.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"40 ","pages":"Article 101546"},"PeriodicalIF":4.8,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142532471","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":"Reliability evaluation of direct current gathering system in onshore wind farm based on reliability block diagram-sequential monte carlo","authors":"Xueyan Bai,&nbsp;Yanfang Fan,&nbsp;Junjie Hou,&nbsp;Yao Sun,&nbsp;Yujia Liu,&nbsp;Junyi Liu","doi":"10.1016/j.segan.2024.101549","DOIUrl":"10.1016/j.segan.2024.101549","url":null,"abstract":"<div><div>The full DC wind power generation system has effectively overcome the harmonic resonance, reactive power transmission, and other problems of the traditional AC wind power system, which has broad prospects for development. As a key component of the mentioned system, the reliability of the collection system is critical to the safe and stable operation of the entire onshore wind farm. Firstly, this paper investigates the key equipment and topology of the onshore wind farm DC collection system. Secondly, considering both the internal components and external environment of the wind farm, a component outage probability model based on weather factors is constructed to provide accurate data for the reliability evaluation of the DC collection system of the wind farm. The Reliability Block Diagram is used to analyze the internal logical connection of different topologies of onshore wind farm DC collection systems in detail. Then, a reliability evaluation method of an onshore full DC wind farm collection system based on Reliability Block Diagram-Sequential Monte Carlo is proposed. Finally, a 50 MW onshore wind farm is studied as a sample to compare and analyze the assessment results of the reliability of different collection system topologies. The results show that the reliability of the DC collection system of onshore wind farms has significant advantages.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"40 ","pages":"Article 101549"},"PeriodicalIF":4.8,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142532464","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":"Optimization of offshore wind farm cluster transmission system topology based on Stackelberg game","authors":"Siyu Tao,&nbsp;Fuqing Jiang","doi":"10.1016/j.segan.2024.101542","DOIUrl":"10.1016/j.segan.2024.101542","url":null,"abstract":"<div><div>Offshore wind energy is pivotal in the global energy transition, with a global installed capacity reaching 64.3 GW by 2022 and an expected annual increase of 60.2 GW over the next decade. This study aims to optimize the topology of transmission systems (TS) for offshore wind farm (OWF) clusters using Stackelberg game theory. The OWF investor (OWFI) acts as the leader, optimizing investment returns while considering wake effects, and the offshore TS operator (OTSO) follows by adjusting transmission strategies to reduce costs. The analysis includes the wake effects within OWF clusters and their impact on power generation efficiency. Simulation results demonstrate that the proposed model can balance stakeholder interests and enhance the economic viability of OWF clusters, showing a potential increase in net present value (NPV) by up to 30 %. This study validates the practical application of the Stackelberg game model in optimizing OWF cluster TS topology, contributing to more efficient and cost-effective renewable energy integration.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"40 ","pages":"Article 101542"},"PeriodicalIF":4.8,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142446503","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":"Reliability-aware techno-economic assessment of floating solar power systems","authors":"Anik Goswami ,&nbsp;Jose I. Aizpurua","doi":"10.1016/j.segan.2024.101536","DOIUrl":"10.1016/j.segan.2024.101536","url":null,"abstract":"<div><div>Floating solar photovoltaic systems (FPV) have emerged as a promising technology to harness solar energy on water surfaces. With its numerous benefits, including increased land availability, reduced water evaporation, and improved system cooling, FPV systems hold great potential for sustainable energy generation. However, due to its unique installation and operation in water bodies, the management of ageing becomes a critical factor to ensure long-term success. Consequently, reliability analysis plays a pivotal role in predicting and mitigating operational risks and estimating the economic feasibility of FPV projects. In this context, this paper presents a reliability-aware techno-economic assessment approach of FPV systems. The approach is tested with a case study in India, and the results are compared with ground-based photovoltaic (GPV) systems. Here, different failure and repair strategies are taken into account to determine the lifetime performance. Results showed that even though FPV system has higher failure rate, considering standard maintenance, the energy generated by the FPV system is 5.38% higher than similar GPV system. The cost of electricity by the PV system depends on the repair and maintenance. For normal maintenance the levelized cost of electricity (LCOE) for FPV system is calculated as 0.0551 $/kWh which is comparable to the LCOE by GPV systems, while for reduced repair actions, the LCOE of the FPV is higher than the LCOE of the GPV system.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"40 ","pages":"Article 101536"},"PeriodicalIF":4.8,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142532463","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":"Swarm electrification for Raqaypampa: Impact of different battery control setpoints on energy sharing in interconnected solar homes systems","authors":"Ida Fuchs ,&nbsp;Claudia Sanchez-Solis ,&nbsp;Sergio Balderrama ,&nbsp;Govert Valkenburg","doi":"10.1016/j.segan.2024.101535","DOIUrl":"10.1016/j.segan.2024.101535","url":null,"abstract":"<div><div>In rural electrification, decentralized systems have proven to bring fast, affordable, and sustainable electricity supply for the last mile of energy access. Especially, solar home systems (SHS) have lately increased in number and impact. Recently, a new concept promises even better utilization of SHS and the potential for higher access to electricity. This concept is found under the name of swarm electrification, also known as interconnected SHS, nanogrids, or decentralized DC systems in rural areas. This paper studies the benefits of such interconnected SHS for a case study in the indigenous rural Highlands of Bolivia, an area called Raqaypampa. Our study emphasizes analyzing the energy sharing setpoints for the decentralized battery control and how the choice of these values influences energy distribution in the community. We draw concepts of energy justice into our discussion to evaluate different combinations of battery state of charge setpoints. Our study finds four types of households in Raqaypampa based on their demand for electricity. The modeled and simulated results of a potential energy sharing through interconnected SHS reveal three outcomes for the households based on the battery state of charge setpoints: Outcome I — Improving households, Outcome II — Depending households, and Outcome III — Deteriorating households. We conclude that a common approach of e.g. minimization of total unmet demand alone will not necessarily lead to just energy distribution, and it is crucial to integrate discussions about justice and community goals into the design process from the beginning.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"40 ","pages":"Article 101535"},"PeriodicalIF":4.8,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142442080","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":"Modeling and detection of false data injection attacks in cyber-physical distribution system with load aggregator interaction","authors":"Xinrui Liu ,&nbsp;Shubo Sun ,&nbsp;Yating Wang ,&nbsp;Zhiyuan Duan ,&nbsp;Xin Li ,&nbsp;Qiuye Sun","doi":"10.1016/j.segan.2024.101533","DOIUrl":"10.1016/j.segan.2024.101533","url":null,"abstract":"<div><div>With the increasing number of users and multi-type loads accessing the cyber–physical distribution system (CPDS), the bidirectional interaction between the system becomes more and more frequent. The Load aggregator (LA) also plays an increasingly important role in the interaction process. However, the LA’s high dependence on information and lack of security measures make it vulnerable to attacks, so this paper analyzes the interactive security of the LAs from two points. Considering the game process between the LAs and users from the attacker’s point of view, this paper puts forward an attack strategy aiming cost function of the LAs, establishes a bi-level multi-objective programming attack model of false data injection attacks(FDIAs), and proposes an attack detection method based on the multi-state matching method and improved similar daily data preprocessing generative adversarial network (P-GAN) from the defender’s point of view to defend against the above attack strategy. Furthermore, a hybrid detection mechanism combining event triggering and periodic detection is proposed to ensure response speed and adaptability of detection. The effectiveness of the proposed attack model and the detection method is verified by simulation analysis.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"40 ","pages":"Article 101533"},"PeriodicalIF":4.8,"publicationDate":"2024-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142432144","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":"Cluster partition-fuzzy broad learning-based fast detection and localization framework for false data injection attack in smart distribution networks","authors":"Haopeng An ,&nbsp;Yankai Xing ,&nbsp;Guangdou Zhang ,&nbsp;Olusola Bamisile ,&nbsp;Jian Li ,&nbsp;Qi Huang","doi":"10.1016/j.segan.2024.101534","DOIUrl":"10.1016/j.segan.2024.101534","url":null,"abstract":"<div><div>The distributed renewable energy generations, as accessible and easily targets for attackers, introduce an extra false data injection attack (FDIA) threat in the smart distribution networks. Scattered attack points and complex attack features hinder the elimination of potential threats. In this context, an FDIA fast detection and pinpoint localization framework is proposed. This framework identifies abnormal signals and attacked nodes from the unique topology structure and status contiguity of smart distribution networks, namely, spatial-temporal correlations of power grids, by using a cluster partition-fuzzy broad learning system (CP-FBLS). Unlike most existing FDIA detection methods, which are dedicated to high accuracy but neglect the urgent need for rapid detection in smart distribution networks, the proposed CP-FBLS framework maintains the fast computational nature of a fuzzy broad learning system (FBLS), while avoiding the accuracy degradation caused by high-dimension of data in large-scale smart distribution networks. Moreover, the multi-layer structure of the proposed framework recognizes the location of FDIA, bridging the research gap of attack localization. To comprehensively evaluate the proposed strategy, datasets containing various FDIA types are constructed. Numerical simulations based on the above datasets in modified IEEE 34-bus and 123-bus distribution systems are implemented. The results of the case studies showed that the proposed method can achieve 98.43 % accuracy with 0.34 ms detection time, realizing rapid detection and localization of various FDIAs with satisfactory accuracy.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"40 ","pages":"Article 101534"},"PeriodicalIF":4.8,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142425278","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":"Adaptive robust optimization framework for market-based wind power investment","authors":"Haitham A. Mahmoud","doi":"10.1016/j.segan.2024.101532","DOIUrl":"10.1016/j.segan.2024.101532","url":null,"abstract":"<div><div>Wind is distinguished by its eco-friendliness and sustainability, making it one of the most rapidly expanding forms of renewable energy sources (RESs). Hence, it is necessary to determine the most profitable plan for wind farm installation. This paper constructs a novel scheme for market-based wind power investment (WPI) problems using adaptive robust optimization (ARO). A tri-level robust WPI (RWPI) model is established, the first level of which is to minimize the investment cost plus the worst-case loss. In the second level, the worst-case loss (also known as the maximum regret) is identified by maximizing the minimum value of minus profit over the uncertainty sets. The third level maximizes the wind farm profit. Since the profit calculation requires the determination of the locational marginal price (LMP), the third level constitutes bi-level programming, with the upper level being the profit maximization and the lower level being the market clearing process. First, Karush-Kuhn-Tucker (KKT) conditions are applied to convert the bi-level model to a single-level model, resulting in an ARO with binary variables at the third level. Afterward, the nested column-and-constraint generation (NCCG) strategy is employed to solve the ARO with mixed-integer recourse. A case study is used to verify the scalability and practical applicability of the proposed model.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"40 ","pages":"Article 101532"},"PeriodicalIF":4.8,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142425236","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 blockchain-based architecture for tracking and remunerating fast frequency response","authors":"Giuseppe Sciumè ,&nbsp;Cosimo Iurlaro ,&nbsp;Sergio Bruno ,&nbsp;Rossano Musca ,&nbsp;Pierluigi Gallo ,&nbsp;Gaetano Zizzo ,&nbsp;Eleonora Riva Sanseverino ,&nbsp;Massimo La Scala","doi":"10.1016/j.segan.2024.101530","DOIUrl":"10.1016/j.segan.2024.101530","url":null,"abstract":"<div><div>The increasing penetration of renewable sources introduces new challenges for power systems’ stability, especially for isolated systems characterized by low inertia and powered through a single diesel power plant, such as it happens in small islands. For this reason, research projects, such as the BLORIN project, have focused on the provision of energy services involving electric vehicles owners residential users to mitigate possible issues on the power system due to unpredictable generation from renewable sources. The residential users were part of a blockchain-based platform, which also the Distributors/Aggregators were accessing. This paper describes the integrated framework that was set up to verify the feasibility and effectiveness of some of the methodologies developed in the BLORIN project for fast frequency response in isolated systems characterized by low rotational inertia. The validation of the proposed methodologies for fast frequency response using Vehicle-to-Grid or Demand Response programs was indeed carried out by emulating the dynamic behavior of different power resources in a Power Hardware-in-the-Loop environment using the equipment installed at the LabZERO laboratory of Politecnico di Bari, Italy. The laboratory, hosting a physical microgrid as well as Power Hardware-in-the-Loop facilities, was integrated within the BLORIN blockchain platform. The tests were conducted by assuming renewable generation development scenarios (mainly photovoltaic) and simulating the system under the worst-case scenarios caused by reduced rotational inertia. The experiments allowed to fully simulate users’ interaction with the energy system and blockchain network reproducing realistic conditions of tracking and remuneration of users’ services. The results obtained show the effectiveness of the BLORIN platform for the provision, tracking and remuneration of grid services by electric vehicles and end users, and the benefits that are achieved in terms of reducing the number of diesel generating units that need to be powered on just to provide operational reserve due to the penetration of renewable sources, resulting in fuel savings and reduced emissions.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"40 ","pages":"Article 101530"},"PeriodicalIF":4.8,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142425237","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}