IET Smart Grid最新文献

{"title":"Voltage regulation in low voltage distribution networks with unbalanced penetrations of photovoltaics and battery storage systems","authors":"Alexander Micallef,&nbsp;Cyril Spiteri-Staines,&nbsp;John Licari","doi":"10.1049/stg2.12155","DOIUrl":"10.1049/stg2.12155","url":null,"abstract":"<p>Grid integration constraints are limiting the deployment potential of renewable energy sources in Malta. Large penetrations of photovoltaics in the low voltage (LV) distribution network pose a significant risk to grid stability due to their inherent intermittency and are known to cause overvoltages and reverse power flows. The authors evaluate how self-consumption strategies with distributed battery energy storage systems can contribute to the voltage regulation in LV networks and the reduction of reverse power flows. The batteries are controlled to absorb the reverse power flow at the dwellings' point of common coupling, before this is injected into the LV network. Simulations show that uncoordinated strategies are not suitable to address the distribution network challenges during reverse power flows and evening peak demands. On the other hand, self-consumption coordinated by a time-varying feed-in tariff (FiT) can provide higher profitability to the prosumers while providing added benefits to the utility. The net-billing profitability for the prosumers in a self-consumption scenario with time-varying FiT is transformed from the downward trend of the uncoordinated scenario to an upward trend against the increasing values of storage capacity.</p>","PeriodicalId":36490,"journal":{"name":"IET Smart Grid","volume":"7 3","pages":"264-276"},"PeriodicalIF":2.3,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/stg2.12155","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139815574","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Total supply capability of electricity distribution networks considering flexible interconnection of low-voltage service transformers","authors":"Guoqiang Zu,&nbsp;Ying Wang,&nbsp;Xun Jiang,&nbsp;Ziyuan Hao,&nbsp;Xin Zhang","doi":"10.1049/stg2.12157","DOIUrl":"10.1049/stg2.12157","url":null,"abstract":"<p>Under the target of ‘emission peak and carbon neutrality’, electricity distribution networks will massively access low-carbon technologies, which will result in problems such as insufficient hosting capacity, unbalanced electricity loads, degraded power quality etc. The low-voltage flexible distribution network (LVFDN), which interconnects its low-voltage service transformers using flexible power electronic devices (flexible interconnected devices [FIDs]) is considered an effective means to deal with the challenges above. The total supply capability (TSC) of LVFDN is proposed. Firstly, the typical structures of LVFDN and their operation modes are proposed. Then, the TSC model of LVFDN, which formulates flexible power flow control and multi-level (medium-voltage feeder and low-voltage flexible interconnection) load transfer is proposed. Due to the non-linear non-convex characteristics of the proposed TSC model, a new algorithm based on the ‘branch and bound algorithm’ is also provided. In the case study, the TSC of an actual electricity distribution network is calculated and tested by the N-1 verification method. Finally, the variations of TSC with different capacities of the low-voltage FID are analysed. Suggestions for the planning and operation of LVFDN are also given. A theoretical basis for the application of flexible interconnection technology in low-voltage electricity distribution networks is provided.</p>","PeriodicalId":36490,"journal":{"name":"IET Smart Grid","volume":"7 4","pages":"386-399"},"PeriodicalIF":2.4,"publicationDate":"2024-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/stg2.12157","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140474897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impacts of grid-scale battery systems on power system operation, case of Baltic region","authors":"Roya AhmadiAhangar,&nbsp;Freddy Plaum,&nbsp;Tobias Haring,&nbsp;Imre Drovtar,&nbsp;Tarmo Korotko,&nbsp;Argo Rosin","doi":"10.1049/stg2.12142","DOIUrl":"10.1049/stg2.12142","url":null,"abstract":"<p>Grid stability can be affected by the large-scale utilisation of renewable energy sources because there are fluctuations in generation and load. These issues can be effectively addressed by grid-scale battery energy storage systems (BESS), which can respond quickly and provide high energy density. Different roles of grid-scale BESS in power systems are addressed, following optimal operation approaches classification. Furthermore, integrating BESSs into distribution grids is discussed to manage challenges from distributed generation. BESSs aid in voltage control, enhance frequency regulation, and offer black-start services. Aggregating distributed BESSs can provide ancillary services and improve grid economics. For consumers, BESSs optimise energy costs, enhance reliability, and support self-consumption from renewables. Novel BESS services include congestion relief, system adequacy, and power quality enhancement. Moreover, the ancillary services provided in different European countries through BESS are analysed. Finally, a case study was conducted among three Baltic DSOs to analyse the required amendments to Grid Codes and Electricity Market Acts for the integration of grid scale BESS.</p>","PeriodicalId":36490,"journal":{"name":"IET Smart Grid","volume":"7 2","pages":"101-119"},"PeriodicalIF":2.3,"publicationDate":"2024-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/stg2.12142","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139618493","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Common direct current (DC) bus integration of DC fast chargers, grid-scale energy storage, and solar photovoltaic: New York City case study","authors":"Mohamed K. Kamaludeen,&nbsp;Kirn Zafar,&nbsp;Yusef Esa,&nbsp;Ahmed Ali A. Mohamed,&nbsp;Elihu Nyemah,&nbsp;Lizzette Salmeron,&nbsp;Simon Odie","doi":"10.1049/stg2.12154","DOIUrl":"10.1049/stg2.12154","url":null,"abstract":"<p>The mass deployment of distributed energy resources (DERs) to achieve clean energy objectives has become a major goal across several states in the U.S. However, the viability and reality of achieving these goals in dense urban areas, such as New York City, are challenged by several ‘Techno-Economic’ barriers associated with available land space and the number of AC/direct current (DC) conversion stages that requires multiple electrical balance of plant (BOP) equipment for pairing/interconnecting these resources to the grid. The fundamental issue of interconnection is addressed by assessing the use of a common DC bus in a one-of-a-kind configuration (to pair grid-connected energy storage, photovoltaic, and electric vehicle chargers (EVC) systems) and reduce the number of BOP equipment needed for deployment. Building on similar work that has touched on distribution-level DC interconnection, this paper will also address the intricacies of interconnecting third-party and Utility DERs to a DC-based point of common coupling. It will examine the requisite site controller configuration (control architecture) and requirements to coordinate the energy storage system's use between managing Utility and Third-Party EVC demand while prioritising dispatch. The result shows that the DC-coupled system is technologically feasible and hierarchical control architecture is recommended to maintain stability during various use cases proposed. This will inform a lab demonstration of this system that aims to test DC integration of the DERs with recommendations for the microgrid (MG) controllers and reduction in the BOP equipment. These learnings will then be applied to practical grid-scale deployment of the systems at Con Edison's Cedar Street Substation. This system, if proven successful, has the potential to change the way community distributed generation and MGs are interconnected to the Utility System.</p>","PeriodicalId":36490,"journal":{"name":"IET Smart Grid","volume":"7 3","pages":"351-365"},"PeriodicalIF":2.3,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/stg2.12154","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139534150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning autoencoder-based parameters prediction for solar power generation systems in smart grid","authors":"Ahsan Zafar,&nbsp;Yanbo Che,&nbsp;Muhammad Faheem,&nbsp;Muhammad Abubakar,&nbsp;Shujaat Ali,&nbsp;Muhammad Shoaib Bhutta","doi":"10.1049/stg2.12153","DOIUrl":"10.1049/stg2.12153","url":null,"abstract":"<p>During the fourth energy revolution, artificial intelligence implementation is necessary in all fields of technology to meet the increasing energy demands and address the diminishing fossil fuel reserves, necessitating the shift towards smart grids. The authors focus on predicting parameters accurately to minimise loss and improve power generation capacity in smart grids, given that accurate parameter prediction is essential for traditional power grid stations converting to smart grids. The authors employ an artificial intelligence-based machine learning model, namely the long short-term memory, to predict parameters of a solar power plant. After analysing the results obtained from the long short-term memory model in graphical visualisation, the model is further improved using two different techniques namely, a convolutional neural network-long short-term memory and the authors proposed an autoencoder long short-term memory. Comparing the results of these models, the study finds that autoencoder long short-term memory outperforms the convolutional neural network-long short-term memory as well as simple long short-term memory. Thus, the use of artificial intelligence in this study substantially enhances the precision of parameter prediction by augmenting the performance of rudimentary machine learning models, thereby facilitating the attainment of a resilient and resourceful power system that overcomes power losses and ameliorates production capacity in the context of Smart Grids.</p>","PeriodicalId":36490,"journal":{"name":"IET Smart Grid","volume":"7 3","pages":"328-350"},"PeriodicalIF":2.3,"publicationDate":"2024-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/stg2.12153","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139389252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The charge-discharge compensation pricing strategy of electric vehicle aggregator considering users response willingness from the perspective of Stackelberg game","authors":"Xiaohong Dong,&nbsp;Xiangyu Wei,&nbsp;Guoqiang Zu,&nbsp;Yang Ma,&nbsp;Xiaodan Yu,&nbsp;Yunfei Mu","doi":"10.1049/stg2.12148","DOIUrl":"10.1049/stg2.12148","url":null,"abstract":"<p>With the rapid increase of electric vehicle (EV) ownership, the impact of EV charging load on the power grid is becoming more and more prominent. To reasonably guide EV charging/discharging to participate in Demand Response (DR) and help the power grid achieve peak cutting and valley filling, the charge-discharge compensation pricing strategy of EV Aggregator (EVA) considering user response willingness from the perspective of Stackelberg game is proposed. Firstly, EVA, as the leader, provides charge-discharge compensation price, to maximise its income within a day, taking into account user satisfaction constraints. Secondly, a user response willingness model is established. User engagement is used to describe the change in the number of EV responses with the change of the charge-discharge compensation price by EVA and select the random EV set that accepts EVA charge-discharge guidance. Finally, EV, as a follower, conducts charging/discharging behaviour to minimise the charging cost. By using the Karush–Kuhn–Tucker (KKT) condition, strong duality theory and iterative method, the strategy equilibrium solution is solved. The results show that considering the user response willingness can effectively reduce the decision risk when EVA participates in bidding. Although EVA income slightly decreases considering the response willingness, the average user satisfaction increases by 0.1.</p>","PeriodicalId":36490,"journal":{"name":"IET Smart Grid","volume":"7 3","pages":"277-293"},"PeriodicalIF":2.3,"publicationDate":"2023-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/stg2.12148","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139154602","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigation on damping mechanism of machine-side dynamics of permanent magnet synchronous generator-based wind generation system","authors":"Xianyu Zhou,&nbsp;Siqi Bu,&nbsp;Bowen Zhou,&nbsp;Dongsheng Yang,&nbsp;Lasantha Meegahapola","doi":"10.1049/stg2.12145","DOIUrl":"10.1049/stg2.12145","url":null,"abstract":"<p>A permanent magnet synchronous generator-based wind generation system has been predominantly applied in wind farms. With the wide application of wind generation, mechanical shafting attracts wide attention as torsional vibration problems may occur in its mechanical rotational system, which can further affect the power system. The paper first intentionally designs a two-open-loop two-mass shaft subsystem model to investigate the interactions among wind turbine mass, generator mass, and machine-side converter, that is, the machine-side dynamics. Then, a bilateral damping contribution analysis is proposed to investigate the damping mechanism of these machine-side dynamics. The impact mechanism of one dynamic on another through the damping contribution channel can be revealed by modal analysis, indicating the coupling of different oscillation modes and the complex interactions of machine-side dynamics. The established two-open-loop two-mass shaft subsystem model and the proposed bilateral damping contribution analysis with the identified damping contribution channel of the permanent magnet synchronous generator-based wind generation system are validated.</p>","PeriodicalId":36490,"journal":{"name":"IET Smart Grid","volume":"7 4","pages":"412-426"},"PeriodicalIF":2.4,"publicationDate":"2023-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/stg2.12145","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139165056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Three-level secondary negawatt trading market mechanism with capability of congestion management","authors":"Amirhossein Amirmahani,&nbsp;Abed Bagheri,&nbsp;Shahram Jadid","doi":"10.1049/stg2.12150","DOIUrl":"10.1049/stg2.12150","url":null,"abstract":"<p>Modern power markets are witnessing various energy transactions, and the participants are focusing on different objectives like energy cost, profit, and environmental concerns as key parts of their strategy. In recent years, producers, prosumers, and other participants found ways to act freely in the grid and maximise their profit. By using negawatt trading (selling the right of buying to other participants), consumers will find a way to choose their role (seller, buyer, or negawatt trader) as they desire in the market and can join the market to maximise their utility function. A three-level secondary market is proposed that would work besides the day-ahead market. In the designed market, the network manager first determines the value of negawatt for each time in each region by considering the network conditions, and then by exchanging the information specific to each group, buyers and sellers have an opportunity to trade negawatt as much as they desire with the specified price in each time. The designed market also provides a mechanism to control the exchanges between different areas, which allows the network manager to control the grid conditions. The results show that the introduced market can be profitable for each participant including the DSO and work without interfering with the day-ahead market process.</p>","PeriodicalId":36490,"journal":{"name":"IET Smart Grid","volume":"7 3","pages":"314-327"},"PeriodicalIF":2.3,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/stg2.12150","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138953617","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting the magnitude and timing of peak electricity demand: A competition case study","authors":"Daniel L. Donaldson,&nbsp;Jethro Browell,&nbsp;Ciaran Gilbert","doi":"10.1049/stg2.12152","DOIUrl":"10.1049/stg2.12152","url":null,"abstract":"<p>As weather dependence of the electricity network grows, there is an increasing need to predict the time at which the network peak load will occur. Improving forecasts of peak hour can lead to more accurate scheduling of generation as well as the ability to use flexibility to improve system utilisation or defer capital investment. While there are extensive benchmark models for forecasting electricity demand, their efficacy at forecasting the time or shape of the peak remains to be seen. Global forecasting competitions provide a unique opportunity to compare multiple methodologies under common performance criteria and incentives. The methodology and results are detailed from the Big Data and Energy Analytics Laboratory Challenge 2022 used by the team ‘peaky-finders’ and investigates the suitability of using hourly methods to forecast daily peak magnitude, time, and shape. The resulting approach provides a reproducible ensemble benchmark against which to evaluate more complex methods. Results indicate that simple regression techniques can perform well and outperform more complicated methods during seasons with low hourly variability, however ensemble methods show higher accuracy overall. The results also highlight the significant impact of extreme weather on forecast accuracy, demonstrating the importance of forecasting processes that are resilient to extreme weather.</p>","PeriodicalId":36490,"journal":{"name":"IET Smart Grid","volume":"7 4","pages":"473-484"},"PeriodicalIF":2.4,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/stg2.12152","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138952664","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhanced demand side management for solar-based isolated microgrid system: Load prioritisation and energy optimisation","authors":"Yaju Rajbhandari,&nbsp;Anup Marahatta,&nbsp;Ashish Shrestha,&nbsp;Anand Gachhadar,&nbsp;Anup Thapa,&nbsp;Francisco Gonzalez-Longatt,&nbsp;Petr Korba","doi":"10.1049/stg2.12151","DOIUrl":"10.1049/stg2.12151","url":null,"abstract":"<p>A novel control mechanism is presented for rural microgrids, standing out in the current literature with its advanced approach to load prioritisation and energy allocation. The system's main goal is to maximise energy supply to essential loads while effectively managing available resources. Distinct from traditional methods, this mechanism dynamically classifies loads according to user-defined priorities, adjustable based on the control system's computational power and complexity. A critical feature is the utilisation of the Particle Swarm Optimisation (PSO) algorithm to optimise demand side management (DSM). This innovative approach leverages day-ahead load and generation forecasts to ensure optimal energy distribution across load levels, maintaining continuous power supply to high-priority loads and reducing blackout risks due to generation and load fluctuations. Analyses under stochastic scenarios demonstrate the robustness of the control action, with percentile-based day-ahead forecasting allowing for adaptation to significant variations in renewable energy generation patterns. The implementation results are significant, maintaining 100% supply continuity to essential loads throughout the day, even with generation fluctuations up to -20%. This marks a considerable improvement in load satisfaction, increasing it from 83% to 96%. A significant advancement in microgrid control is contributed, providing an adaptive, user-centric approach that enhances load management and energy distribution, and facilitates more resilient and efficient microgrid systems in the face of highly variable renewable energy sources (RESs).</p>","PeriodicalId":36490,"journal":{"name":"IET Smart Grid","volume":"7 3","pages":"294-313"},"PeriodicalIF":2.3,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/stg2.12151","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139176177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}