IET Smart Grid最新文献

{"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":null,"pages":null},"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":null,"pages":null},"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":null,"pages":null},"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":null,"pages":null},"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":null,"pages":null},"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":null,"pages":null},"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":null,"pages":null},"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}

{"title":"Variable DC voltage based reactive power enhancement scheme for MMC-STATCOM","authors":"Lujie Yu,&nbsp;Guoyan Wang,&nbsp;Tong Wu,&nbsp;Jiebei Zhu,&nbsp;Campbell D. Booth","doi":"10.1049/stg2.12147","DOIUrl":"10.1049/stg2.12147","url":null,"abstract":"<p>Constrained by the AC voltage amplitude modulated by a modular multilevel converter-based static synchronous compensator (MMC-STATCOM), its reactive power output may be subject to oscillations under grid contingencies, posing a threat to the grid stable operation. To solve this problem, this paper proposes a variable DC voltage (VDCV)-based reactive power enhancement scheme for MMC-STATCOM. In this scheme, a novel variable DC voltage control is designed, which can increase the DC voltage in a transient state for relaxing the constraint of the AC voltage amplitude modulated by MMC-STATCOM and improving its reactive power output capability (RPC). At the same time, to make full use of the improved RPC of MMC-STATCOM, a VDCV scheme also proposes an optimisation algorithm of its reactive current-AC voltage droop coefficient using the established reactive power model of the MMC-STATCOM. Based on small signal modelling and analysis, the key parameters of the proposed VDCV scheme are optimised. The performance and reactive power enhancement of the VDCV scheme is evaluated through the hardware-in-the-loop experiment under grid disturbances.</p>","PeriodicalId":36490,"journal":{"name":"IET Smart Grid","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2023-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/stg2.12147","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138585986","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":"A novel snow conditions-compatible computational intelligence-based PV power forecasting approach for microgrids in snow prone regions","authors":"Behzad Hashemi,&nbsp;Shamsodin Taheri,&nbsp;Ana-Maria Cretu","doi":"10.1049/stg2.12146","DOIUrl":"10.1049/stg2.12146","url":null,"abstract":"<p>Energy management in a renewable energy-based microgrid has a key role in improving energy utilisation and reducing the microgrid operation cost. The optimal energy management strategy can be significantly affected by the intermittency of renewable energies and also harsh weather conditions. In this study, a novel snow conditions-compatible computational intelligence-based short-term photovoltaic (PV) power forecasting (PVPF) approach is proposed that is independent of exogenous weather forecasts. The proposed approach consists of a snow cover detection stage, a snow cover forecasting stage, and a PV power forecasting stage. This approach is then validated for a model predictive control (MPC)-based energy management system (EMS) of a PV energy-based grid-connected microgrid located in a snow-prone area. The PVPF method together with a computational intelligence-based short-term load demand forecasting model constitutes the forecasting block of the EMS. The forecasting block generates day-ahead hourly forecasts based on the local measurements of the meteorological-electrical parameters and sends them to the optimisation block where a two-stage control method, corresponding to the tertiary and secondary control levels, is developed based on mixed-integer linear and quadratic programming. The developed EMS is applied to a test microgrid simulated in MATLAB/Simulink and compared with a heuristic control method. The results show that the proposed approach can reduce the overall operation cost of the microgrid by 8% (24$), 15% (166$), and 13% (235$) on sunny, cloudy, and snowy days under study, respectively, compared to the heuristic controller.</p>","PeriodicalId":36490,"journal":{"name":"IET Smart Grid","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2023-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/stg2.12146","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138587208","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":"A novel hybrid centralised decentralised framework for electric vehicles coordination","authors":"Praveen Verma,&nbsp;Pallab Dasgupta,&nbsp;Chandan Chakraborty","doi":"10.1049/stg2.12144","DOIUrl":"10.1049/stg2.12144","url":null,"abstract":"<p>Hybrid Centralised-Decentralised Electric Vehicle (EV) coordination policy in the urgent charging scenario is presented. First, a robust and complex optimisation problem considering several key features affecting EV coordination is formulated. Then, a solution strategy for the formulated problem is proposed by decomposing the formulated problem into an EV coordination and simple optimisation problem. The decentralised rule-based EV coordination strategy works on the principle of direct load flattening and utilises practical EV aggregator-customer interaction, customer behaviour, and temporospatial shifting of the EVs to flatten the load duration curve at the charging station. Then, the centralised optimisation problem is solved to minimise the operation cost, decrease the power loss, and decrease congestion in the grid. A comparison between uncoordinated and coordinated charging in the case study conducted on the IEEE 24 bus system shows that the proposed approach reduces the average EV load by 1283.26 kW/min, average power loss by 2.465 kW/min, and operation cost by 61.99 $/min during the peak hours.</p>","PeriodicalId":36490,"journal":{"name":"IET Smart Grid","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/stg2.12144","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138603889","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}