IET Smart Grid最新文献

{"title":"Fuzzy optimisation model of an incremental capacity auction formulation with greenhouse gas consideration","authors":"Karanveer Bhachu,&nbsp;Ayman Elkasrawy,&nbsp;Bala Venkatesh","doi":"10.1049/stg2.12065","DOIUrl":"10.1049/stg2.12065","url":null,"abstract":"<p>An incremental capacity auction (ICA) is a mechanism to procure future generation capacity in a power system. Greenhouse gas (GHG) emissions from generators negatively affect our climate and there is a real need to reduce them. Thus, it is critically important for ICA models to procure future generation capacity that reduces GHG emissions. In this paper, we propose two ICA models incorporating energy-limited generation (renewables and storage) and a GHG emission constraint. All offers are converted into unforced capacity, negating any effect of energy limitations of generation offers. The first ICA model uses classical optimisation and considers GHG emission limits and maximises social welfare (SW). The second ICA model uses a fuzzy optimisation technique to simultaneously optimise the objectives of SW maximisation and GHG emission minimisation. Both ICA models are tested on two datasets with 10 and 338 capacity supply offers constructed using Ontario data. While both models control GHG emissions as desired, the ICA model with fuzzy optimisation is shown to find a better balance between maximising net SW and minimising GHG emissions, with superior reductions in GHG for minor decreases in SW. Results demonstrate how GHG emission reduction results in increased selection of low carbon generation.</p>","PeriodicalId":36490,"journal":{"name":"IET Smart Grid","volume":"6 2","pages":"124-135"},"PeriodicalIF":2.3,"publicationDate":"2023-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/stg2.12065","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49291469","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":"Day-ahead continuous double auction-based peer-to-peer energy trading platform incorporating trading losses and network utilisation fee","authors":"Sheroze Liaquat,&nbsp;Tanveer Hussain,&nbsp;Berk Celik,&nbsp;Robert Fourney,&nbsp;Timothy M. Hansen","doi":"10.1049/stg2.12103","DOIUrl":"10.1049/stg2.12103","url":null,"abstract":"<p>Integration of distributed energy resources, such as photovoltaic solar (PV), introduces new opportunities to establish local energy market frameworks to improve renewable energy utilisation in residential sectors. Such peer-to-peer (P2P) energy trading refers to a local market structure where customers (and prosumers) interact to share excess PV generation to enhance the individual and community social welfare. In this work, a day-ahead continuous double auction (CDA)-based P2P market structure considering network losses and network utilisation fees was designed. Day-ahead PV energy is modelled using fractional integral polynomials and the output is forecasted using an autoregressive integrated moving average model for each market interval. Based on the customer load and excess PV energy, the CDA market is cleared using a bid/ask matching mechanism. The performance of the P2P market was evaluated by computing different welfare metrics while analysing the effect of network constraints. The results show that the designed CDA-based P2P market structure increases the social welfare of all participants by an average of 17.75% compared to the baseline for the presented cases. Moreover, the impact of the forecasting error between the day-ahead and real-time market was also quantified.</p>","PeriodicalId":36490,"journal":{"name":"IET Smart Grid","volume":"6 3","pages":"312-329"},"PeriodicalIF":2.3,"publicationDate":"2023-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/stg2.12103","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44461494","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":"Guest Editorial: Transition towards deep decarbonisation of modern energy systems","authors":"Yujian Ye,&nbsp;Can Wan,&nbsp;Chenghong Gu,&nbsp;Dan Wu,&nbsp;Goran Strbac,&nbsp;Hongjian Sun,&nbsp;Peng Zhang,&nbsp;Rui Bo,&nbsp;Yi Tang,&nbsp;Zhongbei Tian","doi":"10.1049/stg2.12102","DOIUrl":"https://doi.org/10.1049/stg2.12102","url":null,"abstract":"&lt;p&gt;The decarbonisation of modern energy systems is key to reducing global greenhouse gas emissions and hence mitigating climate change. While governments worldwide have taken significant initiatives towards decarbonisation and announced their carbon peaking and neutrality targets and plans, significant techno-economic challenges remain along the pathway to achieve this decarbonisation goal. Energy systems generally encompass multiple energy carriers, diverse temporal and spatial resolutions, and heterogenous energy entities. This necessitates a suitable design and control of the interfaces between electricity, natural gas, transportation, and heat networks, as well as the transportation, water and agricultural systems. Meanwhile, digital technologies such as big data, machine learning, blockchain, ICT, and IoT are receiving much attention as they can aid the decarbonisation process. Cyber-physical systems as an orchestration of these novel technologies further increases the efficiency of energy provision, thereby optimising economic feasibility and environmental impact.&lt;/p&gt;&lt;p&gt;This IET Smart Grid special issue on Transition Towards Deep Decarbonisation of Modern Energy Systems invites a broad spectrum of contributors from universities, industry, research laboratories, and policymakers to develop and present novel solutions and technologies that will facilitate and advance the agenda of deep decarbonisation of modern energy systems. This special issue solicits original research papers that target at, but are not restricted to, the following aspects. It is worth noting that this special issue places an emphasis on addressing the mutual research interests of academics and industry.&lt;/p&gt;&lt;p&gt;In this special issue, we have received 17 papers, all of which underwent peer review. Of the submitted papers, only seven have been accepted and nine have been rejected. Thus, the overall submissions were of high quality, which marks the success of this special issue.&lt;/p&gt;&lt;p&gt;The seven accepted papers focus on different aspects of different means of decarbonisation of modern energy systems, which can be clustered into three main categories: energy storage, energy markets, and energy Internet. The papers laying in the first category focus on how the most prominent flexibility sources including electric vehicle and energy storage technologies can be adopted safely and economically to aid the energy system decarbonisation. The papers in this category are of Sun et al., Chen et al., and Rolando et al. The second category of papers looks at how the flexibility potential of distributed energy resources can berealised through suitable participation in energy and ancillary service markets, so as to support renewable energy integration and low-carbon transition of energy systems. These papers are of Wang et al. and Shan et al. The last category of papers exhibits the evolution of smart grids towards the energy Internet and demonstrates their benefits towards decarbonisation. T","PeriodicalId":36490,"journal":{"name":"IET Smart Grid","volume":"6 1","pages":"1-4"},"PeriodicalIF":2.3,"publicationDate":"2023-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/stg2.12102","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50121498","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":"Transition towards deep decarbonisation of modern energy systems","authors":"Yujian Ye, C. Wan, C. Gu, Dan Wu, G. Strbac, Hongjian Sun, P. Zhang, Rui Bo, Yi Tang, Z. Tian","doi":"10.1049/stg2.12102","DOIUrl":"https://doi.org/10.1049/stg2.12102","url":null,"abstract":"","PeriodicalId":36490,"journal":{"name":"IET Smart Grid","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2023-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44359952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Overview of battery energy storage systems readiness for digital twin of electric vehicles","authors":"Rolando Gilbert Zequera,&nbsp;Anton Rassõlkin,&nbsp;Toomas Vaimann,&nbsp;Ants Kallaste","doi":"10.1049/stg2.12101","DOIUrl":"10.1049/stg2.12101","url":null,"abstract":"<p>The demand for energy is a relevant topic in the field of science and engineering, which has been discussed throughout the last years due to the challenges of climate change and environmental concerns around the world. Currently, electric vehicles (EVs) offer a source of mobility that emphasises the use of energy storage devices to reduce CO₂ emissions. The growing development of advanced data analytics and the Internet of Things has driven the implementation of the Digital Twin (DT), all to improve efficiency in the build, design and operation of the system. Regarding the components of EVs, the batteries are considered as the most expensive elements to analyse according to the State of Health and the State of Charge, which lead to implement the most optimal models, along with a DT for battery systems. The present article provides a literature review about the current development trends of EVs' energy storage technologies, with their corresponding battery systems, which gives an overview to understand different type of models and to identify future challenges in the industrial sector. Additionally, a solid explanation of the DT focussed on battery systems for EVs is discussed, highlighting some study cases, characteristics, and technological opportunities.</p>","PeriodicalId":36490,"journal":{"name":"IET Smart Grid","volume":"6 1","pages":"5-16"},"PeriodicalIF":2.3,"publicationDate":"2023-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/stg2.12101","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47037016","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":"Incentive-based demand response program with self-reported baseline supported by blockchain technology","authors":"Bin Li,&nbsp;Izzeddin Banimenia,&nbsp;Liu Chuan,&nbsp;Hou Zhansheng,&nbsp;Jianli Zhao","doi":"10.1049/stg2.12100","DOIUrl":"10.1049/stg2.12100","url":null,"abstract":"<p>This research presents a decentralised incentive-based demand response (DR) program using blockchain technology. Consumers self-report baseline to the system operator (SO), the smart contract confirms the validity of the data to execute transactions and finally the validators record the information on the blockchain network. During the DR event, a set of consumers are randomly selected to deliver the required load reduction. The signalled consumer who delivers the load reduction is rewarded, and the non-called consumers who diverge from their reported baseline are penalised. The randomness of choosing the consumers and penalty function restrict the baseline inflation. Here, we create a blockchain network and deploy a smart contract on the Ethereum build platform. A DR event scenario is adopted with residential houses data sets, all consumers report their baseline information to the SO through the Internet and smart meter. The SO calls four users to deliver the essential load reduction according to the probability of choosing a consumer. The smart contract verifies the received information to start transaction execution. We use proof of authority mechanism to select validation nodes from the participants using voting system. They validate each block before adding it to the blockchain. Last, the monetary transactions settle in participants' wallets. Our results confirm that decentralised systems like blockchain can significantly improve transparency, openness, and customer participation in the DR program. Also contributes to the security and privacy of user information with a minimal investment in new infrastructure.</p>","PeriodicalId":36490,"journal":{"name":"IET Smart Grid","volume":"6 2","pages":"205-218"},"PeriodicalIF":2.3,"publicationDate":"2023-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/stg2.12100","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46544268","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":"Optimal sizing of grid-connected rooftop photovoltaic and battery energy storage for houses with electric vehicle","authors":"Sarah Merrington,&nbsp;Rahmat Khezri,&nbsp;Amin Mahmoudi","doi":"10.1049/stg2.12099","DOIUrl":"10.1049/stg2.12099","url":null,"abstract":"<p>A practical optimal sizing model is developed for grid-connected rooftop solar photovoltaic (PV) and battery energy storage (BES) of homes with electric vehicle (EV) to minimise the net present cost of electricity. Two system configurations, (1) PV-EV and (2) PV-BES-EV, are investigated for optimal sizing of PV and BES by creating new rule-based home energy management systems. The uncertainties of EV availability (arrival and departure times) and its initial state of charge, when arrives home, are incorporated using stochastic functions. The effect of popular EV models in the market is investigated on the optimal sizing and electricity cost of the customers. Several sensitivity analyses are adopted based on variations in the grid constrains, retail price and feed in tariff. Uncertainty analysis is provided based on the variations of insolation, temperature, and load to approve the optimal results of the developed model. A practical guideline is presented for residential customers in a typical grid-connected household to select the optimal capacity of PV or PV-BES system considering the model of EV. While the proposed optimization model is general and can be used for various case studies, real annual data of solar insolation, temperature, household's load, electricity prices, as well as PV and BES market data are used for an Australian case study. The developed optimal sizing model is also applied to residential households in different Australian States.</p>","PeriodicalId":36490,"journal":{"name":"IET Smart Grid","volume":"6 3","pages":"297-311"},"PeriodicalIF":2.3,"publicationDate":"2023-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/stg2.12099","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46135682","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":"Phasor data concentrator placement in phasor measurement unit networks considering communication channel uncertainty and failure","authors":"Maryam Dehghani,&nbsp;Navid Vafamand","doi":"10.1049/stg2.12098","DOIUrl":"10.1049/stg2.12098","url":null,"abstract":"<p>One challenge in Wide Area Measurement System is to design a reliable network which assures data availability. The availability of data in Phasor Measurement Unit (PMU) networks depends on two factors: 1-Reliable data measurements which depend on performance of PMUs and transmission branches, 2-Reliable data transmission which depends on the reliability of communication networks used to transfer data from PMUs to Phasor Data Concentrators (PDCs) and control centre. The reliability of data transmission can be improved by choosing proper locations for PDCs. In this paper, a novel approach for PDC placement is proposed based on two pre-defined indices; observability reliability and Loss Of Data Expectation (LODE). In the proposed method, the probability of regional communication networks' failure and the uncertainty of failure data for all components are also included in the calculation of these two indices to achieve more realistic results. To handle uncertainty, fuzzy membership functions are obtained for repair time and failure rate of all components, and a fuzzy Monte Carlo method is presented to evaluate both indices for each possible PDCs' location. The minimum LODE is used to find the best locations for PDCs. The proposed method is investigated for three sample systems which prove the system efficacy.</p>","PeriodicalId":36490,"journal":{"name":"IET Smart Grid","volume":"6 3","pages":"284-296"},"PeriodicalIF":2.3,"publicationDate":"2022-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/stg2.12098","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49384155","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":"V-I droop-based distributed event- and self-triggered secondary control of AC microgrids","authors":"Masoud Hajian,&nbsp;Mohammad S. Golsorkhi,&nbsp;Alireza Ranjbar,&nbsp;Qobad Shafiee,&nbsp;Mehdi Savaghebi","doi":"10.1049/stg2.12097","DOIUrl":"10.1049/stg2.12097","url":null,"abstract":"<p>In this study, distributed event-and self-triggered (ST) control methods are proposed for accurate load sharing and voltage control in islanded AC microgrids with resistive line impedances. The proposed control framework is comprised of a two-level control structure. At the primary level, the V-I droop control method is adopted. In this method, the distributed energy resources (DERs) are synchronised to a common synchronous reference frame and load sharing is accomplished through voltage-current droop characteristics in this frame. The secondary level, which has a distributed structure, mitigates the voltage deviations induced by the primary level and eliminates the current sharing error caused by the line impedances. The data exchange among the DERs is controlled using event- and ST algorithms. In order to reduce the communication burden, the feedback control laws are realised using estimated variables, which are updated at certain event times. The event times are extracted based on Lyapunov stability analysis and by consideration of the V-I droop characteristics. Comparison of event and ST algorithms shows that while the event-triggered strategy offers superior dynamic response, the ST approach requires lower network traffic. The efficacy of the proposed scheme is verified through real time simulation results.</p>","PeriodicalId":36490,"journal":{"name":"IET Smart Grid","volume":"6 3","pages":"271-283"},"PeriodicalIF":2.3,"publicationDate":"2022-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/stg2.12097","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46581260","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":"Coordinated control strategy for vehicle-to-grid support at distribution node","authors":"Kannan Thirugnanam,&nbsp;Chau Yuen,&nbsp;Praveen Kumar,&nbsp;Tareg Ghaoud,&nbsp;Sgouris Sgouridis","doi":"10.1049/stg2.12086","DOIUrl":"10.1049/stg2.12086","url":null,"abstract":"<p>The increasing number of electric vehicles (EVs) creates voltage rise/drop problems when integrated into a distribution node (DN). This generally occurs when EVs inject energy to or draw energy from the DN in a stochastic manner. A vehicle-to-grid service for voltage support of DN through controlled and coordinated EV charging and discharging techniques to maintain the DN voltage within the threshold limits is proposed. In this context, a fuzzy logic control (FLC) is developed to generate reference power signal and the power flow direction based on DN voltage and electric vehicle charging station’s (EVCS) available energy. Here, the EVCS is a place where the EVs are charged and/or participate for grid support. Then, an EVCS aggregator is implemented to coordinate the large fleet of EVs based on FLC output and EV’s available energy. Furthermore, an EV’s battery charge and discharge rate controller is developed to control the EV’s energy based on EVCS aggregator output and charge/discharge rate threshold limits. Finally, an active and reactive power control methodology is implemented to maintain DN voltage profile within the threshold limits. Extensive simulations are conducted based on real data from a radial distribution system. The results show that the EVCS can successfully maintain the DN voltage within the threshold limit through the proposed control and coordination strategy.</p>","PeriodicalId":36490,"journal":{"name":"IET Smart Grid","volume":"6 2","pages":"158-174"},"PeriodicalIF":2.3,"publicationDate":"2022-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/stg2.12086","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45888228","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}