Yushan Hou , Arthur Gonçalves Givisiez , Michael Z. Liu , Luis F. Ochoa
{"title":"Increasing PV hosting capacity with phase rebalancing in LV networks: A network-agnostic rule-based approach","authors":"Yushan Hou , Arthur Gonçalves Givisiez , Michael Z. Liu , Luis F. Ochoa","doi":"10.1016/j.segan.2024.101615","DOIUrl":null,"url":null,"abstract":"<div><div>Most residential photovoltaic (PV) systems are single-phase installations and, therefore, can increase unbalance. More unbalance exacerbates voltage rise issues on certain phases, potentially limiting the PV hosting capacity of low voltage (LV) networks. Rebalancing customers by adequately switching their phase connection can reduce unbalance and improve voltage headroom, allowing for more PV systems. However, this needs to be done quickly to cater for the normal variations in net demand. Furthermore, since most distribution companies do not have accurate, detailed three-phase LV network models, a solution independent of such models is desirable so it can be implemented. This paper proposes a fast, network-agnostic rule-based rebalancing approach that only requires knowledge of the phase groups, i.e., no network models are needed. Its feasibility is mathematically proven, and its effectiveness is benchmarked against a model-driven AC Optimal Power Flow (OPF)-based approach formulated as MINLP. Using a realistic Australian LV feeder with 29 single-phase customers, results show that the proposed approach mitigates unbalance as effectively as the OPF-based approach, in sub-seconds and without network models. Crucially, this paper demonstrates how a practical and scalable approach to reduce unbalance in two Australian LV networks—with different number of LV feeders and customers—can significantly increase the PV hosting capacity without resorting to PV curtailment.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"41 ","pages":"Article 101615"},"PeriodicalIF":4.8000,"publicationDate":"2024-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sustainable Energy Grids & Networks","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S235246772400345X","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0
Abstract
Most residential photovoltaic (PV) systems are single-phase installations and, therefore, can increase unbalance. More unbalance exacerbates voltage rise issues on certain phases, potentially limiting the PV hosting capacity of low voltage (LV) networks. Rebalancing customers by adequately switching their phase connection can reduce unbalance and improve voltage headroom, allowing for more PV systems. However, this needs to be done quickly to cater for the normal variations in net demand. Furthermore, since most distribution companies do not have accurate, detailed three-phase LV network models, a solution independent of such models is desirable so it can be implemented. This paper proposes a fast, network-agnostic rule-based rebalancing approach that only requires knowledge of the phase groups, i.e., no network models are needed. Its feasibility is mathematically proven, and its effectiveness is benchmarked against a model-driven AC Optimal Power Flow (OPF)-based approach formulated as MINLP. Using a realistic Australian LV feeder with 29 single-phase customers, results show that the proposed approach mitigates unbalance as effectively as the OPF-based approach, in sub-seconds and without network models. Crucially, this paper demonstrates how a practical and scalable approach to reduce unbalance in two Australian LV networks—with different number of LV feeders and customers—can significantly increase the PV hosting capacity without resorting to PV curtailment.
期刊介绍:
Sustainable Energy, Grids and Networks (SEGAN)is an international peer-reviewed publication for theoretical and applied research dealing with energy, information grids and power networks, including smart grids from super to micro grid scales. SEGAN welcomes papers describing fundamental advances in mathematical, statistical or computational methods with application to power and energy systems, as well as papers on applications, computation and modeling in the areas of electrical and energy systems with coupled information and communication technologies.