Tobias Häring, Roya Ahmadiahangar, A. Rosin, H. Biechl
{"title":"Impact of Load Matching Algorithms on the Battery Capacity with different Household Occupancies","authors":"Tobias Häring, Roya Ahmadiahangar, A. Rosin, H. Biechl","doi":"10.1109/IECON.2019.8927495","DOIUrl":null,"url":null,"abstract":"Due to an increasing use of renewable energy sources in the power grid, it is of high importance to balance supply and demand for grid utilities and microgrid operators. If there are mismatches in the balancing, microgrids with islanded operation capabilities would be preferrable. In islanded mode, nearly zero energy buildings commonly use a stand-alone photovoltaics power supply with a battery storage. A battery storage is expensive and the capacity in case of off-grid operation depends on the electricity consumption of the dwelling's occupants. Using thermostatically controlled appliances like a freezer, water heater and space heating as additional storage systems can reduce the capacity of the battery storage system or increase the operation time in islanded mode for a fixed battery size. This paper analyzes the battery capacity dependency both on the control algorithms for the thermal storages and on the occupancy of the dwelling. Possible battery reductions for different selected occupancies are presented in this work by comparing the simulation results of different load matching algorithms to each other and between the different occupancies. The analysis of those results enables recommendations on the most suitable algorithm for most occupancy scenarios of an existing dwelling with respect to a minimized battery capacity. This can be particularly useful, for example, for dwelling and apartment owners who are renting out dwellings.","PeriodicalId":187719,"journal":{"name":"IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society","volume":"78 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IECON.2019.8927495","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 13
Abstract
Due to an increasing use of renewable energy sources in the power grid, it is of high importance to balance supply and demand for grid utilities and microgrid operators. If there are mismatches in the balancing, microgrids with islanded operation capabilities would be preferrable. In islanded mode, nearly zero energy buildings commonly use a stand-alone photovoltaics power supply with a battery storage. A battery storage is expensive and the capacity in case of off-grid operation depends on the electricity consumption of the dwelling's occupants. Using thermostatically controlled appliances like a freezer, water heater and space heating as additional storage systems can reduce the capacity of the battery storage system or increase the operation time in islanded mode for a fixed battery size. This paper analyzes the battery capacity dependency both on the control algorithms for the thermal storages and on the occupancy of the dwelling. Possible battery reductions for different selected occupancies are presented in this work by comparing the simulation results of different load matching algorithms to each other and between the different occupancies. The analysis of those results enables recommendations on the most suitable algorithm for most occupancy scenarios of an existing dwelling with respect to a minimized battery capacity. This can be particularly useful, for example, for dwelling and apartment owners who are renting out dwellings.