Potential and Optimal Sizing of Combined Heat and Electrical Storage in Private Households. (November 2016)

• Record Type: Journal Article
• Authors: Zurmühlen, Sebastian; Wolisz, Henryk; Angenendt, Georg; Magnor, Dirk; Streblow, Rita; Müller, Dirk; Sauer, Dirk Uwe
• Is Part Of: Energy procedia. Volume 99(2016)
• Page Start: 174
• Page End: 181
• Publication Date: 2016-11
• Subjects: PV home storage system -- heat storage -- thermal storage -- self-consumption -- battery energy storage system; Power resources -- Congresses; Power resources -- Periodicals; Power resources; Conference proceedings; Periodicals; 333.7905
• DOI: 10.1016/j.egypro.2016.10.108
• Languages: English
• ISSNs: 1876-6102

Abstract

Abstract: The increase in fluctuating renewable electricity generation requires growing flexibility and balancing capacities in the electric energy grid. Storage systems can provide the necessary balancing capacities. Therefore, it is analyzed which potential for flexible energy consumption can be found in private households. Heat and power in private households are heavily interlinked due to increasing numbers of electrical heating systems (e.g. heat pumps). In addition, installed PV systems on roof tops are making renewable electricity an attractive energy source for space heating and hot water supply. To maximize the consumption of self-generated electricity, battery energy storage systems (BESS) and thermal hot-water based storage systems are used in private households. The challenge is to find economically viable configurations for sizing of combined battery and thermal storage units. The introduced approach simulates a household with a variable size of the relevant components of the thermal and electric system, being the PV system, PV and battery converters (DC linked), the battery (lithium-ion), thermal hot water storage and a heat pump. Profiles for the electrical load are based on empirical analysis of resident behavior coupled with measurements from typical household appliances. The thermal load profiles are derived from representative simulation tools, simulating resident behavior and the resulting heat demand. Based on the simulation results, an optimal sizing of storage units is calculated.