Location and Sizing of Battery Energy Storage Units in Low Voltage Distribution Networks

Andrea Mazza, Hamidreza Mirtaheri, Gianfranco Chicco, Angela Russo and Maurizio Fantino
Additional contact information
Andrea Mazza: Dipartimento Energia “Galileo Ferraris”, Politecnico di Torino, 10129 Turin, Italy
Hamidreza Mirtaheri: Links Foundation, 10138 Torino, Italy
Gianfranco Chicco: Dipartimento Energia “Galileo Ferraris”, Politecnico di Torino, 10129 Turin, Italy
Angela Russo: Dipartimento Energia “Galileo Ferraris”, Politecnico di Torino, 10129 Turin, Italy
Maurizio Fantino: Links Foundation, 10138 Torino, Italy

Energies, 2019, vol. 13, issue 1, 1-20

Abstract: Proper planning of the installation of Battery Energy Storage Systems (BESSs) in distribution networks is needed to maximize the overall technical and economic benefits. The limited lifetime and relatively high cost of BESSs require appropriate decisions on their installation and deployment, in order to make the best investment. This paper proposes a comprehensive method to fully support the BESS location and sizing in a low-voltage (LV) network, taking into account the characteristics of the local generation and demand connected at the network nodes, and the time-variable generation and demand patterns. The proposed procedure aims to improve the overall network conditions, by considering both technical and economic aspects. An original approach is presented to consider both the planning and scheduling of BESSs in an LV system. This approach combines the properties of metaheuristics for BESS sizing and placement with a greedy algorithm to find viable BESS scheduling in a relatively short time considering a specified time horizon, and the application of decision theory concepts to obtain the final solution. The decision theory considers various scenarios with variable energy prices, the diffusion of local renewable generation, evolution of the local demand with the integration of electric vehicles, and a number of planning alternatives selected as the solutions with top-ranked objective functions of the operational schedules in the given scenarios. The proposed approach can be applied to energy communities where the local system operator only manages the portion of the electrical grid of the community and is responsible for providing secure and affordable electricity to its consumers.

Keywords: distribution system; batteries; storage; planning; scheduling; decision theory (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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