Using Load Forecasting to Control Domestic Battery Energy Storage Systems

Juha Koskela, Antti Mutanen and Pertti Järventausta
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Juha Koskela: Unit of Electrical Engineering, Tampere University, FI-33014 Tampere, Finland
Antti Mutanen: Unit of Electrical Engineering, Tampere University, FI-33014 Tampere, Finland
Pertti Järventausta: Unit of Electrical Engineering, Tampere University, FI-33014 Tampere, Finland

Energies, 2020, vol. 13, issue 15, 1-20

Abstract: The profitability of domestic battery energy storage systems has been poor and this is the main barrier to their general use. It is possible to increase profitability by using multiple control targets. Market price-based electricity contracts and power-based distribution tariffs alongside storage of surplus photovoltaic energy make it possible to have multiple control targets in domestic use. The battery control system needs accurate load forecasting so that its capacity can be utilized in an optimally economical way. This study shows how the accuracy of short-term load forecasting affects cost savings by using batteries. The study was conducted by simulating actual customers’ load profiles with batteries utilized for different control targets. The results of the study show that knowledge of customers’ load profiles (i.e., when high and low peaks happen) is more important that actual forecast accuracy, as measured by error criteria. In many cases, the load forecast based on customers’ historical load data and the outdoor temperature is sufficient to be used in the control system, but in some cases a more accurate forecast can give better cost savings.

Keywords: battery energy storage system; load forecast; control system (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: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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