Optimizing a domestic battery and solar photovoltaic system with deep reinforcement learning

2021/09/10 by Kell, Alexander J. M., McGough, A. Stephen, Forshaw, Matthew
#Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG)

paper · doi:10.48550/arxiv.2109.05024

Abstract

A lowering in the cost of batteries and solar PV systems has led to a high uptake of solar battery home systems. In this work, we use the deep deterministic policy gradient algorithm to optimise the charging and discharging behaviour of a battery within such a system. Our approach outputs a continuous action space when it charges and discharges the battery, and can function well in a stochastic environment. We show good performance of this algorithm by lowering the expenditure of a single household on electricity to almost $1AUD for large batteries across selected weeks within a year.

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