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

2021-09-10 10:59:14
Alexander J. M. Kell, A. Stephen McGough, Matthew Forshaw
arXiv_AI
     
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.

Abstract (translated)

URL

https://arxiv.org/abs/2109.05024

PDF

https://arxiv.org/pdf/2109.05024.pdf

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