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arXiv · 2109.05024

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

Alexander J. M. Kell·A. Stephen McGough·Matthew Forshaw
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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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Alexander J. M. Kell, A. Stephen McGough, Matthew Forshaw. 2021-09-10. Optimizing a domestic battery and solar photovoltaic system with deep reinforcement learning. https://arxiv.org/abs/2109.05024

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