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

09/10/2021
by   Alexander J. M. Kell, et al.
0

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.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
10/26/2018

Using solar and load predictions in battery scheduling at the residential level

Smart solar inverters can be used to store, monitor and manage a home's ...
research
07/29/2021

Predicting battery end of life from solar off-grid system field data using machine learning

Hundreds of millions of people lack access to electricity. Decentralised...
research
01/23/2014

Plan-based Policies for Efficient Multiple Battery Load Management

Efficient use of multiple batteries is a practical problem with wide and...
research
07/31/2023

Recovery Policies for Safe Exploration of Lunar Permanently Shadowed Regions by a Solar-Powered Rover

The success of a multi-kilometre drive by a solar-powered rover at the l...
research
06/09/2021

Design and fabrication of solar powered remote controlled all terrain sprayer and mower robot

Manual spraying of pesticides and herbicides to crops and weed inhibitor...
research
09/15/2021

Optimal Cycling of a Heterogenous Battery Bank via Reinforcement Learning

We consider the problem of optimal charging/discharging of a bank of het...
research
12/05/2018

SolarGest: Ubiquitous and Battery-free Gesture Recognition using Solar Cells

We design a system, SolarGest, which can recognize hand gestures near a ...

Please sign up or login with your details

Forgot password? Click here to reset