Data-driven battery operation for energy arbitrage using rainbow deep reinforcement learning

06/10/2021
by   Daniel J. B. Harrold, et al.
0

As the world seeks to become more sustainable, intelligent solutions are needed to increase the penetration of renewable energy. In this paper, the model-free deep reinforcement learning algorithm Rainbow Deep Q-Networks is used to control a battery in a small microgrid to perform energy arbitrage and more efficiently utilise solar and wind energy sources. The grid operates with its own demand and renewable generation based on a dataset collected at Keele University, as well as using dynamic energy pricing from a real wholesale energy market. Four scenarios are tested including using demand and price forecasting produced with local weather data. The algorithm and its subcomponents are evaluated against two continuous control benchmarks with Rainbow able to outperform all other method. This research shows the importance of using the distributional approach for reinforcement learning when working with complex environments and reward functions, as well as how it can be used to visualise and contextualise the agent's behaviour for real-world applications.

READ FULL TEXT
research
08/26/2022

Battery and Hydrogen Energy Storage Control in a Smart Energy Network with Flexible Energy Demand using Deep Reinforcement Learning

Smart energy networks provide for an effective means to accommodate high...
research
03/06/2022

Offline Deep Reinforcement Learning for Dynamic Pricing of Consumer Credit

We introduce a method for pricing consumer credit using recent advances ...
research
10/24/2022

Energy Pricing in P2P Energy Systems Using Reinforcement Learning

The increase in renewable energy on the consumer side gives place to new...
research
08/14/2021

Offline-Online Reinforcement Learning for Energy Pricing in Office Demand Response: Lowering Energy and Data Costs

Our team is proposing to run a full-scale energy demand response experim...
research
12/13/2022

Model-Free Approach to Fair Solar PV Curtailment Using Reinforcement Learning

The rapid adoption of residential solar photovoltaics (PV) has resulted ...
research
02/07/2018

Efficient collective swimming by harnessing vortices through deep reinforcement learning

Fish in schooling formations navigate complex flow-fields replete with m...

Please sign up or login with your details

Forgot password? Click here to reset