  As the share of renewable energy sources in the present electric energy mix
rises, their intermittence proves to be the biggest challenge to carbon free
electricity generation. To address this challenge, we propose an electricity
pricing agent, which sends price signals to the customers and contributes to
shifting the customer demand to periods of high renewable energy generation. We
propose an implementation of a pricing agent with a reinforcement learning
approach where the environment is represented by the customers, the electricity
generation utilities and the weather conditions.
