VidyutVanika: An Autonmous Broker Agent for Smart Grid Environment

We describe the design of an autonomous electricity broker agent, VidyutVanika, the runner-up of the 2018 PowerTAC competition. The agent uses techniques from reinforcement learning, dynamic programming and other areas of machine learning to seek appropriate actions in tariff and wholesale market of the PowerTAC simulation environment. The novelty of our agent lies in defining the reward functions of suitably defined Markov decision processes (MDPs), solving these MDPs, and applying these solutions to real actions in the market. In addition, VidyutVanika uses a neural network to predict the energy consumption of various customers using weather data. The usage forecasts, so obtained, are used to place orders in day-ahead wholesale market. These forecasts also helps in reducing the balancing costs incurred by