Energy Management for Energy Internet: A Combination of Game Theory and Big Data-Based Renewable Power Forecasting

Abstract

Energy internet provides an open framework for integrating every pieces of equipment involved in energy generation, transmission, transformation, distribution and consumption with novel information and communication technologies. In this paper, we adopt a combination of game theory and big data to address the coordinated management of renewable and traditional energy, which is a typical issue on energy interconnections. We formulate the energy management problem as a three-stage Stackelberg game, and employ the backward induction method to derive the closed-form expressions of the optimal strategies. Next, we study the big data-based power generation forecasting techniques, and introduce a scheme of the wind power forecasting, which can assist the microgrid to make strategies. Simulation results show that more accurate prediction results of wind power is conducive to better energy management.