Linear Planning-Based Energy Management Strategies for Home Energy Storage Systems under Virtual Power Plants

In the virtual power plant system, the interaction between the grid and distributed energy sources is a very important link, and the home energy storage system plays an important role as the individual user side in the virtual power plant framework, and the energy storage users can respond to the grid’s regulation needs by reducing or delaying the electricity demand according to the grid’s demand and price signals. Under the dynamic price of the virtual grid, combining the control algorithm with the prediction of the market price of electricity can lead to a linear programming problem, which we solve using a linear programming solver and use it to determine the charging and discharging strategies of the home energy storage system. Relying on simulated price data from a virtual power plant, we conduct experiments that illustrate that the charging and discharging strategy proposed in this paper can save up to 13% of the cost compared to a charging and discharging strategy that does not use forecasts.