Independent microgrid day-ahead optimization based on demand response

According to absorb renewable energy and smooth the load curve of independent microgrid, a strategy of demand response optimization, including controllable distributed generation, energy storing device and shiftable loads resource, is proposed. According to the day-ahead power forecast of renewable energy generation and electric power users' load, the strategy draws the payload power curve. The objective function is to minimize the difference between power supply and demand. Then, a day-ahead optimization model based on demand response is established. The results of the model are used to obtain the working condition at a certain time in the future, such as the switching state of the controllable distributed generation, the working state of the shiftable loads, the reference charging power and discharge power of the energy storage device, and reference state of charge. The example shows that the proposed optimization strategy can effectively reduce the load during the peak period of power consumption, reduce the residual power of renewable energy generation and increase the load rate of the controllable distributed generation. Meanwhile, this method predicts renewable energy generation and the short-term power of the load. According to the level of prediction error, the running state is coordinated and controllable among the controllable distributed generation, shiftable loads and energy storage device, providing an adjustable power margin for real-time scheduling of individual microgrids.