Research on Optimal Schedule of Multi-Source Joint System with High Wind Power Penetration

Aiming at the problem that the economic benefit of multi-source joint system is reduced due to the actual output of wind turbine tracking the dispatching command, a two-layer optimization strategy considering the wind power prediction error and demand side response is proposed in this paper. Aiming at minimizing the total operating cost of wind power, thermal power and translatable load, the upper model uses improved particle swarm optimization (IPSO) to formulate the optimal scheduling strategy of thermal power and translatable load, and samples the probability density function of the maximum output prediction error of the wind turbine to obtain the power shortage of the upper power supply of each sample. The lower model aims to minimize the total operating cost of energy storage and interruptible load, uses linear programming method to hedge the power shortage of the upper model, and then formulates the power scheduling strategy of the lower model. Under the background of a large number of samples, the economy and effectiveness of the proposed bi-level optimization strategy are verified by comparing the expectation and variance of the total cost function of each sample.