Scenario based stochastic optimal operated for hybrid energy system with random drift swarm optimization

To deal with the uncertainties of wind power and solar energy, the theory of stochastic programming is introduced, and this paper proposes an optimal model of economic dispatch of power system which the prediction error of wind power and photovoltaic output power is considered. Firstly, the stochastic probability distribution model of wind power and solar energy is analyzed. And then the scenarios are constructed by Latin hypercube sampling(LHS). To reduce the complexity of the model, the secenarios reduction method is used to reduce the similarity and low probability scenarios. On the basis of the above analysis, the costs of thermal power unit fuel and energy storage system operation are comprehensively considered, and the random drift particle swarm optimization algorithm which is used to obtain the minimum expected total cost of the hybrid system in the research period is applied. The energy storage system is introduced to reduce the impact of the prediction error of wind power and solar energy on power system stability. The case study indicates the rationality and effectiveness of the proposed model.