Multi-Objective Optimal Scheduling for Multi-Renewable Energy Power System Considering Flexibility Constraints

Along with the connection of renewable energy sources to the power system, the economy and the reliability of the power system may be significantly affected due to the uncertainty and ran-domness of the renewable energy if the multi-renewable energy power system (MREPS) lacks flexibility. Therefore, minimizing the operation cost, curtailment rate of the renewable energy and power fluctuations on tie-line are considered in this paper. Moreover, an optimal day-ahead scheduling model of MREPS is also presented with involving the flexibility constraints for the distributed generations. Using the multi-objective particle swarm optimization (MOPSO) algorithm, the model can achieve a set of Pareto non-dominated solutions for the day-ahead scheduling strategy. Finally, the best compromise solution in the set is determined by fuzzy comprehensive evaluation method. The experimental results show the effectiveness of the presented method.