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

As renewable energy penetration increases, the lack of flexibility in a multi-renewable power system can seriously affect its own economics and reliability. To address this issue, three objectives are considered study: fluctuations on tie-line, operating cost, curtailment rate energy. Presented also is an optimal day-ahead scheduling model based MREPS for distributed generations with constraints. The multi-objective particle swarm optimization (MOPSO) algorithm be applied to obtain set Pareto non-dominated solutions strategy proposed model. By using fuzzy comprehensive evaluation, compromise solution determined set. presented method sacrifices small amount economy fluctuation, but it reduce deviation between forecast realized while improving utilization