An Integrated Progressive Hedging and Benders Decomposition With Multiple Master Method to Solve the Brazilian Generation Expansion Problem

This paper exploits the decomposition structure of large-scale hydrothermal generation expansion planning problem with an integrated modified Benders Decomposition and Progressive Hedging approach. We consider detailed realistic data from Brazilian power system to represent hourly chronological constraints based on typical days per month year. Also, we multistage stochastic nature optimal operational policy through co-optimized linear decision rules for individual reservoirs. Therefore, ensure investment decisions compatible a nonanticipative (implementable) policy. To solve optimization problem, propose improved method multiple instances master each which strengthened by primal cuts new generated master’s trial solution. Additionally, our approach allows using penalization terms accelerating convergence method. show that is 60% faster than benchmark. Finally, consideration can save 7.64% total cost (16.18% costs) significantly improve spot price profiles.