Crisscross PSO algorithm for multi-objective generation scheduling of pumped storage hydrothermal system incorporating solar units

Abstract

This paper investigates the integration of conventional and renewable energy sources and its impact over the power system generation scheduling. The multi-objective optimization framework is implemented for the economic emission scheduling of the pumped storage hydrothermal (PSHT) system incorporating solar units. The heuristic optimization technique named as crisscross search particle swarm optimization (CSPSO) has been implemented to solve the scheduling problem. In the heuristic approach, an initial solution has been updated by the improved particle swarm optimization (IPSO) approach and then local best solutions are updated by using horizontal and vertical crossover operators. The horizontal crossover operator is applied to enhance the search capability and the vertical crossover operation is implemented to mitigate the dimensional stagnancy problem. The improved binary PSO is applied to update the discrete binary variables. The cardinal priority method is used to search most satisfying the non dominated solution. In order to validate the performance of CSPSO, it has been applied to minimize cost and pollutant emission of the standard hydrothermal system and PSHT system incorporating solar units. The obtained results have been compared with the reported results in the literature and found satisfactory. More specifically, it has been observed from the results of test system-I and II that inclusion of pumped storage unit (PSU) and solar power generation is able to decrease the cost by 3.87% and 6.79%, respectively and emission by 22.01% and 23.69%, respectively. Further, the mutual impact of solar power and the PSU is able to decrease the cost and emission by 10.27% and 39.74%, respectively. The statistical test has been performed to validate the robustness of the optimization technique.