Multi-objective generation scheduling of integrated energy system using fuzzy based surrogate worth trade-off approach

Abstract

The aim of this research work is to resolve the economic, emission and multi-objective scheduling problem (MOSP) of the integrated energy system (IES). The integrated energy system incorporates pumped storage hydrothermal system (PSHTS) with wind, solar and battery units. The pumped storage unit can work in generating or pumping mode and its operation is controlled by binary decision variables, hence, the integrated energy system consist mixed mode decision variables. In order to search optimum generation schedule, a modified crisscross PSO (MCPSO) and improved binary PSO technique has been undertaken. The crisscross search in the CPSO technique exhibits horizontal and vertical crossover operators to explore the search space in every dimension and mitigate the stagnancy problem. In MCPSO technique, the search has been enhanced in way of pattern search in every search direction. In this work, the surrogate worth trade-off (SWT) function perform as an interface between the decision maker and Pareto-front to select the best-compromised solution of the MOSP and reduces the computational efforts. The performance of the MCPSO-SWT has been verified on four different test systems. The test results achieved from the economic, emission and MOSP have been compared with results obtain from the well-established techniques and found satisfactory.