A New Fast Deterministic Economic Dispatch Method and Statistical Performance Evaluation for the Cascaded Short-Term Hydrothermal Scheduling Problem

The Cascaded Short-Term Hydrothermal Scheduling (CSTHTS) problem is a highly non-linear, multi-modal, non-convex, and NP-hard optimization that has been solved by conventional metaheuristic algorithms in the past. As CSTHTS falls under category of applied operational research, therefore, work still on-going to find new variants existing would better approximate optimal global solution shorter computational time. This article proposes novel deterministic thermal economic dispatch method embedded with improved Accelerated Particle Swarm Optimization (APSO) algorithm infinitesimally reduce Big O time complexity for standard benchmark test case problem. Then, it discusses presents importance performing statistical tests establish supremacy one over other solving results obtained are than many state-of-the-art solve considered literature, superiority APSO established statistically using parametric independent samples t-test non-parametric Mann–Whitney U-test such as particle swarm chosen