Efficient and Reliable Dynamic Economic Dispatch for a Hybrid Power System

Abstract

Hybrid electrical power systems are recently the trend for securing sustainable and environmental compatibility electrical energy source.  The article proposes Dynamic Economic Dispatch (DED) for running the hybrid power system over long time horizon with the objectives of reducing the operating costs while fulfilling the load requirements. A comprehensive comparative assessment of three distinctive metaheuristic optimizers for solving the DED problem of the standard 30-bus IEEE system is proposed. Marine Predators Algorithm (MPA), Artificial Protozoa Optimizer (APO) and Particle Swarm Optimizer (PSO) are the candidate optimizers under concern. The statistical measures are used to assess the stability and robustness of each technique in consistently obtaining the optimal solution. The results clearly demonstrated the superiority of MPA in achieving the minimum operating cost with remarkably high efficiency, robustness, and stability for both investigated power systems when compared with the other optimization techniques. The statistical analysis further confirmed the consistency and reliability of the proposed method across multiple independent runs and different system dimensions. In addition, the results revealed that the integration of renewable energy sources significantly contributed to reducing both the total operating cost and emission levels, highlighting the important economic and environmental advantages of renewable energy incorporation within modern DED frameworks.