FRAMEWORK OF HYBRID RENEWABLE ENERGYWITH CONVENTIONAL POWER GENERATION SCHEDULING USING NOVEL METAHEURISTIC OPTIMIZATION ALGORITHM

Abstract

In the present era, only thermal generation cannot be a solution to modern demand. The hybrid renewable energy with conventional power generation is the answer to save mother nature and meet the current electricity demand. In this article, traditional thermal power plants are interconnected with natural resources like wind, hydro units with all-day planning and operation strategies. And the generated power is needed to transfer from one section to another section in the existing grid system, which is the subject of available transfer capability (ATC), the modern power system’s critical factor. In this article, the minimization of power generation cost of the thermal power units is achieved by incorporating renewable sources, says hydro, and wind plants for 24 h scheduled, and ATC calculation is the prime objective. In recent literature, the mayfly algorithm (MA) optimization approach, which combines the advantages of evolutionary algorithms and swarms intelligence to attend better results, is successfully implemented. In this article, optimum power flow (OPF)-based ATC is enforced under various conditions with hydro–thermal–wind scheduling concept on the IEEE 39-test bus system to check the proposed chaotic MA’s performance. The chaotic MA (CHMA) is a hybridized format of the MA and chaotic map method. It is noted from the simulation study that the suggested novel CHMA approach has a dominant nature over other well-established optimization algorithms. Also in the case of multi-objective function, the cost function value is improved by more than 10% and ATC value is enhanced by near about 60% and more.