Optimal operation of wind-hydrothermal systems considering certainty and uncertainty of wind

This paper proposes a High Performance Cuckoo Search Algorithm (HPCSA) for determining suitable operation parameters of the optimal wind-hydro-thermal system scheduling (OWHTSS) problem. The objective of the problem is to reach the lowest electricity generation cost of thermal power plants (TPPs) and wind power plants (WPPs) while exactly meeting all constraints of TPPs, WPPs and hydroelectric plants (HEPs). HPCSA is formed by applying improvements on the two main techniques of original Cuckoo Search Algorithm (CSA) to cover CSA' drawbacks such as searching random solution spaces, always using two random solutions for getting a jumping step and suffering from slow convergence. HPCSA accompany with CSA, Adaptive CSA (ACSA), Snap-Drift CSA (SDCSA) and Water Cycle Algorithm (WCA) are run for solving four test systems in which the largest and complicated system is comprised of four TPPs, four HEPs and two WPPs with the uncertain wind feature. The result comparisons indicate that HPCSA is superior to applied and previous methods, and other modified versions of CSA in the literature in terms of better cost, higher stability, faster search ability and higher success rate. As a result, it leads to a conclusion that HPCSA is a strong metaheuristic algorithm for solving OWHTSS problem. (C) 2021 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Alexandria University.

Automated summary

This paper proposes a High Performance Cuckoo Search Algorithm (HPCSA) for determining suitable operation parameters of the optimal wind-hydro-thermal system scheduling (OWHTSS) problem, and experiments show that it outperforms other methods in terms of cost, stability, search speed, and success rate.