An Improved Honey Badger Algorithm for Solving Congestion Management of Power System Considering Effective of Renewable Energy Resources

Abstract

To achieve the goal of operating the power system economically, the transmission system is normally operated in stressed conditions. Congestion management (CM) is a suitable solution to reduce the burden of transmission systems by rescheduling generators. In this paper, an Improved honey badger algorithm (IHBA) is proposed to resolve the CM problems with minimal total cost and minimal CO2 Emissions cost. The main idea of the this improved algorithm is to improve the exploitation strategy of the HBA algorithm based on the best individual in the population. The IEEE 30-bus system with and without RESs is used to test the effectiveness of the proposed IHBA algorithm. The simulation results of IHBA are compared with the original HBA, Carpet Weaver Optimization (CWO) algorithm, Electric eel foraging optimization and multiobjective salp swarm algorithm. The simulation results show that the optimal value obtained by the proposed IHBA algorithm reduces 0.02% compared with the original HBA, 0.313% for MOSSA, 0.007% for EEFO and 0.55 % for CWO with Generation Costs. For CO2 Emissions cost, IHBA reduces 0.039% compared with the original HBA, 15.582% for MOSSA, 0.204% for EEFO and 3.481 % for CWO. Thus, the proposed algorithm is one of the suitable methods, powerful, and reliable techniques for solving the CM problem with the penetration of RESs.