Application of Multi-objective New Whale Optimization Algorithm for Environment Economic Power Dispatch Problem

This study proposes a multi-objective new whale optimization algorithm (MONWOA) to solve environment economic power dispatch (EED) problem. The EED problem is a nonlinear multi-constrained multi-objective optimization problem, which can be solved by MONWOA method that has strong ability to find the best compromise solution (BCS). In order to balance exploration and exploitation of the algorithm, the Gaussian mutation operator, variation process of differential evolution algorithm and search mode parameter are adopted to improve the standard multi-objective whale optimization algorithm (MOWOA). Furthermore, a new constraint handling method combined with the MONWOA is put forward to find the Pareto solution set with better distribution. Six experiments aimed at simultaneously optimizing fuel cost and emission, fuel cost with valve-point effect and emission, power loss and emission are carried on IEEE 30 bus, 57 bus and 118 bus systems. Compared with MOWOA and traditional MOPSO methods, the results of Pareto fronts and BCS show the superiority of WONWOA to solve EED problems. Moreover, the result of two performance indicators, it is clearly show that the stability and diversity of MONOWA method were stronger than the other two comparison algorithms.