An optimal power flow solution to deregulated electricity power market using meta-heuristic algorithms considering load congestion environment

Abstract

In this article, the Improved Mayfly Algorithm (IMA) is used as an upgraded form of the Mayfly Algorithm (MA), featuring simulated binary crossover and polynomial mutation operators replacing the arithmetic crossover and standard distribution mutation operators of the MA. With MA, IMA's achievements and significance are acknowledged. The algorithms achieve a final best solution for the investigated objective functions of the optimal power flow problem in a deregulated electrical power market under different load conditions. The overall load of the power system varies between half of the base load (-50%) and twice the base load (+100%). The investigated objective functions are associated with the financial worth of generators, dissipation of active power in transmission lines, variation of voltage magnitudes at the system bus, and voltage stability index at the load bus of the power system networks. The result achieved by GA, PSO, MA and IMA are attained using the IEEE-30 bus test system in a deregulated power system. Investigations are conducted on the best solutions for each objective function; offers of generators and bids of loads; generator sales and load purchases; and system revenues associated with different load scenarios. The simulated outcomes have confirmed that IMA would triumph over GA, PSO and MA.