A Power System Profitable Load Dispatch Based on Golden Eagle Optimizer

A Power System Profitable Load Dispatch Based on Golden Eagle Optimizer

Profitable load dispatch (PLD) is a typical multi-constrained nonlinear optimization problem considered an essential vital part of the power system to achieve energy-saving and consumption reduction. Dealing with the PLD problem using additional methods, e.g., gradient computing quadratic programming, would suffer from computational time complexity. The swarm intelligence optimization algorithm is one of the most promising effective ways of dealing with nonlinear optimization problems like the PLD issue. Gold-en Eagle optimizer (GEO) is a recent robust swarm intelligence optimization algorithm that has advantages as a few parameters, easy implementation, and powerful search capability. This study suggests a solution to the actual operation constraints of the power system of the PLD model based on novel GEO. The sum of a series of piecewise quadratic polynomials is modeled for the fitness function as the cost function used for figuring optimization out by the first-time GEO. In the experimental section, the IEEE-bus benchmark of 15 and 40-unit test systems are used as the case study to test the performance of the pro-posed scheme system. The results show that the proposed scheme can solve the power system PLD prob-lem with good robustness and significant economic benefits.