Combined heat and power economic dispatch using opposition-based group search optimization

• This paper presents OGSO to solve CHEPD problem.
• Group search optimization is inspired by the animal searching behavior.
• OGSO has been used here to improve the effectiveness and quality of the solution.

This paper presents opposition-based group search optimization to solve non-smooth non-convex combined heat and power economic dispatch problem. Valve-point loading and prohibited operating zones of conventional thermal generators are taken into account. Group search optimization inspired by the animal searching behavior is a biologically realistic algorithm. Opposition-based group search optimization has been used here to improve the effectiveness and quality of the solution. The proposed opposition-based group search optimization employs opposition-based learning for population initialization and also for iteration wise update operation. The effectiveness of the proposed method has been verified on four test systems. The results of the proposed approach are compared with those obtained by other evolutionary methods. It is found that the proposed opposition-based group search optimization based approach is able to provide better solution.