A Novel Mantis Search Algorithm for Economic Dispatch in Combined Heat and Power Systems

Economic dispatch in combined heat and power (CHP) schemes takes into account the trade-off between generating electricity and producing heat, ensuring that the system operates at the highest level of efficiency and cost-effectiveness. A Mantis Search Algorithm (MSA), in this paper, is developed to address the CHP economic dispatch taking into consideration valve points effect, feasible region constraints for CHP units, and power losses are considered all at once. The MSA draws its inspiration from the unique sexual cannibalism and foraging strategies of praying mantises including three stages of optimization which are hunting, attacking, and cannibalism. Moreover, various recent meta-heuristic optimization algorithms, such as the Aquila Optimizer (AO), Gradient-based Optimizer (GBO), Coot Optimizer (CO), and African Vultures Algorithm (AVO), are utilized for comparative analysis across the two test systems. The developed MSA is demonstrated to be superior across three power and heat loading levels for both a 7-unit system and a larger 84-unit system. In the case of the large 84-unit system, MSA exhibits a significant cost reduction, surpassing AVO, GBO, CO, and AO by 2.017%, 2.511%, 0.817%, and 0.126%, respectively. Simulation results confirm the remarkable efficiency of MSA as a promising solution for economic dispatch in combined heat and power schemes. Testing outcomes indicate that MSA outperforms several previously published methods in the literature, as well as the four adopted optimizers.