Application of Hyper-Spherical Search Algorithm for Combined Heat and Power Planning Considering Peak Load Model and Valve Point Effect

The combined heat and power (CHP) generation is an energy-saving method in which power and heat are simultaneously generated. The important features of heat and power units are the interdependence between the amount of power and heat generated, which increases the complexity of the problem and can be solved by powerful optimization methods. In this paper, planning and optimizing the combined heat and power generation, including the supply of electrical and thermal power required by the network, are performed. This goal is achieved with two main approaches, including the valve point effect and examining this effect while modeling load peak in the presence of energy storage systems of the battery type, which is the novelty of this paper. This paper offers the hyper-spherical search (HSS) algorithm and particle swarm optimization method to optimize and solve the problem of CHPED in large units and, then, compares and validates the results. The simulation results show that the proposed methods can be used as a reliable method to solve the problem of CHPED by considering different constraints.