Enhancing Heap-Based Optimizer for Better Dispatching of Combined Heat and Power Units

Associate Professor, Department of CS & IT, Kalinga University, Raipur, India.
Research Scholar, Department of CS & IT, Kalinga University, Raipur, India.

Abstract

The present state of the energy industry has led to increased energy prices and restrictions on the use of fossil fuels as a source of energy. As a result, combined heat and power units evolve more quickly than they would in the existing systems. An actual optimization problem with several intricate constraints is the best way to dispatch CGUs. This study therefore proposes an enhanced heap-based optimizer approach that strikes a healthy balance between the beginning and end phases of global search and convergence, respectively, in order to address the optimal dispatch problem. This problem provides the optimal scheduling for heat and power producing units while considering their working constraints in order to reduce the overall fuel cost supplied for the combined units. Three test systems—a 7-unit, a 24-unit, and a 48-unit system—have been utilized to confirm the efficacy of the proposed IHBO algorithm. At three distinct power and heat loading levels, the anticipated MSA is demonstrated to be superior for both a smaller 7-unit system and a larger 84-unit system. The method was improved in this work to solve the system of nonlinear equations that arises from explicitly describing the EDP lossy optimization issue.