An Intelligent Heap-Based Technique With Enhanced Discriminatory Attribute for Large-Scale Combined Heat and Power Economic Dispatch

Abstract

The basic goal of Combined Heat and Power Economic Dispatch (CHPED) is to find the best value for heat obtained from heat generators, power obtained from power generators, and both power and heat obtained from co-generators such that fuel costs are kept minimum while heat and power demands and constraints are met precisely. Based on enhanced discriminatory attribute, a newly Improved version of the Heap-based Technique (IHT) is to increase the searching capacity around the leader position and avoid trapping in a local optimum. Additionally, an adaptive parameter is used linearly to half of the iteration to select an effective operation for creating the new solutions. On 25 benchmark optimizing functions of unimodal or multimodal properties, the efficacy of the proposed IHT in contrast to the traditional HT is tested. Additionally, the proposed IHT in contrast to the traditional HT are employed for CHPED with small scale (seven units), medium scale (twenty-four) and two large-scale (eighty-four and ninety-six) systems with consideration of valve point loading and transmission losses constraints. According to comparisons of results obtained by the IHT with existing approaches, it is shown that the proposed IHT is particularly effective and resilient for finding optimal solutions for the CHPED.