Self-adaptive differential evolution with Gaussian–Cauchy mutation for large-scale CHP economic dispatch problem

With the widespread application of co-generation units, the combined heat and power economic dispatch (CHPED) has become an important issue in the power system operation. Existing research work mostly focuses on small- or medium-scale CHPED problem, and there is very little research work on large-scale CHPED problems. Considering the characteristics of high-dimensional variables and huge search space in large-scale CHPED problem, it brings great challenge to the existing algorithms. In this paper, an improved differential evolution algorithm, called self-adaptive differential evolution with Gaussian–Cauchy mutation (SDEGCM), is proposed to solve the large-scale CHPED problem. In SDEGCM, in order to improve the performance, two strategies namely Gaussian–Cauchy mutation and parameter self-adaptation are introduced. Moreover, a constraint repair technique is used in SDEGCM to deal with complex operating constraints. The SDEGCM is applied to solve three large-scale CHPED problems with 48, 84 and 96 units, and compared with three well-established differential evolution and other methods in the literature. It is found that the proposed SDEGCM has advantages in terms of solution accuracy and stability for the large-scale CHPED problem.