Crisscross optimization algorithm for solving combined heat and power economic dispatch problem

As cogeneration plays an increasingly important role in energy utilization, the combined heat and power economic dispatch (CHPED) becomes an important task in power system operation. In this paper, a novel crisscross optimization (CSO) algorithm is implemented to solve the large scale CHPED problem, which is a challenging non-convex optimization problem with a large number of local minima. The feature of applying CSO to address the CHPED problem lies in two interacting operators, namely horizontal crossover and vertical crossover. The horizontal crossover searches for the new solutions within a half population of hyper-cubes with a large probability while in their respective peripheries with a decreasing probability. The vertical crossover provides a effective mechanism for those stagnant dimensions of a population to escape from premature convergence. The combination of both gifts CSO with a powerful global search ability. The effectiveness of the proposed method is validated on six cogeneration systems with different characteristics. The numeric results demonstrates that the proposed CSO method achieves much better results than other methods reported in the literature. To investigate the robustness and applicability of CSO in large power system, two new systems with 96 and 192 units by duplicating the system of case 4 two times and four times are also studied. The results obtained substantiates the suitability of CSO for large-scale constrained CHPED problem.