Crisscross Optimization Algorithm For Solving Combined Heat And Power Economic Dispatch Problem

Combined heat and power (Cogeneration) as clean and environmentally friendly technology to supply power and heat, in the face of global climate change and energy crisis in the background, all countries have strengthened the research of this advanced technology. Cogeneration can provide electricity and heat products without additional increase coal consumption which has a good economic and environmental benefits. In recent years, with the deterioration of the air, people have paid more attention on environmental issues, increasingly concerned about healthy. Cogeneration units accounted for the proportion of the entire thermal generation units continues to expand, installed capacity continues to improve, and the research on cogeneration has important significance.The non-convex combined heat and power economic dispatch (CHPED) problem has a large number of local minima, and an additional so called coupling term to guarantee the dependence between the power and the heat productions put forward higher requirement of the algorithm. In this paper, crisscross optimization (CSO) algorithm is implemented to solve the large scale CHPED problem. 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 demonstrate that the proposed CSO method achieves much better results than other methods reported in the literature.In the view of environmental protection, the conflicting objectives of cost and emissions should be synthetical consideration for the CHPED problem. In this paper, a novel hybrid small world network (SWN) and crisscross optimization (CSO) algorithm based on Pareto optimal is proposed to solve the combined heat and power environmental economic dispatch (CHPEED) problem. Building the interconnected SWN between the particles, a stochastic bordered approach is adopted to promote the particles exchange excellent information. In each iteration, two crisscross operators of CSO only operate in the neighborhood network of the SWN according to the population number. Then the better information can rapidly spread in the whole population, greatly improving the global search ability of this hybrid algorithm, increasing the diversity of the population. Based on the non dominated sorting mechanism, the method of extracting the integrated optimal solution is established by using the fuzzy theory. Finally, case studies were carried out on two types of CHPEED problem which consider different situation. Compared the simulation results obtained by other hybrid algorithm and CSO, the proposed hybrid algorithm is suitable to solve this problem.