Abstract
Today, global energy shortages and environmental pollution are getting worse. The global energy conservation and emission reduction situation is extremely severe, the combined cooling, heating and power (CCHP) system not only improves primary energy utilization, but also has great economic benefits. Therefore, it is considered to be an important trend in the development of future energy technologies. However, CCHP has significant features such as complex structure, varied working conditions, diverse modes, and mixed disturbances. There are many serious challenges to its optimal control. In response to this problem, this paper presents a collaborative optimization model for maximizing primary energy utilization and minimizing energy costs for CCHP systems. The discrete immune parallel evolutionary algorithm (DIPEA) was introduced to solve the optimal equipment selection and optimal operating parameters by establishing MATLAB simulation platform. And the optimization results of discrete immune parallel evolutionary algorithm (DIPEA) are compared with the optimization results of ant colony optimization (ACO) and genetic algorithm (GA). As simulation experiments show the DIPEA optimized CCHP system has higher primary energy utilization rate and greater economic benefits.
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