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摘要
A multi-network combined cooling heating and power (CCHP) system is composed of different energy resources and customer demand, which are connected by electricity network and heating/cooling pipe network. In this paper, the joint probability distribution of available power generation by multiple wind turbines is established based on Copula function and marginal prob-ability distribution of wind speed. The optimal scheduling model for multi-network CCHP system is proposed to reduce greenhouse gas emissions and maximize renewable energy utilization, meanwhile considering the impacts of emission trading scheme on fossil-fired units and security operation constraints of electricity network and heating/cooling pipe network. After that, sampling average approximation, function smoothing and global descent algorithm are employed in order to address the calculation of non-smooth and non-convex scheduling optimization problem. The global descent algorithm continuously updates the local optimal solutions to find global optimal solutions. Finally, one modified 15-bus system is used to analyze the impacts of joint probability distribution, sampling number and emission trading scheme on the scheduling results, which verify the effectiveness of the proposed model and solving algorithm.
