Abstract
In order to solve the randomness and volatility of new energy power generation, promote the local consumption of renewable energy, and maximize the economic efficiency of CCHP system, this paper combines the schedulable resources of energy production, energy storage and energy consumption into a “source storage” system, which can meet the demand of power supply, heating and cooling at the same time. The objective function is to minimize the daily operation cost of the cold heat electric hybrid energy system, and the power balance and equipment capacity of the system are constrained. Using the established mathematical model of the system framework, the particle swarm optimization algorithm is used to improve the CCHP programming model to obtain the adaptation curve and the hourly output of the optimal operation of the equipment with the maximum economic benefit. The operation and maintenance costs of the two modes are analyzed in depth. The results show that the optimization of “source storage and load” system not only improves the reliability of energy supply, but also reduces the cost of operation and maintenance and improves the economic benefits of the system.
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