A multi-time-scale optimization operation method for a combined cooling heating and power system

Abstract

The invention discloses a multi-time scale optimization operation method for a combined cooling heating and power system, and the method comprises the steps: building an electric energy static optimization model of the combined cooling heating and power system with the comprehensive optimization of the operation cost, the energy utilization rate and the emission of the combined cooling heating andpower system as an optimization target; taking t as an electric energy optimization period to predict renewable energy power generation output and an electric load; solving the electric energy staticoptimization model of the combined cooling heating and power system by adopting a particle swarm algorithm, and determining the output of each device in the combined cooling heating and power system;establishing a heat/cold energy dynamic optimization model based on heat storage by taking the comprehensive optimization of the operation cost, the energy utilization rate and the emission of the combined cooling heating and power system as an optimization target and considering the inertia of heat/cold energy flow; and using k as a heat/cold energy flow optimization period, asopting a dynamic planning method to solve the dynamic optimization model, and determining the output heat power and the heat storage power of the generator set.

Description

technical field [0001] The disclosure belongs to the field of energy technology, and specifically relates to a multi-time-scale dynamic scheduling strategy and operation method for a new energy combined cooling, heating and power supply system. Background technique [0002] As one of the forms of distributed energy supply, the combined cooling, heating and power system has developed rapidly in recent years. A typical CCHP system is composed of a power generation system, a waste heat recovery system and an auxiliary system. Through optimal dispatching of energy, it can realize cascade utilization of energy while meeting the user's various load demands of cooling, heating and electricity, and effectively improve the efficiency of energy utilization. To achieve the goals of energy saving, environmental protection and economic benefits. The combined cooling, heating and power system itself is a complex system of multiple energy sources (cold, heat, and electricity). In recent ...

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Problems solved by technology

However, the disadvantages of static optimization on the same time scale are: due to the large difference in thermoelectric time scales, there are big problems in using the same time scale

If the matching slow reference scale optimization is adopted according to the change speed of thermal energy, it will not be able to make an appropriate and timely response to the fast time scale electric energy; if the matching fast reference scale optimization is adopted according to the change speed of electric energy, the thermal energy The difference between slow time scale dynamics is almost zero, resulting in a serious loss of significant figures and huge errors; if an intermediate time sca

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