CCHP system capacity optimization configuration method

Abstract

The invention provides a capacity optimization configuration method for a combined cooling heating and power system. The method comprises the following steps: establishing a capacity optimization model of the combined cooling heating and power supply system by taking equipment capacity and an electric refrigeration ratio in the combined cooling heating and power supply system as decision variables and taking minimum economic cost, minimum energy consumption and minimum environmental influence as three objective functions; defining energy balance constraint, equipment capacity constraint and output power constraint conditions; adopting a reverse learning mechanism, a control level, a population guidance mechanism and a seagull attack operator to improve a multi-target multi-element universe algorithm (MOMVO); solving the multi-objective optimization function by using an improved multi-objective multivariate universe algorithm; and outputting an optimal compromise solution, namely an optimal configuration scheme, of the capacity optimization configuration problem of the combined cooling heating and power system by using a TOPSIS decision method. A final configuration result shows that the optimal configuration scheme obtained by the improved multi-target multivariate universe algorithm under various operation strategies enables the operation of the combined cooling heating and power system to be more economical, energy-saving and environment-friendly.

Description

technical field [0001] The technical solution of the present invention belongs to the technical field of electric power systems, specifically a method for optimizing the capacity configuration of a combined cooling, heating and power generation system based on an improved multi-objective multiverse algorithm. Background technique [0002] Combined cooling, heating and power (CCHP) system is a cogeneration system that couples multiple energy sources such as cold, heat, and electricity. It can realize energy cascade utilization and improve energy utilization efficiency. The combined cooling, heating and power (CCHP) system mainly uses gas internal combustion engines driven by primary energy and distributed power sources driven by renewable energy as power equipment to provide electric energy, and then recovers and utilizes the excess heat generated by waste heat utilization devices to achieve full energy. purpose of use. The combined cooling, heating and power (CCHP) system h...

AI Technical Summary

Problems solved by technology

[0004] Combined Cooling, Heating and Power (CCHP) system has many forms of energy coupling and the characteristics of random fluctuations in the output power of distributed power generation equipment, so when the posteriori method is used to optimize the capacity configuration of the CCHP system, the output Random clustering occurs in the pareto solution, and ultimately it is impossible to obtain a CCHP system equipment capacity configuration scheme with excellent comprehensive performance; most intelligent optimization algorithms have convergence when solving the CCHP system capacity optimization problem Limitations of slow speed and uneven distribution of pareto solutions

Images