Park intelligent energy network dynamic scheduling method based on prediction control

Abstract

A park intelligent energy network dynamic scheduling method based on prediction control relates to the energy management technology field, aims to solve a technical problem of the energy network power control, relates to an energy network comprising a combined cooling heating and power system, a conventional electrical refrigeration system and an ice storage system, and comprises the steps of according to the power consumption power and a cooling water inlet temperature of a conventional electrical refrigerator in the energy network, fitting the energy efficiency ratio of the conventional electrical refrigerator in the energy network into a function represented by the power consumption power and the cooling water inlet temperature, according to the power consumption power, the cooling water inlet temperature and the refrigerating capacity of the conventional electrical refrigerator in the energy network, utilizing a regression analysis method to convert the power consumption power into a function represented by the cooling water inlet temperature and the refrigerating capacity to thereby construct an economic model of the energy network, and then adopting a model prediction control method to optimize the dynamic performance of the conventional electrical refrigerator. The method provided by the present invention can realize the optimal power while satisfying the overall load demand.

Description

technical field [0001] The invention relates to energy management technology, in particular to a technology based on predictive control-based dynamic scheduling method for park intelligent energy network. Background technique [0002] Traditional park energy is mainly composed of centralized energy supply energy systems, which use large-capacity equipment for centralized production, and then transport energy through dedicated pipelines. With the emergence of emerging technologies, energy grids composed of free refrigeration, triple power supply, ice storage, and conventional electric refrigeration have become more and more popular. [0003] This multi-energy complementary energy system is an emerging energy grid system. With the promotion of the time-of-use electricity price policy, most parks currently only have some simple controls on this emerging energy grid, that is, ice storage when the electricity price is low. Cold storage is carried out, and cooling is carried out ...

AI Technical Summary

Problems solved by technology

[0003] This multi-energy complementary energy system is an emerging energy grid system. With the promotion of the time-of-use electricity price policy, most parks currently only have some simple controls on this emerging energy grid, that is, ice storage when the electricity price is low. Cold storage is carried out, and cooling is carried out when the electricity price peaks, lacking quantitative analysis and efficient control of the entire energy network

Moreover, it is a dynamic process from the start-up of the refrigeration equipment to the set power. Simply considering the steady-state control method is difficult to ensure that the actual energy supply capacity of the entire system can quickly keep up with the predicted load.

Therefore, the existing energy grid system cannot achieve optimal power while meeting the total load demand

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