Heat exchange station parallel water pump optimization control method and system under distributed architecture

Abstract

The invention discloses a heat exchange station parallel water pump optimization control method and system under a distributed architecture. Based on the distributed control architecture, electromechanical equipment in a heat exchange station is upgraded by adding intelligent equipment, so that the whole control system of parallel water pumps becomes a distributed control system; an optimization model under a centralized framework is converted into a sub-optimization model under the distributed architecture through a penalty function, and a target function is improved by using an adaptive factor; the optimization model is solved by using an improved meta-start method SCAFOA, the optimization model is converted into an improved distributed fruit fly optimization algorithm D-SCAFOA based on the distributed architecture, and the improved distributed fruit fly optimization algorithm D-SCAFOA is downloaded to each controller so as to complete solving of the optimization model; and finally, on the basis of actual engineering data, combination and distribution optimization are conducted on a set of parallel water pumps of different models, so that the thermal load requirement of a terminal user is met. The problem of local optimum is avoided, and the method and system can be used for energy-saving optimization control of the parallel water pumps of the heat exchange station.

Description

technical field [0001] The invention belongs to the technical field of optimization control of related equipment of heat exchange stations in district heating systems, and in particular relates to an optimization control method and system for parallel water pumps of heat exchange stations under a distributed architecture. Background technique [0002] As the main energy-consuming equipment of the district heating (DH, District heating) system, the parallel water pump is driven by an electric motor. Globally, electric motors account for 46% of electrical energy consumption, with pumps and fans in water distribution systems accounting for as much as 60-70%. By updating the equipment or adding intelligent modules to the equipment in the building management system, 30% of energy can be saved. Therefore, the parallel pumps of the heat exchange stations in the DH system have great potential for energy saving. The operating efficiency of water pumps not only depends on the design,...

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Problems solved by technology

[0003] In order to solve this problem, the previous method is based on the traditional centralized control architecture. In actual engineering, it not only needs to be developed case by case, but also must collect information in a global scope during calculation; this has high performance requirements for the central processing unit. Once If this processor fails, the entire parallel pump unit will not work, while the increase in communication and computing costs seriously hinders the popularization of these methods in practical engineering

Later, related methods optimize and solve this problem based on the traditional distributed control architecture. These methods first require a main controller to act as a centralized agent, and then assign sub-tasks to the secondary controllers for separate calculations, thereby completing the optimization under the distributed control architecture. ; Although better energy-saving effects can be obtained than under the centralized control architecture, if the main controller fails, the entire parallel pump group will also fail to work; therefore, this traditional distributed optimization method cannot make full use of the distributed The advantages of the traditional architecture cannot achieve complete distributed optimization

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