Peak-shaving boiler heating station heating demand optimized dispatching method using particle swarm optimization

Abstract

The invention provides a peak-shaving boiler heating station heating demand optimized dispatching method using particle swarm optimization, and belongs to the technical field of heating station heating demand control. By means of the method, in order to enable energy consumption and economy of a heating system to be considered at the same time in optimized dispatching of a heating station, different dispatching modes are used in heating peak periods and non-peak periods, comprehensive optimum is enabled to be achieved, optimized dispatching calculation speed is enabled to be higher, and results are enabled to be more accurate. The method mainly comprises the steps of constructing a peak-shaving boiler heating station optimized dispatching model, and determining weight coefficients lambda 1 and lambda 2; and using a particle swarm optimization algorithm to obtain corresponding boiler heating load Qb and secondary net boiler heating channel flow rate Gb when comprehensive energy consumption Ew is the smallest under the condition that a constraint condition is satisfied, and therefore peak-shaving boiler heating station heating demand optimized dispatching is completed. According to the method, the peak-shaving boiler heating station optimized dispatching model with energy consumption and economy combined is built, therefore the optimal distribution of heating demands of different heat sources is achieved, energy consumption and economy are comprehensively optimal, and the purpose of energy conservation is achieved.

Description

technical field [0001] The invention relates to a heating load optimization scheduling method of a peak-shaving furnace thermal station, and belongs to the technical field of heating load control of a thermal station. Background technique [0002] The optimal scheduling of the heat power station of the peak shaving furnace is to optimize the distribution of the heat supply load of the heat power station, so that the heat power station can achieve the best energy consumption or economy under the same heat load. There are the following three problems in the actual engineering of the optimal dispatching of the thermal station of the peak-shaving furnace. [0003] 1. The optimal scheduling of traditional thermal power stations usually depends on the experience of the dispatchers, which is generally the result of rough estimation. This result cannot accurately reflect the heating load demand of the thermal power station, nor can it realize the optimal configuration of the heating...

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Problems solved by technology

[0003] 1. The optimal scheduling of traditional thermal stations usually depends on the experience of dispatchers, which is generally the result of a rough estimate. This result cannot accurately reflect the heating load demand of the thermal station, nor can it achieve the optimal configuration of the heating load

[0004] 2. The traditional thermal station optimization scheduling generally determines the heating load based on the outdoor temperature, and pays attention to the economy of the heating load, but lacks the consideration of the energy consumption of the heating load

[0005] 3. The optimal scheduling of thermal stations is generally carried out manually, and cannot be automatically calculated based on real-time online data, and the degree of intelligence is low

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