Method for constructing multi-energy load situation awareness model of regional integrated energy system
An integrated energy system and situational awareness technology, which is applied in the construction of a multi-energy load situational awareness model of a regional integrated energy system, can solve the problems of insufficient load situation prediction accuracy and excessive processing data, and achieves increased energy utilization and economical operation. performance, increase forecast accuracy, and reduce unnecessary waste of energy
Pending Publication Date: 2022-04-08
NINGBO POWER SUPPLY COMPANY STATE GRID ZHEJIANG ELECTRIC POWER +1
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[0003] The purpose of the present invention is to provide a method for constructing a multi-energy load situation awareness model of a regional integrated energy system, which can solve the problems of too much processing data required for regional multi-energy load situation awareness and insufficient load situation prediction accuracy
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[0102] The comprehensive energy system of a university campus has hot summer and warm winter, sufficient sunlight throughout the year, and a large demand for electricity and cooling loads. Using the 2018.8-2019.8 24h daily cold, heat, electricity, and gas load data (including basic unit load and IES total load) recorded by the school’s Campus Metabolism project network platform, the time resolution is 1h. The electrical load needs to be eliminated and normalized by abnormal data, and the training set and test set are divided according to the ratio of 80% and 20%.
[0103] The training set data collected adopts the CNN-LSTM method without pixel reconstruction, the LSTM method, the CNN-LSTM method of pixel reconstruction, the MCNN-LSTM method (model of the present invention) of pixel reconstruction to carry out load situation prediction, electric load prediction The result is as Figure 5 As shown, the heat load prediction results are as follows Image 6 As shown, the cooling ...
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The invention discloses a method for constructing a multi-energy load situation perception model of a regional integrated energy system, and the method can effectively improve the prediction precision of a load situation prediction stage through employing an MCNN-LSTM load situation prediction method considering load feature fusion on the basis of pixel reconstruction, thereby enabling the optimization scheduling accuracy of the integrated energy system to be improved. The energy consumption requirement of a user side can be met; and meanwhile, the multi-energy cooperation and multi-energy coupling efficiency of the integrated energy system is higher, and the energy utilization rate and the operation economy of the regional integrated energy system are improved. According to the multi-energy load situation awareness technology of the regional integrated energy system, the data processing difficulty in the load situation understanding stage can be effectively reduced by adopting the time domain feature expansion random forest algorithm, so that the time required by the load situation awareness process can be reduced, load prediction can be carried out more timely, and the load awareness efficiency is improved. The flexibility of optimal scheduling of the integrated energy system is improved, and unnecessary waste of energy is reduced.
Description
technical field [0001] The invention belongs to the technical field of comprehensive energy situational awareness, and in particular relates to a method for constructing a multi-energy load situational awareness model of a regional comprehensive energy system. Background technique [0002] The integrated energy system has the characteristics of multi-energy coordination and multi-source coupling. The coordinated utilization of various energy sources through scheduling optimization can not only meet the energy demand of the user side but also avoid energy waste, and improve energy utilization and economy. The dispatch optimization of integrated energy system requires timely and accurate multi-energy load situation awareness technology. The current multi-energy load situation awareness technology will cause the lack of one-dimensional correlation features when understanding the load situation, which makes it necessary to process huge load data in the load situation prediction...
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IPC IPC(8): G06K9/62G06N3/08G06Q10/04G06Q50/06
Inventor 张志刚钟良亮王亮刘沛立杨志义郭高鹏严浩军康家乐陈玄俊杨劲松操瑞发胡旭波金迪马国平蔡振华应芳义杨跃平胡锡王元凯孙晨航
Owner NINGBO POWER SUPPLY COMPANY STATE GRID ZHEJIANG ELECTRIC POWER
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