Air conditioner cold load dynamic prediction method based on combination of PSO-BP and Markov chain

Abstract

The invention discloses an air conditioner cold load dynamic prediction method based on the combination of a PSO-BP and a Markov chain. The air conditioner cold load dynamic prediction method comprises the following steps of 1, classifying the air conditioner energy consumption data; 2, carrying out the cold load correlation analysis on ten input variables and output variables at the moment T, such as the outdoor temperature of an air conditioner cooling load at the moment T, the outdoor temperature at the T-1 moment, solar radiation quantity at T moment, the solar radiation quantity at T-1 moment, solar radiation quantity at T-2 moment, relative humidity at T moment, outdoor wind speed ag T moment, cold load at T-1 moment, cold load at T-2 moment and cold load at T-4 moment, etc.; 3, carrying out load prediction by using a PSO-BP neural network; 4, dividing an error interval by utilizing a prediction result of the PSO-BP neural network, and constructing a Markov probability transfer matrix; and 5, carrying out Markov chain error correction to obtain a final prediction value. According to the method, the energy consumption conditions in the week and at the end of the week are distinguished, the variables related to the cold load are subjected to correlation analysis, the variables with the high correlation are selected as the input variables of the model, the error correction is performed on the combined model, the redundancy and the complexity of the feature model are reduced, and the operation efficiency of the algorithm is improved.

Description

technical field [0001] The invention belongs to the field of air-conditioning load forecasting, in particular to an air-conditioning cooling load dynamic forecasting method based on the combination of PSO-BP and Markov chain. Background technique [0002] At present, the energy consumption of air-conditioning accounts for an increasing proportion of the building energy consumption of shopping malls, and its huge power consumption intensifies the pressure on the power grid. Some researchers use ice-storage air-conditioning to solve this problem. The operation of ice-storage air-conditioning needs to reasonably match the cooling capacity provided by the chiller and ice tank during the peak and valley of the electricity price. First, the cooling load in the building at each moment of the next day is predicted, and then the cooling capacity is calculated according to the forecast results. division. Therefore, the dynamic prediction of cooling load is the core content of ice sto...

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Problems solved by technology

[0003] Traditional air-conditioning cooling load forecasting mainly uses support vector machines, statistical regression, and neural networks. Due to the low matching degree between input data and output data, and process errors in the combined model, the forecast results cannot meet the ideal requirements.

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