A Load Forecasting System Combining PLC Technology and Principal Component Analysis-BP Neural Network

Abstract

The invention discloses a load forecasting system integrating PLC technology and principal component analysis-BP neural network, including a PLC logic controller, a touch screen, an intelligent gateway, a storage module, an operation module, a principal component analysis module and a BP neural network building module, The PLC logic controller is connected to the touch screen and the intelligent gateway respectively, the intelligent gateway is connected to the storage module, the storage module is connected to the operation module and the touch screen, the operation module is connected to the principal component analysis module and the BP neural network building module, the principal component analysis module is connected to the BP neural network The network construction module feeds back the calculated results to the storage module. The invention can reduce the dimension of the original data, thereby greatly reducing the demand time of the terminal load algorithm, which has very important significance for the real-time operation status adjustment of the terminal equipment, and has a small amount of calculation. , high reliability, small time lag and other advantages.

Description

technical field [0001] The invention relates to the technical field of PLC, in particular to a load forecasting system integrating PLC technology and principal component analysis-BP neural network. Background technique [0002] In the field of HVAC, the accurate prediction of end-use cooling load is a very difficult problem. At present, due to the advanced manufacturing process, the efficiency of the equipment can basically reach the maximum value of the design conditions. At this time, the more prominent problem is how to reasonably call the equipment, so as to minimize the overall energy consumption. The end-use cooling load prediction can effectively solve the above problems. Through the relevant algorithm, the time series cooling capacity of the end can be known in advance, and the operation state of the equipment can be preset through a program based on the overall energy consumption minimization strategy. At present, due to the various factors related to the terminal ...

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Problems solved by technology

At present, due to the many factors related to the terminal load in the HVAC system and the large amount of calculation, it is very difficult to directly use a large number of initial data to realize the prediction of the terminal load, and it will also lead to a large time lag in the terminal load prediction results, which is not conducive to equipment. real-time adjustment

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