Central Heating Load Forecasting Based On Fuzzy Neural Network

Heating load forecasting is great significant for the movement management of the heating system,environment and energy saving,it is one of the keys in development,operation and management of heating system, it is also a very important prerequisite for carry on Optimal adjustment for district heating system, so it has a direct contribution for the central heating system efficiency,energy saving and environmental protection.This paper makes a analysis of the status of central heating system, thorough analysis and studies the various factors that affect the heating load, proposed to the processing approach for influencing factors using quantitative of fuzzy data. On this basis, this paper used a new type of fuzzy neural network forecasting system. In the system, the sophisticated feedback BP network is used as the design core, and the quantitative parameters of fuzzy data of influencing factors are used as input values, and apply the neural networks to adjust and calculate the weights, then get the forecast network model through training and learning.Determined the operating parameters of prediction models and apply MATLAB7.0 to predict simulation, the predict results show that the results of the forecast would be to achieve the desired degree of accuracy with high precision and reliability, greatly improving heating quality and save energy in the same or similar conditions.