Improved Lagrange Air-conditioning Load Forecasting Algorithm Based on Uncertainty Measurement

Uncertainty exists in every corner and field of air-conditioning control process, which affects accurately predict the load of the air-conditioning systems. This paper proposed a Lagrange optimization algorithm based on uncertainty measurement. The concept of uncertainty measurement was based on maximum entropy theory, and the idea of uncertainty measurement is introduced into the load objective optimization function. Experimental results show that the accuracy of the improved Langrange optimization algorithm is improved by 41.2% compared with the traditional Langrange optimization algorithm, and the root means the square error is obviously reduced. This improved Langrange optimization algorithm makes the predicted cooling capacity more accurate than traditional one.