Knowledge-based Algorithm for Daily Thermal Load Prediction of a Building

摘要

This article describes an innovative algorithm to predict the daily thermal loading of a building. The prediction algorithm is crucial to the operation of a thermal storage plant as it determines how much amount of storage to be generated for the next day use. The new algorithm utilizes updated weather forecast information from the internet and analyzes it by a knowledge-based system to simulate the overall weather condition in terms of air temperature profile, air relative humidity profile, and solar radiation profile. Computer simulation is then carried out to predict the daily thermal loading of a building using the simulated weather condition. Two case studies verify that the algorithm can provide accurate daily thermal load prediction. Building managers are recommended to employ it for improving the overall efficiency of their plants.