Occupant-centric dynamic heating and cooling loads simplified prediction model for urban community at energy planning stage

Abstract

Simplified and accurate prediction of dynamic heating and cooling loads is the basis for urban energy planning and optimal operation of integrated urban energy systems. Majority existed urban community heating and cooling loads prediction models focus on the effects of building physics, weather conditions, and construction features, barely consider the impact of occupant presence rate, operating schedule, and internal heat gain on heating and cooling loads, which affects the prediction accuracy. Thus, aiming to get the balance of simplification and accuracy, an occupant-centric prediction model of dynamic heating and cooling loads for urban community at energy planning stage with simplified calculation principles, reduced input parameters, improved simulation accuracy, and preserved characteristics of the individual building in the community was proposed. Based on the previously developed building envelope simplification model, internal heat gain modules and operating schedule modules were developed. After verifying the prediction accuracy of the model by comparison with EnergyPlus software, the model was applied to a typical university campus. Case study analysis shows that this model can accurately predict dynamic space heating and cooling loads of urban community with simplified inputs at energy planning stage, which provides theoretical support and convenience for optimizing the urban energy prediction model.