Building Energy Management Technology Considering Usual Power Consumption Pattern and Prediction Uncertainty

Abstract

This paper proposes a building energy management model in the Korean electric tariff system with the consideration of prediction errors in load consumption and renewable energy generation. The increase in controllable power resources has enabled demand-side managements in the practical environment, and various approaches to optimize power consumption in the building are studied and implemented. However, demand side management has a problem in that it is difficult for power consumers to control power consumption due to the lack of consideration of actual use environment. To resolve this issue, we propose penalty factor to minimize the gap between power scheduling results and usual power usage patterns. In addition, the prediction error of power consumption in real environment causes difficulty in power operation. To resolve the issue, this paper proposes a method to control power demand resources and energy storage system based on a set of reserve portion. The proposed model includes analysis on prediction errors of power data, and set of proper reserve proportion in demand response and energy storage system operation. The simulation results show that the electricity rate of consumers in the building is reduced by more than 21% per month.