Enhancing Grid Stability and Economic Operation through Heuristic Control: A Simulation Case Study

A positive interaction between buildings and power grids can enhance green power utilization. Notwithstanding these advancements, the unforeseen voltage stability challenges, leading to critical grid states, remains a salient concern. In this research, the power demand optimization of a case building is accomplished through the application of rule-based predictive heuristic control, with a primary focus on achieving economical operation while considering the requests from the smart grid system. As part of the Solar Decathlon Europe 21/22 competition, one of the competition buildings is exploited as case building. Cost optimized operation of the building is driven by historical electricity spot prices from the power grid of Germany. The critical grid state measurements of smart grid system are undertaken by the local utility company. During critical status, the building is expected to respond to the smart grid system by decreasing the power demand. To conduct the analysis, a co-simulation environment is developed between IDA-ICE and MATLAB. The power demand profiles of subcomponents — namely, heat pump, photovoltaic, electrical energy storage, and user-related loads— are simulated by IDA-ICE, while cost and power optimization is run in MATLAB. In conclusion, this research demonstrates an approach to support grid stability challenges through building-grid interaction.