Optimal Scheduling of Distributed Generation and Flexible Storage in Smart Buildings
Abstract
In the past, the main reason for the large scale integration of PV plants at consumer level was a potential profit guaranteed through feed-in tariffs. With this incentive mechanism and significant battery storage installation costs, there wasn’t any motivation for the consumers to integrate energy storage to balance out the mismatch between local generation and demand. With the significant cost reduction of PV modules and falling costs of battery storage, these technologies become more attractive. By integrating these technologies together with the other distributed generation resources available at the consumer level, we can reduce grid supply costs and use this to finance such projects. In order to achieve such cost reduction, available production and storage resources need to be scheduled in optimal manner. This paper describes an optimization model for the optimal scheduling of distributed generation and battery storage in order to assure minimal supply costs for the grid connected consumer. The model is casted as MIP and verified through year-scale simulations based on the actual electricity consumption data, electricity price and PV plant production data for University building.
Damir Jakus
Full Professor | Department of Power Grids and Substations
Researcher and a full professor at the Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture in Split. His research interests include power system optimization and planning, RES integration, electricity market modeling.
Josip Vasilj
Associate Professor | Department of Power Grids and Substations
Researcher and Associate Professor at the Faculty of Electrical Engineering, Mechanical Engineering, and Naval Architecture in Split, where he teaches courses related to engineering economics, power system analysis, power grids and machine learning. His research focus is the application of advanced numerical methods to problems in the analysis and planning of power system operations.
