Optimal Distributed Generator Scheduling in a Campus Microgrid - Case Study at a Building Microgrid

Abstract

Distributed energy resources, especially renewable energy in a building microgrid, are examined to improve the microgrid's performance. Proper management of the building microgrid through scheduling the energy resources is essential to maximize the benefit of implementing such a microgrid. This paper discusses innovative algorithms to manage energy flow from the different resources to improve the performance in terms of losses, operating costs, and emissions. A Particle Swarm Optimization method is applied to scheduling of the energy resources. Different case studies have been conducted to present the $\mathbf{b}$ enefits of building microgrids' scheduling and to validate the proposed methodology. The results are discussed and compared to the experimental results, obtained from a building microgrid in a university campus. A sensitivity analysis is performed to see how the load and price uncertainty impact building microgrid operations. This research shows that integrating more renewables into the building microgrid and optimizing the scheduling help improve the performance during a 24-hour operation.