Optimal Energy Management and Control of an Industrial Microgrid With Plug-in Electric Vehicles

Abstract

An industrial microgrid (IMG) consists in a microgrid involving manufacturer plants that are usually equipped with distributed generation facilities, industrial electric vehicles, energy storage systems, and so on. In this paper, the problem of IMG-efficient operation in the presence of plug-in electric vehicles is addressed. To this purpose, the schedule of the different device operations of IMGs has to be optimally computed, minimizing the operation cost while guaranteeing the electrical network stability and the production constraints. Such a problem is formulated in a receding horizon framework involving dynamic optimal power flow equations. Uncertainty affecting plug-in electric vehicles is handled by means of a chance constraint approach. The obtained nonconvex problem is then approximately solved by exploiting suitable convex relaxation techniques. The numerical simulations have been performed showing computational feasibility and robustness of the proposed approach against increased penetration of the electric vehicles.

Keywords

• Industrial microgrids
• receding horizon control
• dynamic optimal power flow
• plug-in electric vehicles
• chance constraints