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Worst-Case Optimal Scheduling and Real-Time Control of a Microgrid Offering Active Power Reserve

This work is focused on optimization problems within the predictive control framework for determining and engaging the flexibility of a microgrid in grid-microgrid energy exchange. The microgrid has a controllable battery storage and other components represented with a residual power flow. All major economic constituents of the grid- connected microgrid operation are considered: day- ahead, intra-day, peak power and battery degradation costs, as well as rewards and penalties for providing flexibility. The problems are posed as linear worst-case minimization programs in which all flexibility activation scenarios are taken into account. An analysis is conducted for various combinations of flexibility reservation and activation prices that can be bid to a grid entity. The technical and economic feasibility of the flexibility provision is confirmed by the use of an online model predictive controller that optimally meets the requirements of grid flexibility according to the declared reserve in the environment of online occurring disturbances and events.

smart grids, microgrids, linear programming, model predictive control, demand response

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