Production planning in a Virtual Power Plant

Distributed electricity generation is increasingly applied in the electricity grid. This generation can be more energy efficient than conventional generation; however, a large scale introduction of distributed generators implies possible instability in the grid. A Virtual Power Plant (VPP) deals with this problem by controlling the distributed generators in such a way, that the complete group acts like a normal power plant. All generators need to be steered individually, which makes the control more complex than the control of a normal power plant. The VPP we describe in this paper consists of a large number of microCHP (Combined Heat and Power) appliances. As the produced heat of such a microCHP is completely consumed locally, the production opportunities of the distributed generators are determined by the local heat demand. This heat demand can be predicted one day ahead, see e.g. [2]. A feasible schedule of a single generator ensures that the heat demand is supplied in time. The objective is to generate at the most profitable times. In [3] a dynamic programming formulation is described which schedules one generator optimally (for local objectives) within reasonable time. We extend this method to the case of a Virtual Power Plant. The costs of the basic state changes in the dynamic programming formulation of the individual generators are altered, according to the objective of the VPP, which is to generate a predefined electricity pattern for a full day. Starting from the point of view of local objectives of individual generators the global objective of the VPP is gradually (iteratively) incorporated. This results in a production planning that can be done in reasonable time, compared to the planning horizon