Multi-agent Planning Under Uncertainty for Capacity Management
Frits de Nijs (TU Delft - Algorithmics)
Mathijs M. Weerdt (TU Delft - Algorithmics)
Matthijs Spaan (TU Delft - Algorithmics)
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Abstract
Demand response refers to the concept that power consumption should aim to match supply, instead of supply following demand. It is a key technology to enable the successful transition to an electricity system that incorporates more and more intermittent and uncontrollable renewable energy sources. For instance, loads such as heat pumps or charging of electric vehicles are potentially flexible and could be shifted in time to take advantage of renewable generation. Load shifting is most effective, however, when it is performed in a coordinated fashion to avoid merely shifting the peak instead of flattening it. In this chapter, we discuss multi-agent planning algorithms for capacity management to address this issue. Our methods focus in particular on addressing the challenges that result from the need to plan ahead into the future given uncertainty in supply and demand. We demonstrate that by decoupling the interactions of agents with the constraint, the resulting algorithms are able to compute effective demand response policies for hundreds of agents.