As the share of renewable energy sources increases, electricity prices and thus consumption will become more weather-dependent. Current markets and regulations assume the network to be like a copper plate, obliging network operators to facilitate any market transaction at any cost.

We develop a novel approach to congestion management by efficiently scheduling flexible loads of multiple customers within the capacity constraints of the local energy networks, exploiting stochastic information on generation and consumption. For this purpose we develop new planning approaches, combining plans for different horizons and temporal resolutions, and exploiting hierarchy, all under such incentive constraints.

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