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Co-optimizing Distributed Energy Resources in Linear Complexity under Net Energy Metering. (arXiv:2208.09781v3 [eess.SY] UPDATED)

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The co-optimization of behind-the-meter distributed energy resources is
considered for prosumers under the net energy metering tariff. The distributed
energy resources considered include renewable generations, flexible demands,
and battery energy storage systems. An energy management system schedules the
consumptions and battery storage based on locally available stochastic
renewables by maximizing the expected operation surplus under the net energy
metering tariff. A stochastic dynamic programming formulation is introduced for
which structural properties of the dynamic optimization are derived. A
closed-form optimal myopic co-optimization algorithm is proposed, which
achieves optimality when the storage capacity constraints are nonbinding. The
proposed co-optimization algorithm has linear computation complexity and can be
implemented in a decentralized fashion. The performance of the myopic
co-optimization algorithm and economic benefits of the optimal co-optimization
policy to prosumers and grid operations are evaluated in numerical simulations.

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