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• W2291016864 abstract "In this paper, we address a key issue of designing architectures and algorithms which generate optimal demand response in a decentralized manner for a smart-grid consisting of several stochastic renewables and dynamic loads. By optimal demand response, we refer to the demand response which maximizes the utility of the agents connected to the smart-grid. By decentralized we refer to the desirable case where neither the independent system operator (ISO) needs to know the dynamics/utilities of the agents, nor do the agents need to have a knowledge of the dynamics/utilities of other agents connected to the grid. The communication between the ISO and agents is restricted to the ISO announcing a pricing policy and the agents responding with their energy generation/consumption bids in response to the pricing policy. We provide a complete solution for both the deterministic and stochastic cases. It features a price iteration scheme that results in optimality of social welfare. We also provide an optimal solution for the case where there is a common randomness affecting and observed by all agents. This solution can be computationally complex, and we pose approximations. For the more general partially observed randomness case, we exhibit a relaxation that significantly reduces complexity. We also provide an approximation strategy that leads to a model predictive control (MPC) approach. Simulation results comparing the resulting optimal demand response with the existing architectures employed by the ISO illustrate the benefit in social welfare utility realized by our scheme. To the best of the authors' knowledge, this is the first work of its kind to explicitly mark out the optimal response of dynamic demand." @default.
• W2291016864 created "2016-06-24" @default.
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• W2291016864 date "2015-12-01" @default.
• W2291016864 modified "2023-10-17" @default.
• W2291016864 title "A theory for the economic operation of a smart grid with stochastic renewables, demand response and storage" @default.
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• W2291016864 doi "https://doi.org/10.1109/cdc.2015.7402806" @default.
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