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- W2887122928 abstract "The rapid penetration of uncertain and unpredictable renewable energy resources into the power grid has made generation planning and real-time power balancing a challenge, thus rendering demand side advanced control a necessity. In this work, we introduce a distributed optimization framework for load flexibility control in the grid. The proposed scheme is based on Newton iteration to provide fast convergence, and is scalable to large numbers of loads at the aggregation level. The developed optimization framework is based on interior point methods and concepts of model predictive control. It uses load-aggregator communications to solve a large-scale optimization problem in a computationally distributed manner without geometric structural assumptions." @default.
- W2887122928 created "2018-08-22" @default.
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- W2887122928 date "2018-06-01" @default.
- W2887122928 modified "2023-09-25" @default.
- W2887122928 title "Scalable Optimal Flexibility Control of Distributed Loads in the Power Grid" @default.
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- W2887122928 doi "https://doi.org/10.23919/acc.2018.8431276" @default.
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