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A Data-Driven Machine Learning Approach for Consumer Modeling with Load Disaggregation

Autor: Zarabie, A. Khaled, Das, Sanjoy, Wu, Hongyu

While non-parametric models, such as neural networks, are sufficient in the load forecasting, separate estimates of fixed and shiftable loads are beneficial to a wide range of applications such as distribution system operational planning, load schedu

Externí odkaz: http://arxiv.org/abs/2011.03519

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An L0-Norm Constrained Non-Negative Matrix Factorization Algorithm for the Simultaneous Disaggregation of Fixed and Shiftable Loads

Autor: Zarabie, Ahmad Khaled, Das, Sanjoy

Energy disaggregation refers to the decomposition of energy use time series data into its constituent loads. This paper decomposes daily use data of a household unit into fixed loads and one or more classes of shiftable loads. The latter is character

Externí odkaz: http://arxiv.org/abs/1908.00142

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Pareto-Optimal Allocation of Transactive Energy at Market Equilibrium in Distribution Systems: A Constrained Vector Optimization Approach

Autor: Zarabie, Ahmad Khaled, Das, Sanjoy

In a grid constrained transactive distribution system market, distribution locational marginal pricing DLMP is influenced by the distance from the substation to an energy user, thereby causing households that are further away from the substation to b

Externí odkaz: http://arxiv.org/abs/1905.05892

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