2021/02/15 by S. Lin, Shanny Lin, Hao Zhu +2
Computer Science · Engineering · Mathematics · #Computer science #Distributed computing #Distributed generation #Electrical engineering #Engineering #Enhanced Data Rates for GSM Evolution #Exploit #Grid #Image and Signal Denoising Methods #Key (lock) #Mathematical optimization #Mathematics #Observability #Photovoltaic system #Real-time computing #Renewable energy #Smart Grid Energy Management #Smart grid #Smart meter #Sparse and Compressive Sensing Techniques #Telecommunications #cs.LG #cs.SY #eess.SP #eess.SY
paper · pdf · doi:10.48550/arxiv.2102.07801
published in arXiv (Cornell University) (Cornell University)
openalex publication_date 2021/02/15 · openalex created_date 2021/03/01 · arxiv created 2021/08/21 · arxiv updated 2021/08/24 · openalex updated_date 2026/08/06
Enhancing the spatio-temporal observability of distributed energy resources (DERs) is crucial for achieving secure and efficient operations in distribution grids. This paper puts forth a joint recovery framework for residential loads by leveraging the complimentary strengths of heterogeneous measurements in real time. The proposed framework integrates low-resolution smart meter data collected at every load node with fast-sampled feeder-level measurements from limited number of distribution phasor measurement units. To address the lack of data, we exploit two key characteristics for the loads and DERs, namely the sparse changes due to infrequent activities of appliances and electric vehicles (EVs) and the locational dependence of solar photovoltaic (PV) generation. Accordingly, meaningful regularization terms are introduced to cast a convex load recovery problem, which will be further simplified to reduce the computational complexity. The load recovery solutions can be utilized to identify the EV charging events at each load node and to infer the total behind-the-meter PV output. Numerical tests using real-world data have demonstrated the effectiveness of the proposed approaches in enhancing the visibility of grid-edge DERs.