  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 types of
measurements. The proposed approaches integrate the low-resolution smart meter
data collected for every load node with the fast-sampled feeder-level
measurements provided by limited number of 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
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 these grid-edge DERs.
