A Two-layer Approach for Estimating Behind-the-Meter PV Generation Using Smart Meter Data

TL;DR

This paper introduces a two-layer method to estimate behind-the-meter PV generation from smart meter data, enabling utilities to better understand distributed solar contributions without needing detailed PV or weather data.

Contribution

The novel approach disaggregates PV generation and native demand from net demand data without relying on PV parameters or meteorological information.

Findings

Successfully verified with real data

Effective at separating PV and native demand

Does not require PV system parameters or weather data

Abstract

As the cost of the residential solar system decreases, rooftop photovoltaic (PV) has been widely integrated into distribution systems. Most rooftop PV systems are installed behind-the-meter (BTM), i.e., only the net demand is metered, while the native demand and PV generation are not separately recorded. Under this condition, the PV generation and native demand are invisible to utilities, which brings challenges for optimal distribution system operation and expansion. In this paper, we have come up with a novel two-layer approach to disaggregate the unknown PV generation and native demand from the known hourly net demand data recorded by smart meters: 1) At the aggregate level, the proposed approach separates the total PV generation and native demand time series from the total net demand time series for customers with PVs. 2) At the customer level, the separated aggregate-level PV generation is allocated to individual PVs. These two layers leverage the spatial correlations of native demand and PV generation, respectively. One primary advantage of our proposed approach is that it is more independent and practical compared to previous works because it does not require PV array parameters, meteorological data and previously recorded solar power exemplars. We have verified our proposed approach using real native demand and PV generation data.