Probabilistic analysis of masked loads with aggregated photovoltaic production

TL;DR

This paper introduces a probabilistic framework for real-time estimation of behind-the-meter photovoltaic generation, utilizing a stochastic model to disaggregate PV output from net load and irradiance data.

Contribution

It presents a novel stochastic modeling approach combining a spatiotemporal process and differential equations for PV generation disaggregation.

Findings

Effective real-time PV generation estimation demonstrated

Model accurately captures PV variability and demand dynamics

Framework improves grid management and planning

Abstract

In this paper we present a probabilistic analysis framework to estimate behind-the-meter photovoltaic generation in real time. We develop a forward model consisting of a spatiotemporal stochastic process that represents the photovoltaic generation and a stochastic differential equation with jumps that represents the demand. We employ this model to disaggregate the behind-the-meter photovoltaic generation using net load and irradiance measurements.