Probabilistic Short-Term Load Forecasting Incorporating Behind-the-Meter (BTM) Photovoltaic (PV) Generation and Battery Energy Storage Systems (BESSs)

Ji-Won Cha,Sung-Kwan Joo

doi:10.3390/en14217067

Abstract

Increased behind-the-meter (BTM) solar generation causes additional errors in short-term load forecasting. To ensure power grid reliability, it is necessary to consider the influence of the behind-the-meter distributed resources. This study proposes a method to estimate the size of behind-the-meter assets by region to enhance load forecasting accuracy. This paper proposes a semi-supervised approach to BTM capacity estimation, including PV and battery energy storage systems (BESSs), to improve net load forecast using a probabilistic approach. A co-optimization is proposed to simultaneously optimize the hidden BTM capacity estimation and the expected improvement to the net load forecast. Finally, this paper presents a net load forecasting method that incorporates the results of BTM capacity estimation. To describe the efficiency of the proposed method, a study was conducted using actual utility data. The numerical results show that the proposed method improves the load forecasting accuracy by revealing the gross load pattern and reducing the influence of the BTM patterns.

Highlights

Renewable generation has rapidly increased based on governmental support to reduce carbon emissions and improve energy sustainability
The incentive schemes were designed to favor small-scale distributed energy resources (DERs), especially solar plus batteries, and most are developed as smallscale photovoltaic (PV) power systems that are more profitable than other generation types
This study proposes a method for considering the uncertainties inherent in the BTM capacity estimation results for short-term load forecasting

Summary

Introduction

Renewable generation has rapidly increased based on governmental support to reduce carbon emissions and improve energy sustainability. Many countries have provided financial incentives and deregulated the installation of renewable energy systems to achieve penetration goals. The incentive schemes were designed to favor small-scale distributed energy resources (DERs), especially solar plus batteries, and most are developed as smallscale photovoltaic (PV) power systems that are more profitable than other generation types. Most small-scale PV companies have signed power purchase agreements (PPAs) with utilities to avoid financial risk and there are privately owned small PVs such as rooftop solar systems. Unlike utility-scale PV systems, facility deregulation allows small-scale PV systems to use inexpensive metering systems that cannot monitor power in real-time or distinguish between solar and battery output. It has been more difficult to accurately forecast the net load because the capacity of BTM DERs has increased while it cannot be properly monitored [3].

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Results

Conclusion