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Title: Solar plus: Optimization of distributed solar PV through battery storage and dispatchable load in residential buildings

Abstract

As utility electricity rates evolve, pairing solar photovoltaic (PV) systems with battery storage has potential to ensure the value proposition of residential solar by mitigating economic uncertainty. In addition to batteries, load control technologies can reshape customer load profiles to optimize PV system use. The combination of PV, energy storage, and load control provides an integrated approach to PV deployment, which we call 'solar plus'. The U.S. National Renewable Energy Laboratory's Renewable Energy Optimization (REopt) model is utilized to evaluate cost-optimal technology selection, sizing, and dispatch in residential buildings under a variety of rate structures and locations. The REopt model is extended to include a controllable or 'smart' domestic hot water heater model and smart air conditioner model. We find that the solar plus approach improves end user economics across a variety of rate structures - especially those that are challenging for PV - including lower grid export rates, non-coincident time-of-use structures, and demand charges.

Authors:
; ; ;
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Solar Energy Technologies Office (EE-4S)
OSTI Identifier:
1417734
Report Number(s):
NREL/JA-6A20-70778
Journal ID: ISSN 0306-2619
DOE Contract Number:
AC36-08GO28308
Resource Type:
Journal Article
Resource Relation:
Journal Name: Applied Energy; Journal Volume: 213; Journal Issue: C
Country of Publication:
United States
Language:
English
Subject:
14 SOLAR ENERGY; 25 ENERGY STORAGE; solar; storage; load control; optimization; residential buildings

Citation Formats

O'Shaughnessy, Eric, Cutler, Dylan, Ardani, Kristen, and Margolis, Robert. Solar plus: Optimization of distributed solar PV through battery storage and dispatchable load in residential buildings. United States: N. p., 2018. Web. doi:10.1016/j.apenergy.2017.12.118.
O'Shaughnessy, Eric, Cutler, Dylan, Ardani, Kristen, & Margolis, Robert. Solar plus: Optimization of distributed solar PV through battery storage and dispatchable load in residential buildings. United States. doi:10.1016/j.apenergy.2017.12.118.
O'Shaughnessy, Eric, Cutler, Dylan, Ardani, Kristen, and Margolis, Robert. 2018. "Solar plus: Optimization of distributed solar PV through battery storage and dispatchable load in residential buildings". United States. doi:10.1016/j.apenergy.2017.12.118.
@article{osti_1417734,
title = {Solar plus: Optimization of distributed solar PV through battery storage and dispatchable load in residential buildings},
author = {O'Shaughnessy, Eric and Cutler, Dylan and Ardani, Kristen and Margolis, Robert},
abstractNote = {As utility electricity rates evolve, pairing solar photovoltaic (PV) systems with battery storage has potential to ensure the value proposition of residential solar by mitigating economic uncertainty. In addition to batteries, load control technologies can reshape customer load profiles to optimize PV system use. The combination of PV, energy storage, and load control provides an integrated approach to PV deployment, which we call 'solar plus'. The U.S. National Renewable Energy Laboratory's Renewable Energy Optimization (REopt) model is utilized to evaluate cost-optimal technology selection, sizing, and dispatch in residential buildings under a variety of rate structures and locations. The REopt model is extended to include a controllable or 'smart' domestic hot water heater model and smart air conditioner model. We find that the solar plus approach improves end user economics across a variety of rate structures - especially those that are challenging for PV - including lower grid export rates, non-coincident time-of-use structures, and demand charges.},
doi = {10.1016/j.apenergy.2017.12.118},
journal = {Applied Energy},
number = C,
volume = 213,
place = {United States},
year = 2018,
month = 3
}
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