Informed Decision Making of Battery Storage for Solar-PV Homes Using Smart Meter Data

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Informed Decision Making of Battery Storage for Solar-PV Homes Using Smart Meter Data. / Li, Hong Xian; Horan, Peter; Luther, Mark B.; Ahmed, Tarek.

In: Energy and Buildings, Vol. 198, 01.09.2019, p. 491-502.

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Li, Hong Xian ; Horan, Peter ; Luther, Mark B. ; Ahmed, Tarek. / Informed Decision Making of Battery Storage for Solar-PV Homes Using Smart Meter Data. In: Energy and Buildings. 2019 ; Vol. 198. pp. 491-502.

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@article{f830d0a6f50f4d2bb55dc7f381c60851,
title = "Informed Decision Making of Battery Storage for Solar-PV Homes Using Smart Meter Data",
abstract = "As the cost of solar photovoltaic (PV) systems decreases and incentives such as feed-in tariffs (FiTs) are offered, solar-PV homes are becoming popular. Furthermore, solar-PV homes integrated with hybrid or electric vehicles (EVs) are emerging as a paradigm for future homes. Given the fact that there exists a considerable price difference between grid electricity supply and FiTs, decision making of energy storage using batteries becomes an imperative topic. This research proposes an innovative and generic framework for the decision making of energy storage using batteries based on Smart Meter data, which incorporates the actual energy generation and consumption patterns of solar-PV homes. The proposed energy storage decision is based on a developed economic model, with the consideration of the electricity price from the grid, the FiTs, and the storage cost using batteries (i.e. the average price per kWh of battery capital cost and maintenance cost). Moreover, an intelligent algorithm is developed to calculate the electricity quantities, i.e. electricity supplied from the grid, fed into the grid and stored in a battery of a given capacity, based on the monitored data obtained from a Smart Meter over a year.​ The results reveal that at the present utility prices of $0.3/kWh and a feed-in-tariff of $0.10/kWh in the studied region, energy storage with a battery cost of $0.2 /kWh or more is excessive and not economically feasible. However, with the increasing cost of electricity in recent years and constant changes in battery price, the outcomes could quickly reverse. This research contributes an innovative framework for battery storage decision-making of solar-PV homes, based on economic analysis and Smart Meter data.",
keywords = "Solar-PV homes, Smart meter, Home battery, Solar photovoltaic (PV), Electric vehicle (EV)",
author = "Li, {Hong Xian} and Peter Horan and Luther, {Mark B.} and Tarek Ahmed",
year = "2019",
month = "9",
day = "1",
doi = "10.1016/j.enbuild.2019.06.036",
language = "English",
volume = "198",
pages = "491--502",
journal = "Energy and Buildings",
issn = "0378-7788",
publisher = "Elsevier",

}

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TY - JOUR

T1 - Informed Decision Making of Battery Storage for Solar-PV Homes Using Smart Meter Data

AU - Li, Hong Xian

AU - Horan, Peter

AU - Luther, Mark B.

AU - Ahmed, Tarek

PY - 2019/9/1

Y1 - 2019/9/1

N2 - As the cost of solar photovoltaic (PV) systems decreases and incentives such as feed-in tariffs (FiTs) are offered, solar-PV homes are becoming popular. Furthermore, solar-PV homes integrated with hybrid or electric vehicles (EVs) are emerging as a paradigm for future homes. Given the fact that there exists a considerable price difference between grid electricity supply and FiTs, decision making of energy storage using batteries becomes an imperative topic. This research proposes an innovative and generic framework for the decision making of energy storage using batteries based on Smart Meter data, which incorporates the actual energy generation and consumption patterns of solar-PV homes. The proposed energy storage decision is based on a developed economic model, with the consideration of the electricity price from the grid, the FiTs, and the storage cost using batteries (i.e. the average price per kWh of battery capital cost and maintenance cost). Moreover, an intelligent algorithm is developed to calculate the electricity quantities, i.e. electricity supplied from the grid, fed into the grid and stored in a battery of a given capacity, based on the monitored data obtained from a Smart Meter over a year.​ The results reveal that at the present utility prices of $0.3/kWh and a feed-in-tariff of $0.10/kWh in the studied region, energy storage with a battery cost of $0.2 /kWh or more is excessive and not economically feasible. However, with the increasing cost of electricity in recent years and constant changes in battery price, the outcomes could quickly reverse. This research contributes an innovative framework for battery storage decision-making of solar-PV homes, based on economic analysis and Smart Meter data.

AB - As the cost of solar photovoltaic (PV) systems decreases and incentives such as feed-in tariffs (FiTs) are offered, solar-PV homes are becoming popular. Furthermore, solar-PV homes integrated with hybrid or electric vehicles (EVs) are emerging as a paradigm for future homes. Given the fact that there exists a considerable price difference between grid electricity supply and FiTs, decision making of energy storage using batteries becomes an imperative topic. This research proposes an innovative and generic framework for the decision making of energy storage using batteries based on Smart Meter data, which incorporates the actual energy generation and consumption patterns of solar-PV homes. The proposed energy storage decision is based on a developed economic model, with the consideration of the electricity price from the grid, the FiTs, and the storage cost using batteries (i.e. the average price per kWh of battery capital cost and maintenance cost). Moreover, an intelligent algorithm is developed to calculate the electricity quantities, i.e. electricity supplied from the grid, fed into the grid and stored in a battery of a given capacity, based on the monitored data obtained from a Smart Meter over a year.​ The results reveal that at the present utility prices of $0.3/kWh and a feed-in-tariff of $0.10/kWh in the studied region, energy storage with a battery cost of $0.2 /kWh or more is excessive and not economically feasible. However, with the increasing cost of electricity in recent years and constant changes in battery price, the outcomes could quickly reverse. This research contributes an innovative framework for battery storage decision-making of solar-PV homes, based on economic analysis and Smart Meter data.

KW - Solar-PV homes

KW - Smart meter

KW - Home battery

KW - Solar photovoltaic (PV)

KW - Electric vehicle (EV)

U2 - 10.1016/j.enbuild.2019.06.036

DO - 10.1016/j.enbuild.2019.06.036

M3 - Article

VL - 198

SP - 491

EP - 502

JO - Energy and Buildings

JF - Energy and Buildings

SN - 0378-7788

ER -