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The value of electricity storage in domestic homes: a smart grid perspective

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The value of electricity storage in domestic homes: a smart grid perspective. / Crespo Del Granado, Pedro; Pang, Zhan; Wallace, Stein W.
In: Energy Systems, Vol. 5, No. 2, 06.2014, p. 211-232.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

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Crespo Del Granado P, Pang Z, Wallace SW. The value of electricity storage in domestic homes: a smart grid perspective. Energy Systems. 2014 Jun;5(2):211-232. Epub 2014 Mar 1. doi: 10.1007/s12667-013-0108-y

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Crespo Del Granado, Pedro ; Pang, Zhan ; Wallace, Stein W. / The value of electricity storage in domestic homes : a smart grid perspective. In: Energy Systems. 2014 ; Vol. 5, No. 2. pp. 211-232.

Bibtex

@article{a25056e3db1a4fe6809befeaf032abfa,
title = "The value of electricity storage in domestic homes: a smart grid perspective",
abstract = "About 7% of the energy consumption in the UK presently comes from wind, but this is expected to grow to well over 20 %. This causes serious concerns about the ability of the energy system to balance supply and demand, as it is already very inflexible. Though each household is very small, in total they contribute substantially to the energy demand, and in particular to the peak demand. In this paper, we develop a bottom-up approach, focusing on the value of energy storage and renewable microgeneration in domestic homes. Specifically, we consider a connection to the grid, a boiler, a solar collector, a small wind turbine, a water tank, and a battery. We use the wholesale spot prices as proxies for the provision costs of gas and electricity.We focus on the predictable inter-temporal variations of energy demand, wind speed, and spot prices, and thus assume that these parameters, though deterministic, are time varying. The objective of the model is to minimize the total energy consumption cost, as seen from the grid, throughout a finite horizon. We conduct a numerical case study using a sample of real-life demand and weather data for some typical houses in the UK and recent spot price data. Our results show that a battery might have a significant contribution to energy cost savings, and shed new light on the design of distributed energy systems for a smart grid, especially when coupled with a wind turbine. The benefits do not depend on behavioural changes in the households.",
keywords = "Smart grid , Wind energy, Energy storage, Demand-side management",
author = "{Crespo Del Granado}, Pedro and Zhan Pang and Wallace, {Stein W.}",
year = "2014",
month = jun,
doi = "10.1007/s12667-013-0108-y",
language = "English",
volume = "5",
pages = "211--232",
journal = "Energy Systems",
issn = "1868-3967",
publisher = "Springer Verlag",
number = "2",

}

RIS

TY - JOUR

T1 - The value of electricity storage in domestic homes

T2 - a smart grid perspective

AU - Crespo Del Granado, Pedro

AU - Pang, Zhan

AU - Wallace, Stein W.

PY - 2014/6

Y1 - 2014/6

N2 - About 7% of the energy consumption in the UK presently comes from wind, but this is expected to grow to well over 20 %. This causes serious concerns about the ability of the energy system to balance supply and demand, as it is already very inflexible. Though each household is very small, in total they contribute substantially to the energy demand, and in particular to the peak demand. In this paper, we develop a bottom-up approach, focusing on the value of energy storage and renewable microgeneration in domestic homes. Specifically, we consider a connection to the grid, a boiler, a solar collector, a small wind turbine, a water tank, and a battery. We use the wholesale spot prices as proxies for the provision costs of gas and electricity.We focus on the predictable inter-temporal variations of energy demand, wind speed, and spot prices, and thus assume that these parameters, though deterministic, are time varying. The objective of the model is to minimize the total energy consumption cost, as seen from the grid, throughout a finite horizon. We conduct a numerical case study using a sample of real-life demand and weather data for some typical houses in the UK and recent spot price data. Our results show that a battery might have a significant contribution to energy cost savings, and shed new light on the design of distributed energy systems for a smart grid, especially when coupled with a wind turbine. The benefits do not depend on behavioural changes in the households.

AB - About 7% of the energy consumption in the UK presently comes from wind, but this is expected to grow to well over 20 %. This causes serious concerns about the ability of the energy system to balance supply and demand, as it is already very inflexible. Though each household is very small, in total they contribute substantially to the energy demand, and in particular to the peak demand. In this paper, we develop a bottom-up approach, focusing on the value of energy storage and renewable microgeneration in domestic homes. Specifically, we consider a connection to the grid, a boiler, a solar collector, a small wind turbine, a water tank, and a battery. We use the wholesale spot prices as proxies for the provision costs of gas and electricity.We focus on the predictable inter-temporal variations of energy demand, wind speed, and spot prices, and thus assume that these parameters, though deterministic, are time varying. The objective of the model is to minimize the total energy consumption cost, as seen from the grid, throughout a finite horizon. We conduct a numerical case study using a sample of real-life demand and weather data for some typical houses in the UK and recent spot price data. Our results show that a battery might have a significant contribution to energy cost savings, and shed new light on the design of distributed energy systems for a smart grid, especially when coupled with a wind turbine. The benefits do not depend on behavioural changes in the households.

KW - Smart grid

KW - Wind energy

KW - Energy storage

KW - Demand-side management

U2 - 10.1007/s12667-013-0108-y

DO - 10.1007/s12667-013-0108-y

M3 - Journal article

VL - 5

SP - 211

EP - 232

JO - Energy Systems

JF - Energy Systems

SN - 1868-3967

IS - 2

ER -