Grid-scale energy storage promises to reduce the cost of decarbonising electricity, but is not yet economically viable. Either costs must fall, or revenue must be extracted from more of the services that storage provides the electricity system. To help understand the economic prospects for storage, we review the sources of revenue available and the barriers faced in accessing them. We then demonstrate a simple algorithm that maximises the profit from storage providing arbitrage with reserve under both perfect and no foresight, which avoids complex linear programming techniques. This is made open source and freely available to help promote further research. We demonstrate that battery systems in the UK could triple their profits by participating in the reserve market rather than just providing arbitrage. With no foresight of future prices, 75-95% of the optimal profits are gained. In addition, we model a battery combined with a 322 MW wind farm to evaluate the benefits of shifting time of delivery. The revenues currently available are not sufficient to justify the current investment costs for battery technologies, and so further revenue streams and cost reductions are required. (C) 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
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Australian Red Cross Blood Serv, Res & Dev, Sydney, NSW, AustraliaAustralian Red Cross Blood Serv, Res & Dev, Sydney, NSW, Australia
Wood, B.
Johnson, L.
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Australian Red Cross Blood Serv, Res & Dev, Sydney, NSW, AustraliaAustralian Red Cross Blood Serv, Res & Dev, Sydney, NSW, Australia
Johnson, L.
Hyland, R. A.
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Australian Red Cross Blood Serv, Res & Dev, Sydney, NSW, AustraliaAustralian Red Cross Blood Serv, Res & Dev, Sydney, NSW, Australia
Hyland, R. A.
Marks, D. C.
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Australian Red Cross Blood Serv, Res & Dev, Sydney, NSW, Australia
Univ Sydney, Sydney Med Sch, Sydney, NSW, AustraliaAustralian Red Cross Blood Serv, Res & Dev, Sydney, NSW, Australia
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Univ South Australia, Sch Informat Technol & Math Sci, Mawson Lakes, SA 5095, AustraliaUniv South Australia, Sch Informat Technol & Math Sci, Mawson Lakes, SA 5095, Australia