Optimum community energy storage system for PV energy time-shift
•The performance and economic benefits of Pb-acid and Li-ion batteries are compared.•The business case during the decarbonisation pathway is assessed.•The aggregation from a community approach reduced the levelised cost by 37% by 2020.•For a forecast price of 16.3p/kWh Li-ion battery cost must be le...
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| Published in: | Applied energy Vol. 137; pp. 576 - 587 |
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| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
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01-01-2015
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| Abstract | •The performance and economic benefits of Pb-acid and Li-ion batteries are compared.•The business case during the decarbonisation pathway is assessed.•The aggregation from a community approach reduced the levelised cost by 37% by 2020.•For a forecast price of 16.3p/kWh Li-ion battery cost must be less than 275£/kWh.•A 10% subsidy will be needed for Li-ion batteries to achieve the 2020 forecast.
A novel method has been designed to obtain the optimum community energy storage (CES) systems for end user applications. The method evaluates the optimum performance (including the round trip efficiency and annual discharge), levelised cost (LCOES), the internal rate of return and the levelised value of suitable energy storage technologies. A complimentary methodology was developed including three reference years (2012, 2020 and zero carbon year) to show the evolution of the business case during the low carbon transition. The method follows a community approach and the optimum CES system was calculated as a function of the size of the community. In this work, this method was put in practice with lead-acid (PbA) and lithium-ion battery (Li-ion) technologies when performing PV energy time-shift using real demand data from a single home to a 100-home community. The community approach reduced the LCOES down to 0.30£/kWh and 0.11£/kWh in 2020 and the zero carbon year respectively. These values meant a cost reduction by 37% and 66% regarding a single home. Results demonstrated that PbA batteries needs from 1.5 to 2.5 times more capacity than Li-ion chemistry to reduce the LCOES, the worst case scenario being for the smallest communities, because the more spiky demand profile required proportionately larger PbA battery capacities. |
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| AbstractList | A novel method has been designed to obtain the optimum community energy storage (CES) systems for end user applications. The method evaluates the optimum performance (including the round trip efficiency and annual discharge), levelised cost (LCOES), the internal rate of return and the levelised value of suitable energy storage technologies. A complimentary methodology was developed including three reference years (2012, 2020 and zero carbon year) to show the evolution of the business case during the low carbon transition. The method follows a community approach and the optimum CES system was calculated as a function of the size of the community. In this work, this method was put in practice with lead-acid (PbA) and lithium-ion battery (Li-ion) technologies when performing PV energy time-shift using real demand data from a single home to a 100-home community. The community approach reduced the LCOES down to 0.30 pound sterling /kW h and 0.11 pound sterling /kW h in 2020 and the zero carbon year respectively. These values meant a cost reduction by 37% and 66% regarding a single home. Results demonstrated that PbA batteries needs from 1.5 to 2.5 times more capacity than Li-ion chemistry to reduce the LCOES, the worst case scenario being for the smallest communities, because the more spiky demand profile required proportionately larger PbA battery capacities. •The performance and economic benefits of Pb-acid and Li-ion batteries are compared.•The business case during the decarbonisation pathway is assessed.•The aggregation from a community approach reduced the levelised cost by 37% by 2020.•For a forecast price of 16.3p/kWh Li-ion battery cost must be less than 275£/kWh.•A 10% subsidy will be needed for Li-ion batteries to achieve the 2020 forecast. A novel method has been designed to obtain the optimum community energy storage (CES) systems for end user applications. The method evaluates the optimum performance (including the round trip efficiency and annual discharge), levelised cost (LCOES), the internal rate of return and the levelised value of suitable energy storage technologies. A complimentary methodology was developed including three reference years (2012, 2020 and zero carbon year) to show the evolution of the business case during the low carbon transition. The method follows a community approach and the optimum CES system was calculated as a function of the size of the community. In this work, this method was put in practice with lead-acid (PbA) and lithium-ion battery (Li-ion) technologies when performing PV energy time-shift using real demand data from a single home to a 100-home community. The community approach reduced the LCOES down to 0.30£/kWh and 0.11£/kWh in 2020 and the zero carbon year respectively. These values meant a cost reduction by 37% and 66% regarding a single home. Results demonstrated that PbA batteries needs from 1.5 to 2.5 times more capacity than Li-ion chemistry to reduce the LCOES, the worst case scenario being for the smallest communities, because the more spiky demand profile required proportionately larger PbA battery capacities. |
| Author | Gillott, Mark Parra, David Norman, Stuart A. Walker, Gavin S. |
| Author_xml | – sequence: 1 givenname: David surname: Parra fullname: Parra, David organization: Infrastructure, Geomatics and Architecture Research Division, Faculty of Engineering, University of Nottingham, University Park, Nottingham NG7 2RD, UK – sequence: 2 givenname: Mark surname: Gillott fullname: Gillott, Mark organization: Infrastructure, Geomatics and Architecture Research Division, Faculty of Engineering, University of Nottingham, University Park, Nottingham NG7 2RD, UK – sequence: 3 givenname: Stuart A. surname: Norman fullname: Norman, Stuart A. organization: E.ON Technology Centre, Ratcliffe on Soar, Nottingham NG11 0EE, UK – sequence: 4 givenname: Gavin S. surname: Walker fullname: Walker, Gavin S. email: Gavin.Walker@nottingham.ac.uk organization: Energy and Sustainability Research Division, Faculty of Engineering, University of Nottingham, University Park, Nottingham NG7 2RD, UK |
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| Title | Optimum community energy storage system for PV energy time-shift |
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