The Cost Efficiency of the Electricity Retailers with the Integration of the Cloud Energy Storage
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作者:
Xiong, Chu
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Univ Reading, Henley Business Sch, Reading RG6 6R, EnglandUniv Reading, Henley Business Sch, Reading RG6 6R, England
Xiong, Chu
[1
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Luo, Dan
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Univ Reading, Henley Business Sch, Reading RG6 6R, England
Chongqing Univ, State Key Lab Power Transmiss Equipment & Syst Sec, Chongqing 400044, Peoples R ChinaUniv Reading, Henley Business Sch, Reading RG6 6R, England
Luo, Dan
[1
,2
]
Han, Liang
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Dongbei Univ Finance & Econ, Surrey Int Inst, Dalian 116025, Peoples R ChinaUniv Reading, Henley Business Sch, Reading RG6 6R, England
Han, Liang
[3
]
机构:
[1] Univ Reading, Henley Business Sch, Reading RG6 6R, England
[2] Chongqing Univ, State Key Lab Power Transmiss Equipment & Syst Sec, Chongqing 400044, Peoples R China
[3] Dongbei Univ Finance & Econ, Surrey Int Inst, Dalian 116025, Peoples R China
As a result of market liberalisation, a large number of electricity retailers have emerged in the electricity market. Acting as the intermediaries between the electricity producers and the customers, the electricity retailers aim to balance the supply and demand and shoulder substantial risks generated from both sides. Due to the randomness of the electricity load, it is difficult for electricity retailers to make an accurate electricity purchasing plan in advance to meet customer demand. This deviation leads to a proportion of spot electricity purchases that require a higher purchase cost. As a result, one of the most serious concerns facing electricity retailers is how to improve their balancing abilities and reduce power purchase deviation. In contrast to previous research, which has generally recommended that electricity retailers invest in energy storage systems or develop optimised purchasing strategies, this paper proposes a new strategy for the electricity retailers, which is renting external flexible resources to solve the market uncertainty of the electricity retailers, thereby lowering purchase costs and increasing profits. The proposed business model makes use of the cloud energy storage to solve the supply-demand imbalance issue of electricity retailers. The cost calculation model and decision optimisation model have been established in the process of renting cloud energy storage. Charging and discharging cloud energy storage have been separately rented to deal with different positive and negative load deviations, which can simplify the optimisation model. As an experimental paper, the proposed model has been tested in the PJM power market in the United States and the New South Wales power market in Australia. The findings confirm that renting the cloud energy storage capacities can significantly reduce costs and maximise profits for the electricity retailers when compared to the situation without the cloud energy storage. The biggest saving can reach 24.5% in the PJM market. With the rapid fall of battery prices, the advantage of the proposed strategy will be more obvious.
机构:
Univ Utah, Dept Chem Engn, 50 S Cent Campus Dr, Salt Lake City, UT 84112 USAUniv Utah, Dept Chem Engn, 50 S Cent Campus Dr, Salt Lake City, UT 84112 USA
Powell, Kody M.
Kim, Jong Suk
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Idaho Natl Lab, Idaho Falls, ID USAUniv Utah, Dept Chem Engn, 50 S Cent Campus Dr, Salt Lake City, UT 84112 USA
Kim, Jong Suk
Cole, Wesley J.
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Natl Renewable Energy Lab, Golden, CO USAUniv Utah, Dept Chem Engn, 50 S Cent Campus Dr, Salt Lake City, UT 84112 USA
Cole, Wesley J.
Kapoor, Kriti
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NXP Semicond, San Jose, CA USAUniv Utah, Dept Chem Engn, 50 S Cent Campus Dr, Salt Lake City, UT 84112 USA
Kapoor, Kriti
Mojica, Jose L.
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ExxonMobil, Irving, TX USAUniv Utah, Dept Chem Engn, 50 S Cent Campus Dr, Salt Lake City, UT 84112 USA
Mojica, Jose L.
Hedengren, John D.
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Brigham Young Univ, Dept Chem Engn, Provo, UT 84602 USAUniv Utah, Dept Chem Engn, 50 S Cent Campus Dr, Salt Lake City, UT 84112 USA
Hedengren, John D.
Edgar, Thomas F.
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Univ Texas Austin, Dept Chem Engn, Austin, TX 78712 USAUniv Utah, Dept Chem Engn, 50 S Cent Campus Dr, Salt Lake City, UT 84112 USA
机构:
Univ Oxford, Dept Engn Sci, Energy & Power Grp, 17 Parks Rd, Oxford OX1 3PJ, EnglandUniv Oxford, Dept Engn Sci, Energy & Power Grp, 17 Parks Rd, Oxford OX1 3PJ, England
Lai, Chun Sing
McCulloch, Malcolm D.
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Univ Oxford, Dept Engn Sci, Energy & Power Grp, 17 Parks Rd, Oxford OX1 3PJ, EnglandUniv Oxford, Dept Engn Sci, Energy & Power Grp, 17 Parks Rd, Oxford OX1 3PJ, England