Parametric optimization-based peer-to-peer energy trading among commercial buildings considering multiple energy conversion
被引:26
作者:
Zhang, Heng
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Shanghai Jiao Tong Univ, Key Lab Control Power Transmission & Convers, Minist Educ, Shanghai 200240, Peoples R ChinaShanghai Jiao Tong Univ, Key Lab Control Power Transmission & Convers, Minist Educ, Shanghai 200240, Peoples R China
Zhang, Heng
[1
]
Zhang, Shenxi
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Shanghai Jiao Tong Univ, Key Lab Control Power Transmission & Convers, Minist Educ, Shanghai 200240, Peoples R ChinaShanghai Jiao Tong Univ, Key Lab Control Power Transmission & Convers, Minist Educ, Shanghai 200240, Peoples R China
Zhang, Shenxi
[1
]
Hu, Xiao
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Northeast Elect Power Univ, Jilin, Jilin, Peoples R ChinaShanghai Jiao Tong Univ, Key Lab Control Power Transmission & Convers, Minist Educ, Shanghai 200240, Peoples R China
Hu, Xiao
[2
]
Cheng, Haozhong
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Shanghai Jiao Tong Univ, Key Lab Control Power Transmission & Convers, Minist Educ, Shanghai 200240, Peoples R ChinaShanghai Jiao Tong Univ, Key Lab Control Power Transmission & Convers, Minist Educ, Shanghai 200240, Peoples R China
Cheng, Haozhong
[1
]
Gu, Qingfa
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State Grid Henan Elect Power Res Inst, Zhengzhou, Peoples R ChinaShanghai Jiao Tong Univ, Key Lab Control Power Transmission & Convers, Minist Educ, Shanghai 200240, Peoples R China
Gu, Qingfa
[3
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Du, Mengke
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State Grid Chaoyang Elect Supply Co, Chaoyang, Peoples R ChinaShanghai Jiao Tong Univ, Key Lab Control Power Transmission & Convers, Minist Educ, Shanghai 200240, Peoples R China
Du, Mengke
[4
]
机构:
[1] Shanghai Jiao Tong Univ, Key Lab Control Power Transmission & Convers, Minist Educ, Shanghai 200240, Peoples R China
[2] Northeast Elect Power Univ, Jilin, Jilin, Peoples R China
[3] State Grid Henan Elect Power Res Inst, Zhengzhou, Peoples R China
[4] State Grid Chaoyang Elect Supply Co, Chaoyang, Peoples R China
A peer-to-peer energy trading framework of buildings considering multi-energy coupling is presented in this study to improve energy efficiency and achieve cost savings. Microsources, such as photovoltaic and microcombined heat and power, are used to meet electricity and heating demands, while the problem of unbalanced power is solved via the main grid and other peers through peer-to-peer energy trading. All peers aim to maximize their revenue and create trading strategies (i.e., trading period and volume) based on the time-of-use tariff released by the main grid. The trading model established by each peer is a parametric optimization-based problem because each peer must consider the trading willingness of other peers when formulating strategies. A new mixed-integer linear programming problem to maximize total profit can be finally formulated to obtain an equilibrium solution that satisfies all peers. Results show that the proposed peer-to-peer transaction approach can reduce energy bills of buildings. Daily purchased electricity from the main grid decreases by 8.9% through peerto-peer energy trading between different buildings. In addition, compared with the building peer-to-peer transaction that only considers electricity energy management, the amount of purchased electricity from the main network can be reduced by 4.2% a day when multi-energy coupling is considered in peer-to-peer.