Capacity sizing method of virtual power plants based on game theory
Abstract In the context of a low‐carbon economy, considering the output uncertainties of the renewable energy sources and the fluctuation of electrical price, the cost–benefit analysis is proposed for multi‐investor virtual power plant (VPP) under different risk preferences, and multi‐investor VPP c...
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| Format: | Article |
| Language: | English |
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Wiley
2024-04-01
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| Series: | Energy Science & Engineering |
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| Online Access: | https://doi.org/10.1002/ese3.1702 |
| _version_ | 1797202878363860992 |
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| author | Xiaoou Liu |
| author_facet | Xiaoou Liu |
| author_sort | Xiaoou Liu |
| collection | DOAJ |
| description | Abstract In the context of a low‐carbon economy, considering the output uncertainties of the renewable energy sources and the fluctuation of electrical price, the cost–benefit analysis is proposed for multi‐investor virtual power plant (VPP) under different risk preferences, and multi‐investor VPP capacity sizing problem is researched. First, the structural organization and flexible regulation characteristics of multi‐investor VPPs are analyzed. Second, integrated model and cost–benefit analysis indexes of VPP are built. Third, an optimal capacity sizing model of multi‐investor VPP is established, aiming at income maximization. Game theory is used to configure the distributed generators in the VPP under various cooperative modes and noncooperative modes of multiple investors. Fourth, according to the installed proportion of each distributed generator and the risk preference coefficient of each investor, the income allocation correction model based on the improved Shapley value method is proposed to stabilize the optimal VPP alliance. Finally, the demonstration project in the animation industry park of Sino‐Singapore Tianjin Eco‐City is employed as representative scenarios, which is used to validate the effectiveness of the proposed model. The results prove that the method proposed in this paper can guide knowledge for the investors with different risk preferences when planning the optimal capacity of multiple distributed generators in the VPP. |
| first_indexed | 2024-04-24T08:10:26Z |
| format | Article |
| id | doaj.art-41b1f65960dd4371a1b4bd434e5b2fe9 |
| institution | Directory Open Access Journal |
| issn | 2050-0505 |
| language | English |
| last_indexed | 2024-04-24T08:10:26Z |
| publishDate | 2024-04-01 |
| publisher | Wiley |
| record_format | Article |
| series | Energy Science & Engineering |
| spelling | doaj.art-41b1f65960dd4371a1b4bd434e5b2fe92024-04-17T05:33:22ZengWileyEnergy Science & Engineering2050-05052024-04-011241675169810.1002/ese3.1702Capacity sizing method of virtual power plants based on game theoryXiaoou Liu0China Power Engineering Consulting Group Co., Ltd. Beijing Xicheng District ChinaAbstract In the context of a low‐carbon economy, considering the output uncertainties of the renewable energy sources and the fluctuation of electrical price, the cost–benefit analysis is proposed for multi‐investor virtual power plant (VPP) under different risk preferences, and multi‐investor VPP capacity sizing problem is researched. First, the structural organization and flexible regulation characteristics of multi‐investor VPPs are analyzed. Second, integrated model and cost–benefit analysis indexes of VPP are built. Third, an optimal capacity sizing model of multi‐investor VPP is established, aiming at income maximization. Game theory is used to configure the distributed generators in the VPP under various cooperative modes and noncooperative modes of multiple investors. Fourth, according to the installed proportion of each distributed generator and the risk preference coefficient of each investor, the income allocation correction model based on the improved Shapley value method is proposed to stabilize the optimal VPP alliance. Finally, the demonstration project in the animation industry park of Sino‐Singapore Tianjin Eco‐City is employed as representative scenarios, which is used to validate the effectiveness of the proposed model. The results prove that the method proposed in this paper can guide knowledge for the investors with different risk preferences when planning the optimal capacity of multiple distributed generators in the VPP.https://doi.org/10.1002/ese3.1702capacity sizing optimizationconditional value at riskgame theoryregulation capacityvirtual power plant |
| spellingShingle | Xiaoou Liu Capacity sizing method of virtual power plants based on game theory Energy Science & Engineering capacity sizing optimization conditional value at risk game theory regulation capacity virtual power plant |
| title | Capacity sizing method of virtual power plants based on game theory |
| title_full | Capacity sizing method of virtual power plants based on game theory |
| title_fullStr | Capacity sizing method of virtual power plants based on game theory |
| title_full_unstemmed | Capacity sizing method of virtual power plants based on game theory |
| title_short | Capacity sizing method of virtual power plants based on game theory |
| title_sort | capacity sizing method of virtual power plants based on game theory |
| topic | capacity sizing optimization conditional value at risk game theory regulation capacity virtual power plant |
| url | https://doi.org/10.1002/ese3.1702 |
| work_keys_str_mv | AT xiaoouliu capacitysizingmethodofvirtualpowerplantsbasedongametheory |