A hybrid stochastic-interval Mean–CVaR model for the wind-storage system offering strategy under uncertainties
As an integral component of the green-oriented transition of energy, wind-storage systems have experienced vigorous development in recent years. The integration of wind-storage systems into the day-ahead market (DAM) is challenged by the multiple uncertainties associated with wind power and electric...
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Elsevier
2025-04-01
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| Series: | International Journal of Electrical Power & Energy Systems |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S0142061525000432 |
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| author | Ziang Wang Xiuli Wang Zhicheng Wang Jing Huang Xiancheng Ren Mengfu Tu |
| author_facet | Ziang Wang Xiuli Wang Zhicheng Wang Jing Huang Xiancheng Ren Mengfu Tu |
| author_sort | Ziang Wang |
| collection | DOAJ |
| description | As an integral component of the green-oriented transition of energy, wind-storage systems have experienced vigorous development in recent years. The integration of wind-storage systems into the day-ahead market (DAM) is challenged by the multiple uncertainties associated with wind power and electricity prices. This significantly impacts the design of the offering strategy for wind-storage system operators and creates substantial financial risks for their operations. To address this issue, this paper proposes a hybrid stochastic-interval Mean–CVaR (MCVaR) model for designing flexible and diverse offering strategies that cater to different risk appetites. The model employs scenario generation to depict internal uncertainty and utilizes interval formulation to model external uncertainty. Firstly, a three-layer optimal model for scenario generation is proposed to tackle the internal uncertainty commonly associated with wind power. The scenario generation is aligned with the physical information model. Then, a virtual decision pre-construction and evaluation model is established to minimize the decision error. The corresponding solution process is designed accordingly. Secondly, an stochastic-interval MCVaR model is developed to account for the interval uncertainty of electricity price and the risk appetite of wind-storage system operators. In conjunction with the wind power scenarios, the offering strategy of the wind-storage system is designed based on this model. Finally, the case study verifies the superiority of the hybrid stochastic-interval optimization framework. The impact of interval uncertainty on the offering strategy and income of wind-storage systems is analyzed in detail, aiming to provide a reliable economic benefit analysis. Multiple offering strategies are developed for operators of wind-storage systems based on different risk appetites. |
| format | Article |
| id | doaj-art-7302607be1294ed79b87789e58f120a9 |
| institution | Kabale University |
| issn | 0142-0615 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Elsevier |
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| series | International Journal of Electrical Power & Energy Systems |
| spelling | doaj-art-7302607be1294ed79b87789e58f120a92025-02-08T04:59:21ZengElsevierInternational Journal of Electrical Power & Energy Systems0142-06152025-04-01165110492A hybrid stochastic-interval Mean–CVaR model for the wind-storage system offering strategy under uncertaintiesZiang Wang0Xiuli Wang1Zhicheng Wang2Jing Huang3Xiancheng Ren4Mengfu Tu5School of Electrical Engineering, Xi’an Jiaotong University (Shaanxi Key Laboratory on Smart Grid), Xi’an, 710049, Shaanxi Province, China; Corresponding author.School of Electrical Engineering, Xi’an Jiaotong University (Shaanxi Key Laboratory on Smart Grid), Xi’an, 710049, Shaanxi Province, ChinaSchool of Electrical Engineering, Xi’an Jiaotong University (Shaanxi Key Laboratory on Smart Grid), Xi’an, 710049, Shaanxi Province, ChinaSchool of Electrical Engineering, Xi’an Jiaotong University (Shaanxi Key Laboratory on Smart Grid), Xi’an, 710049, Shaanxi Province, ChinaNari Technology Co., Ltd., No. 19, Chengxin Avenue, Jiangning District, Nanjing, 211106, Jiangsu Province, ChinaNational Key Laboratory of Risk Defense Technology and Equipment for Power Grid Operation, No. 19, Chengxin Avenue, Jiangning District, Nanjing, 211106, Jiangsu Province, ChinaAs an integral component of the green-oriented transition of energy, wind-storage systems have experienced vigorous development in recent years. The integration of wind-storage systems into the day-ahead market (DAM) is challenged by the multiple uncertainties associated with wind power and electricity prices. This significantly impacts the design of the offering strategy for wind-storage system operators and creates substantial financial risks for their operations. To address this issue, this paper proposes a hybrid stochastic-interval Mean–CVaR (MCVaR) model for designing flexible and diverse offering strategies that cater to different risk appetites. The model employs scenario generation to depict internal uncertainty and utilizes interval formulation to model external uncertainty. Firstly, a three-layer optimal model for scenario generation is proposed to tackle the internal uncertainty commonly associated with wind power. The scenario generation is aligned with the physical information model. Then, a virtual decision pre-construction and evaluation model is established to minimize the decision error. The corresponding solution process is designed accordingly. Secondly, an stochastic-interval MCVaR model is developed to account for the interval uncertainty of electricity price and the risk appetite of wind-storage system operators. In conjunction with the wind power scenarios, the offering strategy of the wind-storage system is designed based on this model. Finally, the case study verifies the superiority of the hybrid stochastic-interval optimization framework. The impact of interval uncertainty on the offering strategy and income of wind-storage systems is analyzed in detail, aiming to provide a reliable economic benefit analysis. Multiple offering strategies are developed for operators of wind-storage systems based on different risk appetites.http://www.sciencedirect.com/science/article/pii/S0142061525000432Wind-storage systemOffering strategyScenario generationDecision errorConditional value-at-risk |
| spellingShingle | Ziang Wang Xiuli Wang Zhicheng Wang Jing Huang Xiancheng Ren Mengfu Tu A hybrid stochastic-interval Mean–CVaR model for the wind-storage system offering strategy under uncertainties International Journal of Electrical Power & Energy Systems Wind-storage system Offering strategy Scenario generation Decision error Conditional value-at-risk |
| title | A hybrid stochastic-interval Mean–CVaR model for the wind-storage system offering strategy under uncertainties |
| title_full | A hybrid stochastic-interval Mean–CVaR model for the wind-storage system offering strategy under uncertainties |
| title_fullStr | A hybrid stochastic-interval Mean–CVaR model for the wind-storage system offering strategy under uncertainties |
| title_full_unstemmed | A hybrid stochastic-interval Mean–CVaR model for the wind-storage system offering strategy under uncertainties |
| title_short | A hybrid stochastic-interval Mean–CVaR model for the wind-storage system offering strategy under uncertainties |
| title_sort | hybrid stochastic interval mean cvar model for the wind storage system offering strategy under uncertainties |
| topic | Wind-storage system Offering strategy Scenario generation Decision error Conditional value-at-risk |
| url | http://www.sciencedirect.com/science/article/pii/S0142061525000432 |
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