Distributionally robust multi-stage stochastic programming for mid- and long-term cross-regional power markets
The widespread integration of renewable energy sources (RESs) has presented significant challenges in deregulated power markets. The inherent uncertainty of RES poses challenges for clearing cross-temporal and cross-regional transactions, manifesting as curses of dimensionality and premature converg...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-09-01
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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/S0142061525004983 |
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| author | Yuhan Huang Tao Ding Xiaosheng Zhang Shuhai Feng Yiding Jin Yangsheng Sun Tong Xing |
| author_facet | Yuhan Huang Tao Ding Xiaosheng Zhang Shuhai Feng Yiding Jin Yangsheng Sun Tong Xing |
| author_sort | Yuhan Huang |
| collection | DOAJ |
| description | The widespread integration of renewable energy sources (RESs) has presented significant challenges in deregulated power markets. The inherent uncertainty of RES poses challenges for clearing cross-temporal and cross-regional transactions, manifesting as curses of dimensionality and premature convergence in conventional approaches. This paper proposes a distributionally robust multi-stage stochastic programming model for cross-regional power market clearing considering available transfer capacity constraints. The uncertainties from RESs are modeled through distributionally robust formulations circumventing exact probability distributions, while multiple stages are introduced to maintain applicability to mid- and long-term trading. To overcome the premature convergence problem in conventional methods, a distributionally robust stochastic dual dynamic programming algorithm is proposed to give an exact upper bound. To resolve the nested “max–min-max” structure preventing direct dual problem derivation, a 1-norm ambiguity set is employed to reformulate the nested structure into a single “max” structure. Numerical results for a practical power system in Northwestern China demonstrate that the proposed method provides an exact upper bound that avoids premature convergence for better accuracy at the cost of longer computation time. |
| format | Article |
| id | doaj-art-65b203c87acf45a996f8a82b230c8c95 |
| institution | DOAJ |
| issn | 0142-0615 |
| language | English |
| publishDate | 2025-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Electrical Power & Energy Systems |
| spelling | doaj-art-65b203c87acf45a996f8a82b230c8c952025-08-20T03:03:46ZengElsevierInternational Journal of Electrical Power & Energy Systems0142-06152025-09-0117011095010.1016/j.ijepes.2025.110950Distributionally robust multi-stage stochastic programming for mid- and long-term cross-regional power marketsYuhan Huang0Tao Ding1Xiaosheng Zhang2Shuhai Feng3Yiding Jin4Yangsheng Sun5Tong Xing6State Key Laboratory of Electrical Insulation and Power Equipment, Xi’an Jiaotong University, Xi’an 710049, ChinaState Key Laboratory of Electrical Insulation and Power Equipment, Xi’an Jiaotong University, Xi’an 710049, China; Corresponding author.State Key Laboratory of Electrical Insulation and Power Equipment, Xi’an Jiaotong University, Xi’an 710049, ChinaChina Electric Power Research Institute, Nanjing 210037, ChinaBeijing Power Exchange Center, Beijing 100031, ChinaState Grid Shanghai Municipal Electric Power Company, Shanghai 200120, ChinaBeijing Power Exchange Center, Beijing 100031, ChinaThe widespread integration of renewable energy sources (RESs) has presented significant challenges in deregulated power markets. The inherent uncertainty of RES poses challenges for clearing cross-temporal and cross-regional transactions, manifesting as curses of dimensionality and premature convergence in conventional approaches. This paper proposes a distributionally robust multi-stage stochastic programming model for cross-regional power market clearing considering available transfer capacity constraints. The uncertainties from RESs are modeled through distributionally robust formulations circumventing exact probability distributions, while multiple stages are introduced to maintain applicability to mid- and long-term trading. To overcome the premature convergence problem in conventional methods, a distributionally robust stochastic dual dynamic programming algorithm is proposed to give an exact upper bound. To resolve the nested “max–min-max” structure preventing direct dual problem derivation, a 1-norm ambiguity set is employed to reformulate the nested structure into a single “max” structure. Numerical results for a practical power system in Northwestern China demonstrate that the proposed method provides an exact upper bound that avoids premature convergence for better accuracy at the cost of longer computation time.http://www.sciencedirect.com/science/article/pii/S0142061525004983Cross-regional power marketsAvailable transfer capacityDistributionally robust multi-stage stochastic programmingStochastic dual dynamic programming |
| spellingShingle | Yuhan Huang Tao Ding Xiaosheng Zhang Shuhai Feng Yiding Jin Yangsheng Sun Tong Xing Distributionally robust multi-stage stochastic programming for mid- and long-term cross-regional power markets International Journal of Electrical Power & Energy Systems Cross-regional power markets Available transfer capacity Distributionally robust multi-stage stochastic programming Stochastic dual dynamic programming |
| title | Distributionally robust multi-stage stochastic programming for mid- and long-term cross-regional power markets |
| title_full | Distributionally robust multi-stage stochastic programming for mid- and long-term cross-regional power markets |
| title_fullStr | Distributionally robust multi-stage stochastic programming for mid- and long-term cross-regional power markets |
| title_full_unstemmed | Distributionally robust multi-stage stochastic programming for mid- and long-term cross-regional power markets |
| title_short | Distributionally robust multi-stage stochastic programming for mid- and long-term cross-regional power markets |
| title_sort | distributionally robust multi stage stochastic programming for mid and long term cross regional power markets |
| topic | Cross-regional power markets Available transfer capacity Distributionally robust multi-stage stochastic programming Stochastic dual dynamic programming |
| url | http://www.sciencedirect.com/science/article/pii/S0142061525004983 |
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