IDEAS home Printed from https://ideas.repec.org/r/eee/appene/v279y2020ics0306261920312010.html
   My bibliography  Save this item

Robust stochastic optimal dispatching method of multi-energy virtual power plant considering multiple uncertainties

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Hongwei Li & Xingmin Li & Siyu Chen & Shuaibing Li & Yongqiang Kang & Xiping Ma, 2024. "Low-Carbon Optimal Scheduling of Integrated Energy System Considering Multiple Uncertainties and Electricity–Heat Integrated Demand Response," Energies, MDPI, vol. 17(1), pages 1-20, January.
  2. Kim, Seokwoo & Choi, Dong Gu, 2024. "A sample robust optimal bidding model for a virtual power plant," European Journal of Operational Research, Elsevier, vol. 316(3), pages 1101-1113.
  3. Chen, Liudong & Liu, Nian & Li, Chenchen & Wu, Lei & Chen, Yubing, 2021. "Multi-party stochastic energy scheduling for industrial integrated energy systems considering thermal delay and thermoelectric coupling," Applied Energy, Elsevier, vol. 304(C).
  4. Wei Wei & Li Ye & Yi Fang & Yingchun Wang & Xi Chen & Zhenhua Li, 2023. "Optimal Allocation of Energy Storage Capacity in Microgrids Considering the Uncertainty of Renewable Energy Generation," Sustainability, MDPI, vol. 15(12), pages 1-17, June.
  5. Ju, Liwei & Yin, Zhe & Zhou, Qingqing & Li, Qiaochu & Wang, Peng & Tian, Wenxu & Li, Peng & Tan, Zhongfu, 2022. "Nearly-zero carbon optimal operation model and benefit allocation strategy for a novel virtual power plant using carbon capture, power-to-gas, and waste incineration power in rural areas," Applied Energy, Elsevier, vol. 310(C).
  6. Xinghua Wang & Xixian Liu & Fucheng Zhong & Zilv Li & Kaiguo Xuan & Zhuoli Zhao, 2023. "A Scenario Generation Method for Typical Operations of Power Systems with PV Integration Considering Weather Factors," Sustainability, MDPI, vol. 15(20), pages 1-20, October.
  7. Alabi, Tobi Michael & Aghimien, Emmanuel I. & Agbajor, Favour D. & Yang, Zaiyue & Lu, Lin & Adeoye, Adebusola R. & Gopaluni, Bhushan, 2022. "A review on the integrated optimization techniques and machine learning approaches for modeling, prediction, and decision making on integrated energy systems," Renewable Energy, Elsevier, vol. 194(C), pages 822-849.
  8. Yang, Shenbo & Fang, Jiangpeng & Zhang, Zheyu & Lv, ShuoShuo & Lin, Hongyu & Ju, Liwei, 2024. "Two-stage coordinated optimal dispatching model and benefit allocation strategy for rural new energy microgrid," Energy, Elsevier, vol. 292(C).
  9. An, Su & Wang, Honglei & Leng, Xiaoxia, 2022. "Optimal operation of multi-micro energy grids under distribution network in Southwest China," Applied Energy, Elsevier, vol. 309(C).
  10. Mei Cai & Suqiong Hu & Ya Wang & Jingmei Xiao, 2022. "A Dynamic Social Network Matching Model for Virtual Power Plants and Distributed Energy Resources with Probabilistic Linguistic Information," Sustainability, MDPI, vol. 14(22), pages 1-33, November.
  11. Wang, Yanjia & Xu, Chao & Xie, Da & Gu, Chenghong & Zhao, Pengfei & Gong, Jinxia & Pan, Mingjie & Wang, Xitian, 2023. "A novel scheduling strategy for virtual power plant based on power market dynamic triggers," Applied Energy, Elsevier, vol. 350(C).
  12. Michał Jasiński & Tomasz Sikorski & Dominika Kaczorowska & Jacek Rezmer & Vishnu Suresh & Zbigniew Leonowicz & Paweł Kostyła & Jarosław Szymańda & Przemysław Janik & Jacek Bieńkowski & Przemysław Prus, 2021. "A Case Study on Data Mining Application in a Virtual Power Plant: Cluster Analysis of Power Quality Measurements," Energies, MDPI, vol. 14(4), pages 1-14, February.
  13. Alabi, Tobi Michael & Lu, Lin & Yang, Zaiyue, 2022. "Data-driven optimal scheduling of multi-energy system virtual power plant (MEVPP) incorporating carbon capture system (CCS), electric vehicle flexibility, and clean energy marketer (CEM) strategy," Applied Energy, Elsevier, vol. 314(C).
  14. Navid Shirzadi & Hadise Rasoulian & Fuzhan Nasiri & Ursula Eicker, 2022. "Resilience Enhancement of an Urban Microgrid during Off-Grid Mode Operation Using Critical Load Indicators," Energies, MDPI, vol. 15(20), pages 1-15, October.
  15. Mostafa Darvishi & Mehrdad Tahmasebi & Ehsan Shokouhmand & Jagadeesh Pasupuleti & Pitshou Bokoro & Jwan Satei Raafat, 2023. "Optimal Operation of Sustainable Virtual Power Plant Considering the Amount of Emission in the Presence of Renewable Energy Sources and Demand Response," Sustainability, MDPI, vol. 15(14), pages 1-25, July.
  16. Liu, Zhiqiang & Cui, Yanping & Wang, Jiaqiang & Yue, Chang & Agbodjan, Yawovi Souley & Yang, Yu, 2022. "Multi-objective optimization of multi-energy complementary integrated energy systems considering load prediction and renewable energy production uncertainties," Energy, Elsevier, vol. 254(PC).
  17. Tan, Caixia & Wang, Jing & Geng, Shiping & Pu, Lei & Tan, Zhongfu, 2021. "Three-level market optimization model of virtual power plant with carbon capture equipment considering copula–CVaR theory," Energy, Elsevier, vol. 237(C).
  18. Li, Yuchun & Wang, Jinkuan & Zhang, Yan & Han, Yinghua, 2022. "Day-ahead scheduling strategy for integrated heating and power system with high wind power penetration and integrated demand response: A hybrid stochastic/interval approach," Energy, Elsevier, vol. 253(C).
  19. Lv, Chaoxian & Liang, Rui & Jin, Wei & Chai, Yuanyuan & Yang, Tiankai, 2022. "Multi-stage resilience scheduling of electricity-gas integrated energy system with multi-level decentralized reserve," Applied Energy, Elsevier, vol. 317(C).
  20. Ju, Liwei & Yin, Zhe & Lu, Xiaolong & Yang, Shenbo & Li, Peng & Rao, Rao & Tan, Zhongfu, 2022. "A Tri-dimensional Equilibrium-based stochastic optimal dispatching model for a novel virtual power plant incorporating carbon Capture, Power-to-Gas and electric vehicle aggregator," Applied Energy, Elsevier, vol. 324(C).
  21. Michał Jasiński & Tomasz Sikorski & Dominika Kaczorowska & Jacek Rezmer & Vishnu Suresh & Zbigniew Leonowicz & Paweł Kostyła & Jarosław Szymańda & Przemysław Janik & Jacek Bieńkowski & Przemysław Prus, 2021. "A Case Study on a Hierarchical Clustering Application in a Virtual Power Plant: Detection of Specific Working Conditions from Power Quality Data," Energies, MDPI, vol. 14(4), pages 1-13, February.
  22. Ye, Lin & Peng, Yishu & Li, Yilin & Li, Zhuo, 2024. "A novel informer-time-series generative adversarial networks for day-ahead scenario generation of wind power," Applied Energy, Elsevier, vol. 364(C).
  23. Sun, Qie & Fu, Yu & Lin, Haiyang & Wennersten, Ronald, 2022. "A novel integrated stochastic programming-information gap decision theory (IGDT) approach for optimization of integrated energy systems (IESs) with multiple uncertainties," Applied Energy, Elsevier, vol. 314(C).
  24. Li, Yang & Wang, Bin & Yang, Zhen & Li, Jiazheng & Chen, Chen, 2022. "Hierarchical stochastic scheduling of multi-community integrated energy systems in uncertain environments via Stackelberg game," Applied Energy, Elsevier, vol. 308(C).
  25. Shiping Geng & Gengqi Wu & Caixia Tan & Dongxiao Niu & Xiaopeng Guo, 2021. "Multi-Objective Optimization of a Microgrid Considering the Uncertainty of Supply and Demand," Sustainability, MDPI, vol. 13(3), pages 1-21, January.
  26. Li, Yang & Han, Meng & Shahidehpour, Mohammad & Li, Jiazheng & Long, Chao, 2023. "Data-driven distributionally robust scheduling of community integrated energy systems with uncertain renewable generations considering integrated demand response," Applied Energy, Elsevier, vol. 335(C).
  27. Esfahani, Moein & Alizadeh, Ali & Amjady, Nima & Kamwa, Innocent, 2024. "A distributed VPP-integrated co-optimization framework for energy scheduling, frequency regulation, and voltage support using data-driven distributionally robust optimization with Wasserstein metric," Applied Energy, Elsevier, vol. 361(C).
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.