A data mining-driven incentive-based demand response scheme for a virtual power plant
Author
Abstract
Suggested Citation
DOI: 10.1016/j.apenergy.2019.01.142
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Wang, Yong & Li, Lin, 2016. "Critical peak electricity pricing for sustainable manufacturing: Modeling and case studies," Applied Energy, Elsevier, vol. 175(C), pages 40-53.
- Yu, Mengmeng & Hong, Seung Ho, 2017. "Incentive-based demand response considering hierarchical electricity market: A Stackelberg game approach," Applied Energy, Elsevier, vol. 203(C), pages 267-279.
- Lu, Renzhi & Hong, Seung Ho & Zhang, Xiongfeng, 2018. "A Dynamic pricing demand response algorithm for smart grid: Reinforcement learning approach," Applied Energy, Elsevier, vol. 220(C), pages 220-230.
- Dilip Mookherjee & Ivan Png, 1989. "Optimal Auditing, Insurance, and Redistribution," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 104(2), pages 399-415.
- Roos, Aleksandra & Bolkesjø, Torjus Folsland, 2018. "Value of demand flexibility on spot and reserve electricity markets in future power system with increased shares of variable renewable energy," Energy, Elsevier, vol. 144(C), pages 207-217.
- Yu, Mengmeng & Hong, Seung Ho, 2016. "Supply–demand balancing for power management in smart grid: A Stackelberg game approach," Applied Energy, Elsevier, vol. 164(C), pages 702-710.
- Joung, Manho & Kim, Jinho, 2013. "Assessing demand response and smart metering impacts on long-term electricity market prices and system reliability," Applied Energy, Elsevier, vol. 101(C), pages 441-448.
- Faruqui, Ahmad & Hledik, Ryan & Newell, Sam & Pfeifenberger, Hannes, 2007. "The Power of 5 Percent," The Electricity Journal, Elsevier, vol. 20(8), pages 68-77, October.
- Molina-Solana, Miguel & Ros, María & Ruiz, M. Dolores & Gómez-Romero, Juan & Martin-Bautista, M.J., 2017. "Data science for building energy management: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 598-609.
- Wei, Congying & Xu, Jian & Liao, Siyang & Sun, Yuanzhang & Jiang, Yibo & Ke, Deping & Zhang, Zhen & Wang, Jing, 2018. "A bi-level scheduling model for virtual power plants with aggregated thermostatically controlled loads and renewable energy," Applied Energy, Elsevier, vol. 224(C), pages 659-670.
- Cappers, Peter & Goldman, Charles & Kathan, David, 2010. "Demand response in U.S. electricity markets: Empirical evidence," Energy, Elsevier, vol. 35(4), pages 1526-1535.
- Kasaei, Mohammad Javad & Gandomkar, Majid & Nikoukar, Javad, 2017. "Optimal management of renewable energy sources by virtual power plant," Renewable Energy, Elsevier, vol. 114(PB), pages 1180-1188.
- Nosratabadi, Seyyed Mostafa & Hooshmand, Rahmat-Allah & Gholipour, Eskandar, 2017. "A comprehensive review on microgrid and virtual power plant concepts employed for distributed energy resources scheduling in power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 341-363.
- Shabanzadeh, Morteza & Sheikh-El-Eslami, Mohammad-Kazem & Haghifam, Mahmoud-Reza, 2017. "An interactive cooperation model for neighboring virtual power plants," Applied Energy, Elsevier, vol. 200(C), pages 273-289.
- Pandžić, Hrvoje & Kuzle, Igor & Capuder, Tomislav, 2013. "Virtual power plant mid-term dispatch optimization," Applied Energy, Elsevier, vol. 101(C), pages 134-141.
- Moreno, Blanca & Díaz, Guzmán, 2019. "The impact of virtual power plant technology composition on wholesale electricity prices: A comparative study of some European Union electricity markets," Renewable and Sustainable Energy Reviews, Elsevier, vol. 99(C), pages 100-108.
- Saffari, Mohammad & de Gracia, Alvaro & Fernández, Cèsar & Belusko, Martin & Boer, Dieter & Cabeza, Luisa F., 2018. "Optimized demand side management (DSM) of peak electricity demand by coupling low temperature thermal energy storage (TES) and solar PV," Applied Energy, Elsevier, vol. 211(C), pages 604-616.
- Wang, Fei & Xu, Hanchen & Xu, Ti & Li, Kangping & Shafie-khah, Miadreza & Catalão, João. P.S., 2017. "The values of market-based demand response on improving power system reliability under extreme circumstances," Applied Energy, Elsevier, vol. 193(C), pages 220-231.
- Andersen, Frits Møller & Baldini, Mattia & Hansen, Lars Gårn & Jensen, Carsten Lynge, 2017. "Households’ hourly electricity consumption and peak demand in Denmark," Applied Energy, Elsevier, vol. 208(C), pages 607-619.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Zhou, Kaile & Peng, Ning & Yin, Hui & Hu, Rong, 2023. "Urban virtual power plant operation optimization with incentive-based demand response," Energy, Elsevier, vol. 282(C).
- Yu, Songyuan & Fang, Fang & Liu, Yajuan & Liu, Jizhen, 2019. "Uncertainties of virtual power plant: Problems and countermeasures," Applied Energy, Elsevier, vol. 239(C), pages 454-470.
- Naval, Natalia & Yusta, Jose M., 2021. "Virtual power plant models and electricity markets - A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
- Mahmud, Khizir & Khan, Behram & Ravishankar, Jayashri & Ahmadi, Abdollah & Siano, Pierluigi, 2020. "An internet of energy framework with distributed energy resources, prosumers and small-scale virtual power plants: An overview," Renewable and Sustainable Energy Reviews, Elsevier, vol. 127(C).
- Naval, Natalia & Sánchez, Raul & Yusta, Jose M., 2020. "A virtual power plant optimal dispatch model with large and small-scale distributed renewable generation," Renewable Energy, Elsevier, vol. 151(C), pages 57-69.
- Natalia Naval & Jose M. Yusta, 2020. "Water-Energy Management for Demand Charges and Energy Cost Optimization of a Pumping Stations System under a Renewable Virtual Power Plant Model," Energies, MDPI, vol. 13(11), pages 1-21, June.
- Wafa Nafkha-Tayari & Seifeddine Ben Elghali & Ehsan Heydarian-Forushani & Mohamed Benbouzid, 2022. "Virtual Power Plants Optimization Issue: A Comprehensive Review on Methods, Solutions, and Prospects," Energies, MDPI, vol. 15(10), pages 1-20, May.
- Quetzalcoatl Hernandez-Escobedo & Javier Garrido & Fernando Rueda-Martinez & Gerardo Alcalá & Alberto-Jesus Perea-Moreno, 2019. "Wind Power Cogeneration to Reduce Peak Electricity Demand in Mexican States Along the Gulf of Mexico," Energies, MDPI, vol. 12(12), pages 1-22, June.
- Märkle-Huß, Joscha & Feuerriegel, Stefan & Neumann, Dirk, 2018. "Large-scale demand response and its implications for spot prices, load and policies: Insights from the German-Austrian electricity market," Applied Energy, Elsevier, vol. 210(C), pages 1290-1298.
- Mohammad Mohammadi Roozbehani & Ehsan Heydarian-Forushani & Saeed Hasanzadeh & Seifeddine Ben Elghali, 2022. "Virtual Power Plant Operational Strategies: Models, Markets, Optimization, Challenges, and Opportunities," Sustainability, MDPI, vol. 14(19), pages 1-23, September.
- Amit Kumer Podder & Sayemul Islam & Nallapaneni Manoj Kumar & Aneesh A. Chand & Pulivarthi Nageswara Rao & Kushal A. Prasad & T. Logeswaran & Kabir A. Mamun, 2020. "Systematic Categorization of Optimization Strategies for Virtual Power Plants," Energies, MDPI, vol. 13(23), pages 1-46, November.
- Moreno, Blanca & Díaz, Guzmán, 2019. "The impact of virtual power plant technology composition on wholesale electricity prices: A comparative study of some European Union electricity markets," Renewable and Sustainable Energy Reviews, Elsevier, vol. 99(C), pages 100-108.
- Wen, Lulu & Zhou, Kaile & Li, Jun & Wang, Shanyong, 2020. "Modified deep learning and reinforcement learning for an incentive-based demand response model," Energy, Elsevier, vol. 205(C).
- Rui Gao & Hongxia Guo & Ruihong Zhang & Tian Mao & Qianyao Xu & Baorong Zhou & Ping Yang, 2019. "A Two-Stage Dispatch Mechanism for Virtual Power Plant Utilizing the CVaR Theory in the Electricity Spot Market," Energies, MDPI, vol. 12(17), pages 1-18, September.
- Andrew J. Satchwell & Peter A. Cappers & Jeff Deason & Sydney P. Forrester & Natalie Mims Frick & Brian F. Gerke & Mary Ann Piette, 2020. "A Conceptual Framework to Describe Energy Efficiency and Demand Response Interactions," Energies, MDPI, vol. 13(17), pages 1-14, August.
- Kim, H.J. & Kim, M.K., 2023. "A novel deep learning-based forecasting model optimized by heuristic algorithm for energy management of microgrid," Applied Energy, Elsevier, vol. 332(C).
- Saffari, Mohammad & de Gracia, Alvaro & Fernández, Cèsar & Belusko, Martin & Boer, Dieter & Cabeza, Luisa F., 2018. "Optimized demand side management (DSM) of peak electricity demand by coupling low temperature thermal energy storage (TES) and solar PV," Applied Energy, Elsevier, vol. 211(C), pages 604-616.
- Bhuiyan, Erphan A. & Hossain, Md. Zahid & Muyeen, S.M. & Fahim, Shahriar Rahman & Sarker, Subrata K. & Das, Sajal K., 2021. "Towards next generation virtual power plant: Technology review and frameworks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
- Lu, Renzhi & Hong, Seung Ho, 2019. "Incentive-based demand response for smart grid with reinforcement learning and deep neural network," Applied Energy, Elsevier, vol. 236(C), pages 937-949.
- Dong, Jun & Xue, Guiyuan & Li, Rong, 2016. "Demand response in China: Regulations, pilot projects and recommendations – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 13-27.
More about this item
Keywords
Virtual power plant; Data mining; Incentive-based demand response; Incentive rate strategy;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:239:y:2019:i:c:p:549-559. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.