مروری بر برنامهریزی بهینه پاسخگویی تقاضای منازل مسکونی از طریق تجمیع‌کننده
الموضوعات :غلامرضا کامیاب 1 , محمد حسین عرفانی مجد 2 , سعید بلوچیان 3
1 - دانشکده مهندسی برق، واحد گناباد، دانشگاه آزاد اسلامی، گناباد، ایران
2 - دانشکده مهندسی برق، واحد گناباد، دانشگاه آزاد اسلامی، گناباد، ایران
3 - گروه مهندسی برق، واحد گناباد، دانشگاه آزاد اسلامی، گناباد، ایران
الکلمات المفتاحية: پاسخگویی تقاضا, تجمیع‌کننده, شبکه هوشمند, مدیریت مصرف انرژی,
ملخص المقالة :
در این مقاله به مرور جامع راهکارهای بهینه‌سازی پاسخگویی بار در منازل مسکونی از طریق تجمیع‌کننده‌ها پرداخته شده است. با افزایش فزاینده فشار بر شبکه‌های برق به دلیل رشد قابل توجه تقاضا، برنامهریزی و اجرای موثر استراتژی‌های پاسخگویی به تقاضا اهمیت زیادی یافته است. استفاده از روش‌های بهینه‌سازی غیرخطی و هوشمند، مدل‌سازی اقتصادی، تحلیل‌های آماری و فرآیندهای داده‌کاوی، و همچنین توجه به جنبه‌های محیطی و بهبود بهره‌وری انرژی از مهم‌ترین رویکردهای مورد بحث در منابع مرور شده است. مزایای قابل توجه استفاده از تجمیع‌کننده‌ها شامل کاهش هزینه‌های انرژی، بهبود پایداری شبکه، افزایش انعطاف‌پذیری و کاهش قابل توجه انتشار آلاینده‌ها می‌باشد. با این حال، چالش‌هایی نظیر پیچیدگی‌های فنی، نیاز به هماهنگی موثر بین ذی‌نفعان مختلف، و محدودیت‌های زیرساختی در اجرای این راهکارها وجود دارد. به‌منظور غلبه بر این چالش‌ها، استفاده از روش‌های پیشرفته تحلیل داده، توسعه الگوهای نوین و نوآور تجمیع و به‌کارگیری استراتژی‌های کارآمد مدیریت انرژی توصیه شده است. نتایج مرور نشان می‌دهد که با به‌کارگیری مناسب و مؤثر تجمیع‌کننده‌ها، می‌توان به تحقق اهداف کلیدی بهینه‌سازی پاسخگویی بار در منازل مسکونی دست یافت که این امر نه تنها بهبود کارایی شبکه‌های برق را به‌دنبال دارد، بلکه به کاهش هزینه‌های انرژی مصرف‌کنندگان نیز کمک شایانی می‌کند. با توجه به تنوع و گستردگی روش‌های موجود، تحقیق و توسعه بیشتر در این حوزه به‌ویژه در زمینه‌ی یکپارچه‌سازی فناوری‌های نوین و همچنین افزایش مشارکت فعال مصرف‌کنندگان در برنامه‌های موثر پاسخگویی بار پیشنهاد می‌شود.
المصادر:
[1] Fei Wang, Biao Xiang, Kangping Li, Xinxin Ge, Hai Lu, Jingang Lai and Payman Dehghanian, "Smart Households’ Aggregated Capacity Forecasting for Load Aggregators Under Incentive-Based Demand Response Programs," IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, vol. 56, no. 2, 2020.
[2] Zhaofang Song, Jing Shi, Shujian Li, Zexu Chen, Wangwang Yang and Zitong Zhang, "Day ahead bidding of a load aggregator considering residential consumers demand response uncertainty modeling," Applied Sciences, vol. 10, no. 20, p. 7310, 2020.
[3] Masood Parvania, Mahmud Fotuhi-Firuzabad and Mohammad Shahidehpour, "Optimal Demand Response Aggregation in Wholesale Electricity Markets," IEEE TRANSACTIONS ON SMART GRID, vol. 4, no. 4, 2013.
[4] Homa Rashidizadeh-Kermani, Mostafa Vahedipour-Dahraie, Miadreza Shafie-khah and João P.S. Catalão, "Stochastic programming model for scheduling demand response aggregators considering uncertain market prices and demands," International Journal of Electrical Power & Energy Systems, vol. 113, pp. 528-538, 2019.
[5] "The use of intelligent aggregator agents for advanced control of demand response," WIREs Energy and Environment, vol. 7, no. 3, p. https://doi.org/10.1002/wene.287, 2018.
[6] Xiaoxing Lu, Xinxin Ge, Kangping Li, Fei Wang, Hongtao Shen, Peng Tao, Junjie Hu, Jingang Lai, Zhao Zhen, Miadreza Shafie-khah and João P. S. Catalão, "Optimal Bidding Strategy of Demand Response Aggregator Based On Customers’ Responsiveness Behaviors Modeling Under Different Incentives," IEEE Transactions on Industry Applications, vol. 57, no. 4, pp. 3329-3340, 2021.
[7] Chaman Lal Dewangan, Vineeth Vijayan, Devesh Shukla, S. Chakrabarti, S.N. Singh, Ankush Sharma and Md. Alamgir Hossain, "An improved decentralized scheme for incentive-based demand response from residential customers," Energy, vol. 284, no. Article 128568, 2023.
[8] Valentín Rigoni, Damian Flynn and Andrew Keane, "Coordinating Demand Response Aggregation With LV Network Operational Constraints," IEEE Transactions on Power Systems, vol. 36, no. 2, pp. 979-990, 2021. [9] Lokesh Kumar Panwar, Srikanth Reddy Konda, Ashu Verma, Bijaya K. Panigrahi and Rajesh Kumar, "Demand response aggregator coordinated two‐stage responsive load scheduling in distribution system considering customer behavior," IET Generation, Transmission & Distribution, vol. 11, no. 4, pp. 1023-1032, 2017.
[10] Ehsan Reihani, Mahdi Motalleb, Matsu Thornton and Reza Ghorbani, "A novel approach using flexible scheduling and aggregation to optimize demand response in the developing interactive grid market architecture," Applied Energy, vol. 183, pp. 445-455, 2016.
[11] Wenjie Lv, Jian Wu, Zhao Luo, Min Ding, Xiang Jiang, Hejian Li and Qian Wang, "Load Aggregator-Based Integrated Demand Response for Residential Smart Energy Hubs," Mathematical Problems in Engineering, vol. 1 (2019), no. Article 6925980, p. https://doi.org/10.1155/2019/6925980, 2019.
[12] Biao Xiang, Kangping Li, Xinxin Ge, Fei Wang, Jingang Lai and Payman Dehghanian, "Smart Households' Available Aggregated Capacity Day-ahead Forecast Model for Load Aggregators under Incentive-based Demand Response Program," in 2019 IEEE Industry Applications Society Annual Meeting, Baltimore, MD, USA, 2019.
[13] Michael David de Souza Dutra and Natalia Alguacil, "Optimal residential users coordination via demand response: An exact distributed framework," Applied Energy, vol. 279, no. Article 115851, 2020. [14] Amit Shewale, Anil Mokhade, Nitesh Funde and Neeraj Dhanraj Bokde, "An Overview of Demand Response in Smart Grid and Optimization Techniques for Efficient Residential Appliance Scheduling Problem," Energies, vol. 13, no. 16, p. 4266, 2020.
[15] Robin Roche, Siddharth Suryanarayanan, Timothy M. Hansen, Sila Kiliccote and Abdellatif Miraoui, "A multi-agent model and strategy for residential demand response coordination," in 2015 IEEE Eindhoven PowerTech, Eindhoven, Netherlands, 2015.
[16] Zhenyuan Zhang, Zihan Chen and Wei-Jen Lee, "Soft Actor–Critic Algorithm Featured Residential Demand Response Strategic Bidding for Load Aggregators," IEEE Transactions on Industry Application, vol. 58, no. 4, pp. 4298-4308, 2022.
[17] Morteza Vahid-Ghavidel, Mohammad S. Javadi, Sergio F. Santos, Matthew Gough, Behnam Mohammadi-Ivatloo, Miadreza Shafie-Khah and João P. S. Catalão, "Novel Hybrid Stochastic-Robust Optimal Trading Strategy for a Demand Response Aggregator in the Wholesale Electricity Market," IEEE Transactions on Industry Applications, vol. 57, no. 5, pp. 5488-5498, 2021.
[18] Alejandro Fraija, Kodjo Agbossou, Nilson Henao and Sousso Kelouwani, "Peak-to-average ratio analysis of a load aggregator for incentive-based demand response," in IEEE 29th International Symposium on Industrial Electronics, Delft, Netherlands, 2020.
[19] Fadi Elghitani and Weihua Zhuang, "Aggregating a Large Number of Residential Appliances for Demand Response Applications," IEEE Transactions on Smart Grid, vol. 9, no. 5, pp. 5092-5100, 2018.
[20] Pradnya Jadhav, Dagadu More and Surender Reddy Salkuti, "Smart residential distribution energy management system with integration of demand response and Aggregator," Cleaner and Responsible Consumption, vol. 9, p. 100115, 2023.
[21] Hessam Golmohamadi, Reza Keypour, Birgitte Bak-Jensen and Jayakrishnan R. Pillai, "A multi-agent based optimization of residential and industrial demand response aggregators," International Journal of Electrical Power & Energy Systems, vol. 107, pp. 472-485, 2019.
[22] Sleiman Mhanna, Archie C. Chapman and Gregor Verbič, "A Fast Distributed Algorithm for Large-Scale Demand Response Aggregation," IEEE Transactions on Smart Grid, vol. 7, no. 4, pp. 2094-2107, 2016.
[23] Chen Chen, Jianhui Wang and Shalinee Kishore, "A distributed direct load control approach for large-scale residential demand response," IEEE Transactions on Power Systems, vol. 29, no. 5, pp. 2219-2228, 2014.
[24] Minsu Park, Jihoan Lee and Dong-Jun Won, "Demand Response Strategy of Energy Prosumer Based on Robust Optimization Through Aggregator," IEEE Access, vol. 8, pp. 202969-202979, 2020.
[25] Mostafa Vahedipour-Dahraie, Homa Rashidizadeh-Kermani, Miadreza Shafie-Khah and Pierluigi Siano, "Peer-to-Peer Energy Trading Between Wind Power Producer and Demand Response Aggregators for Scheduling Joint Energy and Reserve," IEEE Systems Journal, vol. 15, no. 1, pp. 705-714, 2021.
[26] Kangping Li, Zhenghui Li, Chunyi Huang and Qian Ai, "Online transfer learning-based residential demand response potential forecasting for load aggregator," Applied Energy, vol. 358, p. 122631, 2024.
[27] Morteza Vahid-Ghavidel, Mohammad Sadegh Javadi, Sérgio F. Santos, Matthew Gough, Miadreza Shafie-khah and João P.S. Catalão, "Energy storage system impact on the operation of a demand response aggregator," Journal of Energy Storage, vol. 64, no. Article 107222, 2023.
[28] X.M. Fan, X.H. Li, Y.M. Ding, J. He and M. Zhao, "Demand response scheduling algorithm for smart residential communities considering heterogeneous energy consumption," Energy and Buildings, vol. 279, p. 112691, 2023.
[29] Kenneth Bruninx, Hrvoje Pandži´, Hélène Le Cadre and Erik Delarue, "On the Interaction Between Aggregators, Electricity Markets and Residential Demand Response Providers," IEEE TRANSACTIONS ON POWER SYSTEMS, vol. 35, no. 2, pp. 840-853, 2020.
[30] Sibo Nan, Ming Zhou and Gengyin Li, "Optimal residential community demand response scheduling in smart grid," Applied Energy, vol. 210, pp. 1280-1289, 2018.
[31] Lazaros Gkatzikis, Iordanis Koutsopoulos and Theodoros Salonidis, "The Role of Aggregators in Smart Grid Demand Response Markets," IEEE Journal on selected areas in communications, vol. 31, no. 7, pp. 1247-1257, 2013.
[32] Rajasekhar Batchu and Naran M. Pindoriya, "Residential Demand Response Algorithms: State-of-the-Art, Key Issues and Challenges," in Wireless and Satellite Systems: 7th International Conference, WiSATS 2015, Bradford, UK, 2015.
[33] Amin Rajabi, Li Li, Jiangfeng Zhang and Jianguo Zhu, "Aggregation of Small Loads for Demand Response Programs - Implementation and Challenges: A review," in 2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe, Milan, Italy, 2017.
[34] K. M. Tsui and S. C. Chan, "Demand Response Optimization for Smart Home Scheduling Under Real-Time Pricing," IEEE Transactions on Smart Grid, vol. 3, no. 4, pp. 1812 - 1821, 2012.
[35] Zhanle Wang and Raman Paranjape, "Optimal scheduling algorithm for charging electric vehicle in a residential sector under demand response," in 2015 IEEE Electrical Power and Energy Conference (EPEC), London, ON, Canada, 2015.
[36] Seokjae Moon and Jang-Won Lee, "Multi-Residential Demand Response Scheduling With Multi-Class Appliances in Smart Grid," IEEE Transactions on Smart Grid, vol. 9, no. 4, pp. 2518-2528, 2018.
[37] Zhanle Wang, Raman Paranjape, Zhikun Chen and Kai Zeng, "Multi-Agent Optimization for Residential Demand Response under Real-Time Pricing," Energies, vol. 12, no. 15, 2019.
[38] Haider Tarish Haider, Ong Hang See and Wilfried Elmenreich, "A review of residential demand response of smart grid," Renewable and Sustainable Energy Reviews, vol. 59, pp. 166-178, 2016.
[39] Hessam Golmohamadi, Reza Keypour, Birgitte Bak-Jensen, Jayakrishnan R. Pillai and Mohammad Hassan Khooban, "Robust Self-Scheduling of Operational Processes for Industrial Demand Response Aggregators," IEEE Transactions on Industrial Electronics, vol. 67, no. 2, pp. 1387-1395, 2019.
[40] Aiming Chen, Lu Shan, Jingtao Wang, Xiuxin Chen and Xiao Chen, "Research on Demand Response Day-Ahead Scheduling Model for Multi-type Residential Customers," in 2021 IEEE 4th International Electrical and Energy Conference, Wuhan, China, 2021.
[41] Changhai Yang, Jianjun Tuo, Zhengying Liu, Yongcheng Liu, Jichuan Yan and Fei Wang, "Optimal Scheduling Strategy of Demand Response Aggregators Considering Customers' Complicated Response Characteristic," in 2021 IEEE 5th Conference on Energy Internet and Energy System Integration (EI2), Taiyuan, China, 2021.
[42] Ameena Sumaiti, Srikanth Reddy Konda, Lokesh Panwar, Vishu Gupta, Rajesh Kumar and Bijaya Ketan Panigrahi, "Aggregated Demand Response Scheduling in Competitive Market Considering Load Behavior Through Fuzzy Intelligence," IEEE Transactions on Industry Applications, vol. 56, no. 4, pp. 4236 - 4247, 2020.
[43] Stefan Woltmann and Julia Kittel, "Development and implementation of multi-agent systems for demand response aggregators in an industrial context," Applied Energy, vol. 314, no. Article 118841, 2022.
[44] Pierluigi Siano and Debora Sarno, "Assessing the benefits of residential demand response in a real time distribution energy market," Applied Energy, vol. 161, pp. 533-551, 2016.
[45] Cátia Silva, Pedro Faria and Zita Vale, "Rating the Participation in Demand Response Programs for a More Accurate Aggregated Schedule of Consumers after Enrolment Period," Electronics, vol. 9, no. 2, p. 349, 2020.
[46] Hui Ren, Aiwei Zhang, Fei Wang, Xihui Yan, Yu Li, Neven Duić, Miadreza Shafie-khah and João P.S. Catalão, "Optimal scheduling of an EV aggregator for demand response considering triple level benefits of three-parties," International Journal of Electrical Power & Energy Systems, vol. 125, p. 106447, 2021.
[47] Yusuf Ozturk, Prakash Jha, Sunil Kumar and Gordon Lee, "A personalized home energy management system for residential demand response," in 4th International Conference on Power Engineering, Energy and Electrical Drives, Istanbul, Turkey, 2013.
[48] Shalini Pal and Rajesh Kumar, "Electric Vehicle Scheduling Strategy in Residential Demand Response Programs With Neighbor Connection," IEEE Transactions on Industrial Informatics ( Volume: 14, Issue: 3, March 2018), vol. 14, no. 3, pp. 980 - 988, 2018.
[49] Ying Li, Boon Loong Ng, Mark Trayer and Lingjia Liu, "Automated Residential Demand Response: Algorithmic Implications of Pricing Models," IEEE Transactions on Smart Grid, vol. 3, no. 4, pp. 1712 - 1721, 2012.
[50] Ricardo Faia, Pedro Faria, Zita Vale and João Spinola, "Demand Response Optimization Using Particle Swarm Algorithm Considering Optimum Battery Energy Storage Schedule in a Residential House," Energies, vol. 12, no. 9, p. 1645, 2019.
[51] Xiaoxing Lu, Kangping Li, Hanchen Xu, Fei Wang, Zhenyu Zhou and Yagang Zhang, "Fundamentals and business model for resource aggregator of demand response in electricity markets," Energy, vol. 204, p. Article 117885, 2020.
[52] Yunwei Shen, Yang Li, Qiwei Zhang, Fangxing Li and Zhe Wang, "Consumer Psychology Based Optimal Portfolio Design for Demand Response Aggregators," Journal of Modern Power Systems and Clean Energy, vol. 9, no. 2, pp. 431-439, 2021.
[53] Jingjing Zhang, Peng Zhang, Hongbin Wu, Xianjun Qi, Shihai Yang and Zhixin Li, "Two-stage load-scheduling model for the incentive-based demand response of industrial users considering load aggregators," IET Generation, Transmission & Distribution, vol. 12, no. 14, pp. 3518-3526, 2018.
[54] Xiao Kou, Fangxing Li, Jin Dong, Mohammed Olama, Michael Starke, Yang Chen and Helia Zandi, "A Comprehensive Scheduling Framework Using SP-ADMM for Residential Demand Response With Weather and Consumer Uncertainties," IEEE Transactions on Power Systems, vol. 36, no. 4, pp. 3004-3016, 2021.
[55] X. Ayón, J.K. Gruber, B.P. Hayes, J. Usaola and M. Prodanović, "An optimal day-ahead load scheduling approach based on the flexibility of aggregate demands," Applied Energy, vol. 198, pp. 1-11, 2017.
[56] Qifen Li, Yihan Zhao, Yongwen Yang, Liting Zhang and Chen Ju, "Demand-Response-Oriented Load Aggregation Scheduling Optimization Strategy for Inverter Air Conditioner," energies, vol. 16, no. 1, 2023.
[57] Julian Garcia-Guarin, David Alvarez, Arturo Bretas and Sergio Rivera, "Schedule Optimization in a Smart Microgrid Considering Demand Response Constraints," Energies, vol. 13, no. 17, p. 4567, 2020.
[58] Zorica Bogdanović, Mirjana Stojanović, Miloš Radenković, Aleksandra Labus and Marijana Despotović-Zrakić , "Mobile Operator as the Aggregator in a Demand Response Model for Smart Residential Communities," in Proceedings of the Fifteenth International Conference on Management Science and Engineering Management , 2021.
[59] Zhe Chen, Yongbao Chen, Ruikai He, Jingnan Liu, Ming Gao and Lixin Zhang, "Multi-objective residential load scheduling approach for demand response in smart grid," Sustainable Cities and Society, vol. 76, p. 103530, 2022.
[60] T. Sarris, G. Messini and N. Hatziargyriou, "Residential demand response with low cost smart load controllers," in Mediterranean Conference on Power Generation, Transmission, Distribution and Energy Conversion, 2016.
[61] Zhenyuan Zhang, Zihan Chen and Wei-Jen Lee, "Residential Demand Response Considered Strategic Bidding for Load Aggregators with Soft Actor-Critic Algorithm," in 2021 IEEE Industry Applications Society Annual Meeting (IAS), Vancouver, BC, Canada, 2021.
[62] Kaveh Paridari, Alessandra Parisio, Henrik Sandber and Karl Henrik Johansson, "Demand response for aggregated residential consumers with energy storage sharing," in 2015 54th IEEE Conference on Decision and Control, Osaka, Japan, 2015.
[63] Berk Celik, Venkat Durvasulu, Fernando Bereta dos Reis, Timothy M. Hansen and Yingying Zheng, "A Framework for Large-Scale Incentive-Based Residential Demand Response using Aggregators," in 2019 IEEE International Conference on Electro Information Technology, Brookings, SD, USA, 2019.
[64] Fei Wang, Xinxin Ge, Peng Yang, Kangping Li, Zengqiang Mi, Pierluigi Siano and Neven Duić, "Day-ahead optimal bidding and scheduling strategies for DER aggregator considering responsive uncertainty under real-time pricing," Energy, vol. 213, p. 118765, 2020.
[65] Mubbashir Ali, Antti Alahäivälä, Farhan Malik, Muhammad Humayun, Amir Safdarian and Amir Safdarian, "A market-oriented hierarchical framework for residential demand response," International Journal of Electrical Power & Energy Systems, vol. 69, pp. 257-263, 2015.
[66] Özge Okur, Nina Voulis, Petra Heijnen and Zofia Lukszo, "Aggregator-mediated demand response: Minimizing imbalances caused by uncertainty of solar generation," Applied Energy, vol. 247, pp. 426-437, 2019.
[67] Nur Mohammad and Yateendra Mishra, "The Role of Demand Response Aggregators and the Effect of GenCos Strategic Bidding on the Flexibility of Demand," Energies, vol. 11, no. 12, p. 3296, 2018.
[68] Mahdi Motalleb and Reza Ghorbani, "Non-cooperative game-theoretic model of demand response aggregator competition for selling stored energy in storage devices," Applied Energy, vol. 202, pp. 581-596, 2017.
[69] Abouzar Estebsari, Pietro Rando Mazzarino, Lorenzo Bottaccioli and Edoardo Patti, "IoT-Enabled Real-Time Management of Smart Grids With Demand Response Aggregators," IEEE Transactions on Industry Applications, vol. 58, no. 1, pp. 102-112, 2022.
[70] Pratik Harsh and Debapriya Das, "Optimal coordination strategy of demand response and electric vehicle aggregators for the energy management of reconfigured grid-connected microgrid," Renewable and Sustainable Energy Reviews, vol. 160, no. Article 112251, 2022.
[71] Kaveh Paridari, Lars Nordstrom and Claes Sandels, "Aggregator strategy for planning demand response resources under uncertainty based on load flexibility modeling," in 2017 IEEE International Conference on Smart Grid Communications (SmartGridComm), Dresden, Germany, 2017.
[72] Saeed Abapour, Behnam Mohammadi-Ivatloo and Mehrdad Tarafdar Hagh, "Robust bidding strategy for demand response aggregators in electricity market based on game theory," Journal of Cleaner Production, vol. 243, p. 118393, 2020.
[73] Mohammad Ostadijafari, Rahul Ranjan Jha and Anamika Dube, "Aggregation and Bidding of Residential Demand Response into Wholesale Market," in 2020 IEEE Texas Power and Energy Conference (TPEC), College Station, TX, USA, 2020.
[74] Sleiman Mhanna, Gregor Verbič and Archie C. Chapman, "A Faithful Distributed Mechanism for Demand Response Aggregation," IEEE Transactions on Smart Grid, vol. 7, no. 3, pp. 1743-1753, 2016.
[75] K. Bruninx, H. Pandžic, H. Le Cadre and E. Delarue, "On Controllability of Demand Response Resources & Aggregators' Bidding Strategies," in 2018 Power Systems Computation Conference (PSCC), Dublin, Ireland, 2018.
[76] Mehdi Tavakkoli, Sajjad Fattaheian-dehkordi, Mahdi Pourakbari-kasmaei, Matti Liski and Matti Lehtonen, "An Incentive Based Demand Response by HVAC Systems in Residential Houses," in 2019 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe), Bucharest, Romania, 2019.
[77] Xiao Zhou, Jing Shi and Shujian Li, "Optimal control strategy of load aggregators with demand response," The Journal of Engineering, vol. 2019, no. 16, pp. 1033-1036, 2019.
[78] Heyang Yu, Jingchen Zhang, Junchao Ma, Changyu Chen and Guangchao Geng, "Privacy-preserving demand response of aggregated residential load," Applied Energy 339, vol. 339, p. Article 121018, 2023.
[79] Zhanle Wang, Raman Paranjape, Zhikun Chen and Kai Zeng, "Layered stochastic approach for residential demand response based on real-time pricing and incentive mechanism," IET Generation, Transmission & Distribution, vol. 14, no. 3, pp. 423-431, 2020.
[80] Shuyang Xu, Xingying Chen, Jun Xie, Saifur Rahman, Jixiang Wang, Hongxun Hui and Tao Chen, "Agent-based modeling and simulation for the electricity market with residential demand response," CSEE Journal of Power and Energy Systems, vol. 7, no. 2, pp. 368-380, 2021.
[81] Sara Haghifam, Mojtaba Dadashi, Kazem Zare and Heresh Seyedi, "Optimal operation of smart distribution networks in the presence of demand response aggregators and microgrid owners: A multi follower Bi-Level approach," Sustainable Cities and Society, vol. 55, no. Article 102033, 2020.
[82] Xiaoyu Zhou, Xiaofeng Liu, Huai Liu, Zhenya Ji and Feng Li, "Optimal dispatching strategy for residential demand response considering load participation," Global Energy Interconnection, vol. 7, no. 1, pp. 38-47, 2024.
[83] Qinran Hu and Fangxing Li, "An Optimal Framework for Residential Load Aggregators," p. arXiv:1506.04447, 2015.
[84] Rodrigo Henríquez, George Wenzel, Daniel E. Olivares and Matías Negrete-Pincetic, "Participation of demand response aggregators in electricity markets: Optimal portfolio management," IEEE Transactions on Smart Grid, vol. 9, no. 5, pp. 4861-4871, 2018.
[85] Lingqiao Zhang, Lin Zeng, Haiyan Wu, Hanlin Liu, Peng Liao and Yusi Chen, "Optimal Scheduling of Load Aggregators Participating in Demand Response Market under Low-Carbon Power System," in 2021 IEEE 5th Conference on Energy Internet and Energy System Integration, Taiyuan, China, 2021.
[1] Fei Wang, Biao Xiang, Kangping Li, Xinxin Ge, Hai Lu, Jingang Lai and Payman Dehghanian, "Smart Households’ Aggregated Capacity Forecasting for Load Aggregators Under Incentive-Based Demand Response Programs," IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, vol. 56, no. 2, 2020.
[2] Zhaofang Song, Jing Shi, Shujian Li, Zexu Chen, Wangwang Yang and Zitong Zhang, "Day ahead bidding of a load aggregator considering residential consumers demand response uncertainty modeling," Applied Sciences, vol. 10, no. 20, p. 7310, 2020.
[3] Masood Parvania, Mahmud Fotuhi-Firuzabad and Mohammad Shahidehpour, "Optimal Demand Response Aggregation in Wholesale Electricity Markets," IEEE TRANSACTIONS ON SMART GRID, vol. 4, no. 4, 2013.
[4] Homa Rashidizadeh-Kermani, Mostafa Vahedipour-Dahraie, Miadreza Shafie-khah and João P.S. Catalão, "Stochastic programming model for scheduling demand response aggregators considering uncertain market prices and demands," International Journal of Electrical Power & Energy Systems, vol. 113, pp. 528-538, 2019.
[5] "The use of intelligent aggregator agents for advanced control of demand response," WIREs Energy and Environment, vol. 7, no. 3, p. https://doi.org/10.1002/wene.287, 2018.
[6] Xiaoxing Lu, Xinxin Ge, Kangping Li, Fei Wang, Hongtao Shen, Peng Tao, Junjie Hu, Jingang Lai, Zhao Zhen, Miadreza Shafie-khah and João P. S. Catalão, "Optimal Bidding Strategy of Demand Response Aggregator Based On Customers’ Responsiveness Behaviors Modeling Under Different Incentives," IEEE Transactions on Industry Applications, vol. 57, no. 4, pp. 3329-3340, 2021.
[7] Chaman Lal Dewangan, Vineeth Vijayan, Devesh Shukla, S. Chakrabarti, S.N. Singh, Ankush Sharma and Md. Alamgir Hossain, "An improved decentralized scheme for incentive-based demand response from residential customers," Energy, vol. 284, no. Article 128568, 2023.
[8] Valentín Rigoni, Damian Flynn and Andrew Keane, "Coordinating Demand Response Aggregation With LV Network Operational Constraints," IEEE Transactions on Power Systems, vol. 36, no. 2, pp. 979-990, 2021. [9] Lokesh Kumar Panwar, Srikanth Reddy Konda, Ashu Verma, Bijaya K. Panigrahi and Rajesh Kumar, "Demand response aggregator coordinated two‐stage responsive load scheduling in distribution system considering customer behavior," IET Generation, Transmission & Distribution, vol. 11, no. 4, pp. 1023-1032, 2017.
[10] Ehsan Reihani, Mahdi Motalleb, Matsu Thornton and Reza Ghorbani, "A novel approach using flexible scheduling and aggregation to optimize demand response in the developing interactive grid market architecture," Applied Energy, vol. 183, pp. 445-455, 2016.
[11] Wenjie Lv, Jian Wu, Zhao Luo, Min Ding, Xiang Jiang, Hejian Li and Qian Wang, "Load Aggregator-Based Integrated Demand Response for Residential Smart Energy Hubs," Mathematical Problems in Engineering, vol. 1 (2019), no. Article 6925980, p. https://doi.org/10.1155/2019/6925980, 2019.
[12] Biao Xiang, Kangping Li, Xinxin Ge, Fei Wang, Jingang Lai and Payman Dehghanian, "Smart Households' Available Aggregated Capacity Day-ahead Forecast Model for Load Aggregators under Incentive-based Demand Response Program," in 2019 IEEE Industry Applications Society Annual Meeting, Baltimore, MD, USA, 2019.
[13] Michael David de Souza Dutra and Natalia Alguacil, "Optimal residential users coordination via demand response: An exact distributed framework," Applied Energy, vol. 279, no. Article 115851, 2020. [14] Amit Shewale, Anil Mokhade, Nitesh Funde and Neeraj Dhanraj Bokde, "An Overview of Demand Response in Smart Grid and Optimization Techniques for Efficient Residential Appliance Scheduling Problem," Energies, vol. 13, no. 16, p. 4266, 2020.
[15] Robin Roche, Siddharth Suryanarayanan, Timothy M. Hansen, Sila Kiliccote and Abdellatif Miraoui, "A multi-agent model and strategy for residential demand response coordination," in 2015 IEEE Eindhoven PowerTech, Eindhoven, Netherlands, 2015.
[16] Zhenyuan Zhang, Zihan Chen and Wei-Jen Lee, "Soft Actor–Critic Algorithm Featured Residential Demand Response Strategic Bidding for Load Aggregators," IEEE Transactions on Industry Application, vol. 58, no. 4, pp. 4298-4308, 2022.
[17] Morteza Vahid-Ghavidel, Mohammad S. Javadi, Sergio F. Santos, Matthew Gough, Behnam Mohammadi-Ivatloo, Miadreza Shafie-Khah and João P. S. Catalão, "Novel Hybrid Stochastic-Robust Optimal Trading Strategy for a Demand Response Aggregator in the Wholesale Electricity Market," IEEE Transactions on Industry Applications, vol. 57, no. 5, pp. 5488-5498, 2021.
[18] Alejandro Fraija, Kodjo Agbossou, Nilson Henao and Sousso Kelouwani, "Peak-to-average ratio analysis of a load aggregator for incentive-based demand response," in IEEE 29th International Symposium on Industrial Electronics, Delft, Netherlands, 2020.
[19] Fadi Elghitani and Weihua Zhuang, "Aggregating a Large Number of Residential Appliances for Demand Response Applications," IEEE Transactions on Smart Grid, vol. 9, no. 5, pp. 5092-5100, 2018.
[20] Pradnya Jadhav, Dagadu More and Surender Reddy Salkuti, "Smart residential distribution energy management system with integration of demand response and Aggregator," Cleaner and Responsible Consumption, vol. 9, p. 100115, 2023.
[21] Hessam Golmohamadi, Reza Keypour, Birgitte Bak-Jensen and Jayakrishnan R. Pillai, "A multi-agent based optimization of residential and industrial demand response aggregators," International Journal of Electrical Power & Energy Systems, vol. 107, pp. 472-485, 2019.
[22] Sleiman Mhanna, Archie C. Chapman and Gregor Verbič, "A Fast Distributed Algorithm for Large-Scale Demand Response Aggregation," IEEE Transactions on Smart Grid, vol. 7, no. 4, pp. 2094-2107, 2016.
[23] Chen Chen, Jianhui Wang and Shalinee Kishore, "A distributed direct load control approach for large-scale residential demand response," IEEE Transactions on Power Systems, vol. 29, no. 5, pp. 2219-2228, 2014.
[24] Minsu Park, Jihoan Lee and Dong-Jun Won, "Demand Response Strategy of Energy Prosumer Based on Robust Optimization Through Aggregator," IEEE Access, vol. 8, pp. 202969-202979, 2020.
[25] Mostafa Vahedipour-Dahraie, Homa Rashidizadeh-Kermani, Miadreza Shafie-Khah and Pierluigi Siano, "Peer-to-Peer Energy Trading Between Wind Power Producer and Demand Response Aggregators for Scheduling Joint Energy and Reserve," IEEE Systems Journal, vol. 15, no. 1, pp. 705-714, 2021.
[26] Kangping Li, Zhenghui Li, Chunyi Huang and Qian Ai, "Online transfer learning-based residential demand response potential forecasting for load aggregator," Applied Energy, vol. 358, p. 122631, 2024.
[27] Morteza Vahid-Ghavidel, Mohammad Sadegh Javadi, Sérgio F. Santos, Matthew Gough, Miadreza Shafie-khah and João P.S. Catalão, "Energy storage system impact on the operation of a demand response aggregator," Journal of Energy Storage, vol. 64, no. Article 107222, 2023.
[28] X.M. Fan, X.H. Li, Y.M. Ding, J. He and M. Zhao, "Demand response scheduling algorithm for smart residential communities considering heterogeneous energy consumption," Energy and Buildings, vol. 279, p. 112691, 2023.
[29] Kenneth Bruninx, Hrvoje Pandži´, Hélène Le Cadre and Erik Delarue, "On the Interaction Between Aggregators, Electricity Markets and Residential Demand Response Providers," IEEE TRANSACTIONS ON POWER SYSTEMS, vol. 35, no. 2, pp. 840-853, 2020.
[30] Sibo Nan, Ming Zhou and Gengyin Li, "Optimal residential community demand response scheduling in smart grid," Applied Energy, vol. 210, pp. 1280-1289, 2018.
[31] Lazaros Gkatzikis, Iordanis Koutsopoulos and Theodoros Salonidis, "The Role of Aggregators in Smart Grid Demand Response Markets," IEEE Journal on selected areas in communications, vol. 31, no. 7, pp. 1247-1257, 2013.
[32] Rajasekhar Batchu and Naran M. Pindoriya, "Residential Demand Response Algorithms: State-of-the-Art, Key Issues and Challenges," in Wireless and Satellite Systems: 7th International Conference, WiSATS 2015, Bradford, UK, 2015.
[33] Amin Rajabi, Li Li, Jiangfeng Zhang and Jianguo Zhu, "Aggregation of Small Loads for Demand Response Programs - Implementation and Challenges: A review," in 2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe, Milan, Italy, 2017.
[34] K. M. Tsui and S. C. Chan, "Demand Response Optimization for Smart Home Scheduling Under Real-Time Pricing," IEEE Transactions on Smart Grid, vol. 3, no. 4, pp. 1812 - 1821, 2012.
[35] Zhanle Wang and Raman Paranjape, "Optimal scheduling algorithm for charging electric vehicle in a residential sector under demand response," in 2015 IEEE Electrical Power and Energy Conference (EPEC), London, ON, Canada, 2015.
[36] Seokjae Moon and Jang-Won Lee, "Multi-Residential Demand Response Scheduling With Multi-Class Appliances in Smart Grid," IEEE Transactions on Smart Grid, vol. 9, no. 4, pp. 2518-2528, 2018.
[37] Zhanle Wang, Raman Paranjape, Zhikun Chen and Kai Zeng, "Multi-Agent Optimization for Residential Demand Response under Real-Time Pricing," Energies, vol. 12, no. 15, 2019.
[38] Haider Tarish Haider, Ong Hang See and Wilfried Elmenreich, "A review of residential demand response of smart grid," Renewable and Sustainable Energy Reviews, vol. 59, pp. 166-178, 2016.
[39] Hessam Golmohamadi, Reza Keypour, Birgitte Bak-Jensen, Jayakrishnan R. Pillai and Mohammad Hassan Khooban, "Robust Self-Scheduling of Operational Processes for Industrial Demand Response Aggregators," IEEE Transactions on Industrial Electronics, vol. 67, no. 2, pp. 1387-1395, 2019.
[40] Aiming Chen, Lu Shan, Jingtao Wang, Xiuxin Chen and Xiao Chen, "Research on Demand Response Day-Ahead Scheduling Model for Multi-type Residential Customers," in 2021 IEEE 4th International Electrical and Energy Conference, Wuhan, China, 2021.
[41] Changhai Yang, Jianjun Tuo, Zhengying Liu, Yongcheng Liu, Jichuan Yan and Fei Wang, "Optimal Scheduling Strategy of Demand Response Aggregators Considering Customers' Complicated Response Characteristic," in 2021 IEEE 5th Conference on Energy Internet and Energy System Integration (EI2), Taiyuan, China, 2021.
[42] Ameena Sumaiti, Srikanth Reddy Konda, Lokesh Panwar, Vishu Gupta, Rajesh Kumar and Bijaya Ketan Panigrahi, "Aggregated Demand Response Scheduling in Competitive Market Considering Load Behavior Through Fuzzy Intelligence," IEEE Transactions on Industry Applications, vol. 56, no. 4, pp. 4236 - 4247, 2020.
[43] Stefan Woltmann and Julia Kittel, "Development and implementation of multi-agent systems for demand response aggregators in an industrial context," Applied Energy, vol. 314, no. Article 118841, 2022.
[44] Pierluigi Siano and Debora Sarno, "Assessing the benefits of residential demand response in a real time distribution energy market," Applied Energy, vol. 161, pp. 533-551, 2016.
[45] Cátia Silva, Pedro Faria and Zita Vale, "Rating the Participation in Demand Response Programs for a More Accurate Aggregated Schedule of Consumers after Enrolment Period," Electronics, vol. 9, no. 2, p. 349, 2020.
[46] Hui Ren, Aiwei Zhang, Fei Wang, Xihui Yan, Yu Li, Neven Duić, Miadreza Shafie-khah and João P.S. Catalão, "Optimal scheduling of an EV aggregator for demand response considering triple level benefits of three-parties," International Journal of Electrical Power & Energy Systems, vol. 125, p. 106447, 2021.
[47] Yusuf Ozturk, Prakash Jha, Sunil Kumar and Gordon Lee, "A personalized home energy management system for residential demand response," in 4th International Conference on Power Engineering, Energy and Electrical Drives, Istanbul, Turkey, 2013.
[48] Shalini Pal and Rajesh Kumar, "Electric Vehicle Scheduling Strategy in Residential Demand Response Programs With Neighbor Connection," IEEE Transactions on Industrial Informatics ( Volume: 14, Issue: 3, March 2018), vol. 14, no. 3, pp. 980 - 988, 2018.
[49] Ying Li, Boon Loong Ng, Mark Trayer and Lingjia Liu, "Automated Residential Demand Response: Algorithmic Implications of Pricing Models," IEEE Transactions on Smart Grid, vol. 3, no. 4, pp. 1712 - 1721, 2012.
[50] Ricardo Faia, Pedro Faria, Zita Vale and João Spinola, "Demand Response Optimization Using Particle Swarm Algorithm Considering Optimum Battery Energy Storage Schedule in a Residential House," Energies, vol. 12, no. 9, p. 1645, 2019.
[51] Xiaoxing Lu, Kangping Li, Hanchen Xu, Fei Wang, Zhenyu Zhou and Yagang Zhang, "Fundamentals and business model for resource aggregator of demand response in electricity markets," Energy, vol. 204, p. Article 117885, 2020.
[52] Yunwei Shen, Yang Li, Qiwei Zhang, Fangxing Li and Zhe Wang, "Consumer Psychology Based Optimal Portfolio Design for Demand Response Aggregators," Journal of Modern Power Systems and Clean Energy, vol. 9, no. 2, pp. 431-439, 2021.
[53] Jingjing Zhang, Peng Zhang, Hongbin Wu, Xianjun Qi, Shihai Yang and Zhixin Li, "Two-stage load-scheduling model for the incentive-based demand response of industrial users considering load aggregators," IET Generation, Transmission & Distribution, vol. 12, no. 14, pp. 3518-3526, 2018.
[54] Xiao Kou, Fangxing Li, Jin Dong, Mohammed Olama, Michael Starke, Yang Chen and Helia Zandi, "A Comprehensive Scheduling Framework Using SP-ADMM for Residential Demand Response With Weather and Consumer Uncertainties," IEEE Transactions on Power Systems, vol. 36, no. 4, pp. 3004-3016, 2021.
[55] X. Ayón, J.K. Gruber, B.P. Hayes, J. Usaola and M. Prodanović, "An optimal day-ahead load scheduling approach based on the flexibility of aggregate demands," Applied Energy, vol. 198, pp. 1-11, 2017.
[56] Qifen Li, Yihan Zhao, Yongwen Yang, Liting Zhang and Chen Ju, "Demand-Response-Oriented Load Aggregation Scheduling Optimization Strategy for Inverter Air Conditioner," energies, vol. 16, no. 1, 2023.
[57] Julian Garcia-Guarin, David Alvarez, Arturo Bretas and Sergio Rivera, "Schedule Optimization in a Smart Microgrid Considering Demand Response Constraints," Energies, vol. 13, no. 17, p. 4567, 2020.
[58] Zorica Bogdanović, Mirjana Stojanović, Miloš Radenković, Aleksandra Labus and Marijana Despotović-Zrakić , "Mobile Operator as the Aggregator in a Demand Response Model for Smart Residential Communities," in Proceedings of the Fifteenth International Conference on Management Science and Engineering Management , 2021.
[59] Zhe Chen, Yongbao Chen, Ruikai He, Jingnan Liu, Ming Gao and Lixin Zhang, "Multi-objective residential load scheduling approach for demand response in smart grid," Sustainable Cities and Society, vol. 76, p. 103530, 2022.
[60] T. Sarris, G. Messini and N. Hatziargyriou, "Residential demand response with low cost smart load controllers," in Mediterranean Conference on Power Generation, Transmission, Distribution and Energy Conversion, 2016.
[61] Zhenyuan Zhang, Zihan Chen and Wei-Jen Lee, "Residential Demand Response Considered Strategic Bidding for Load Aggregators with Soft Actor-Critic Algorithm," in 2021 IEEE Industry Applications Society Annual Meeting (IAS), Vancouver, BC, Canada, 2021.
[62] Kaveh Paridari, Alessandra Parisio, Henrik Sandber and Karl Henrik Johansson, "Demand response for aggregated residential consumers with energy storage sharing," in 2015 54th IEEE Conference on Decision and Control, Osaka, Japan, 2015.
[63] Berk Celik, Venkat Durvasulu, Fernando Bereta dos Reis, Timothy M. Hansen and Yingying Zheng, "A Framework for Large-Scale Incentive-Based Residential Demand Response using Aggregators," in 2019 IEEE International Conference on Electro Information Technology, Brookings, SD, USA, 2019.
[64] Fei Wang, Xinxin Ge, Peng Yang, Kangping Li, Zengqiang Mi, Pierluigi Siano and Neven Duić, "Day-ahead optimal bidding and scheduling strategies for DER aggregator considering responsive uncertainty under real-time pricing," Energy, vol. 213, p. 118765, 2020.
[65] Mubbashir Ali, Antti Alahäivälä, Farhan Malik, Muhammad Humayun, Amir Safdarian and Amir Safdarian, "A market-oriented hierarchical framework for residential demand response," International Journal of Electrical Power & Energy Systems, vol. 69, pp. 257-263, 2015.
[66] Özge Okur, Nina Voulis, Petra Heijnen and Zofia Lukszo, "Aggregator-mediated demand response: Minimizing imbalances caused by uncertainty of solar generation," Applied Energy, vol. 247, pp. 426-437, 2019.
[67] Nur Mohammad and Yateendra Mishra, "The Role of Demand Response Aggregators and the Effect of GenCos Strategic Bidding on the Flexibility of Demand," Energies, vol. 11, no. 12, p. 3296, 2018.
[68] Mahdi Motalleb and Reza Ghorbani, "Non-cooperative game-theoretic model of demand response aggregator competition for selling stored energy in storage devices," Applied Energy, vol. 202, pp. 581-596, 2017.
[69] Abouzar Estebsari, Pietro Rando Mazzarino, Lorenzo Bottaccioli and Edoardo Patti, "IoT-Enabled Real-Time Management of Smart Grids With Demand Response Aggregators," IEEE Transactions on Industry Applications, vol. 58, no. 1, pp. 102-112, 2022.
[70] Pratik Harsh and Debapriya Das, "Optimal coordination strategy of demand response and electric vehicle aggregators for the energy management of reconfigured grid-connected microgrid," Renewable and Sustainable Energy Reviews, vol. 160, no. Article 112251, 2022.
[71] Kaveh Paridari, Lars Nordstrom and Claes Sandels, "Aggregator strategy for planning demand response resources under uncertainty based on load flexibility modeling," in 2017 IEEE International Conference on Smart Grid Communications (SmartGridComm), Dresden, Germany, 2017.
[72] Saeed Abapour, Behnam Mohammadi-Ivatloo and Mehrdad Tarafdar Hagh, "Robust bidding strategy for demand response aggregators in electricity market based on game theory," Journal of Cleaner Production, vol. 243, p. 118393, 2020.
[73] Mohammad Ostadijafari, Rahul Ranjan Jha and Anamika Dube, "Aggregation and Bidding of Residential Demand Response into Wholesale Market," in 2020 IEEE Texas Power and Energy Conference (TPEC), College Station, TX, USA, 2020.
[74] Sleiman Mhanna, Gregor Verbič and Archie C. Chapman, "A Faithful Distributed Mechanism for Demand Response Aggregation," IEEE Transactions on Smart Grid, vol. 7, no. 3, pp. 1743-1753, 2016.
[75] K. Bruninx, H. Pandžic, H. Le Cadre and E. Delarue, "On Controllability of Demand Response Resources & Aggregators' Bidding Strategies," in 2018 Power Systems Computation Conference (PSCC), Dublin, Ireland, 2018.
[76] Mehdi Tavakkoli, Sajjad Fattaheian-dehkordi, Mahdi Pourakbari-kasmaei, Matti Liski and Matti Lehtonen, "An Incentive Based Demand Response by HVAC Systems in Residential Houses," in 2019 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe), Bucharest, Romania, 2019.
[77] Xiao Zhou, Jing Shi and Shujian Li, "Optimal control strategy of load aggregators with demand response," The Journal of Engineering, vol. 2019, no. 16, pp. 1033-1036, 2019.
[78] Heyang Yu, Jingchen Zhang, Junchao Ma, Changyu Chen and Guangchao Geng, "Privacy-preserving demand response of aggregated residential load," Applied Energy 339, vol. 339, p. Article 121018, 2023.
[79] Zhanle Wang, Raman Paranjape, Zhikun Chen and Kai Zeng, "Layered stochastic approach for residential demand response based on real-time pricing and incentive mechanism," IET Generation, Transmission & Distribution, vol. 14, no. 3, pp. 423-431, 2020.
[80] Shuyang Xu, Xingying Chen, Jun Xie, Saifur Rahman, Jixiang Wang, Hongxun Hui and Tao Chen, "Agent-based modeling and simulation for the electricity market with residential demand response," CSEE Journal of Power and Energy Systems, vol. 7, no. 2, pp. 368-380, 2021.
[81] Sara Haghifam, Mojtaba Dadashi, Kazem Zare and Heresh Seyedi, "Optimal operation of smart distribution networks in the presence of demand response aggregators and microgrid owners: A multi follower Bi-Level approach," Sustainable Cities and Society, vol. 55, no. Article 102033, 2020.
[82] Xiaoyu Zhou, Xiaofeng Liu, Huai Liu, Zhenya Ji and Feng Li, "Optimal dispatching strategy for residential demand response considering load participation," Global Energy Interconnection, vol. 7, no. 1, pp. 38-47, 2024.
[83] Qinran Hu and Fangxing Li, "An Optimal Framework for Residential Load Aggregators," p. arXiv:1506.04447, 2015.
[84] Rodrigo Henríquez, George Wenzel, Daniel E. Olivares and Matías Negrete-Pincetic, "Participation of demand response aggregators in electricity markets: Optimal portfolio management," IEEE Transactions on Smart Grid, vol. 9, no. 5, pp. 4861-4871, 2018.
[85] Lingqiao Zhang, Lin Zeng, Haiyan Wu, Hanlin Liu, Peng Liao and Yusi Chen, "Optimal Scheduling of Load Aggregators Participating in Demand Response Market under Low-Carbon Power System," in 2021 IEEE 5th Conference on Energy Internet and Energy System Integration, Taiyuan, China, 2021.
