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Impact of residential demand response on power system operation: A Belgian case study

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  1. Baxter Williams & Daniel Bishop & Patricio Gallardo & J. Geoffrey Chase, 2023. "Demand Side Management in Industrial, Commercial, and Residential Sectors: A Review of Constraints and Considerations," Energies, MDPI, vol. 16(13), pages 1-28, July.
  2. Brouwer, Anne Sjoerd & van den Broek, Machteld & Zappa, William & Turkenburg, Wim C. & Faaij, André, 2016. "Least-cost options for integrating intermittent renewables in low-carbon power systems," Applied Energy, Elsevier, vol. 161(C), pages 48-74.
  3. McPherson, Madeleine & Stoll, Brady, 2020. "Demand response for variable renewable energy integration: A proposed approach and its impacts," Energy, Elsevier, vol. 197(C).
  4. Saffari, Mohammadali & Crownshaw, Timothy & McPherson, Madeleine, 2023. "Assessing the potential of demand-side flexibility to improve the performance of electricity systems under high variable renewable energy penetration," Energy, Elsevier, vol. 272(C).
  5. Xu, Xiandong & Jin, Xiaolong & Jia, Hongjie & Yu, Xiaodan & Li, Kang, 2015. "Hierarchical management for integrated community energy systems," Applied Energy, Elsevier, vol. 160(C), pages 231-243.
  6. Korjani, Saman & Casu, Fabio & Damiano, Alfonso & Pilloni, Virginia & Serpi, Alessandro, 2022. "An online energy management tool for sizing integrated PV-BESS systems for residential prosumers," Applied Energy, Elsevier, vol. 313(C).
  7. Jun Dong & Rong Li & Hui Huang, 2018. "Performance Evaluation of Residential Demand Response Based on a Modified Fuzzy VIKOR and Scalable Computing Method," Energies, MDPI, vol. 11(5), pages 1-27, April.
  8. Diestelmeier, Lea, 2019. "Changing power: Shifting the role of electricity consumers with blockchain technology – Policy implications for EU electricity law," Energy Policy, Elsevier, vol. 128(C), pages 189-196.
  9. Chiara Magni & Alessia Arteconi & Konstantinos Kavvadias & Sylvain Quoilin, 2020. "Modelling the Integration of Residential Heat Demand and Demand Response in Power Systems with High Shares of Renewables," Energies, MDPI, vol. 13(24), pages 1-19, December.
  10. Behl, Madhur & Smarra, Francesco & Mangharam, Rahul, 2016. "DR-Advisor: A data-driven demand response recommender system," Applied Energy, Elsevier, vol. 170(C), pages 30-46.
  11. Vázquez-Canteli, José R. & Nagy, Zoltán, 2019. "Reinforcement learning for demand response: A review of algorithms and modeling techniques," Applied Energy, Elsevier, vol. 235(C), pages 1072-1089.
  12. Anilkumar, T.T. & Simon, Sishaj P. & Padhy, Narayana Prasad, 2017. "Residential electricity cost minimization model through open well-pico turbine pumped storage system," Applied Energy, Elsevier, vol. 195(C), pages 23-35.
  13. Curtis, John & Brazil, William & Harold, Jason, 2019. "Understanding preference heterogeneity in electricity services: the case of domestic appliance curtailment contracts," Papers WP638, Economic and Social Research Institute (ESRI).
  14. Klaassen, E.A.M. & van Gerwen, R.J.F. & Frunt, J. & Slootweg, J.G., 2017. "A methodology to assess demand response benefits from a system perspective: A Dutch case study," Utilities Policy, Elsevier, vol. 44(C), pages 25-37.
  15. Bert Willems & Juulia Zhou, 2020. "The Clean Energy Package and Demand Response: Setting Correct Incentives," Energies, MDPI, vol. 13(21), pages 1-19, October.
  16. Li, Jinghua & Fang, Jiakun & Zeng, Qing & Chen, Zhe, 2016. "Optimal operation of the integrated electrical and heating systems to accommodate the intermittent renewable sources," Applied Energy, Elsevier, vol. 167(C), pages 244-254.
  17. Liang, Yile & Liu, Feng & Wang, Cheng & Mei, Shengwei, 2017. "Distributed demand-side energy management scheme in residential smart grids: An ordinal state-based potential game approach," Applied Energy, Elsevier, vol. 206(C), pages 991-1008.
  18. Alahäivälä, Antti & Heß, Tobias & Cao, Sunliang & Lehtonen, Matti, 2015. "Analyzing the optimal coordination of a residential micro-CHP system with a power sink," Applied Energy, Elsevier, vol. 149(C), pages 326-337.
  19. Olkkonen, Ville & Ekström, Jussi & Hast, Aira & Syri, Sanna, 2018. "Utilising demand response in the future Finnish energy system with increased shares of baseload nuclear power and variable renewable energy," Energy, Elsevier, vol. 164(C), pages 204-217.
  20. de Oliveira e Silva, Guilherme & Hendrick, Patrick, 2016. "Lead–acid batteries coupled with photovoltaics for increased electricity self-sufficiency in households," Applied Energy, Elsevier, vol. 178(C), pages 856-867.
  21. 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.
  22. Olkkonen, Ville & Rinne, Samuli & Hast, Aira & Syri, Sanna, 2017. "Benefits of DSM measures in the future Finnish energy system," Energy, Elsevier, vol. 137(C), pages 729-738.
  23. Neves, Diana & Pina, André & Silva, Carlos A., 2015. "Demand response modeling: A comparison between tools," Applied Energy, Elsevier, vol. 146(C), pages 288-297.
  24. Behboodi, Sahand & Chassin, David P. & Crawford, Curran & Djilali, Ned, 2016. "Renewable resources portfolio optimization in the presence of demand response," Applied Energy, Elsevier, vol. 162(C), pages 139-148.
  25. Bing Wang & Qiran Cai & Zhenming Sun, 2020. "Determinants of Willingness to Participate in Urban Incentive-Based Energy Demand-Side Response: An Empirical Micro-Data Analysis," Sustainability, MDPI, vol. 12(19), pages 1-18, September.
  26. Nistor, Silviu & Wu, Jianzhong & Sooriyabandara, Mahesh & Ekanayake, Janaka, 2015. "Capability of smart appliances to provide reserve services," Applied Energy, Elsevier, vol. 138(C), pages 590-597.
  27. Wang, Xiaonan & Palazoglu, Ahmet & El-Farra, Nael H., 2015. "Operational optimization and demand response of hybrid renewable energy systems," Applied Energy, Elsevier, vol. 143(C), pages 324-335.
  28. Zeng, Qing & Fang, Jiakun & Li, Jinghua & Chen, Zhe, 2016. "Steady-state analysis of the integrated natural gas and electric power system with bi-directional energy conversion," Applied Energy, Elsevier, vol. 184(C), pages 1483-1492.
  29. Guo, Peiyang & Li, Victor O.K. & Lam, Jacqueline C.K., 2017. "Smart demand response in China: Challenges and drivers," Energy Policy, Elsevier, vol. 107(C), pages 1-10.
  30. Stadler, Michael & Cardoso, Gonçalo & Mashayekh, Salman & Forget, Thibault & DeForest, Nicholas & Agarwal, Ankit & Schönbein, Anna, 2016. "Value streams in microgrids: A literature review," Applied Energy, Elsevier, vol. 162(C), pages 980-989.
  31. Wang, Mingshen & Mu, Yunfei & Jia, Hongjie & Wu, Jianzhong & Yu, Xiaodan & Qi, Yan, 2017. "Active power regulation for large-scale wind farms through an efficient power plant model of electric vehicles," Applied Energy, Elsevier, vol. 185(P2), pages 1673-1683.
  32. Zhang, Menglin & Ai, Xiaomeng & Fang, Jiakun & Yao, Wei & Zuo, Wenping & Chen, Zhe & Wen, Jinyu, 2018. "A systematic approach for the joint dispatch of energy and reserve incorporating demand response," Applied Energy, Elsevier, vol. 230(C), pages 1279-1291.
  33. Patteeuw, Dieter & Henze, Gregor P. & Helsen, Lieve, 2016. "Comparison of load shifting incentives for low-energy buildings with heat pumps to attain grid flexibility benefits," Applied Energy, Elsevier, vol. 167(C), pages 80-92.
  34. Schreiber, Michael & Wainstein, Martin E. & Hochloff, Patrick & Dargaville, Roger, 2015. "Flexible electricity tariffs: Power and energy price signals designed for a smarter grid," Energy, Elsevier, vol. 93(P2), pages 2568-2581.
  35. Zamani, Ali Ghahgharaee & Zakariazadeh, Alireza & Jadid, Shahram, 2016. "Day-ahead resource scheduling of a renewable energy based virtual power plant," Applied Energy, Elsevier, vol. 169(C), pages 324-340.
  36. Xu, Bing & Nayak, Amar & Gray, David & Ouenniche, Jamal, 2016. "Assessing energy business cases implemented in the North Sea Region and strategy recommendations," Applied Energy, Elsevier, vol. 172(C), pages 360-371.
  37. Cruz, Marco R.M. & Fitiwi, Desta Z. & Santos, Sérgio F. & Catalão, João P.S., 2018. "A comprehensive survey of flexibility options for supporting the low-carbon energy future," Renewable and Sustainable Energy Reviews, Elsevier, vol. 97(C), pages 338-353.
  38. Kwon, Pil Seok & Østergaard, Poul, 2014. "Assessment and evaluation of flexible demand in a Danish future energy scenario," Applied Energy, Elsevier, vol. 134(C), pages 309-320.
  39. Yu, Xinran & Ergan, Semiha, 2022. "Estimating power demand shaving capacity of buildings on an urban scale using extracted demand response profiles through machine learning models," Applied Energy, Elsevier, vol. 310(C).
  40. Yuchun Li & Yinghua Han & Jinkuan Wang & Qiang Zhao, 2018. "A MBCRF Algorithm Based on Ensemble Learning for Building Demand Response Considering the Thermal Comfort," Energies, MDPI, vol. 11(12), pages 1-20, December.
  41. Arteconi, Alessia & Patteeuw, Dieter & Bruninx, Kenneth & Delarue, Erik & D’haeseleer, William & Helsen, Lieve, 2016. "Active demand response with electric heating systems: Impact of market penetration," Applied Energy, Elsevier, vol. 177(C), pages 636-648.
  42. Patteeuw, Dieter & Reynders, Glenn & Bruninx, Kenneth & Protopapadaki, Christina & Delarue, Erik & D’haeseleer, William & Saelens, Dirk & Helsen, Lieve, 2015. "CO2-abatement cost of residential heat pumps with active demand response: demand- and supply-side effects," Applied Energy, Elsevier, vol. 156(C), pages 490-501.
  43. Zhixin Pan & Jianming Wang & Wenlong Liao & Haiwen Chen & Dong Yuan & Weiping Zhu & Xin Fang & Zhen Zhu, 2019. "Data-Driven EV Load Profiles Generation Using a Variational Auto-Encoder," Energies, MDPI, vol. 12(5), pages 1-15, March.
  44. Yamaguchi, Yohei & Chen, Chien-fei & Shimoda, Yoshiyuki & Yagita, Yoshie & Iwafune, Yumiko & Ishii, Hideo & Hayashi, Yasuhiro, 2020. "An integrated approach of estimating demand response flexibility of domestic laundry appliances based on household heterogeneity and activities," Energy Policy, Elsevier, vol. 142(C).
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