Indirect Impact of the COVID-19 Pandemic on Natural Gas Consumption by Commercial Consumers in a Selected City in Poland
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- López Prol, Javier & O, Sungmin, 2020. "Impact of COVID-19 measures on electricity consumption," MPRA Paper 101649, University Library of Munich, Germany.
- Siemek, Jakub & Nagy, Stanislaw & Rychlicki, Stanislaw, 2003. "Estimation of natural-gas consumption in Poland based on the logistic-curve interpretation," Applied Energy, Elsevier, vol. 75(1-2), pages 1-7, May.
- Khan, Muhammad Arshad, 2015. "Modelling and forecasting the demand for natural gas in Pakistan," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 1145-1159.
- Yu, Feng & Xu, Xiaozhong, 2014. "A short-term load forecasting model of natural gas based on optimized genetic algorithm and improved BP neural network," Applied Energy, Elsevier, vol. 134(C), pages 102-113.
- Oliver, Ronan & Duffy, Aidan & Enright, Bernard & O'Connor, Rodger, 2017. "Forecasting peak-day consumption for year-ahead management of natural gas networks," Utilities Policy, Elsevier, vol. 44(C), pages 1-11.
- Luis M. Abadie, 2021. "Energy Market Prices in Times of COVID-19: The Case of Electricity and Natural Gas in Spain," Energies, MDPI, vol. 14(6), pages 1-17, March.
- Prol, Javier López & O, Sungmin, 2020. "Impact of COVID-19 Measures on Short-Term Electricity Consumption in the Most Affected EU Countries and USA States," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 23(10).
- Werth, Annette & Gravino, Pietro & Prevedello, Giulio, 2021. "Impact analysis of COVID-19 responses on energy grid dynamics in Europe," Applied Energy, Elsevier, vol. 281(C).
- Shaikh, Faheemullah & Ji, Qiang & Shaikh, Pervez Hameed & Mirjat, Nayyar Hussain & Uqaili, Muhammad Aslam, 2017. "Forecasting China’s natural gas demand based on optimised nonlinear grey models," Energy, Elsevier, vol. 140(P1), pages 941-951.
- Sarak, H & Satman, A, 2003. "The degree-day method to estimate the residential heating natural gas consumption in Turkey: a case study," Energy, Elsevier, vol. 28(9), pages 929-939.
- Ruan, Guangchun & Wu, Jiahan & Zhong, Haiwang & Xia, Qing & Xie, Le, 2021. "Quantitative assessment of U.S. bulk power systems and market operations during the COVID-19 pandemic," Applied Energy, Elsevier, vol. 286(C).
- Yu, Yihua & Zheng, Xinye & Han, Yi, 2014. "On the demand for natural gas in urban China," Energy Policy, Elsevier, vol. 70(C), pages 57-63.
- Halbrügge, Stephanie & Schott, Paul & Weibelzahl, Martin & Buhl, Hans Ulrich & Fridgen, Gilbert & Schöpf, Michael, 2021. "How did the German and other European electricity systems react to the COVID-19 pandemic?," Applied Energy, Elsevier, vol. 285(C).
- Xiaoyu Wang & Dongkun Luo & Jianye Liu & Wenhuan Wang & Guixin Jie, 2017. "Prediction of Natural Gas Consumption in Different Regions of China Using a Hybrid MVO-NNGBM Model," Mathematical Problems in Engineering, Hindawi, vol. 2017, pages 1-10, November.
- Szoplik, Jolanta, 2015. "Forecasting of natural gas consumption with artificial neural networks," Energy, Elsevier, vol. 85(C), pages 208-220.
- Donia Aloui & Stéphane Goutte & Khaled Guesmi & Rafla Hchaichi, 2020. "COVID 19's impact on crude oil and natural gas S&P GS Indexes," Working Papers halshs-02613280, HAL.
- Sanchez-Ubeda, Eugenio Fco. & Berzosa, Ana, 2007. "Modeling and forecasting industrial end-use natural gas consumption," Energy Economics, Elsevier, vol. 29(4), pages 710-742, July.
- Hribar, Rok & Potočnik, Primož & Šilc, Jurij & Papa, Gregor, 2019. "A comparison of models for forecasting the residential natural gas demand of an urban area," Energy, Elsevier, vol. 167(C), pages 511-522.
- Madurai Elavarasan, Rajvikram & Shafiullah, GM & Raju, Kannadasan & Mudgal, Vijay & Arif, M.T. & Jamal, Taskin & Subramanian, Senthilkumar & Sriraja Balaguru, V.S. & Reddy, K.S. & Subramaniam, Umashan, 2020. "COVID-19: Impact analysis and recommendations for power sector operation," Applied Energy, Elsevier, vol. 279(C).
- Douglas B. Reynolds & Marek Kolodziej, 2009. "North American Natural Gas Supply Forecast: The Hubbert Method Including the Effects of Institutions," Energies, MDPI, vol. 2(2), pages 1-38, May.
- Kim, Dongwoo & Yim, Taesu & Lee, Jae Yong, 2021. "Analytical study on changes in domestic hot water use caused by COVID-19 pandemic," Energy, Elsevier, vol. 231(C).
- Huang, Liqiao & Liao, Qi & Qiu, Rui & Liang, Yongtu & Long, Yin, 2021. "Prediction-based analysis on power consumption gap under long-term emergency: A case in China under COVID-19," Applied Energy, Elsevier, vol. 283(C).
- Izadyar, Nima & Ghadamian, Hossein & Ong, Hwai Chyuan & moghadam, Zeinab & Tong, Chong Wen & Shamshirband, Shahaboddin, 2015. "Appraisal of the support vector machine to forecast residential heating demand for the District Heating System based on the monthly overall natural gas consumption," Energy, Elsevier, vol. 93(P2), pages 1558-1567.
- Gutiérrez, R. & Nafidi, A. & Gutiérrez Sánchez, R., 2005. "Forecasting total natural-gas consumption in Spain by using the stochastic Gompertz innovation diffusion model," Applied Energy, Elsevier, vol. 80(2), pages 115-124, February.
- Emilio Ghiani & Marco Galici & Mario Mureddu & Fabrizio Pilo, 2020. "Impact on Electricity Consumption and Market Pricing of Energy and Ancillary Services during Pandemic of COVID-19 in Italy," Energies, MDPI, vol. 13(13), pages 1-19, July.
- Gabriella Balacco & Vincenzo Totaro & Vito Iacobellis & Alessandro Manni & Mauro Spagnoletta & Alberto Ferruccio Piccinni, 2020. "Influence of COVID-19 Spread on Water Drinking Demand: The Case of Puglia Region (Southern Italy)," Sustainability, MDPI, vol. 12(15), pages 1-16, July.
- Wei, Nan & Li, Changjun & Peng, Xiaolong & Li, Yang & Zeng, Fanhua, 2019. "Daily natural gas consumption forecasting via the application of a novel hybrid model," Applied Energy, Elsevier, vol. 250(C), pages 358-368.
- Özmen, Ayşe & Yılmaz, Yavuz & Weber, Gerhard-Wilhelm, 2018. "Natural gas consumption forecast with MARS and CMARS models for residential users," Energy Economics, Elsevier, vol. 70(C), pages 357-381.
- Beyca, Omer Faruk & Ervural, Beyzanur Cayir & Tatoglu, Ekrem & Ozuyar, Pinar Gokcin & Zaim, Selim, 2019. "Using machine learning tools for forecasting natural gas consumption in the province of Istanbul," Energy Economics, Elsevier, vol. 80(C), pages 937-949.
- Soldo, Božidar, 2012. "Forecasting natural gas consumption," Applied Energy, Elsevier, vol. 92(C), pages 26-37.
- Nan Wei & Changjun Li & Jiehao Duan & Jinyuan Liu & Fanhua Zeng, 2019. "Daily Natural Gas Load Forecasting Based on a Hybrid Deep Learning Model," Energies, MDPI, vol. 12(2), pages 1-15, January.
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forecasting gas consumption; neural networks; lockdown;All these keywords.
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