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Forecasting methods in energy planning models

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Cited by:

  1. Zheng, Li & Abbasi, Kashif Raza & Salem, Sultan & Irfan, Muhammad & Alvarado, Rafael & Lv, Kangjuan, 2022. "How technological innovation and institutional quality affect sectoral energy consumption in Pakistan? Fresh policy insights from novel econometric approach," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
  2. Liyang Tang, 2020. "Application of Nonlinear Autoregressive with Exogenous Input (NARX) neural network in macroeconomic forecasting, national goal setting and global competitiveness assessment," Papers 2005.08735, arXiv.org.
  3. Mesbaholdin Salami & Farzad Movahedi Sobhani & Mohammad Sadegh Ghazizadeh, 2018. "Short-Term Forecasting of Electricity Supply and Demand by Using the Wavelet-PSO-NNs-SO Technique for Searching in Big Data of Iran’s Electricity Market," Data, MDPI, vol. 3(4), pages 1-26, October.
  4. Jānis Krūmiņš & Māris Kļaviņš, 2023. "Investigating the Potential of Nuclear Energy in Achieving a Carbon-Free Energy Future," Energies, MDPI, vol. 16(9), pages 1-31, April.
  5. Mousavi, Navid & Kothapalli, Ganesh & Habibi, Daryoush & Das, Choton K. & Baniasadi, Ali, 2020. "A novel photovoltaic-pumped hydro storage microgrid applicable to rural areas," Applied Energy, Elsevier, vol. 262(C).
  6. Moshe Kelner & Zinoviy Landsman & Udi E. Makov, 2022. "Probabilistic Peak Demand Estimation Using Members of the Clayton Generalized Gamma Copula Family," Energies, MDPI, vol. 15(16), pages 1-15, August.
  7. Hossein Yousefi & Mohammad Hasan Ghodusinejad & Armin Ghodrati, 2022. "Multi-Criteria Future Energy System Planning and Analysis for Hot Arid Areas of Iran," Energies, MDPI, vol. 15(24), pages 1-25, December.
  8. Jiang, Weiheng & Wu, Xiaogang & Gong, Yi & Yu, Wanxin & Zhong, Xinhui, 2020. "Holt–Winters smoothing enhanced by fruit fly optimization algorithm to forecast monthly electricity consumption," Energy, Elsevier, vol. 193(C).
  9. Barbara Glensk & Reinhard Madlener, 2019. "Energiewende @ Risk: On the Continuation of Renewable Power Generation at the End of Public Policy Support," Energies, MDPI, vol. 12(19), pages 1-25, September.
  10. Agbessi Akuété Pierre & Salami Adekunlé Akim & Agbosse Kodjovi Semenyo & Birregah Babiga, 2023. "Peak Electrical Energy Consumption Prediction by ARIMA, LSTM, GRU, ARIMA-LSTM and ARIMA-GRU Approaches," Energies, MDPI, vol. 16(12), pages 1-12, June.
  11. Alonso-Montesinos, J. & Polo, Jesús & Ballestrín, Jesús & Batlles, F.J. & Portillo, C., 2019. "Impact of DNI forecasting on CSP tower plant power production," Renewable Energy, Elsevier, vol. 138(C), pages 368-377.
  12. Adedayo Ajayi & Patrick Chi-Kwong Luk & Liyun Lao & Mohammad Farhan Khan, 2023. "Energy Forecasting Model for Ground Movement Operation in Green Airport," Energies, MDPI, vol. 16(13), pages 1-19, June.
  13. Wu, Wei & Zhang, Tingting & Xie, Xiaomin & Huang, Zhen, 2021. "Regional low carbon development pathways for the Yangtze River Delta region in China," Energy Policy, Elsevier, vol. 151(C).
  14. Wang, Zheng-Xin & Wang, Zhi-Wei & Li, Qin, 2020. "Forecasting the industrial solar energy consumption using a novel seasonal GM(1,1) model with dynamic seasonal adjustment factors," Energy, Elsevier, vol. 200(C).
  15. Sylvia Mardiana & Ferdinand Saragih & Martani Huseini, 2020. "Forecasting Gasoline Demand in Indonesia Using Time Series," International Journal of Energy Economics and Policy, Econjournals, vol. 10(6), pages 132-145.
  16. Krzysztof Księżopolski & Grzegorz Maśloch, 2021. "Time Delay Approach to Renewable Energy in the Visegrad Group," Energies, MDPI, vol. 14(7), pages 1-18, March.
  17. Hu, Huanling & Wang, Lin & Lv, Sheng-Xiang, 2020. "Forecasting energy consumption and wind power generation using deep echo state network," Renewable Energy, Elsevier, vol. 154(C), pages 598-613.
  18. Ding, Yan & Lyu, Yacong & Lu, Shilei & Wang, Ran, 2022. "Load shifting potential assessment of building thermal storage performance for building design," Energy, Elsevier, vol. 243(C).
  19. Dennis Dreier & Mark Howells, 2019. "OSeMOSYS-PuLP: A Stochastic Modeling Framework for Long-Term Energy Systems Modeling," Energies, MDPI, vol. 12(7), pages 1-26, April.
  20. Anna Karbowniczak & Hubert Latała & Krzysztof Nęcka & Sławomir Kurpaska & Tomasz Bergel, 2022. "Modelling of the Electric Energy Storage Process in a PCM Battery," Energies, MDPI, vol. 15(3), pages 1-17, January.
  21. Papetti, Alessandra & Menghi, Roberto & Di Domizio, Giulia & Germani, Michele & Marconi, Marco, 2019. "Resources value mapping: A method to assess the resource efficiency of manufacturing systems," Applied Energy, Elsevier, vol. 249(C), pages 326-342.
  22. Guefano, Serge & Tamba, Jean Gaston & Azong, Tchitile Emmanuel Wilfried & Monkam, Louis, 2021. "Forecast of electricity consumption in the Cameroonian residential sector by Grey and vector autoregressive models," Energy, Elsevier, vol. 214(C).
  23. Wenting Zhao & Juanjuan Zhao & Xilong Yao & Zhixin Jin & Pan Wang, 2019. "A Novel Adaptive Intelligent Ensemble Model for Forecasting Primary Energy Demand," Energies, MDPI, vol. 12(7), pages 1-28, April.
  24. Lee, Yoonjae & Ha, Byeongmin & Hwangbo, Soonho, 2022. "Generative model-based hybrid forecasting model for renewable electricity supply using long short-term memory networks: A case study of South Korea's energy transition policy," Renewable Energy, Elsevier, vol. 200(C), pages 69-87.
  25. Ma, Haoran, 2022. "Prediction of industrial power consumption in Jiangsu Province by regression model of time variable," Energy, Elsevier, vol. 239(PB).
  26. Liang, Yi & Niu, Dongxiao & Hong, Wei-Chiang, 2019. "Short term load forecasting based on feature extraction and improved general regression neural network model," Energy, Elsevier, vol. 166(C), pages 653-663.
  27. Glensk, Barbara & Madlener, Reinhard, 2019. "The value of enhanced flexibility of gas-fired power plants: A real options analysis," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
  28. Larisa Vazhenina & Elena Magaril & Igor Mayburov, 2022. "Resource Conservation as the Main Factor in Increasing the Resource Efficiency of Russian Gas Companies," Resources, MDPI, vol. 11(12), pages 1-14, December.
  29. Jun Hao & Xiaolei Sun & Qianqian Feng, 2020. "A Novel Ensemble Approach for the Forecasting of Energy Demand Based on the Artificial Bee Colony Algorithm," Energies, MDPI, vol. 13(3), pages 1-25, January.
  30. Hasinat Raquiba & Zuaini Ishak, 2020. "Sustainability Reporting Practices in the Energy Sector of Bangladesh," International Journal of Energy Economics and Policy, Econjournals, vol. 10(1), pages 508-516.
  31. Da Liu & Kun Sun & Han Huang & Pingzhou Tang, 2018. "Monthly Load Forecasting Based on Economic Data by Decomposition Integration Theory," Sustainability, MDPI, vol. 10(9), pages 1-22, September.
  32. 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.
  33. Jamil, Rehan, 2020. "Hydroelectricity consumption forecast for Pakistan using ARIMA modeling and supply-demand analysis for the year 2030," Renewable Energy, Elsevier, vol. 154(C), pages 1-10.
  34. Faheem Jan & Ismail Shah & Sajid Ali, 2022. "Short-Term Electricity Prices Forecasting Using Functional Time Series Analysis," Energies, MDPI, vol. 15(9), pages 1-15, May.
  35. Rendón, Juan F. & Trespalacios, Alfredo & Cortés, Lina M. & Villada-Medina, Hernán D., 2021. "Modelización de la demanda de energía eléctrica: más allá de la normalidad || Electrical energy demand modeling: beyond normality," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 32(1), pages 83-98, December.
  36. Asit Kumar Das & Debahuti Mishra & Kaberi Das & Pradeep Kumar Mallick & Sachin Kumar & Mikhail Zymbler & Hesham El-Sayed, 2022. "Prophesying the Short-Term Dynamics of the Crude Oil Future Price by Adopting the Survival of the Fittest Principle of Improved Grey Optimization and Extreme Learning Machine," Mathematics, MDPI, vol. 10(7), pages 1-33, March.
  37. Ali M. Hakami & Kazi N. Hasan & Mohammed Alzubaidi & Manoj Datta, 2022. "A Review of Uncertainty Modelling Techniques for Probabilistic Stability Analysis of Renewable-Rich Power Systems," Energies, MDPI, vol. 16(1), pages 1-26, December.
  38. Md Mijanur Rahman & Mohammad Shakeri & Sieh Kiong Tiong & Fatema Khatun & Nowshad Amin & Jagadeesh Pasupuleti & Mohammad Kamrul Hasan, 2021. "Prospective Methodologies in Hybrid Renewable Energy Systems for Energy Prediction Using Artificial Neural Networks," Sustainability, MDPI, vol. 13(4), pages 1-28, February.
  39. Hamad M. Alhajeri & Abdulrahman Almutairi & Abdulrahman Alenezi & Faisal Alshammari, 2020. "Energy Demand in the State of Kuwait During the Covid-19 Pandemic: Technical, Economic, and Environmental Perspectives," Energies, MDPI, vol. 13(17), pages 1-16, August.
  40. Figueiredo, Raquel & Nunes, Pedro & Brito, Miguel C., 2018. "Multiyear calibration of simulations of energy systems," Energy, Elsevier, vol. 157(C), pages 932-939.
  41. Thangjam, Aditya & Jaipuria, Sanjita & Dadabada, Pradeep Kumar, 2023. "Time-Varying approaches for Long-Term Electric Load Forecasting under economic shocks," Applied Energy, Elsevier, vol. 333(C).
  42. Tang, Tao & Jiang, Weiheng & Zhang, Hui & Nie, Jiangtian & Xiong, Zehui & Wu, Xiaogang & Feng, Wenjiang, 2022. "GM(1,1) based improved seasonal index model for monthly electricity consumption forecasting," Energy, Elsevier, vol. 252(C).
  43. Manickavasagam, Jeevananthan & Visalakshmi, S. & Apergis, Nicholas, 2020. "A novel hybrid approach to forecast crude oil futures using intraday data," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
  44. Ahmad, Tanveer & Zhang, Hongcai, 2020. "Novel deep supervised ML models with feature selection approach for large-scale utilities and buildings short and medium-term load requirement forecasts," Energy, Elsevier, vol. 209(C).
  45. Letnik, Tomislav & Marksel, Maršenka & Luppino, Giuseppe & Bardi, Andrea & Božičnik, Stane, 2018. "Review of policies and measures for sustainable and energy efficient urban transport," Energy, Elsevier, vol. 163(C), pages 245-257.
  46. Paul Anton Verwiebe & Stephan Seim & Simon Burges & Lennart Schulz & Joachim Müller-Kirchenbauer, 2021. "Modeling Energy Demand—A Systematic Literature Review," Energies, MDPI, vol. 14(23), pages 1-58, November.
  47. Ahmad, Tanveer & Huanxin, Chen & Zhang, Dongdong & Zhang, Hongcai, 2020. "Smart energy forecasting strategy with four machine learning models for climate-sensitive and non-climate sensitive conditions," Energy, Elsevier, vol. 198(C).
  48. Ahmad, Tanveer & Zhang, Dongdong & Huang, Chao, 2021. "Methodological framework for short-and medium-term energy, solar and wind power forecasting with stochastic-based machine learning approach to monetary and energy policy applications," Energy, Elsevier, vol. 231(C).
  49. Hugo Radet & Bruno Sareni & Xavier Roboam, 2023. "Synthesis of Solar Production and Energy Demand Profiles Using Markov Chains for Microgrid Design," Energies, MDPI, vol. 16(23), pages 1-12, December.
  50. Aristeidis Mystakidis & Paraskevas Koukaras & Nikolaos Tsalikidis & Dimosthenis Ioannidis & Christos Tjortjis, 2024. "Energy Forecasting: A Comprehensive Review of Techniques and Technologies," Energies, MDPI, vol. 17(7), pages 1-33, March.
  51. Papadimitrakis, M. & Giamarelos, N. & Stogiannos, M. & Zois, E.N. & Livanos, N.A.-I. & Alexandridis, A., 2021. "Metaheuristic search in smart grid: A review with emphasis on planning, scheduling and power flow optimization applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
  52. Zheng, Chong-wei, 2021. "Global oceanic wave energy resource dataset—with the Maritime Silk Road as a case study," Renewable Energy, Elsevier, vol. 169(C), pages 843-854.
  53. Eduardo Machado & Tiago Pinto & Vanessa Guedes & Hugo Morais, 2021. "Electrical Load Demand Forecasting Using Feed-Forward Neural Networks," Energies, MDPI, vol. 14(22), pages 1-24, November.
  54. Miriam Benedetti & Francesca Bonfà & Vito Introna & Annalisa Santolamazza & Stefano Ubertini, 2019. "Real Time Energy Performance Control for Industrial Compressed Air Systems: Methodology and Applications," Energies, MDPI, vol. 12(20), pages 1-28, October.
  55. de Oliveira Ventura, Lucas & Melo, Joel D. & Padilha-Feltrin, Antonio & Fernández-Gutiérrez, Juan Pablo & Sánchez Zuleta, Carmen C. & Piedrahita Escobar, Carlos César, 2020. "A new way for comparing solutions to non-technical electricity losses in South America," Utilities Policy, Elsevier, vol. 67(C).
  56. Yin, Linfei & Xie, Jiaxing, 2021. "Multi-temporal-spatial-scale temporal convolution network for short-term load forecasting of power systems," Applied Energy, Elsevier, vol. 283(C).
  57. Karol Bot & Samira Santos & Inoussa Laouali & Antonio Ruano & Maria da Graça Ruano, 2021. "Design of Ensemble Forecasting Models for Home Energy Management Systems," Energies, MDPI, vol. 14(22), pages 1-37, November.
  58. Anton A. Gerunov, 2022. "Performance of 109 Machine Learning Algorithms across Five Forecasting Tasks: Employee Behavior Modeling, Online Communication, House Pricing, IT Support and Demand Planning," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 2, pages 15-43.
  59. Marta Moure-Garrido & Celeste Campo & Carlos Garcia-Rubio, 2022. "Entropy-Based Anomaly Detection in Household Electricity Consumption," Energies, MDPI, vol. 15(5), pages 1-21, March.
  60. Ofosu-Adarkwa, Jeffrey & Xie, Naiming & Javed, Saad Ahmed, 2020. "Forecasting CO2 emissions of China's cement industry using a hybrid Verhulst-GM(1,N) model and emissions' technical conversion," Renewable and Sustainable Energy Reviews, Elsevier, vol. 130(C).
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