Long term electric load forecasting based on particle swarm optimization
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- Shao, Zhen & Chao, Fu & Yang, Shan-Lin & Zhou, Kai-Le, 2017. "A review of the decomposition methodology for extracting and identifying the fluctuation characteristics in electricity demand forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 123-136.
- Wang, Jianzhou & Jia, Ruiling & Zhao, Weigang & Wu, Jie & Dong, Yao, 2012. "Application of the largest Lyapunov exponent and non-linear fractal extrapolation algorithm to short-term load forecasting," Chaos, Solitons & Fractals, Elsevier, vol. 45(9), pages 1277-1287.
- Fanidhar Dewangan & Almoataz Y. Abdelaziz & Monalisa Biswal, 2023. "Load Forecasting Models in Smart Grid Using Smart Meter Information: A Review," Energies, MDPI, vol. 16(3), pages 1-55, January.
- Abdalrahman Alsulaili & Noor Aboramyah & Nasser Alenezi & Mohamad Alkhalidi, 2024. "Advancing Electricity Consumption Forecasts in Arid Climates through Machine Learning and Statistical Approaches," Sustainability, MDPI, vol. 16(15), pages 1-14, July.
- Swasti R. Khuntia & Jose L. Rueda & Mart A.M.M. Van der Meijden, 2018. "Long-Term Electricity Load Forecasting Considering Volatility Using Multiplicative Error Model," Energies, MDPI, vol. 11(12), pages 1-19, November.
- Manh-Hai Pham & T-A-Tho Vu & Duc-Quang Nguyen & Viet-Hung Dang & Ngoc-Trung Nguyen & Thu-Huyen Dang & The Vinh Nguyen, 2019. "Study on Selecting the Optimal Algorithm and the Effective Methodology to ANN-Based Short-Term Load Forecasting Model for the Southern Power Company in Vietnam," Energies, MDPI, vol. 12(12), pages 1-19, June.
- Gholami, M. & Barbaresi, A. & Torreggiani, D. & Tassinari, P., 2020. "Upscaling of spatial energy planning, phases, methods, and techniques: A systematic review through meta-analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
- Changrui Deng & Xiaoyuan Zhang & Yanmei Huang & Yukun Bao, 2021. "Equipping Seasonal Exponential Smoothing Models with Particle Swarm Optimization Algorithm for Electricity Consumption Forecasting," Energies, MDPI, vol. 14(13), pages 1-14, July.
- Yukseltan, Ergun & Yucekaya, Ahmet & Bilge, Ayse Humeyra, 2017. "Forecasting electricity demand for Turkey: Modeling periodic variations and demand segregation," Applied Energy, Elsevier, vol. 193(C), pages 287-296.
- Pereira, Sérgio & Ferreira, Paula & Vaz, A.I.F., 2016. "Optimization modeling to support renewables integration in power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 316-325.
- Wang, Xingwei & Cai, Yanpeng & Chen, Jiajun & Dai, Chao, 2013. "A grey-forecasting interval-parameter mixed-integer programming approach for integrated electric-environmental management–A case study of Beijing," Energy, Elsevier, vol. 63(C), pages 334-344.
- Wu, Zhibin & Xu, Jiuping, 2013. "Predicting and optimization of energy consumption using system dynamics-fuzzy multiple objective programming in world heritage areas," Energy, Elsevier, vol. 49(C), pages 19-31.
- Bingchun Liu & Chuanchuan Fu & Arlene Bielefield & Yan Quan Liu, 2017. "Forecasting of Chinese Primary Energy Consumption in 2021 with GRU Artificial Neural Network," Energies, MDPI, vol. 10(10), pages 1-15, September.
- Afzal, Asif & Buradi, Abdulrajak & Jilte, Ravindra & Shaik, Saboor & Kaladgi, Abdul Razak & Arıcı, Muslum & Lee, Chew Tin & Nižetić, Sandro, 2023. "Optimizing the thermal performance of solar energy devices using meta-heuristic algorithms: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 173(C).
- Al-Sulttani, Ali O. & Ahsan, Amimul & Hanoon, Ammar N. & Rahman, A. & Daud, N.N.N. & Idrus, S., 2017. "Hourly yield prediction of a double-slope solar still hybrid with rubber scrapers in low-latitude areas based on the particle swarm optimization technique," Applied Energy, Elsevier, vol. 203(C), pages 280-303.
- Zhao, Huiru & Guo, Sen, 2016. "An optimized grey model for annual power load forecasting," Energy, Elsevier, vol. 107(C), pages 272-286.
- S. Hr. Aghay Kaboli & Amer Al Hinai & A.H. Al-Badi & Yassine Charabi & Abdulrahim Al Saifi, 2019. "Prediction of Metallic Conductor Voltage Owing to Electromagnetic Coupling Via a Hybrid ANFIS and Backtracking Search Algorithm," Energies, MDPI, vol. 12(19), pages 1-18, September.
- Zhou, Kaile & Fu, Chao & Yang, Shanlin, 2016. "Big data driven smart energy management: From big data to big insights," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 215-225.
- Debnath, Kumar Biswajit & Mourshed, Monjur, 2018. "Forecasting methods in energy planning models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 297-325.
- Kaboli, S. Hr. Aghay & Fallahpour, A. & Selvaraj, J. & Rahim, N.A., 2017. "Long-term electrical energy consumption formulating and forecasting via optimized gene expression programming," Energy, Elsevier, vol. 126(C), pages 144-164.
- Hosseini, Seyyed Ahmad & Amjady, Nima & Shafie-khah, Miadreza & Catalão, João P.S., 2016. "A new multi-objective solution approach to solve transmission congestion management problem of energy markets," Applied Energy, Elsevier, vol. 165(C), pages 462-471.
- Behm, Christian & Nolting, Lars & Praktiknjo, Aaron, 2020. "How to model European electricity load profiles using artificial neural networks," Applied Energy, Elsevier, vol. 277(C).
- Jiyang Wang & Yuyang Gao & Xuejun Chen, 2018. "A Novel Hybrid Interval Prediction Approach Based on Modified Lower Upper Bound Estimation in Combination with Multi-Objective Salp Swarm Algorithm for Short-Term Load Forecasting," Energies, MDPI, vol. 11(6), pages 1-30, June.
- Liu, Nian & Tang, Qingfeng & Zhang, Jianhua & Fan, Wei & Liu, Jie, 2014. "A hybrid forecasting model with parameter optimization for short-term load forecasting of micro-grids," Applied Energy, Elsevier, vol. 129(C), pages 336-345.
- Ali K k & Erg n Y kseltan & Mustafa Hekimo lu & Esra Agca Aktunc & Ahmet Y cekaya & Ay e Bilge, 2022. "Forecasting Hourly Electricity Demand Under COVID-19 Restrictions," International Journal of Energy Economics and Policy, Econjournals, vol. 12(1), pages 73-85.
- Ke, Ming-Tsun & Yeh, Chia-Hung & Su, Cheng-Jie, 2017. "Cloud computing platform for real-time measurement and verification of energy performance," Applied Energy, Elsevier, vol. 188(C), pages 497-507.
- Li, Song & Goel, Lalit & Wang, Peng, 2016. "An ensemble approach for short-term load forecasting by extreme learning machine," Applied Energy, Elsevier, vol. 170(C), pages 22-29.
- Seyedeh Narjes Fallah & Ravinesh Chand Deo & Mohammad Shojafar & Mauro Conti & Shahaboddin Shamshirband, 2018. "Computational Intelligence Approaches for Energy Load Forecasting in Smart Energy Management Grids: State of the Art, Future Challenges, and Research Directions," Energies, MDPI, vol. 11(3), pages 1-31, March.
- Alireza Pourdaryaei & Mohammad Mohammadi & Mazaher Karimi & Hazlie Mokhlis & Hazlee A. Illias & Seyed Hamidreza Aghay Kaboli & Shameem Ahmad, 2021. "Recent Development in Electricity Price Forecasting Based on Computational Intelligence Techniques in Deregulated Power Market," Energies, MDPI, vol. 14(19), pages 1-28, September.
- Kazemzadeh, Mohammad-Rasool & Amjadian, Ali & Amraee, Turaj, 2020. "A hybrid data mining driven algorithm for long term electric peak load and energy demand forecasting," Energy, Elsevier, vol. 204(C).
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