IDEAS home Printed from https://ideas.repec.org/r/eee/appene/v87y2010i1p320-326.html
   My bibliography  Save this item

Long term electric load forecasting based on particle swarm optimization

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Javed, Fahad & Arshad, Naveed & Wallin, Fredrik & Vassileva, Iana & Dahlquist, Erik, 2012. "Forecasting for demand response in smart grids: An analysis on use of anthropologic and structural data and short term multiple loads forecasting," Applied Energy, Elsevier, vol. 96(C), pages 150-160.
  2. Lin, Whei-Min & Gow, Hong-Jey & Tsai, Ming-Tang, 2010. "An enhanced radial basis function network for short-term electricity price forecasting," Applied Energy, Elsevier, vol. 87(10), pages 3226-3234, October.
  3. Moazzami, M. & Khodabakhshian, A. & Hooshmand, R., 2013. "A new hybrid day-ahead peak load forecasting method for Iran’s National Grid," Applied Energy, Elsevier, vol. 101(C), pages 489-501.
  4. Shao, Zhen & Gao, Fei & Zhang, Qiang & Yang, Shan-Lin, 2015. "Multivariate statistical and similarity measure based semiparametric modeling of the probability distribution: A novel approach to the case study of mid-long term electricity consumption forecasting i," Applied Energy, Elsevier, vol. 156(C), pages 502-518.
  5. Byungsung Lee & Haesung Lee & Hyun Ahn, 2020. "Improving Load Forecasting of Electric Vehicle Charging Stations Through Missing Data Imputation," Energies, MDPI, vol. 13(18), pages 1-15, September.
  6. Baños, R. & Manzano-Agugliaro, F. & Montoya, F.G. & Gil, C. & Alcayde, A. & Gómez, J., 2011. "Optimization methods applied to renewable and sustainable energy: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(4), pages 1753-1766, May.
  7. Dong, Yao & Wang, Jianzhou & Jiang, He & Shi, Xiaomeng, 2013. "Intelligent optimized wind resource assessment and wind turbines selection in Huitengxile of Inner Mongolia, China," Applied Energy, Elsevier, vol. 109(C), pages 239-253.
  8. Muhyaddin Rawa, 2022. "Towards Avoiding Cascading Failures in Transmission Expansion Planning of Modern Active Power Systems Using Hybrid Snake-Sine Cosine Optimization Algorithm," Mathematics, MDPI, vol. 10(8), pages 1-25, April.
  9. Siddhartha, & Sharma, Naveen & Varun,, 2012. "A particle swarm optimization algorithm for optimization of thermal performance of a smooth flat plate solar air heater," Energy, Elsevier, vol. 38(1), pages 406-413.
  10. Zhu, Suling & Wang, Jianzhou & Zhao, Weigang & Wang, Jujie, 2011. "A seasonal hybrid procedure for electricity demand forecasting in China," Applied Energy, Elsevier, vol. 88(11), pages 3807-3815.
  11. Taslimi-Renani, Ehsan & Modiri-Delshad, Mostafa & Elias, Mohamad Fathi Mohamad & Rahim, Nasrudin Abd., 2016. "Development of an enhanced parametric model for wind turbine power curve," Applied Energy, Elsevier, vol. 177(C), pages 544-552.
  12. Suganthi, L. & Samuel, Anand A., 2012. "Energy models for demand forecasting—A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(2), pages 1223-1240.
  13. Esmaili, Masoud & Shayanfar, Heidar Ali & Amjady, Nima, 2010. "Congestion management enhancing transient stability of power systems," Applied Energy, Elsevier, vol. 87(3), pages 971-981, March.
  14. 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.
  15. 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.
  16. 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.
  17. 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.
  18. 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.
  19. 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.
  20. 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).
  21. 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.
  22. 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.
  23. 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.
  24. 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.
  25. 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.
  26. 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.
  27. 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).
  28. 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.
  29. Zhao, Huiru & Guo, Sen, 2016. "An optimized grey model for annual power load forecasting," Energy, Elsevier, vol. 107(C), pages 272-286.
  30. 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.
  31. 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.
  32. Debnath, Kumar Biswajit & Mourshed, Monjur, 2018. "Forecasting methods in energy planning models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 297-325.
  33. 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.
  34. 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.
  35. Behm, Christian & Nolting, Lars & Praktiknjo, Aaron, 2020. "How to model European electricity load profiles using artificial neural networks," Applied Energy, Elsevier, vol. 277(C).
  36. 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.
  37. 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.
  38. 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.
  39. 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.
  40. 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.
  41. 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.
  42. 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.
  43. 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).
  44. Asif Afzal & Saad Alshahrani & Abdulrahman Alrobaian & Abdulrajak Buradi & Sher Afghan Khan, 2021. "Power Plant Energy Predictions Based on Thermal Factors Using Ridge and Support Vector Regressor Algorithms," Energies, MDPI, vol. 14(21), pages 1-22, November.
  45. Laha, Priyanka & Chakraborty, Basab, 2017. "Energy model – A tool for preventing energy dysfunction," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 95-114.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.