Advanced Optimisation and Forecasting Methods in Power Engineering—Introduction to the Special Issue
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Cheng-Hong Yang & Bo-Hong Chen & Chih-Hsien Wu & Kuo-Chang Chen & Li-Yeh Chuang, 2022. "Deep Learning for Forecasting Electricity Demand in Taiwan," Mathematics, MDPI, vol. 10(14), pages 1-19, July.
- Pookpunt, Sittichoke & Ongsakul, Weerakorn, 2013. "Optimal placement of wind turbines within wind farm using binary particle swarm optimization with time-varying acceleration coefficients," Renewable Energy, Elsevier, vol. 55(C), pages 266-276.
- Michał Izdebski & Robert Małkowski & Piotr Miller, 2022. "New Performance Indices for Power System Stabilizers," Energies, MDPI, vol. 15(24), pages 1-23, December.
- A. Cavallo & G. Canciello & B. Guida, 2017. "Energy Storage System Control for Energy Management in Advanced Aeronautic Applications," Mathematical Problems in Engineering, Hindawi, vol. 2017, pages 1-9, April.
- Piotr Kacejko & Piotr Miller & Paweł Pijarski, 2021. "Determination of Maximum Acceptable Standing Phase Angle across Open Circuit Breaker as an Optimisation Task," Energies, MDPI, vol. 14(23), pages 1-19, December.
- Alessandro Niccolai & Emanuele Ogliari & Alfredo Nespoli & Riccardo Zich & Valentina Vanetti, 2022. "Very Short-Term Forecast: Different Classification Methods of the Whole Sky Camera Images for Sudden PV Power Variations Detection," Energies, MDPI, vol. 15(24), pages 1-16, December.
- Robert Małkowski & Michał Izdebski & Piotr Miller, 2020. "Adaptive Algorithm of a Tap-Changer Controller of the Power Transformer Supplying the Radial Network Reducing the Risk of Voltage Collapse," Energies, MDPI, vol. 13(20), pages 1-25, October.
- Bartłomiej Mroczek & Paweł Pijarski, 2021. "DSO Strategies Proposal for the LV Grid of the Future," Energies, MDPI, vol. 14(19), pages 1-19, October.
- Mohammed A. A. Al-qaness & Ahmed A. Ewees & Mohamed Abd Elaziz & Ahmed H. Samak, 2022. "Wind Power Forecasting Using Optimized Dendritic Neural Model Based on Seagull Optimization Algorithm and Aquila Optimizer," Energies, MDPI, vol. 15(24), pages 1-14, December.
- Paszek, Stefan & Nocoń, Adrian, 2015. "Parameter polyoptimization of PSS2A power system stabilizers operating in a multi-machine power system including the uncertainty of model parameters," Applied Mathematics and Computation, Elsevier, vol. 267(C), pages 750-757.
- Bicer, Y. & Dincer, I. & Aydin, M., 2016. "Maximizing performance of fuel cell using artificial neural network approach for smart grid applications," Energy, Elsevier, vol. 116(P1), pages 1205-1217.
- Saad Ouali & Abdeljabbar Cherkaoui, 2020. "Elimination of the Impact Produced by DG Units on the Voltage Profile of Distribution Networks," Journal of Applied Mathematics, Hindawi, vol. 2020, pages 1-8, August.
- Masood, Nahid-Al- & Mahmud, Sajjad Uddin & Ansary, Md Nazmuddoha & Deeba, Shohana Rahman, 2022. "Improvement of system strength under high wind penetration: A techno-economic assessment using synchronous condenser and SVC," Energy, Elsevier, vol. 246(C).
- Hu, Jianming & Wang, Jianzhou & Zeng, Guowei, 2013. "A hybrid forecasting approach applied to wind speed time series," Renewable Energy, Elsevier, vol. 60(C), pages 185-194.
- Paweł Pijarski & Piotr Kacejko, 2021. "Voltage Optimization in MV Network with Distributed Generation Using Power Consumption Control in Electrolysis Installations," Energies, MDPI, vol. 14(4), pages 1-21, February.
- Adam F. Abdin & E. Zio, 2019. "Optimal Planning of Electric Power Systems," Springer Optimization and Its Applications, in: Mahdi Fathi & Marzieh Khakifirooz & Panos M. Pardalos (ed.), Optimization in Large Scale Problems, pages 53-65, Springer.
- Amir Abdul Majid, 2022. "Forecasting Monthly Wind Energy Using an Alternative Machine Training Method with Curve Fitting and Temporal Error Extraction Algorithm," Energies, MDPI, vol. 15(22), pages 1-24, November.
- Shukur, Osamah Basheer & Lee, Muhammad Hisyam, 2015. "Daily wind speed forecasting through hybrid KF-ANN model based on ARIMA," Renewable Energy, Elsevier, vol. 76(C), pages 637-647.
- Piotr Kacejko & Paweł Pijarski, 2021. "Optimal Voltage Control in MV Network with Distributed Generation," Energies, MDPI, vol. 14(2), pages 1-19, January.
- Petar Sarajcev & Antonijo Kunac & Goran Petrovic & Marin Despalatovic, 2022. "Artificial Intelligence Techniques for Power System Transient Stability Assessment," Energies, MDPI, vol. 15(2), pages 1-21, January.
- Tostado-Véliz, Marcos & Kamel, Salah & Aymen, Flah & Rezaee Jordehi, Ahmad & Jurado, Francisco, 2022. "A Stochastic-IGDT model for energy management in isolated microgrids considering failures and demand response," Applied Energy, Elsevier, vol. 317(C).
- Francisco G. Montoya & Raúl Baños & Alfredo Alcayde & Francisco Manzano-Agugliaro, 2019. "Optimization Methods Applied to Power Systems," Energies, MDPI, vol. 12(12), pages 1-8, June.
- Bartłomiej Mroczek & Paweł Pijarski, 2022. "Machine Learning in Operating of Low Voltage Future Grid," Energies, MDPI, vol. 15(15), pages 1-30, July.
- Robinius, Martin & Raje, Tanmay & Nykamp, Stefan & Rott, Tobias & Müller, Martin & Grube, Thomas & Katzenbach, Burkhard & Küppers, Stefan & Stolten, Detlef, 2018. "Power-to-Gas: Electrolyzers as an alternative to network expansion – An example from a distribution system operator," Applied Energy, Elsevier, vol. 210(C), pages 182-197.
- Khaled Guerraiche & Latifa Dekhici & Eric Chatelet & Abdelkader Zeblah, 2021. "Multi-Objective Electrical Power System Design Optimization Using a Modified Bat Algorithm," Energies, MDPI, vol. 14(13), pages 1-19, July.
- Paweł Pijarski & Piotr Kacejko & Marek Wancerz, 2022. "Voltage Control in MV Network with Distributed Generation—Possibilities of Real Quality Enhancement," Energies, MDPI, vol. 15(6), pages 1-22, March.
- Samat Iderus & Geno Peter & K. Praghash & Aruna Rai Vadde & Ravi Samikannu, 2022. "Optimization and Design of a Sustainable Industrial Grid System," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-12, July.
- Ibrahim Salem Jahan & Vaclav Snasel & Stanislav Misak, 2020. "Intelligent Systems for Power Load Forecasting: A Study Review," Energies, MDPI, vol. 13(22), pages 1-12, November.
- Sharmila Sumsurooah & Yun He & Marcello Torchio & Konstantinos Kouramas & Beniamino Guida & Fabrizio Cuomo & Jason Atkin & Serhiy Bozhko & Alfredo Renzetti & Antonio Russo & Stefano Riverso & Alberto , 2021. "ENIGMA—A Centralised Supervisory Controller for Enhanced Onboard Electrical Energy Management with Model in the Loop Demonstration," Energies, MDPI, vol. 14(17), pages 1-17, September.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Han Peng & Songyin Li & Linjian Shangguan & Yisa Fan & Hai Zhang, 2023. "Analysis of Wind Turbine Equipment Failure and Intelligent Operation and Maintenance Research," Sustainability, MDPI, vol. 15(10), pages 1-35, May.
- Paweł Pijarski & Adrian Belowski, 2024. "Application of Methods Based on Artificial Intelligence and Optimisation in Power Engineering—Introduction to the Special Issue," Energies, MDPI, vol. 17(2), pages 1-42, January.
- Paweł Pijarski & Piotr Kacejko, 2023. "Elimination of Line Overloads in a Power System Saturated with Renewable Energy Sources," Energies, MDPI, vol. 16(9), pages 1-19, April.
- Łukasz Mazur & Sławomir Cieślik & Stanislaw Czapp, 2023. "Trends in Locally Balanced Energy Systems without the Use of Fossil Fuels: A Review," Energies, MDPI, vol. 16(12), pages 1-31, June.
- Zbigniew Kłosowski & Łukasz Mazur, 2023. "Influence of the Type of Receiver on Electrical Energy Losses in Power Grids," Energies, MDPI, vol. 16(15), pages 1-22, July.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Paweł Pijarski & Piotr Kacejko & Marek Wancerz, 2022. "Voltage Control in MV Network with Distributed Generation—Possibilities of Real Quality Enhancement," Energies, MDPI, vol. 15(6), pages 1-22, March.
- Bartłomiej Mroczek & Paweł Pijarski, 2022. "Machine Learning in Operating of Low Voltage Future Grid," Energies, MDPI, vol. 15(15), pages 1-30, July.
- Adrian Nocoń & Stefan Paszek, 2023. "A Comprehensive Review of Power System Stabilizers," Energies, MDPI, vol. 16(4), pages 1-32, February.
- Juan D. Velásquez & Lorena Cadavid & Carlos J. Franco, 2023. "Intelligence Techniques in Sustainable Energy: Analysis of a Decade of Advances," Energies, MDPI, vol. 16(19), pages 1-45, October.
- Michał Izdebski & Robert Małkowski & Piotr Miller, 2022. "New Performance Indices for Power System Stabilizers," Energies, MDPI, vol. 15(24), pages 1-23, December.
- Paweł Pijarski & Adrian Belowski, 2024. "Application of Methods Based on Artificial Intelligence and Optimisation in Power Engineering—Introduction to the Special Issue," Energies, MDPI, vol. 17(2), pages 1-42, January.
- Bartłomiej Mroczek & Paweł Pijarski, 2021. "DSO Strategies Proposal for the LV Grid of the Future," Energies, MDPI, vol. 14(19), pages 1-19, October.
- Xuejiao Ma & Dandan Liu, 2016. "Comparative Study of Hybrid Models Based on a Series of Optimization Algorithms and Their Application in Energy System Forecasting," Energies, MDPI, vol. 9(8), pages 1-34, August.
- Łukasz Mazur & Zbigniew Kłosowski, 2023. "A New Approach to the Use of Energy from Renewable Sources in Low-Voltage Power Distribution Networks," Energies, MDPI, vol. 16(2), pages 1-29, January.
- Paweł Pijarski & Piotr Kacejko, 2021. "Voltage Optimization in MV Network with Distributed Generation Using Power Consumption Control in Electrolysis Installations," Energies, MDPI, vol. 14(4), pages 1-21, February.
- García, Irene & Huo, Stella & Prado, Raquel & Bravo, Lelys, 2020. "Dynamic Bayesian temporal modeling and forecasting of short-term wind measurements," Renewable Energy, Elsevier, vol. 161(C), pages 55-64.
- Jhoan Alejandro Montenegro-Oviedo & Carlos Andres Ramos-Paja & Martha Lucia Orozco-Gutierrez & Edinson Franco-Mejía & Sergio Ignacio Serna-Garcés, 2023. "Adaptive Controller for Bus Voltage Regulation on a DC Microgrid Using a Sepic/Zeta Battery Charger/Discharger," Mathematics, MDPI, vol. 11(4), pages 1-30, February.
- Li, Min & Yang, Yi & He, Zhaoshuang & Guo, Xinbo & Zhang, Ruisheng & Huang, Bingqing, 2023. "A wind speed forecasting model based on multi-objective algorithm and interpretability learning," Energy, Elsevier, vol. 269(C).
- Liu, Xiaolei & Lin, Zi & Feng, Ziming, 2021. "Short-term offshore wind speed forecast by seasonal ARIMA - A comparison against GRU and LSTM," Energy, Elsevier, vol. 227(C).
- Wang, Jianzhou & Xiong, Shenghua, 2014. "A hybrid forecasting model based on outlier detection and fuzzy time series – A case study on Hainan wind farm of China," Energy, Elsevier, vol. 76(C), pages 526-541.
- Konstantina Peloriadi & Petros Iliadis & Panagiotis Boutikos & Konstantinos Atsonios & Panagiotis Grammelis & Aristeidis Nikolopoulos, 2022. "Technoeconomic Assessment of LNG-Fueled Solid Oxide Fuel Cells in Small Island Systems: The Patmos Island Case Study," Energies, MDPI, vol. 15(11), pages 1-20, May.
- Fang, Ping & Fu, Wenlong & Wang, Kai & Xiong, Dongzhen & Zhang, Kai, 2022. "A compositive architecture coupling outlier correction, EWT, nonlinear Volterra multi-model fusion with multi-objective optimization for short-term wind speed forecasting," Applied Energy, Elsevier, vol. 307(C).
- Prince Waqas Khan & Yung-Cheol Byun & Sang-Joon Lee & Dong-Ho Kang & Jin-Young Kang & Hae-Su Park, 2020. "Machine Learning-Based Approach to Predict Energy Consumption of Renewable and Nonrenewable Power Sources," Energies, MDPI, vol. 13(18), pages 1-16, September.
- Juangsa, Firman Bagja & Prananto, Lukman Adi & Mufrodi, Zahrul & Budiman, Arief & Oda, Takuya & Aziz, Muhammad, 2018. "Highly energy-efficient combination of dehydrogenation of methylcyclohexane and hydrogen-based power generation," Applied Energy, Elsevier, vol. 226(C), pages 31-38.
- Liu, Xingdou & Zhang, Li & Wang, Jiangong & Zhou, Yue & Gan, Wei, 2023. "A unified multi-step wind speed forecasting framework based on numerical weather prediction grids and wind farm monitoring data," Renewable Energy, Elsevier, vol. 211(C), pages 948-963.
More about this item
Keywords
power engineering; optimisation; metaheuristics; RES; machine learning; probability; statistics;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:16:y:2023:i:6:p:2804-:d:1100402. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.