IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i10p3985-d1142727.html
   My bibliography  Save this article

A Review of Research on Dynamic and Static Economic Dispatching of Hybrid Wind–Thermal Power Microgrids

Author

Listed:
  • Lingling Li

    (State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300130, China)

  • Jiarui Pei

    (State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300130, China)

  • Qiang Shen

    (State Grid Henan Xinxiang Electric Power Company Xinxiang Power Supply Company, Zhengzhou 450100, China)

Abstract

As fossil energy is increasingly depleted, promoting the integration of renewable energy into the grid and improving its utilization rate has become an irresistible development trend in China’s power industry. However, the volatility of wind power increases the difficulty of economic dispatch in power systems. With the rising participation of wind power in the system, the complexity of traditional microgrid dynamic scheduling problems has increased, transforming into a dynamic economic scheduling problem for wind power thermal power hybrid microgrids. Starting from the concept and research significance of economic dispatch, this article analyzes the current research status of microgrid economic dispatch as well as the impact and influencing factors of wind energy grid connection on it. It summarizes the research performed by scholars in two aspects: scheduling models and solving algorithms in static dispatch, as well as how to deal with wind power randomness in dynamic dispatch and how to balance environmental protection while ensuring economic maximization. Finally, the existing problems in current research were summarized and future development directions were prospected. This research has important application prospects in improving the economy of the system and protecting the ecological environment.

Suggested Citation

  • Lingling Li & Jiarui Pei & Qiang Shen, 2023. "A Review of Research on Dynamic and Static Economic Dispatching of Hybrid Wind–Thermal Power Microgrids," Energies, MDPI, vol. 16(10), pages 1-23, May.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:10:p:3985-:d:1142727
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/10/3985/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/10/3985/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Oracio I. Barbosa-Ayala & Jhon A. Montañez-Barrera & Cesar E. Damian-Ascencio & Adriana Saldaña-Robles & J. Arturo Alfaro-Ayala & Jose Alfredo Padilla-Medina & Sergio Cano-Andrade, 2020. "Solution to the Economic Emission Dispatch Problem Using Numerical Polynomial Homotopy Continuation," Energies, MDPI, vol. 13(17), pages 1-15, August.
    2. Xiuyun Wang & Shaoxin Chen & Yibing Zhou & Jian Wang & Yang Cui, 2018. "Optimal Dispatch of Microgrid with Combined Heat and Power System Considering Environmental Cost," Energies, MDPI, vol. 11(10), pages 1-23, September.
    3. Gang Zhang & Yaning Zhu & Tuo Xie & Kaoshe Zhang & Xin He, 2022. "Wind Power Consumption Model Based on the Connection between Mid- and Long-Term Monthly Bidding Power Decomposition and Short-Term Wind-Thermal Power Joint Dispatch," Energies, MDPI, vol. 15(19), pages 1-25, September.
    4. Kumar Biswajit Debnath & Monjur Mourshed, 2018. "Author Correction: Challenges and gaps for energy planning models in the developing-world context," Nature Energy, Nature, vol. 3(6), pages 528-528, June.
    5. Tingli Cheng & Minyou Chen & Yingxiang Wang & Bo Li & Muhammad Arshad Shehzad Hassan & Tao Chen & Ruilin Xu, 2018. "Adaptive Robust Method for Dynamic Economic Emission Dispatch Incorporating Renewable Energy and Energy Storage," Complexity, Hindawi, vol. 2018, pages 1-13, June.
    6. Kumar Biswajit Debnath & Monjur Mourshed, 2018. "Challenges and gaps for energy planning models in the developing-world context," Nature Energy, Nature, vol. 3(3), pages 172-184, March.
    7. Zhengjie Li & Zhisheng Zhang, 2021. "Day-Ahead and Intra-Day Optimal Scheduling of Integrated Energy System Considering Uncertainty of Source & Load Power Forecasting," Energies, MDPI, vol. 14(9), pages 1-14, April.
    8. Elio Chiodo & Maurizio Fantauzzi & Giovanni Mazzanti, 2022. "The Compound Inverse Rayleigh as an Extreme Wind Speed Distribution and Its Bayes Estimation," Energies, MDPI, vol. 15(3), pages 1-26, January.
    9. Hanifa Teimourian & Mahmoud Abubakar & Melih Yildiz & Amir Teimourian, 2022. "A Comparative Study on Wind Energy Assessment Distribution Models: A Case Study on Weibull Distribution," Energies, MDPI, vol. 15(15), pages 1-15, August.
    10. Rodríguez, Fermín & Galarza, Ainhoa & Vasquez, Juan C. & Guerrero, Josep M., 2022. "Using deep learning and meteorological parameters to forecast the photovoltaic generators intra-hour output power interval for smart grid control," Energy, Elsevier, vol. 239(PB).
    11. Cazzaro, Davide & Fischetti, Martina & Fischetti, Matteo, 2020. "Heuristic algorithms for the Wind Farm Cable Routing problem," Applied Energy, Elsevier, vol. 278(C).
    12. F. Daniel Santillán-Lemus & Hertwin Minor-Popocatl & Omar Aguilar-Mejía & Ruben Tapia-Olvera, 2019. "Optimal Economic Dispatch in Microgrids with Renewable Energy Sources," Energies, MDPI, vol. 12(1), pages 1-14, January.
    13. Li Yan & Zhengyu Zhu & Xiaopeng Kang & Boyang Qu & Baihao Qiao & Jiajia Huan & Xuzhao Chai, 2022. "Multi-Objective Dynamic Economic Emission Dispatch with Electric Vehicle–Wind Power Interaction Based on a Self-Adaptive Multiple-Learning Harmony-Search Algorithm," Energies, MDPI, vol. 15(14), pages 1-22, July.
    14. Dai, Wei & Yang, Zhifang & Yu, Juan & Cui, Wei & Li, Wenyuan & Li, Jinghua & Liu, Hui, 2021. "Economic dispatch of interconnected networks considering hidden flexibility," Energy, Elsevier, vol. 223(C).
    15. Huifeng Zhang & Xiaohui Lei & Chao Wang & Dong Yue & Xiangpeng Xie, 2017. "Adaptive grid based multi-objective Cauchy differential evolution for stochastic dynamic economic emission dispatch with wind power uncertainty," PLOS ONE, Public Library of Science, vol. 12(9), pages 1-25, September.
    16. Qiao, Baihao & Liu, Jing, 2020. "Multi-objective dynamic economic emission dispatch based on electric vehicles and wind power integrated system using differential evolution algorithm," Renewable Energy, Elsevier, vol. 154(C), pages 316-336.
    17. Rongquan Zhang & Saddam Aziz & Muhammad Umar Farooq & Kazi Nazmul Hasan & Nabil Mohammed & Sadiq Ahmad & Nisrine Ibadah, 2021. "A Wind Energy Supplier Bidding Strategy Using Combined EGA-Inspired HPSOIFA Optimizer and Deep Learning Predictor," Energies, MDPI, vol. 14(11), pages 1-22, May.
    18. Zhang, Guo-Xing & Yang, Yang & Su, Bin & Nie, Yan & Duan, Hong-Bo, 2023. "Electricity production, power generation structure, and air pollution: A monthly data analysis for 279 cities in China (2015–2019)," Energy Economics, Elsevier, vol. 120(C).
    19. Ke Jiang & Feng Wu & Linjun Shi & Keman Lin, 2020. "Distributed Hierarchical Consensus-Based Economic Dispatch for Isolated AC/DC Hybrid Microgrid," Energies, MDPI, vol. 13(12), pages 1-23, June.
    20. Jian Yang & Yu Liu & Shangguang Jiang & Yazhou Luo & Nianzhang Liu & Deping Ke, 2022. "A Method of Probability Distribution Modeling of Multi-Dimensional Conditions for Wind Power Forecast Error Based on MNSGA-II-Kmeans," Energies, MDPI, vol. 15(7), pages 1-21, March.
    21. Zhenhua Xiong & Yan Chen & Guihua Ban & Yixin Zhuo & Kui Huang, 2022. "A Hybrid Algorithm for Short-Term Wind Power Prediction," Energies, MDPI, vol. 15(19), pages 1-11, October.
    22. Roy, Sanjoy, 2018. "The maximum likelihood optima for an economic load dispatch in presence of demand and generation variability," Energy, Elsevier, vol. 147(C), pages 915-923.
    23. Jianzhong Xu & Fu Yan & Kumchol Yun & Lifei Su & Fengshu Li & Jun Guan, 2019. "Noninferior Solution Grey Wolf Optimizer with an Independent Local Search Mechanism for Solving Economic Load Dispatch Problems," Energies, MDPI, vol. 12(12), pages 1-26, June.
    Full references (including those not matched with items on IDEAS)

    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.
    1. Sourav Basak & Bishwajit Dey & Biplab Bhattacharyya, 2023. "Uncertainty-based dynamic economic dispatch for diverse load and wind profiles using a novel hybrid algorithm," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(5), pages 4723-4763, May.
    2. Sheng, Wanxing & Li, Rui & Yan, Tao & Tseng, Ming-Lang & Lou, Jiale & Li, Lingling, 2023. "A hybrid dynamic economics emissions dispatch model: Distributed renewable power systems based on improved COOT optimization algorithm," Renewable Energy, Elsevier, vol. 204(C), pages 493-506.
    3. Liu, Zhi-Feng & Li, Ling-Ling & Liu, Yu-Wei & Liu, Jia-Qi & Li, Heng-Yi & Shen, Qiang, 2021. "Dynamic economic emission dispatch considering renewable energy generation: A novel multi-objective optimization approach," Energy, Elsevier, vol. 235(C).
    4. Paul Wolfram & Qingshi Tu & Niko Heeren & Stefan Pauliuk & Edgar G. Hertwich, 2021. "Material efficiency and climate change mitigation of passenger vehicles," Journal of Industrial Ecology, Yale University, vol. 25(2), pages 494-510, April.
    5. Le Chi Kien & Thanh Long Duong & Van-Duc Phan & Thang Trung Nguyen, 2020. "Maximizing Total Profit of Thermal Generation Units in Competitive Electric Market by Using a Proposed Particle Swarm Optimization," Sustainability, MDPI, vol. 12(3), pages 1-35, February.
    6. Seyid Abdellahi Ebnou Abdem & Jérôme Chenal & El Bachir Diop & Rida Azmi & Meriem Adraoui & Cédric Stéphane Tekouabou Koumetio, 2023. "Using Logistic Regression to Predict Access to Essential Services: Electricity and Internet in Nouakchott, Mauritania," Sustainability, MDPI, vol. 15(23), pages 1-28, November.
    7. Hofbauer, Leonhard & McDowall, Will & Pye, Steve, 2022. "Challenges and opportunities for energy system modelling to foster multi-level governance of energy transitions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    8. Swarupa Pinninti & Srinivasa Rao Sura, 2023. "Renewables based dynamic cost-effective optimal scheduling of distributed generators using teaching–learning-based optimization," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(1), pages 353-373, March.
    9. Carlos Roberto de Sousa Costa & Paula Ferreira, 2023. "A Review on the Internalization of Externalities in Electricity Generation Expansion Planning," Energies, MDPI, vol. 16(4), pages 1-19, February.
    10. Zhang, Jiaqi & Tian, Guang & Chen, Xiangyu & Liu, Pei & Li, Zheng, 2023. "A chance-constrained programming approach to optimal planning of low-carbon transition of a regional energy system," Energy, Elsevier, vol. 278(PA).
    11. Sourav Basak & Biplab Bhattacharyya & Bishwajit Dey, 2022. "Combined economic emission dispatch on dynamic systems using hybrid CSA-JAYA Algorithm," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(5), pages 2269-2290, October.
    12. Marta Daroń & Monika Górska, 2023. "Relationships between Selected Quality Tools and Energy Efficiency in Production Processes," Energies, MDPI, vol. 16(13), pages 1-20, June.
    13. Kansal, Veenus & Dhillon, J.S., 2022. "Ameliorated artificial hummingbird algorithm for coordinated wind-solar-thermal generation scheduling problem in multiobjective framework," Applied Energy, Elsevier, vol. 326(C).
    14. Hampton, Harrison & Foley, Aoife, 2022. "A review of current analytical methods, modelling tools and development frameworks applicable for future retail electricity market design," Energy, Elsevier, vol. 260(C).
    15. Tong, Wenxuan & Lu, Zhengang & Chen, Yanbo & Zhao, Guoliang & Hunt, Julian David & Ren, Dawei & Xu, GuiZhi & Han, Minxiao, 2024. "Typical unit capacity configuration strategies and their control methods of modular gravity energy storage plants," Energy, Elsevier, vol. 295(C).
    16. Osorio-Aravena, Juan Carlos & Aghahosseini, Arman & Bogdanov, Dmitrii & Caldera, Upeksha & Ghorbani, Narges & Mensah, Theophilus Nii Odai & Khalili, Siavash & Muñoz-Cerón, Emilio & Breyer, Christian, 2021. "The impact of renewable energy and sector coupling on the pathway towards a sustainable energy system in Chile," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
    17. Pablo E. Carvajal & Asami Miketa & Nadeem Goussous & Pauline Fulcheri, 2022. "Best Practice in Government Use and Development of Long-Term Energy Transition Scenarios," Energies, MDPI, vol. 15(6), pages 1-21, March.
    18. Du, Binglin & Liu, Pei & Li, Zheng, 2023. "Coal power plants transition based on joint planning of power and central heating sectors: A case study of China," Energy, Elsevier, vol. 283(C).
    19. Srikant Misra & P. K. Panigrahi & Bishwajit Dey, 2023. "An efficient way to schedule dispersed generators for a microgrid system's economical operation under various power market conditions and grid involvement," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(5), pages 1799-1809, October.
    20. Song, Siming & Li, Tianxiao & Liu, Pei & Li, Zheng, 2022. "The transition pathway of energy supply systems towards carbon neutrality based on a multi-regional energy infrastructure planning approach: A case study of China," Energy, Elsevier, vol. 238(PC).

    Corrections

    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:10:p:3985-:d:1142727. 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.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.