IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i11p2840-d366694.html
   My bibliography  Save this article

Generation Units Maintenance in Combined Heat and Power Integrated Systems Using the Mixed Integer Quadratic Programming Approach

Author

Listed:
  • Omid Sadeghian

    (Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz 5166616471, Iran)

  • Arash Moradzadeh

    (Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz 5166616471, Iran)

  • Behnam Mohammadi-Ivatloo

    (Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz 5166616471, Iran
    Institute of Research and Development, Duy Tan University, Da Nang 550000, Vietnam)

  • Mehdi Abapour

    (Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz 5166616471, Iran)

  • Fausto Pedro Garcia Marquez

    (Ingneium Research Group, University of Castilla-La Mancha, 13071 Ciudad Real, Spain)

Abstract

Yearly generation maintenance scheduling (GMS) of generation units is important in each system such as combined heat and power (CHP)-based systems to decrease sudden failures and premature degradation of units. Imposing repair costs and reliability deterioration of system are the consequences of ignoring the GMS program. In this regard, this research accomplishes GMS inside CHP-based systems in order to determine the optimal intervals for predetermined maintenance required duration of CHPs and other units. In this paper, cost minimization is targeted, and violation of units’ technical constraints like feasible operation region of CHPs and power/heat demand balances are avoided by considering related constraints. Demand-response-based short-term generation scheduling is accomplished in this paper considering the maintenance intervals obtained in the long-term plan. Numerical simulation is performed and discussed in detail to evaluate the application of the suggested mixed-integer quadratic programming model that implemented in the General Algebraic Modeling System software package for optimization. Numerical simulation is performed to justify the model effectiveness. The results reveal that long-term maintenance scheduling considerably impacts short-term generation scheduling and total operation cost. Additionally, it is found that the demand response is effective from the cost perspective and changes the generation schedule.

Suggested Citation

  • Omid Sadeghian & Arash Moradzadeh & Behnam Mohammadi-Ivatloo & Mehdi Abapour & Fausto Pedro Garcia Marquez, 2020. "Generation Units Maintenance in Combined Heat and Power Integrated Systems Using the Mixed Integer Quadratic Programming Approach," Energies, MDPI, vol. 13(11), pages 1-25, June.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:11:p:2840-:d:366694
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/11/2840/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/11/2840/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Dahal, Keshav & Al-Arfaj, Khalid & Paudyal, Krishna, 2015. "Modelling generator maintenance scheduling costs in deregulated power markets," European Journal of Operational Research, Elsevier, vol. 240(2), pages 551-561.
    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. Bach Hoang Dinh & Thang Trung Nguyen & Nguyen Vu Quynh & Le Van Dai, 2018. "A Novel Method for Economic Dispatch of Combined Heat and Power Generation," Energies, MDPI, vol. 11(11), pages 1-27, November.
    4. Zou, Dexuan & Li, Steven & Kong, Xiangyong & Ouyang, Haibin & Li, Zongyan, 2019. "Solving the combined heat and power economic dispatch problems by an improved genetic algorithm and a new constraint handling strategy," Applied Energy, Elsevier, vol. 237(C), pages 646-670.
    5. Mazidi, Mohammadreza & Rezaei, Navid & Ghaderi, Abdolsalam, 2019. "Simultaneous power and heat scheduling of microgrids considering operational uncertainties: A new stochastic p-robust optimization approach," Energy, Elsevier, vol. 185(C), pages 239-253.
    6. Quan Lyu & Haoyan Gong & Nan Yang & Xiandong Xu & Na Zhang & Haixia Wang, 2019. "An Evaluation Method of Wind Power Integration in Power Systems with Flexible Combined Heat and Power Plant," Energies, MDPI, vol. 12(21), pages 1-17, October.
    7. Fotouhi Ghazvini, M.A. & Morais, Hugo & Vale, Zita, 2012. "Coordination between mid-term maintenance outage decisions and short-term security-constrained scheduling in smart distribution systems," Applied Energy, Elsevier, vol. 96(C), pages 281-291.
    8. Weidong Li & Tie Li & Haixin Wang & Jian Dong & Yunlu Li & Dai Cui & Weichun Ge & Junyou Yang & Martin Onyeka Okoye, 2019. "Optimal Dispatch Model Considering Environmental Cost Based on Combined Heat and Power with Thermal Energy Storage and Demand Response," Energies, MDPI, vol. 12(5), pages 1-18, March.
    9. Asad Waqar & Muhammad Shahbaz Tanveer & Jehanzeb Ahmad & Muhammad Aamir & Muneeb Yaqoob & Fareeha Anwar, 2017. "Multi-Objective Analysis of a CHP Plant Integrated Microgrid in Pakistan," Energies, MDPI, vol. 10(10), pages 1-22, October.
    10. Khuram Pervez Amber & Tony Day & Naeem Iqbal Ratyal & Adnan Khalid Kiani & Rizwan Ahmad, 2018. "Techno, Economic and Environmental Assessment of a Combined Heat and Power (CHP) System—A Case Study for a University Campus," Energies, MDPI, vol. 11(5), pages 1-18, May.
    11. Kia, Mohsen & Setayesh Nazar, Mehrdad & Sepasian, Mohammad Sadegh & Heidari, Alireza & Siano, Pierluigi, 2017. "An efficient linear model for optimal day ahead scheduling of CHP units in active distribution networks considering load commitment programs," Energy, Elsevier, vol. 139(C), pages 798-817.
    12. Rahmat Khezri & Arman Oshnoei & Mehrdad Tarafdar Hagh & SM Muyeen, 2018. "Coordination of Heat Pumps, Electric Vehicles and AGC for Efficient LFC in a Smart Hybrid Power System via SCA-Based Optimized FOPID Controllers," Energies, MDPI, vol. 11(2), pages 1-21, February.
    13. Alipour, Manijeh & Zare, Kazem & Mohammadi-Ivatloo, Behnam, 2014. "Short-term scheduling of combined heat and power generation units in the presence of demand response programs," Energy, Elsevier, vol. 71(C), pages 289-301.
    14. Majidi, Majid & Nojavan, Sayyad & Zare, Kazem, 2017. "A cost-emission framework for hub energy system under demand response program," Energy, Elsevier, vol. 134(C), pages 157-166.
    15. Froger, Aurélien & Gendreau, Michel & Mendoza, Jorge E. & Pinson, Éric & Rousseau, Louis-Martin, 2016. "Maintenance scheduling in the electricity industry: A literature review," European Journal of Operational Research, Elsevier, vol. 251(3), pages 695-706.
    16. Lennart Merkert & Ashvar Abdoul Haime & Sören Hohmann, 2019. "Optimal Scheduling of Combined Heat and Power Generation Units Using the Thermal Inertia of the Connected District Heating Grid as Energy Storage," Energies, MDPI, vol. 12(2), pages 1-9, January.
    17. Rongxiang Yuan & Jun Ye & Jiazhi Lei & Timing Li, 2016. "Integrated Combined Heat and Power System Dispatch Considering Electrical and Thermal Energy Storage," Energies, MDPI, vol. 9(6), pages 1-17, June.
    18. Parhizkar, Tarannom & Mosleh, Ali & Roshandel, Ramin, 2017. "Aging based optimal scheduling framework for power plants using equivalent operating hour approach," Applied Energy, Elsevier, vol. 205(C), pages 1345-1363.
    19. Arash Moradzadeh & Omid Sadeghian & Kazem Pourhossein & Behnam Mohammadi-Ivatloo & Amjad Anvari-Moghaddam, 2020. "Improving Residential Load Disaggregation for Sustainable Development of Energy via Principal Component Analysis," Sustainability, MDPI, vol. 12(8), pages 1-14, April.
    20. Arman Oshnoei & Rahmat Khezri & S. M. Muyeen, 2019. "Model Predictive-Based Secondary Frequency Control Considering Heat Pump Water Heaters," Energies, MDPI, vol. 12(3), pages 1-18, January.
    21. Guanglin Zhang & Yu Cao & Yongsheng Cao & Demin Li & Lin Wang, 2017. "Optimal Energy Management for Microgrids with Combined Heat and Power (CHP) Generation, Energy Storages, and Renewable Energy Sources," Energies, MDPI, vol. 10(9), pages 1-18, August.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Kaiye Gao & Tianshi Wang & Chenjing Han & Jinhao Xie & Ye Ma & Rui Peng, 2021. "A Review of Optimization of Microgrid Operation," Energies, MDPI, vol. 14(10), pages 1-39, May.
    2. Arash Moradzadeh & Sahar Zakeri & Maryam Shoaran & Behnam Mohammadi-Ivatloo & Fazel Mohammadi, 2020. "Short-Term Load Forecasting of Microgrid via Hybrid Support Vector Regression and Long Short-Term Memory Algorithms," Sustainability, MDPI, vol. 12(17), pages 1-17, August.
    3. Sadeghian, Omid & Mohammadpour Shotorbani, Amin & Mohammadi-Ivatloo, Behnam & Sadiq, Rehan & Hewage, Kasun, 2021. "Risk-averse maintenance scheduling of generation units in combined heat and power systems with demand response," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    4. Fausto Pedro García Márquez, 2022. "Special Issue on Advances in Maintenance Management," Energies, MDPI, vol. 15(7), pages 1-4, March.
    5. Mahantesh Marikatti & N. R. Banapurmath & V. S. Yaliwal & Y.H. Basavarajappa & Manzoore Elahi M Soudagar & Fausto Pedro García Márquez & MA Mujtaba & H. Fayaz & Bharat Naik & T.M. Yunus Khan & Asif Af, 2020. "Hydrogen Injection in a Dual Fuel Engine Fueled with Low-Pressure Injection of Methyl Ester of Thevetia Peruviana (METP) for Diesel Engine Maintenance Application," Energies, MDPI, vol. 13(21), pages 1-27, October.
    6. Pavel Y. Gubin & Vladislav P. Oboskalov & Anatolijs Mahnitko & Roman Petrichenko, 2020. "Simulated Annealing, Differential Evolution and Directed Search Methods for Generator Maintenance Scheduling," Energies, MDPI, vol. 13(20), pages 1-26, October.

    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. Sadeghian, Omid & Mohammadpour Shotorbani, Amin & Mohammadi-Ivatloo, Behnam & Sadiq, Rehan & Hewage, Kasun, 2021. "Risk-averse maintenance scheduling of generation units in combined heat and power systems with demand response," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    2. Jingjing Zhai & Xiaobei Wu & Zihao Li & Shaojie Zhu & Bo Yang & Haoming Liu, 2021. "Day-Ahead and Intra-Day Collaborative Optimized Operation among Multiple Energy Stations," Energies, MDPI, vol. 14(4), pages 1-33, February.
    3. Ji, Huichao & Wang, Haixin & Yang, Junyou & Feng, Jiawei & Yang, Yongyue & Okoye, Martin Onyeka, 2021. "Optimal schedule of solid electric thermal storage considering consumer behavior characteristics in combined electricity and heat networks," Energy, Elsevier, vol. 234(C).
    4. Nouri, Alireza & Khodaei, Hossein & Darvishan, Ayda & Sharifian, Seyedmehdi & Ghadimi, Noradin, 2018. "Optimal performance of fuel cell-CHP-battery based micro-grid under real-time energy management: An epsilon constraint method and fuzzy satisfying approach," Energy, Elsevier, vol. 159(C), pages 121-133.
    5. Jun Ye & Rongxiang Yuan, 2017. "Integrated Natural Gas, Heat, and Power Dispatch Considering Wind Power and Power-to-Gas," Sustainability, MDPI, vol. 9(4), pages 1-16, April.
    6. Pavel Atănăsoae, 2022. "Allocation of Joint Costs and Price Setting for Electricity and Heat Generated in Cogeneration," Energies, MDPI, vol. 16(1), pages 1-20, December.
    7. Santos, Maria Izabel & Uturbey, Wadaed, 2018. "A practical model for energy dispatch in cogeneration plants," Energy, Elsevier, vol. 151(C), pages 144-159.
    8. Misaghian, M.S. & Saffari, M. & Kia, M. & Heidari, A. & Shafie-khah, M. & Catalão, J.P.S., 2018. "Tri-level optimization of industrial microgrids considering renewable energy sources, combined heat and power units, thermal and electrical storage systems," Energy, Elsevier, vol. 161(C), pages 396-411.
    9. Valdes, Javier & Poque González, Axel Bastián & Masip Macia, Yunesky & Dorner, Wolfgang & Ramirez Camargo, Luis, 2020. "Unveiling the potential for combined heat and power in Chilean industry - A policy perspective," Energy Policy, Elsevier, vol. 140(C).
    10. Hoseini, Naghi & Sheikholeslami, Abdolreza & Barforoushi, Taghi & Latify, Mohammad Amin, 2020. "Preventive maintenance mid-term scheduling of resources in multi-carrier energy systems," Energy, Elsevier, vol. 197(C).
    11. Oshnoei, Arman & Kheradmandi, Morteza & Blaabjerg, Frede & Hatziargyriou, Nikos D. & Muyeen, S.M. & Anvari-Moghaddam, Amjad, 2022. "Coordinated control scheme for provision of frequency regulation service by virtual power plants," Applied Energy, Elsevier, vol. 325(C).
    12. Salehimaleh, Mohammad & Akbarimajd, Adel & Valipour, Khalil & Dejamkhooy, Abdolmajid, 2018. "Generalized modeling and optimal management of energy hub based electricity, heat and cooling demands," Energy, Elsevier, vol. 159(C), pages 669-685.
    13. Heng Chen & Jidong Xu & Yao Xiao & Zhen Qi & Gang Xu & Yongping Yang, 2018. "An Improved Heating System with Waste Pressure Utilization in a Combined Heat and Power Unit," Energies, MDPI, vol. 11(6), pages 1-20, June.
    14. Liu, Ming & Wang, Shan & Zhao, Yongliang & Tang, Haiyu & Yan, Junjie, 2019. "Heat–power decoupling technologies for coal-fired CHP plants: Operation flexibility and thermodynamic performance," Energy, Elsevier, vol. 188(C).
    15. Ma, Yiming & Wang, Haixin & Hong, Feng & Yang, Junyou & Chen, Zhe & Cui, Haoqian & Feng, Jiawei, 2021. "Modeling and optimization of combined heat and power with power-to-gas and carbon capture system in integrated energy system," Energy, Elsevier, vol. 236(C).
    16. Ksenija Stepanovic & Jichen Wu & Rob Everhardt & Mathijs de Weerdt, 2022. "Unlocking the Flexibility of District Heating Pipeline Energy Storage with Reinforcement Learning," Energies, MDPI, vol. 15(9), pages 1-25, April.
    17. Ali Sulaiman Alsagri & Abdulrahman A. Alrobaian, 2022. "Optimization of Combined Heat and Power Systems by Meta-Heuristic Algorithms: An Overview," Energies, MDPI, vol. 15(16), pages 1-34, August.
    18. Ghasemi-Marzbali, Ali & Shafiei, Mohammad & Ahmadiahangar, Roya, 2023. "Day-ahead economical planning of multi-vector energy district considering demand response program," Applied Energy, Elsevier, vol. 332(C).
    19. Wang, Jiangjiang & Deng, Hongda & Qi, Xiaoling, 2022. "Cost-based site and capacity optimization of multi-energy storage system in the regional integrated energy networks," Energy, Elsevier, vol. 261(PA).
    20. Eid Gul & Giorgio Baldinelli & Pietro Bartocci, 2022. "Energy Transition: Renewable Energy-Based Combined Heat and Power Optimization Model for Distributed Communities," Energies, MDPI, vol. 15(18), pages 1-18, September.

    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:13:y:2020:i:11:p:2840-:d:366694. 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.