IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v140y2017ip1p466-480.html
   My bibliography  Save this article

Effects of environmental emissions on optimal combination and allocation of renewable and non-renewable CHP technologies in heat and electricity distribution networks based on improved particle swarm optimization algorithm

Author

Listed:
  • Arandian, B.
  • Ardehali, M.M.

Abstract

Combined heat and power (CHP) units are efficient from view point of source energy, however, for maximum utility company economic profit, it is necessary to account for all revenues and expenditures. The goal of this study is to examine the effects of considerations for environmental emissions in optimal combination and allocation of renewable and non-renewable CHP technologies including fuel cells (FC), internal combustion engines (ICE), and micro turbine (MT) in heat and electricity distribution networks based on improved particle swarm optimization algorithm, where the economic profit of utility company as the CHP owner and operator is maximized over the operation horizon. When all three technologies are available, the optimal combination and allocation results show that FC-CHP and MT-CHP are the preferred technologies and, the environmental emission costs do not allow for ICE-CHP technology to be included in the combination and, the yearly utility company economic profit is increased by 10.39, 28.37, and 13.95% due to optimal combination and allocation of CHP units in comparison with optimal allocation of FC, ICE, and MT technologies on individual basis, respectively. Also, by analyzing various HPRs, it is determined that the yearly utility company economic profit is increased when HPR is decreased.

Suggested Citation

  • Arandian, B. & Ardehali, M.M., 2017. "Effects of environmental emissions on optimal combination and allocation of renewable and non-renewable CHP technologies in heat and electricity distribution networks based on improved particle swarm ," Energy, Elsevier, vol. 140(P1), pages 466-480.
    • Handle: RePEc:eee:energy:v:140:y:2017:i:p1:p:466-480
    DOI: 10.1016/j.energy.2017.08.101
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544217314767
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2017.08.101?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ardakani, F.J. & Ardehali, M.M., 2014. "Long-term electrical energy consumption forecasting for developing and developed economies based on different optimized models and historical data types," Energy, Elsevier, vol. 65(C), pages 452-461.
    2. Vögelin, Philipp & Koch, Ben & Georges, Gil & Boulouchos, Konstatinos, 2017. "Heuristic approach for the economic optimisation of combined heat and power (CHP) plants: Operating strategy, heat storage and power," Energy, Elsevier, vol. 121(C), pages 66-77.
    3. Niknam, Taher & Meymand, Hamed Zeinoddini & Mojarrad, Hasan Doagou, 2011. "An efficient algorithm for multi-objective optimal operation management of distribution network considering fuel cell power plants," Energy, Elsevier, vol. 36(1), pages 119-132.
    4. Wang, Haichao & Yin, Wusong & Abdollahi, Elnaz & Lahdelma, Risto & Jiao, Wenling, 2015. "Modelling and optimization of CHP based district heating system with renewable energy production and energy storage," Applied Energy, Elsevier, vol. 159(C), pages 401-421.
    5. Wang, Yun & Chen, Ken S. & Mishler, Jeffrey & Cho, Sung Chan & Adroher, Xavier Cordobes, 2011. "A review of polymer electrolyte membrane fuel cells: Technology, applications, and needs on fundamental research," Applied Energy, Elsevier, vol. 88(4), pages 981-1007, April.
    6. Meybodi, Mehdi Aghaei & Behnia, Masud, 2011. "Impact of carbon tax on internal combustion engine size selection in a medium scale CHP system," Applied Energy, Elsevier, vol. 88(12), pages 5153-5163.
    7. Zhang, Di & Evangelisti, Sara & Lettieri, Paola & Papageorgiou, Lazaros G., 2015. "Optimal design of CHP-based microgrids: Multiobjective optimisation and life cycle assessment," Energy, Elsevier, vol. 85(C), pages 181-193.
    8. Ebrahim Farjah & Mosayeb Bornapour & Taher Niknam & Bahman Bahmanifirouzi, 2012. "Placement of Combined Heat, Power and Hydrogen Production Fuel Cell Power Plants in a Distribution Network," Energies, MDPI, vol. 5(3), pages 1-25, March.
    9. Gharavi, H. & Ardehali, M.M. & Ghanbari-Tichi, S., 2015. "Imperial competitive algorithm optimization of fuzzy multi-objective design of a hybrid green power system with considerations for economics, reliability, and environmental emissions," Renewable Energy, Elsevier, vol. 78(C), pages 427-437.
    10. Nazari, M.E. & Ardehali, M.M., 2017. "Profit-based unit commitment of integrated CHP-thermal-heat only units in energy and spinning reserve markets with considerations for environmental CO2 emission cost and valve-point effects," Energy, Elsevier, vol. 133(C), pages 621-635.
    11. Tichi, S.G. & Ardehali, M.M. & Nazari, M.E., 2010. "Examination of energy price policies in Iran for optimal configuration of CHP and CCHP systems based on particle swarm optimization algorithm," Energy Policy, Elsevier, vol. 38(10), pages 6240-6250, October.
    12. Sharifi Asl, S.M. & Rowshanzamir, S. & Eikani, M.H., 2010. "Modelling and simulation of the steady-state and dynamic behaviour of a PEM fuel cell," Energy, Elsevier, vol. 35(4), pages 1633-1646.
    13. Stern, Jonathan, 2014. "International gas pricing in Europe and Asia: A crisis of fundamentals," Energy Policy, Elsevier, vol. 64(C), pages 43-48.
    14. Wang, Jiangjiang & Zhai, Zhiqiang (John) & Jing, Youyin & Zhang, Xutao & Zhang, Chunfa, 2011. "Sensitivity analysis of optimal model on building cooling heating and power system," Applied Energy, Elsevier, vol. 88(12), pages 5143-5152.
    15. Franco, Alessandro & Versace, Michele, 2017. "Optimum sizing and operational strategy of CHP plant for district heating based on the use of composite indicators," Energy, Elsevier, vol. 124(C), pages 258-271.
    16. Carpaneto, E. & Lazzeroni, P. & Repetto, M., 2015. "Optimal integration of solar energy in a district heating network," Renewable Energy, Elsevier, vol. 75(C), pages 714-721.
    17. Elmer, Theo & Worall, Mark & Wu, Shenyi & Riffat, Saffa B., 2015. "Fuel cell technology for domestic built environment applications: State of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 913-931.
    18. Sadeghian, H.R. & Ardehali, M.M., 2016. "A novel approach for optimal economic dispatch scheduling of integrated combined heat and power systems for maximum economic profit and minimum environmental emissions based on Benders decomposition," Energy, Elsevier, vol. 102(C), pages 10-23.
    19. Buoro, Dario & Pinamonti, Piero & Reini, Mauro, 2014. "Optimization of a Distributed Cogeneration System with solar district heating," Applied Energy, Elsevier, vol. 124(C), pages 298-308.
    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. Noussan, Michel & Jarre, Matteo & Roberto, Roberta & Russolillo, Daniele, 2018. "Combined vs separate heat and power production – Primary energy comparison in high renewable share contexts," Applied Energy, Elsevier, vol. 213(C), pages 1-10.
    2. 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.
    3. Ahmad Baroutaji & Arun Arjunan & John Robinson & Tabbi Wilberforce & Mohammad Ali Abdelkareem & Abdul Ghani Olabi, 2021. "PEMFC Poly-Generation Systems: Developments, Merits, and Challenges," Sustainability, MDPI, vol. 13(21), pages 1-31, October.
    4. Sun, Jingqi & Ruze, Nuermaimaiti & Zhang, Jianjun & Shi, Jing & Shen, Boyang, 2021. "Capacity planning and optimization for integrated energy system in industrial park considering environmental externalities," Renewable Energy, Elsevier, vol. 167(C), pages 56-65.
    5. Yadegari, Saeed & Abdi, Hamdi & Nikkhah, Saman, 2020. "Risk-averse multi-objective optimal combined heat and power planning considering voltage security constraints," Energy, Elsevier, vol. 212(C).
    6. Zhang, Yan & Meng, Fanlin & Wang, Rui & Kazemtabrizi, Behzad & Shi, Jianmai, 2019. "Uncertainty-resistant stochastic MPC approach for optimal operation of CHP microgrid," Energy, Elsevier, vol. 179(C), pages 1265-1278.
    7. Arul Rajagopalan & Dhivya Swaminathan & Meshal Alharbi & Sudhakar Sengan & Oscar Danilo Montoya & Walid El-Shafai & Mostafa M. Fouda & Moustafa H. Aly, 2022. "Modernized Planning of Smart Grid Based on Distributed Power Generations and Energy Storage Systems Using Soft Computing Methods," Energies, MDPI, vol. 15(23), pages 1-18, November.
    8. Kwan, Trevor Hocksun & Shen, Yongting & Yao, Qinghe, 2019. "An energy management strategy for supplying combined heat and power by the fuel cell thermoelectric hybrid system," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    9. Lorestani, A. & Ardehali, M.M., 2018. "Optimization of autonomous combined heat and power system including PVT, WT, storages, and electric heat utilizing novel evolutionary particle swarm optimization algorithm," Renewable Energy, Elsevier, vol. 119(C), pages 490-503.

    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. Pizzolato, Alberto & Sciacovelli, Adriano & Verda, Vittorio, 2019. "Centralized control of district heating networks during failure events using discrete adjoint sensitivities," Energy, Elsevier, vol. 184(C), pages 58-72.
    2. Chaduvula, Hemanth & Das, Debapriya, 2023. "Analysis of microgrid configuration with optimal power injection from grid using point estimate method embedded fuzzy-particle swarm optimization," Energy, Elsevier, vol. 282(C).
    3. Romanchenko, Dmytro & Odenberger, Mikael & Göransson, Lisa & Johnsson, Filip, 2017. "Impact of electricity price fluctuations on the operation of district heating systems: A case study of district heating in Göteborg, Sweden," Applied Energy, Elsevier, vol. 204(C), pages 16-30.
    4. Isa, Normazlina Mat & Tan, Chee Wei & Yatim, A.H.M., 2018. "A comprehensive review of cogeneration system in a microgrid: A perspective from architecture and operating system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2236-2263.
    5. Olamaei, Javad & Nazari, Mohammad Esmaeil & Bahravar, Sepideh, 2018. "Economic environmental unit commitment for integrated CCHP-thermal-heat only system with considerations for valve-point effect based on a heuristic optimization algorithm," Energy, Elsevier, vol. 159(C), pages 737-750.
    6. Atabay, Dennis, 2017. "An open-source model for optimal design and operation of industrial energy systems," Energy, Elsevier, vol. 121(C), pages 803-821.
    7. Naderipour, Amirreza & Abdul-Malek, Zulkurnain & Nowdeh, Saber Arabi & Ramachandaramurthy, Vigna K. & Kalam, Akhtar & Guerrero, Josep M., 2020. "Optimal allocation for combined heat and power system with respect to maximum allowable capacity for reduced losses and improved voltage profile and reliability of microgrids considering loading condi," Energy, Elsevier, vol. 196(C).
    8. Ondeck, Abigail D. & Edgar, Thomas F. & Baldea, Michael, 2018. "Impact of rooftop photovoltaics and centralized energy storage on the design and operation of a residential CHP system," Applied Energy, Elsevier, vol. 222(C), pages 280-299.
    9. Paiho, Satu & Reda, Francesco, 2016. "Towards next generation district heating in Finland," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 915-924.
    10. Volpe, R. & Catrini, P. & Piacentino, A. & Fichera, A., 2022. "An agent-based model to support the preliminary design and operation of heating and power grids with cogeneration units and photovoltaic panels in densely populated areas," Energy, Elsevier, vol. 261(PB).
    11. Wang, Yang & Zhang, Shanhong & Chow, David & Kuckelkorn, Jens M., 2021. "Evaluation and optimization of district energy network performance: Present and future," Renewable and Sustainable Energy Reviews, Elsevier, vol. 139(C).
    12. Min-Hwi Kim & Dong-Won Lee & Deuk-Won Kim & Young-Sub An & Jae-Ho Yun, 2021. "Energy Performance Investigation of Bi-Directional Convergence Energy Prosumers for an Energy Sharing Community," Energies, MDPI, vol. 14(17), pages 1-17, September.
    13. Najafi, Arsalan & Falaghi, Hamid & Contreras, Javier & Ramezani, Maryam, 2016. "Medium-term energy hub management subject to electricity price and wind uncertainty," Applied Energy, Elsevier, vol. 168(C), pages 418-433.
    14. Luca Urbanucci & Francesco D’Ettorre & Daniele Testi, 2019. "A Comprehensive Methodology for the Integrated Optimal Sizing and Operation of Cogeneration Systems with Thermal Energy Storage," Energies, MDPI, vol. 12(5), pages 1-17, March.
    15. Zare, Mohsen & Niknam, Taher, 2013. "A new multi-objective for environmental and economic management of Volt/Var Control considering renewable energy resources," Energy, Elsevier, vol. 55(C), pages 236-252.
    16. Zheng, Yingying & Jenkins, Bryan M. & Kornbluth, Kurt & Træholt, Chresten, 2018. "Optimization under uncertainty of a biomass-integrated renewable energy microgrid with energy storage," Renewable Energy, Elsevier, vol. 123(C), pages 204-217.
    17. Sun, Zhe & Wang, Ning & Bi, Yunrui & Srinivasan, Dipti, 2015. "Parameter identification of PEMFC model based on hybrid adaptive differential evolution algorithm," Energy, Elsevier, vol. 90(P2), pages 1334-1341.
    18. Ito, Masakazu & Takano, Akihisa & Shinji, Takao & Yagi, Takahiro & Hayashi, Yasuhiro, 2017. "Electricity adjustment for capacity market auction by a district heating and cooling system," Applied Energy, Elsevier, vol. 206(C), pages 623-633.
    19. Gimelli, A. & Mottola, F. & Muccillo, M. & Proto, D. & Amoresano, A. & Andreotti, A. & Langella, G., 2019. "Optimal configuration of modular cogeneration plants integrated by a battery energy storage system providing peak shaving service," Applied Energy, Elsevier, vol. 242(C), pages 974-993.
    20. Ignacio Blanco & Daniela Guericke & Anders N. Andersen & Henrik Madsen, 2018. "Operational Planning and Bidding for District Heating Systems with Uncertain Renewable Energy Production," Energies, MDPI, vol. 11(12), pages 1-26, November.

    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:eee:energy:v:140:y:2017:i:p1:p:466-480. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    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.