IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v373y2024ics0306261924013187.html
   My bibliography  Save this article

Hierarchical optimization of district heating plants by integrating evolutionary and non-linear programming algorithms

Author

Listed:
  • Hassan, Muhammed A.
  • Araji, Mohamad T.

Abstract

In district heating systems, the capacity and types of energy sources, along with their control mechanisms to meet heating demands, are intricately linked. Effective planning must consider financial constraints and system operations, especially with thermal storage. Control methods can significantly influence sizing decisions by adjusting heat production and storage rates across different equipment. Addressing these issues concurrently is essential to maximize cost savings throughout the system's lifespan. This study addresses critical research gaps, such as the lack of integrated bi-level schemes that combine evolutionary and mathematical optimizers while maintaining original non-linear problem formulations. Specifically, it puts forward a novel tri-level optimization framework aimed at minimizing the lifecycle cost (LCC) of district heating plants, powered by a mix of green (solar thermal and biomass) and conventional (gas) heat sources, along with daily thermal storage. The three levels of this scheme are: i) a particle swarm optimizer (PSO) to explore capacities of heat production and storage devices to minimize LCC; ii) an interior-point optimizer (Ipopt) to minimize annual operating costs with explicit operational constraints; and iii) a simulation layer to enhance computational efficiency. Technical suggestions regarding the initialization and early termination of Ipopt to achieve the global optimal solution with reasonable computation time are described in detail. When applied to the multi-source plant, this methodology showed successful and rapid convergence of PSO towards feasible system designs. The study achieved a minimum LCC of 36.34 million USD, corresponding to a levelized cost of heat of 0.0256 USD/kWh, by maximizing green heat sources and using moderate-volume storage. Biomass fuel (74.8%) and capital costs of biomass (8.1%) and solar (7.9%) systems were the primary LCC contributors. Thermal storage enhanced operational flexibility; without it, the gas boiler capacity increased by 112.1 times, and LCC and carbon emissions rose by 3.4% and 106.97%, respectively. In conclusion, the proposed methodology successfully demonstrated substantial cost savings and environmental benefits through strategic renewable energy use and thermal storage, laying the groundwork for its reapplication to more complex system configurations.

Suggested Citation

  • Hassan, Muhammed A. & Araji, Mohamad T., 2024. "Hierarchical optimization of district heating plants by integrating evolutionary and non-linear programming algorithms," Applied Energy, Elsevier, vol. 373(C).
    • Handle: RePEc:eee:appene:v:373:y:2024:i:c:s0306261924013187
    DOI: 10.1016/j.apenergy.2024.123935
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261924013187
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2024.123935?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. Danhong Wang & Jan Carmeliet & Kristina Orehounig, 2021. "Design and Assessment of District Heating Systems with Solar Thermal Prosumers and Thermal Storage," Energies, MDPI, vol. 14(4), pages 1-27, February.
    2. 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.
    3. Ghaemi, Zahra & Tran, Thomas T.D. & Smith, Amanda D., 2022. "Comparing classical and metaheuristic methods to optimize multi-objective operation planning of district energy systems considering uncertainties," Applied Energy, Elsevier, vol. 321(C).
    4. Gabrielli, Paolo & Gazzani, Matteo & Martelli, Emanuele & Mazzotti, Marco, 2018. "Optimal design of multi-energy systems with seasonal storage," Applied Energy, Elsevier, vol. 219(C), pages 408-424.
    5. Arce, Pablo & Medrano, Marc & Gil, Antoni & Oró, Eduard & Cabeza, Luisa F., 2011. "Overview of thermal energy storage (TES) potential energy savings and climate change mitigation in Spain and Europe," Applied Energy, Elsevier, vol. 88(8), pages 2764-2774, August.
    6. Wack, Yannick & Serra, Sylvain & Baelmans, Martine & Reneaume, Jean-Michel & Blommaert, Maarten, 2023. "Nonlinear topology optimization of District Heating Networks: A benchmark of a mixed-integer and a density-based approach," Energy, Elsevier, vol. 278(PB).
    7. Bram van der Heijde & Annelies Vandermeulen & Robbe Salenbien & Lieve Helsen, 2019. "Integrated Optimal Design and Control of Fourth Generation District Heating Networks with Thermal Energy Storage," Energies, MDPI, vol. 12(14), pages 1-34, July.
    8. Leśko, Michał & Bujalski, Wojciech & Futyma, Kamil, 2018. "Operational optimization in district heating systems with the use of thermal energy storage," Energy, Elsevier, vol. 165(PA), pages 902-915.
    9. Michael-Allan Millar & Neil M. Burnside & Zhibin Yu, 2019. "District Heating Challenges for the UK," Energies, MDPI, vol. 12(2), pages 1-21, January.
    10. Ghadimi, P. & Kara, S. & Kornfeld, B., 2014. "The optimal selection of on-site CHP systems through integrated sizing and operational strategy," Applied Energy, Elsevier, vol. 126(C), pages 38-46.
    11. Fiorentini, Massimo & Heer, Philipp & Baldini, Luca, 2023. "Design optimization of a district heating and cooling system with a borehole seasonal thermal energy storage," Energy, Elsevier, vol. 262(PB).
    12. Vesterlund, Mattias & Toffolo, Andrea & Dahl, Jan, 2017. "Optimization of multi-source complex district heating network, a case study," Energy, Elsevier, vol. 126(C), pages 53-63.
    13. 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.
    14. Chiam, Zhonglin & Easwaran, Arvind & Mouquet, David & Fazlollahi, Samira & Millás, Jaume V., 2019. "A hierarchical framework for holistic optimization of the operations of district cooling systems," Applied Energy, Elsevier, vol. 239(C), pages 23-40.
    15. Falke, Tobias & Krengel, Stefan & Meinerzhagen, Ann-Kathrin & Schnettler, Armin, 2016. "Multi-objective optimization and simulation model for the design of distributed energy systems," Applied Energy, Elsevier, vol. 184(C), pages 1508-1516.
    16. Dorotić, Hrvoje & Pukšec, Tomislav & Duić, Neven, 2019. "Economical, environmental and exergetic multi-objective optimization of district heating systems on hourly level for a whole year," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    17. Quanming Zhang & Zhichao Ren & Ruiguang Ma & Ming Tang & Zhongxiao He, 2019. "Research on Double-Layer Optimized Configuration of Multi-Energy Storage in Regional Integrated Energy System with Connected Distributed Wind Power," Energies, MDPI, vol. 12(20), pages 1-16, October.
    18. Régis Delubac & Sylvain Serra & Sabine Sochard & Jean-Michel Reneaume, 2021. "A Dynamic Optimization Tool to Size and Operate Solar Thermal District Heating Networks Production Plants," Energies, MDPI, vol. 14(23), pages 1-27, November.
    19. Morvaj, Boran & Evins, Ralph & Carmeliet, Jan, 2016. "Optimising urban energy systems: Simultaneous system sizing, operation and district heating network layout," Energy, Elsevier, vol. 116(P1), pages 619-636.
    20. Gjoka, Kristian & Rismanchi, Behzad & Crawford, Robert H., 2023. "Fifth-generation district heating and cooling systems: A review of recent advancements and implementation barriers," Renewable and Sustainable Energy Reviews, Elsevier, vol. 171(C).
    21. Ahmadisedigh, Hossein & Gosselin, Louis, 2022. "Combined heating and cooling networks with part-load efficiency curves: Optimization based on energy hub concept," Applied Energy, Elsevier, vol. 307(C).
    22. Chu, Shunzhou & Sethuvenkatraman, Subbu & Goldsworthy, Mark & Yuan, Guofeng, 2022. "Techno-economic assessment of solar assisted precinct level heating systems with seasonal heat storage for Australian cities," Renewable Energy, Elsevier, vol. 201(P1), pages 841-853.
    23. Ciampi, Giovanni & Rosato, Antonio & Sibilio, Sergio, 2018. "Thermo-economic sensitivity analysis by dynamic simulations of a small Italian solar district heating system with a seasonal borehole thermal energy storage," Energy, Elsevier, vol. 143(C), pages 757-771.
    24. Klemm, Christian & Vennemann, Peter, 2021. "Modeling and optimization of multi-energy systems in mixed-use districts: A review of existing methods and approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    25. Alabi, Tobi Michael & Aghimien, Emmanuel I. & Agbajor, Favour D. & Yang, Zaiyue & Lu, Lin & Adeoye, Adebusola R. & Gopaluni, Bhushan, 2022. "A review on the integrated optimization techniques and machine learning approaches for modeling, prediction, and decision making on integrated energy systems," Renewable Energy, Elsevier, vol. 194(C), pages 822-849.
    26. 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).
    27. Joon-Young Kim & Shelly Salim & Jae-Min Cha & Sungho Park, 2019. "Development of Total Capital Investment Estimation Module for Waste Heat Power Plant," Energies, MDPI, vol. 12(8), pages 1-19, April.
    28. Hassan, Muhammed A. & Khalil, Adel & Abubakr, Mohamed, 2021. "Selection methodology of representative meteorological days for assessment of renewable energy systems," Renewable Energy, Elsevier, vol. 177(C), pages 34-51.
    29. Abd Elfadeel, Shehab M. & Amein, Hamza & El-Bakry, M. Medhat & Hassan, Muhammed A., 2021. "Assessment of a multiple port storage tank in a CPC-driven solar process heat system," Renewable Energy, Elsevier, vol. 180(C), pages 860-873.
    30. Verda, Vittorio & Colella, Francesco, 2011. "Primary energy savings through thermal storage in district heating networks," Energy, Elsevier, vol. 36(7), pages 4278-4286.
    31. Dalla Rosa, A. & Boulter, R. & Church, K. & Svendsen, S., 2012. "District heating (DH) network design and operation toward a system-wide methodology for optimizing renewable energy solutions (SMORES) in Canada: A case study," Energy, Elsevier, vol. 45(1), pages 960-974.
    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. 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).
    2. Golmohamadi, Hessam & Larsen, Kim Guldstrand & Jensen, Peter Gjøl & Hasrat, Imran Riaz, 2022. "Integration of flexibility potentials of district heating systems into electricity markets: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    3. Dorotić, Hrvoje & Pukšec, Tomislav & Schneider, Daniel Rolph & Duić, Neven, 2021. "Evaluation of district heating with regard to individual systems – Importance of carbon and cost allocation in cogeneration units," Energy, Elsevier, vol. 221(C).
    4. Guelpa, Elisa & Bischi, Aldo & Verda, Vittorio & Chertkov, Michael & Lund, Henrik, 2019. "Towards future infrastructures for sustainable multi-energy systems: A review," Energy, Elsevier, vol. 184(C), pages 2-21.
    5. Fonseca, Juan D. & Commenge, Jean-Marc & Camargo, Mauricio & Falk, Laurent & Gil, Iván D., 2021. "Sustainability analysis for the design of distributed energy systems: A multi-objective optimization approach," Applied Energy, Elsevier, vol. 290(C).
    6. van der Heijde, Bram & Vandermeulen, Annelies & Salenbien, Robbe & Helsen, Lieve, 2019. "Representative days selection for district energy system optimisation: a solar district heating system with seasonal storage," Applied Energy, Elsevier, vol. 248(C), pages 79-94.
    7. Song, William Hasung & Wang, Yang & Gillich, Aaron & Ford, Andy & Hewitt, Mark, 2019. "Modelling development and analysis on the Balanced Energy Networks (BEN) in London," Applied Energy, Elsevier, vol. 233, pages 114-125.
    8. Fonseca, Juan D. & Commenge, Jean-Marc & Camargo, Mauricio & Falk, Laurent & Gil, Iván D., 2021. "Multi-criteria optimization for the design and operation of distributed energy systems considering sustainability dimensions," Energy, Elsevier, vol. 214(C).
    9. Mengting Jiang & Camilo Rindt & David M. J. Smeulders, 2022. "Optimal Planning of Future District Heating Systems—A Review," Energies, MDPI, vol. 15(19), pages 1-38, September.
    10. Guelpa, Elisa & Verda, Vittorio, 2019. "Thermal energy storage in district heating and cooling systems: A review," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    11. Salenbien, R. & Wack, Y. & Baelmans, M. & Blommaert, M., 2023. "Geographically informed automated non-linear topology optimization of district heating networks," Energy, Elsevier, vol. 283(C).
    12. Simeoni, Patrizia & Ciotti, Gellio & Cottes, Mattia & Meneghetti, Antonella, 2019. "Integrating industrial waste heat recovery into sustainable smart energy systems," Energy, Elsevier, vol. 175(C), pages 941-951.
    13. Wack, Yannick & Sollich, Martin & Salenbien, Robbe & Diriken, Jan & Baelmans, Martine & Blommaert, Maarten, 2024. "A multi-period topology and design optimization approach for district heating networks," Applied Energy, Elsevier, vol. 367(C).
    14. Friebe, Maximilian & Karasu, Arda & Kriegel, Martin, 2023. "Methodology to compare and optimize district heating and decentralized heat supply for energy transformation on a municipality level," Energy, Elsevier, vol. 282(C).
    15. Li, Ximei & Gao, Jianmin & Chen, Bingyuan & You, Shi & Zheng, Yi & Du, Qian & Qin, Yukun, 2023. "Multi-objective optimization of district heating systems with turbine-driving fans and pumps considering economic, exergic, and environmental aspects," Energy, Elsevier, vol. 277(C).
    16. Kachirayil, Febin & Weinand, Jann Michael & Scheller, Fabian & McKenna, Russell, 2022. "Reviewing local and integrated energy system models: insights into flexibility and robustness challenges," Applied Energy, Elsevier, vol. 324(C).
    17. 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).
    18. Østergaard, P.A. & Lund, H. & Thellufsen, J.Z. & Sorknæs, P. & Mathiesen, B.V., 2022. "Review and validation of EnergyPLAN," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    19. Aunedi, Marko & Pantaleo, Antonio Marco & Kuriyan, Kamal & Strbac, Goran & Shah, Nilay, 2020. "Modelling of national and local interactions between heat and electricity networks in low-carbon energy systems," Applied Energy, Elsevier, vol. 276(C).
    20. Xiaoxia Li & Husheng Qiu & Zhifeng Wang & Jinping Li & Guobin Yuan & Xiao Guo & Lifeng Jin, 2023. "Numerical Investigation of a Solar-Heating System with Solar-Tower Receiver and Seasonal Storage in Northern China: Dynamic Performance Assessment and Operation Strategy Analysis," Energies, MDPI, vol. 16(14), pages 1-27, July.

    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:appene:v:373:y:2024:i:c:s0306261924013187. 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.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.