IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v256y2022ics0360544222014803.html
   My bibliography  Save this article

Optimisation of energy usage and carbon emissions monitoring using MILP for an advanced anaerobic digester plant

Author

Listed:
  • Laing, Harry
  • O'Malley, Chris
  • Browne, Anthony
  • Rutherford, Tony
  • Baines, Tony
  • Moore, Andrew
  • Black, Ken
  • Willis, Mark J.

Abstract

This paper proposes a realistic model for energy and carbon management of an advanced municipal wastewater treatment works. Through minimisation of total cost of operations, it provides operators with a visual daily operational schedule based on varying tariffs. This site is the first in the UK with a mixed operational strategy for biomethane produced on site: to burn in CHP (Combined Heat and Power) engines to create electricity, burn in Steam Boilers for onsite steam use or inject the biomethane into the gas distribution network - Natural Gas can be imported to make up shortfalls in biomethane if required. Implemented using a novel mixed integer linear programming (MILP) approach, results indicate that biomethane injection should be maximised for the highest financial gain - the driving force for optimising the remaining operations being the site electricity imports and whether the electricity imported ‘generates’ carbon emissions. Based on the source of electricity and the new carbon emissions performance criteria, under the current operational strategy importing electricity from carbon-based sources has no tangible impact on site revenues (but does impact CO2 emissions), however carbon free (renewable) electricity sources could see shift in operations leading a revenue increase of 12%

Suggested Citation

  • Laing, Harry & O'Malley, Chris & Browne, Anthony & Rutherford, Tony & Baines, Tony & Moore, Andrew & Black, Ken & Willis, Mark J., 2022. "Optimisation of energy usage and carbon emissions monitoring using MILP for an advanced anaerobic digester plant," Energy, Elsevier, vol. 256(C).
  • Handle: RePEc:eee:energy:v:256:y:2022:i:c:s0360544222014803
    DOI: 10.1016/j.energy.2022.124577
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544222014803
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2022.124577?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. Kelley, Morgan T. & Pattison, Richard C. & Baldick, Ross & Baldea, Michael, 2018. "An MILP framework for optimizing demand response operation of air separation units," Applied Energy, Elsevier, vol. 222(C), pages 951-966.
    2. Kopanos, Georgios M. & Georgiadis, Michael C. & Pistikopoulos, Efstratios N., 2013. "Energy production planning of a network of micro combined heat and power generators," Applied Energy, Elsevier, vol. 102(C), pages 1522-1534.
    3. Monfared, Houman Jamshidi & Ghasemi, Ahmad & Loni, Abdolah & Marzband, Mousa, 2019. "A hybrid price-based demand response program for the residential micro-grid," Energy, Elsevier, vol. 185(C), pages 274-285.
    4. Longo, Stefano & d’Antoni, Benedetto Mirko & Bongards, Michael & Chaparro, Antonio & Cronrath, Andreas & Fatone, Francesco & Lema, Juan M. & Mauricio-Iglesias, Miguel & Soares, Ana & Hospido, Almudena, 2016. "Monitoring and diagnosis of energy consumption in wastewater treatment plants. A state of the art and proposals for improvement," Applied Energy, Elsevier, vol. 179(C), pages 1251-1268.
    5. Ali, Syed Muhammad Hassan & Lenzen, Manfred & Sack, Fabian & Yousefzadeh, Moslem, 2020. "Electricity generation and demand flexibility in wastewater treatment plants: Benefits for 100% renewable electricity grids," Applied Energy, Elsevier, vol. 268(C).
    6. Theo, Wai Lip & Lim, Jeng Shiun & Wan Alwi, Sharifah Rafidah & Mohammad Rozali, Nor Erniza & Ho, Wai Shin & Abdul-Manan, Zainuddin, 2016. "An MILP model for cost-optimal planning of an on-grid hybrid power system for an eco-industrial park," Energy, Elsevier, vol. 116(P2), pages 1423-1441.
    7. Christodoulos Floudas & Xiaoxia Lin, 2005. "Mixed Integer Linear Programming in Process Scheduling: Modeling, Algorithms, and Applications," Annals of Operations Research, Springer, vol. 139(1), pages 131-162, October.
    8. Adamson, Richard & Hobbs, Martin & Silcock, Andy & Willis, Mark J., 2017. "Steady-state optimisation of a multiple cryogenic air separation unit and compressor plant," Applied Energy, Elsevier, vol. 189(C), pages 221-232.
    9. van Goor, Harm & Scholtens, Bert, 2014. "Modeling natural gas price volatility: The case of the UK gas market," Energy, Elsevier, vol. 72(C), pages 126-134.
    10. Hong, Xiaodong & Liao, Zuwei & Jiang, Binbo & Wang, Jingdai & Yang, Yongrong, 2017. "Targeting of heat integrated water allocation networks by one-step MILP formulation," Applied Energy, Elsevier, vol. 197(C), pages 254-269.
    11. Silvente, Javier & Papageorgiou, Lazaros G., 2017. "An MILP formulation for the optimal management of microgrids with task interruptions," Applied Energy, Elsevier, vol. 206(C), pages 1131-1146.
    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. Che, Gelegen & Zhang, Yanyan & Tang, Lixin & Zhao, Shengnan, 2023. "A deep reinforcement learning based multi-objective optimization for the scheduling of oxygen production system in integrated iron and steel plants," Applied Energy, Elsevier, vol. 345(C).
    2. Rosa M. Llácer-Iglesias & P. Amparo López-Jiménez & Modesto Pérez-Sánchez, 2021. "Energy Self-Sufficiency Aiming for Sustainable Wastewater Systems: Are All Options Being Explored?," Sustainability, MDPI, vol. 13(10), pages 1-20, May.
    3. Li, Bei & Roche, Robin & Paire, Damien & Miraoui, Abdellatif, 2018. "Optimal sizing of distributed generation in gas/electricity/heat supply networks," Energy, Elsevier, vol. 151(C), pages 675-688.
    4. Zhang, Liu & Zheng, Zhong & Chai, Yi & Xu, Zhaojun & Zhang, Kaitian & Liu, Yu & Chen, Sujun & Zhao, Liuqiang, 2023. "ASU model with multiple adjustment types for oxygen scheduling concerning pipe pressure safety in steel enterprises," Applied Energy, Elsevier, vol. 343(C).
    5. Francesco Liberati & Alessandro Di Giorgio, 2017. "Economic Model Predictive and Feedback Control of a Smart Grid Prosumer Node," Energies, MDPI, vol. 11(1), pages 1-23, December.
    6. Otashu, Joannah I. & Baldea, Michael, 2020. "Scheduling chemical processes for frequency regulation," Applied Energy, Elsevier, vol. 260(C).
    7. Liu, Qipeng & Li, Ran & Dereli, Recep Kaan & Flynn, Damian & Casey, Eoin, 2022. "Water resource recovery facilities as potential energy generation units and their dynamic economic dispatch," Applied Energy, Elsevier, vol. 318(C).
    8. Qi, Meng & Park, Jinwoo & Lee, Inkyu & Moon, Il, 2022. "Liquid air as an emerging energy vector towards carbon neutrality: A multi-scale systems perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    9. Wang, Dongxiao & Qiu, Jing & Reedman, Luke & Meng, Ke & Lai, Loi Lei, 2018. "Two-stage energy management for networked microgrids with high renewable penetration," Applied Energy, Elsevier, vol. 226(C), pages 39-48.
    10. Fu, Xueqian & Guo, Qinglai & Sun, Hongbin & Pan, Zhaoguang & Xiong, Wen & Wang, Li, 2017. "Typical scenario set generation algorithm for an integrated energy system based on the Wasserstein distance metric," Energy, Elsevier, vol. 135(C), pages 153-170.
    11. Misund, Bård & Oglend, Atle, 2016. "Supply and demand determinants of natural gas price volatility in the U.K.: A vector autoregression approach," Energy, Elsevier, vol. 111(C), pages 178-189.
    12. Ahmadi, Seyed Ehsan & Sadeghi, Delnia & Marzband, Mousa & Abusorrah, Abdullah & Sedraoui, Khaled, 2022. "Decentralized bi-level stochastic optimization approach for multi-agent multi-energy networked micro-grids with multi-energy storage technologies," Energy, Elsevier, vol. 245(C).
    13. Romero-Quete, David & Garcia, Javier Rosero, 2019. "An affine arithmetic-model predictive control approach for optimal economic dispatch of combined heat and power microgrids," Applied Energy, Elsevier, vol. 242(C), pages 1436-1447.
    14. Kong, Karen Gah Hie & How, Bing Shen & Lim, Juin Yau & Leong, Wei Dong & Teng, Sin Yong & Ng, Wendy Pei Qin & Moser, Irene & Sunarso, Jaka, 2022. "Shaving electric bills with renewables? A multi-period pinch-based methodology for energy planning," Energy, Elsevier, vol. 239(PD).
    15. Lara, Cristiana L. & Koenemann, Jochen & Nie, Yisu & de Souza, Cid C., 2023. "Scalable timing-aware network design via lagrangian decomposition," European Journal of Operational Research, Elsevier, vol. 309(1), pages 152-169.
    16. Yi, Zonggen & Luo, Yusheng & Westover, Tyler & Katikaneni, Sravya & Ponkiya, Binaka & Sah, Suba & Mahmud, Sadab & Raker, David & Javaid, Ahmad & Heben, Michael J. & Khanna, Raghav, 2022. "Deep reinforcement learning based optimization for a tightly coupled nuclear renewable integrated energy system," Applied Energy, Elsevier, vol. 328(C).
    17. Andrea G. Capodaglio & Gustaf Olsson, 2019. "Energy Issues in Sustainable Urban Wastewater Management: Use, Demand Reduction and Recovery in the Urban Water Cycle," Sustainability, MDPI, vol. 12(1), pages 1-17, December.
    18. Maktabifard, Mojtaba & Al-Hazmi, Hussein E. & Szulc, Paulina & Mousavizadegan, Mohammad & Xu, Xianbao & Zaborowska, Ewa & Li, Xiang & Mąkinia, Jacek, 2023. "Net-zero carbon condition in wastewater treatment plants: A systematic review of mitigation strategies and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 185(C).
    19. Yanina Fumero & Gabriela Corsano & Jorge Montagna, 2012. "Planning and scheduling of multistage multiproduct batch plants operating under production campaigns," Annals of Operations Research, Springer, vol. 199(1), pages 249-268, October.
    20. Yu Liu & Shan Gao & Xin Zhao & Chao Zhang & Ningyu Zhang, 2017. "Coordinated Operation and Control of Combined Electricity and Natural Gas Systems with Thermal Storage," Energies, MDPI, vol. 10(7), pages 1-25, 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:energy:v:256:y:2022:i:c:s0360544222014803. 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.