IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i4p1307-d747006.html
   My bibliography  Save this article

A Methodological Proposal for Implementing Demand-Shifting Strategies in the Wholesale Electricity Market

Author

Listed:
  • Máximo A. Domínguez-Garabitos

    (Basic Sciences, Instituto Tecnológico de Santo Domingo, Santo Domingo 10602, Dominican Republic)

  • Víctor S. Ocaña-Guevara

    (Basic Sciences, Instituto Tecnológico de Santo Domingo, Santo Domingo 10602, Dominican Republic
    Centre for Energy Studies and Environmental Technologies (CEETA), Carretera a Camajuaní Km 5 1/2, Universidad Central “Marta Abreu” de Las Villas, Villa Clara 50100, Cuba)

  • Félix Santos-García

    (Basic Sciences, Instituto Tecnológico de Santo Domingo, Santo Domingo 10602, Dominican Republic
    Centre for Energy Studies and Environmental Technologies (CEETA), Carretera a Camajuaní Km 5 1/2, Universidad Central “Marta Abreu” de Las Villas, Villa Clara 50100, Cuba)

  • Adriana Arango-Manrique

    (Department of Electrical and Electronic Engineering, Universidad del Norte, Barranquilla 080001, Colombia)

  • Miguel Aybar-Mejía

    (Engineering Area, Instituto Tecnológico de Santo Domingo, Santo Domingo 10602, Dominican Republic)

Abstract

The energy transition has shown that fossil generation can be complemented with renewable energy and other resources capable of providing flexibility to the energy system’s operation, in compliance with the wholesale electricity market’s rules. This paper proposes a market-based methodology for introducing flexible demand in the energy dispatch, optimizing the scheduling of electricity system operation in the short-term, and considers the challenge of implementing an incentive scheme for participants in demand-response programs. The scheme includes the criteria of the elasticity of substitution and a renewable energy quota. This methodology is focused on a strategic demand shift to minimize the cost of supply; increase the dispatch of renewable energy; control CO 2 emissions; and satisfy the generation, demand, and transmission operating constraints. These conditions encourage the development of a simulation tool that allows a sensitivity analysis to aid decision-making by operators and agents. The proposed methodology optimizes the operational cost of generation supply and specific performance indicators to determine the percentages of demand shift, the amount of CO 2 emissions, the ratio of unserved power, the demand benefits obtained from an incentive scheme, and the natural market behavior.

Suggested Citation

  • Máximo A. Domínguez-Garabitos & Víctor S. Ocaña-Guevara & Félix Santos-García & Adriana Arango-Manrique & Miguel Aybar-Mejía, 2022. "A Methodological Proposal for Implementing Demand-Shifting Strategies in the Wholesale Electricity Market," Energies, MDPI, vol. 15(4), pages 1-28, February.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:4:p:1307-:d:747006
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/4/1307/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/15/4/1307/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Brown, Marilyn A. & Chapman, Oliver, 2021. "The size, causes, and equity implications of the demand-response gap," Energy Policy, Elsevier, vol. 158(C).
    2. Chinmoy, Lakshmi & Iniyan, S. & Goic, Ranko, 2019. "Modeling wind power investments, policies and social benefits for deregulated electricity market – A review," Applied Energy, Elsevier, vol. 242(C), pages 364-377.
    3. Abdulla Kaya & Denes Csala & Sgouris Sgouridis, 2017. "Constant elasticity of substitution functions for energy modeling in general equilibrium integrated assessment models: a critical review and recommendations," Climatic Change, Springer, vol. 145(1), pages 27-40, November.
    4. Yu, Mengmeng & Hong, Seung Ho, 2017. "Incentive-based demand response considering hierarchical electricity market: A Stackelberg game approach," Applied Energy, Elsevier, vol. 203(C), pages 267-279.
    5. Xu, Bo & Wang, Jiexin & Guo, Mengyuan & Lu, Jiayu & Li, Gehui & Han, Liang, 2021. "A hybrid demand response mechanism based on real-time incentive and real-time pricing," Energy, Elsevier, vol. 231(C).
    6. Gils, Hans Christian, 2014. "Assessment of the theoretical demand response potential in Europe," Energy, Elsevier, vol. 67(C), pages 1-18.
    7. Zha, Donglan & Kavuri, Anil Savio & Si, Songjian, 2017. "Energy biased technology change: Focused on Chinese energy-intensive industries," Applied Energy, Elsevier, vol. 190(C), pages 1081-1089.
    8. Cruz, Marco R.M. & Fitiwi, Desta Z. & Santos, Sérgio F. & Catalão, João P.S., 2018. "A comprehensive survey of flexibility options for supporting the low-carbon energy future," Renewable and Sustainable Energy Reviews, Elsevier, vol. 97(C), pages 338-353.
    9. Ghadi, Mojtaba Jabbari & Rajabi, Amin & Ghavidel, Sahand & Azizivahed, Ali & Li, Li & Zhang, Jiangfeng, 2019. "From active distribution systems to decentralized microgrids: A review on regulations and planning approaches based on operational factors," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    10. Paul E. Brockway & Matthew K. Heun & João Santos & John R. Barrett, 2017. "Energy-Extended CES Aggregate Production: Current Aspects of Their Specification and Econometric Estimation," Energies, MDPI, vol. 10(2), pages 1-23, February.
    11. Khan, Agha Salman M. & Verzijlbergh, Remco A. & Sakinci, Ozgur Can & De Vries, Laurens J., 2018. "How do demand response and electrical energy storage affect (the need for) a capacity market?," Applied Energy, Elsevier, vol. 214(C), pages 39-62.
    12. Meyabadi, A. Fattahi & Deihimi, M.H., 2017. "A review of demand-side management: Reconsidering theoretical framework," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 367-379.
    13. Arnette, Andrew & Zobel, Christopher W., 2012. "An optimization model for regional renewable energy development," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(7), pages 4606-4615.
    14. Pallonetto, Fabiano & De Rosa, Mattia & Milano, Federico & Finn, Donal P., 2019. "Demand response algorithms for smart-grid ready residential buildings using machine learning models," Applied Energy, Elsevier, vol. 239(C), pages 1265-1282.
    15. Klarin Tomislav, 2018. "The Concept of Sustainable Development: From its Beginning to the Contemporary Issues," Zagreb International Review of Economics and Business, Faculty of Economics and Business, University of Zagreb, vol. 21(1), pages 67-94, May.
    16. Lynch, Muireann Á. & Nolan, Sheila & Devine, Mel T. & O’Malley, Mark, 2019. "The impacts of demand response participation in capacity markets," Applied Energy, Elsevier, vol. 250(C), pages 444-451.
    17. Neves, Diana & Pina, André & Silva, Carlos A., 2015. "Demand response modeling: A comparison between tools," Applied Energy, Elsevier, vol. 146(C), pages 288-297.
    18. Kwon, Pil Seok & Østergaard, Poul, 2014. "Assessment and evaluation of flexible demand in a Danish future energy scenario," Applied Energy, Elsevier, vol. 134(C), pages 309-320.
    19. Yıldıran, Uğur & Kayahan, İsmail, 2018. "Risk-averse stochastic model predictive control-based real-time operation method for a wind energy generation system supported by a pumped hydro storage unit," Applied Energy, Elsevier, vol. 226(C), pages 631-643.
    20. Moghaddam, Saeed Zolfaghari & Akbari, Tohid, 2018. "Network-constrained optimal bidding strategy of a plug-in electric vehicle aggregator: A stochastic/robust game theoretic approach," Energy, Elsevier, vol. 151(C), pages 478-489.
    21. Fan, Jin & Li, Jun & Wu, Yanrui & Wang, Shanyong & Zhao, Dingtao, 2016. "The effects of allowance price on energy demand under a personal carbon trading scheme," Applied Energy, Elsevier, vol. 170(C), pages 242-249.
    22. Eriksson, E.L.V. & Gray, E.MacA., 2017. "Optimization and integration of hybrid renewable energy hydrogen fuel cell energy systems – A critical review," Applied Energy, Elsevier, vol. 202(C), pages 348-364.
    23. Dallinger, Bettina & Schwabeneder, Daniel & Lettner, Georg & Auer, Hans, 2019. "Socio-economic benefit and profitability analyses of Austrian hydro storage power plants supporting increasing renewable electricity generation in Central Europe," Renewable and Sustainable Energy Reviews, Elsevier, vol. 107(C), pages 482-496.
    24. Lin, Boqiang & Wu, Wei, 2021. "The impact of electric vehicle penetration: A recursive dynamic CGE analysis of China," Energy Economics, Elsevier, vol. 94(C).
    25. Qingshan Xu & Yifan Ding & Aixia Zheng, 2017. "An Optimal Dispatch Model of Wind-Integrated Power System Considering Demand Response and Reliability," Sustainability, MDPI, vol. 9(5), pages 1-20, May.
    26. Lagomarsino, Elena, 2020. "Estimating elasticities of substitution with nested CES production functions: Where do we stand?," Energy Economics, Elsevier, vol. 88(C).
    27. O’Dwyer, Edward & Pan, Indranil & Acha, Salvador & Shah, Nilay, 2019. "Smart energy systems for sustainable smart cities: Current developments, trends and future directions," Applied Energy, Elsevier, vol. 237(C), pages 581-597.
    28. Ringkjøb, Hans-Kristian & Haugan, Peter M. & Solbrekke, Ida Marie, 2018. "A review of modelling tools for energy and electricity systems with large shares of variable renewables," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 440-459.
    29. Chen, Yongbao & Zhang, Lixin & Xu, Peng & Di Gangi, Alessandra, 2021. "Electricity demand response schemes in China: Pilot study and future outlook," Energy, Elsevier, vol. 224(C).
    30. Wang, Ailun & Hu, Shuo & Lin, Boqiang, 2021. "Can environmental regulation solve pollution problems? Theoretical model and empirical research based on the skill premium," Energy Economics, Elsevier, vol. 94(C).
    31. Kamel Helali & Maha Kalai, 2015. "Estimate of the elasticities of substitution of the CES and translog production functions in Tunisia," International Journal of Economics and Business Research, Inderscience Enterprises Ltd, vol. 9(3), pages 245-253.
    32. Burger, Scott & Chaves-Ávila, Jose Pablo & Batlle, Carlos & Pérez-Arriaga, Ignacio J., 2017. "A review of the value of aggregators in electricity systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 395-405.
    33. Yongli Wang & Yujing Huang & Yudong Wang & Fang Li & Yuanyuan Zhang & Chunzheng Tian, 2018. "Operation Optimization in a Smart Micro-Grid in the Presence of Distributed Generation and Demand Response," Sustainability, MDPI, vol. 10(3), pages 1-25, March.
    34. Carrara, Samuel & Marangoni, Giacomo, 2017. "Including system integration of variable renewable energies in a constant elasticity of substitution framework: The case of the WITCH model," Energy Economics, Elsevier, vol. 64(C), pages 612-626.
    35. Vázquez-Canteli, José R. & Nagy, Zoltán, 2019. "Reinforcement learning for demand response: A review of algorithms and modeling techniques," Applied Energy, Elsevier, vol. 235(C), pages 1072-1089.
    36. Sulaima, Mohamad Fani & Dahlan, Nofri Yenita & Yasin, Zuhaila Mat & Rosli, Marlinda Mohd & Omar, Zulkiflee & Hassan, Mohammad Yusri, 2019. "A review of electricity pricing in peninsular Malaysia: Empirical investigation about the appropriateness of Enhanced Time of Use (ETOU) electricity tariff," Renewable and Sustainable Energy Reviews, Elsevier, vol. 110(C), pages 348-367.
    37. Ahn, Kwangwon & Chu, Zhuang & Lee, Daeyong, 2021. "Effects of renewable energy use in the energy mix on social welfare," Energy Economics, Elsevier, vol. 96(C).
    38. Mills, Andrew D. & Levin, Todd & Wiser, Ryan & Seel, Joachim & Botterud, Audun, 2020. "Impacts of variable renewable energy on wholesale markets and generating assets in the United States: A review of expectations and evidence," Renewable and Sustainable Energy Reviews, Elsevier, vol. 120(C).
    39. Dionysios Pramangioulis & Konstantinos Atsonios & Nikos Nikolopoulos & Dimitrios Rakopoulos & Panagiotis Grammelis & Emmanuel Kakaras, 2019. "A Methodology for Determination and Definition of Key Performance Indicators for Smart Grids Development in Island Energy Systems," Energies, MDPI, vol. 12(2), pages 1-22, January.
    40. Gjorgievski, Vladimir Z. & Markovska, Natasa & Abazi, Alajdin & Duić, Neven, 2021. "The potential of power-to-heat demand response to improve the flexibility of the energy system: An empirical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    41. Dagoumas, Athanasios S. & Koltsaklis, Nikolaos E., 2019. "Review of models for integrating renewable energy in the generation expansion planning," Applied Energy, Elsevier, vol. 242(C), pages 1573-1587.
    42. Anjo, João & Neves, Diana & Silva, Carlos & Shivakumar, Abhishek & Howells, Mark, 2018. "Modeling the long-term impact of demand response in energy planning: The Portuguese electric system case study," Energy, Elsevier, vol. 165(PA), pages 456-468.
    43. Okur, Özge & Voulis, Nina & Heijnen, Petra & Lukszo, Zofia, 2019. "Aggregator-mediated demand response: Minimizing imbalances caused by uncertainty of solar generation," Applied Energy, Elsevier, vol. 247(C), pages 426-437.
    44. Neda Hajibandeh & Mehdi Ehsan & Soodabeh Soleymani & Miadreza Shafie-khah & João P. S. Catalão, 2017. "The Mutual Impact of Demand Response Programs and Renewable Energies: A Survey," Energies, MDPI, vol. 10(9), pages 1-18, September.
    45. Babonneau, Frédéric & Caramanis, Michael & Haurie, Alain, 2016. "A linear programming model for power distribution with demand response and variable renewable energy," Applied Energy, Elsevier, vol. 181(C), pages 83-95.
    46. Mays, Jacob, 2021. "Missing incentives for flexibility in wholesale electricity markets," Energy Policy, Elsevier, vol. 149(C).
    47. Chassin, David P. & Rondeau, Daniel, 2016. "Aggregate modeling of fast-acting demand response and control under real-time pricing," Applied Energy, Elsevier, vol. 181(C), pages 288-298.
    48. Abdul Conteh & Mohammed Elsayed Lotfy & Kiptoo Mark Kipngetich & Tomonobu Senjyu & Paras Mandal & Shantanu Chakraborty, 2019. "An Economic Analysis of Demand Side Management Considering Interruptible Load and Renewable Energy Integration: A Case Study of Freetown Sierra Leone," Sustainability, MDPI, vol. 11(10), pages 1-19, May.
    49. de Christo, Tiago Malavazi & Perron, Sylvain & Fardin, Jussara Farias & Simonetti, Domingos Sávio Lyrio & de Alvarez, Cristina Engel, 2019. "Demand-side energy management by cooperative combination of plans: A multi-objective method applicable to isolated communities," Applied Energy, Elsevier, vol. 240(C), pages 453-472.
    50. Iria, José & Soares, Filipe & Matos, Manuel, 2018. "Optimal supply and demand bidding strategy for an aggregator of small prosumers," Applied Energy, Elsevier, vol. 213(C), pages 658-669.
    51. Kumar, Jitendra & Suryakiran, B.V. & Verma, Ashu & Bhatti, T.S., 2019. "Analysis of techno-economic viability with demand response strategy of a grid-connected microgrid model for enhanced rural electrification in Uttar Pradesh state, India," Energy, Elsevier, vol. 178(C), pages 176-185.
    52. McPherson, Madeleine & Stoll, Brady, 2020. "Demand response for variable renewable energy integration: A proposed approach and its impacts," Energy, Elsevier, vol. 197(C).
    53. Bracco, Stefano & Delfino, Federico & Pampararo, Fabio & Robba, Michela & Rossi, Mansueto, 2014. "A mathematical model for the optimal operation of the University of Genoa Smart Polygeneration Microgrid: Evaluation of technical, economic and environmental performance indicators," Energy, Elsevier, vol. 64(C), pages 912-922.
    54. Kirkerud, J.G. & Nagel, N.O. & Bolkesjø, T.F., 2021. "The role of demand response in the future renewable northern European energy system," Energy, Elsevier, vol. 235(C).
    55. Pothen, Frank & Hübler, Michael, 2021. "A forward calibration method for analyzing energy policy in new quantitative trade models," Energy Economics, Elsevier, vol. 100(C).
    56. Henao, Felipe & Cherni, Judith A. & Jaramillo, Patricia & Dyner, Isaac, 2012. "A multicriteria approach to sustainable energy supply for the rural poor," European Journal of Operational Research, Elsevier, vol. 218(3), pages 801-809.
    57. Kate Anderson & Nicholas D. Laws & Spencer Marr & Lars Lisell & Tony Jimenez & Tria Case & Xiangkun Li & Dag Lohmann & Dylan Cutler, 2018. "Quantifying and Monetizing Renewable Energy Resiliency," Sustainability, MDPI, vol. 10(4), pages 1-13, March.
    58. Cao, Jing & Ho, Mun S. & Ma, Rong, 2020. "Analyzing carbon pricing policies using a general equilibrium model with production parameters estimated using firm data," Energy Economics, Elsevier, vol. 92(C).
    59. Dranka, Géremi Gilson & Ferreira, Paula, 2019. "Review and assessment of the different categories of demand response potentials," Energy, Elsevier, vol. 179(C), pages 280-294.
    60. Amorim, Filipa & Pina, André & Gerbelová, Hana & Pereira da Silva, Patrícia & Vasconcelos, Jorge & Martins, Victor, 2014. "Electricity decarbonisation pathways for 2050 in Portugal: A TIMES (The Integrated MARKAL-EFOM System) based approach in closed versus open systems modelling," Energy, Elsevier, vol. 69(C), pages 104-112.
    61. Wang, Fei & Xu, Hanchen & Xu, Ti & Li, Kangping & Shafie-khah, Miadreza & Catalão, João. P.S., 2017. "The values of market-based demand response on improving power system reliability under extreme circumstances," Applied Energy, Elsevier, vol. 193(C), pages 220-231.
    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. David Gattie & Michael Hewitt, 2023. "National Security as a Value-Added Proposition for Advanced Nuclear Reactors: A U.S. Focus," Energies, MDPI, vol. 16(17), pages 1-26, August.
    2. Ussama Assad & Muhammad Arshad Shehzad Hassan & Umar Farooq & Asif Kabir & Muhammad Zeeshan Khan & S. Sabahat H. Bukhari & Zain ul Abidin Jaffri & Judit Oláh & József Popp, 2022. "Smart Grid, Demand Response and Optimization: A Critical Review of Computational Methods," Energies, MDPI, vol. 15(6), pages 1-36, March.

    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. 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).
    2. Morales-España, Germán & Martínez-Gordón, Rafael & Sijm, Jos, 2022. "Classifying and modelling demand response in power systems," Energy, Elsevier, vol. 242(C).
    3. Okur, Özge & Heijnen, Petra & Lukszo, Zofia, 2021. "Aggregator’s business models in residential and service sectors: A review of operational and financial aspects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 139(C).
    4. Gilson Dranka, Géremi & Ferreira, Paula & Vaz, A. Ismael F., 2022. "Co-benefits between energy efficiency and demand-response on renewable-based energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 169(C).
    5. Carlos Pereyra-Mariñez & Félix Santos-García & Víctor S. Ocaña-Guevara & Alexander Vallejo-Díaz, 2022. "Energy Supply System Modeling Tools Integrating Sustainable Livelihoods Approach—Contribution to Sustainable Development in Remote Communities: A Review," Energies, MDPI, vol. 15(7), pages 1-17, April.
    6. Dranka, Géremi Gilson & Ferreira, Paula, 2019. "Review and assessment of the different categories of demand response potentials," Energy, Elsevier, vol. 179(C), pages 280-294.
    7. Sasaki, Kento & Aki, Hirohisa & Ikegami, Takashi, 2022. "Application of model predictive control to grid flexibility provision by distributed energy resources in residential dwellings under uncertainty," Energy, Elsevier, vol. 239(PB).
    8. Sousa, Joana & Soares, Isabel, 2022. "Demand response potential: An economic analysis for MIBEL and EEX," Energy, Elsevier, vol. 244(PA).
    9. Ieva Pakere & Armands Gravelsins & Girts Bohvalovs & Liga Rozentale & Dagnija Blumberga, 2021. "Will Aggregator Reduce Renewable Power Surpluses? A System Dynamics Approach for the Latvia Case Study," Energies, MDPI, vol. 14(23), pages 1-21, November.
    10. Ribó-Pérez, D. & Carrión, A. & Rodríguez García, J. & Álvarez Bel, C., 2021. "Ex-post evaluation of Interruptible Load programs with a system optimisation perspective," Applied Energy, Elsevier, vol. 303(C).
    11. McPherson, Madeleine & Stoll, Brady, 2020. "Demand response for variable renewable energy integration: A proposed approach and its impacts," Energy, Elsevier, vol. 197(C).
    12. Gils, Hans Christian & Gardian, Hedda & Kittel, Martin & Schill, Wolf-Peter & Zerrahn, Alexander & Murmann, Alexander & Launer, Jann & Fehler, Alexander & Gaumnitz, Felix & van Ouwerkerk, Jonas & Bußa, 2022. "Modeling flexibility in energy systems — comparison of power sector models based on simplified test cases," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    13. Saffari, Mohammadali & Crownshaw, Timothy & McPherson, Madeleine, 2023. "Assessing the potential of demand-side flexibility to improve the performance of electricity systems under high variable renewable energy penetration," Energy, Elsevier, vol. 272(C).
    14. Xu, Fangyuan & Zhu, Weidong & Wang, Yi Fei & Lai, Chun Sing & Yuan, Haoliang & Zhao, Yujia & Guo, Siming & Fu, Zhengxin, 2022. "A new deregulated demand response scheme for load over-shifting city in regulated power market," Applied Energy, Elsevier, vol. 311(C).
    15. Ran, Fengming & Gao, Dian-ce & Zhang, Xu & Chen, Shuyue, 2020. "A virtual sensor based self-adjusting control for HVAC fast demand response in commercial buildings towards smart grid applications," Applied Energy, Elsevier, vol. 269(C).
    16. Lechl, Michael & Fürmann, Tim & de Meer, Hermann & Weidlich, Anke, 2023. "A review of models for energy system flexibility requirements and potentials using the new FLEXBLOX taxonomy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 184(C).
    17. Magdalena Krystyna Wyrwicka & Ewa Więcek-Janka & Łukasz Brzeziński, 2023. "Transition to Sustainable Energy System for Smart Cities—Literature Review," Energies, MDPI, vol. 16(21), pages 1-26, October.
    18. Khanna, Tarun M., 2022. "Using agricultural demand for reducing costs of renewable energy integration in India," Energy, Elsevier, vol. 254(PC).
    19. Märkle-Huß, Joscha & Feuerriegel, Stefan & Neumann, Dirk, 2018. "Large-scale demand response and its implications for spot prices, load and policies: Insights from the German-Austrian electricity market," Applied Energy, Elsevier, vol. 210(C), pages 1290-1298.
    20. Kirchem, Dana & Lynch, Muireann Á. & Bertsch, Valentin & Casey, Eoin, 2020. "Modelling demand response with process models and energy systems models: Potential applications for wastewater treatment within the energy-water nexus," Applied Energy, Elsevier, vol. 260(C).

    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:15:y:2022:i:4:p:1307-:d:747006. 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.