IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v191y2020ics0360544219322480.html
   My bibliography  Save this article

Optimal eco-emission scheduling of distribution network operator and distributed generator owner under employing demand response program

Author

Listed:
  • Hosseinnia, Hamed
  • Modarresi, Javad
  • Nazarpour, Daryoush

Abstract

This paper proposes an optimal operational scheduling framework to integrate the distributed generators (DGs) in the distribution network. This framework is used to maximize the benefit of DG owner and distribution network operator (DNO). In this paper, two optimization model has been proposed to optimum emission and economic operation performance of distribution network in the presence of demand response program (DR). DR under time of use (TOU) pricing is utilized to promote both DG owner and DNO benefits from economic operation issue. The mixed-integer programming (MIP) is used to model a multi-objective problem in General Algebraic Modeling System (GAMS). Then, the problem is solved by employing weighted sum and fuzzy decision making methods. The obtained results reveal that due to positive implementation of DR program, dependency of the distribution network to the upstream network is decreased and load curve become smoother. The under study systems are IEEE 33-bus test system and 101-bus Khoy-Iran actual distribution system which compose electric vehicle parking lot (PL), battery storage, hydrogen storage system (HSS), and local dispatchable generators (LDG).

Suggested Citation

  • Hosseinnia, Hamed & Modarresi, Javad & Nazarpour, Daryoush, 2020. "Optimal eco-emission scheduling of distribution network operator and distributed generator owner under employing demand response program," Energy, Elsevier, vol. 191(C).
    • Handle: RePEc:eee:energy:v:191:y:2020:i:c:s0360544219322480
    DOI: 10.1016/j.energy.2019.116553
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544219322480
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2019.116553?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. 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.
    2. Jalali, Mehdi & Zare, Kazem & Seyedi, Heresh, 2017. "Strategic decision-making of distribution network operator with multi-microgrids considering demand response program," Energy, Elsevier, vol. 141(C), pages 1059-1071.
    3. Tabar, Vahid Sohrabi & Ghassemzadeh, Saeid & Tohidi, Sajjad, 2019. "Energy management in hybrid microgrid with considering multiple power market and real time demand response," Energy, Elsevier, vol. 174(C), pages 10-23.
    4. Olivella-Rosell, Pol & Bullich-Massagué, Eduard & Aragüés-Peñalba, Mònica & Sumper, Andreas & Ottesen, Stig Ødegaard & Vidal-Clos, Josep-Andreu & Villafáfila-Robles, Roberto, 2018. "Optimization problem for meeting distribution system operator requests in local flexibility markets with distributed energy resources," Applied Energy, Elsevier, vol. 210(C), pages 881-895.
    5. Nikmehr, Nima & Najafi-Ravadanegh, Sajad & Khodaei, Amin, 2017. "Probabilistic optimal scheduling of networked microgrids considering time-based demand response programs under uncertainty," Applied Energy, Elsevier, vol. 198(C), pages 267-279.
    6. Perez-Diaz, Alvaro & Gerding, Enrico & McGroarty, Frank, 2018. "Coordination and payment mechanisms for electric vehicle aggregators," Applied Energy, Elsevier, vol. 212(C), pages 185-195.
    7. Moradi, Hadis & Esfahanian, Mahdi & Abtahi, Amir & Zilouchian, Ali, 2018. "Optimization and energy management of a standalone hybrid microgrid in the presence of battery storage system," Energy, Elsevier, vol. 147(C), pages 226-238.
    8. Bornapour, Mosayeb & Hooshmand, Rahmat-Allah & Khodabakhshian, Amin & Parastegari, Moein, 2017. "Optimal stochastic coordinated scheduling of proton exchange membrane fuel cell-combined heat and power, wind and photovoltaic units in micro grids considering hydrogen storage," Applied Energy, Elsevier, vol. 202(C), pages 308-322.
    9. Tabar, Vahid Sohrabi & Jirdehi, Mehdi Ahmadi & Hemmati, Reza, 2017. "Energy management in microgrid based on the multi objective stochastic programming incorporating portable renewable energy resource as demand response option," Energy, Elsevier, vol. 118(C), pages 827-839.
    10. von Appen, J. & Braun, M., 2018. "Strategic decision making of distribution network operators and investors in residential photovoltaic battery storage systems," Applied Energy, Elsevier, vol. 230(C), pages 540-550.
    11. Kalavani, Farshad & Mohammadi-Ivatloo, Behnam & Zare, Kazem, 2019. "Optimal stochastic scheduling of cryogenic energy storage with wind power in the presence of a demand response program," Renewable Energy, Elsevier, vol. 130(C), pages 268-280.
    12. Zeng, Yuan & Zhang, Ruiwen & Wang, Dong & Mu, Yunfei & Jia, Hongjie, 2019. "A regional power grid operation and planning method considering renewable energy generation and load control," Applied Energy, Elsevier, vol. 237(C), pages 304-313.
    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. Suryakiran, B.V. & Nizami, Sohrab & Verma, Ashu & Saha, Tapan Kumar & Mishra, Sukumar, 2023. "A DSO-based day-ahead market mechanism for optimal operational planning of active distribution network," Energy, Elsevier, vol. 282(C).
    2. Zhang, Jingrui & Zhou, Yulu & Li, Zhuoyun & Cai, Junfeng, 2021. "Three-level day-ahead optimal scheduling framework considering multi-stakeholders in active distribution networks: Up-to-down approach," Energy, Elsevier, vol. 219(C).
    3. Rahimi Sadegh, Ainollah & Setayesh Nazar, Mehrdad & Shafie-khah, Miadreza & Catalão, João P.S., 2022. "Optimal resilient allocation of mobile energy storages considering coordinated microgrids biddings," Applied Energy, Elsevier, vol. 328(C).
    4. Luo, Lizi & He, Pinquan & Gu, Wei & Sheng, Wanxing & Liu, Keyan & Bai, Muke, 2022. "Temporal-spatial scheduling of electric vehicles in AC/DC distribution networks," Energy, Elsevier, vol. 255(C).
    5. Morales-España, Germán & Martínez-Gordón, Rafael & Sijm, Jos, 2022. "Classifying and modelling demand response in power systems," Energy, Elsevier, vol. 242(C).
    6. Firouzi, Mehdi & Setayesh Nazar, Mehrdad & Shafie-khah, Miadreza & Catalão, João P.S., 2023. "Integrated framework for modeling the interactions of plug-in hybrid electric vehicles aggregators, parking lots and distributed generation facilities in electricity markets," Applied Energy, Elsevier, vol. 334(C).
    7. Zhang, Jingrui & Li, Zhuoyun & Wang, Beibei, 2021. "Within-day rolling optimal scheduling problem for active distribution networks by multi-objective evolutionary algorithm based on decomposition integrating with thought of simulated annealing," Energy, Elsevier, vol. 223(C).

    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. Àlex Alonso-Travesset & Helena Martín & Sergio Coronas & Jordi de la Hoz, 2022. "Optimization Models under Uncertainty in Distributed Generation Systems: A Review," Energies, MDPI, vol. 15(5), pages 1-40, March.
    2. Shahryari, E. & Shayeghi, H. & Mohammadi-ivatloo, B. & Moradzadeh, M., 2019. "A copula-based method to consider uncertainties for multi-objective energy management of microgrid in presence of demand response," Energy, Elsevier, vol. 175(C), pages 879-890.
    3. de la Hoz, Jordi & Martín, Helena & Alonso, Alex & Carolina Luna, Adriana & Matas, José & Vasquez, Juan C. & Guerrero, Josep M., 2019. "Regulatory-framework-embedded energy management system for microgrids: The case study of the Spanish self-consumption scheme," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    4. Mehrdad Tahmasebi & Jagadeesh Pasupuleti & Fatemeh Mohamadian & Mohammad Shakeri & Josep M. Guerrero & M. Reyasudin Basir Khan & Muhammad Shahzad Nazir & Amir Safari & Najmeh Bazmohammadi, 2021. "Optimal Operation of Stand-Alone Microgrid Considering Emission Issues and Demand Response Program Using Whale Optimization Algorithm," Sustainability, MDPI, vol. 13(14), pages 1-22, July.
    5. Sharma, Pavitra & Dutt Mathur, Hitesh & Mishra, Puneet & Bansal, Ramesh C., 2022. "A critical and comparative review of energy management strategies for microgrids," Applied Energy, Elsevier, vol. 327(C).
    6. Mohseni, Soheil & Brent, Alan C. & Kelly, Scott & Browne, Will N., 2022. "Demand response-integrated investment and operational planning of renewable and sustainable energy systems considering forecast uncertainties: A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    7. Bahramara, Salah & Sheikhahmadi, Pouria & Golpîra, Hêmin, 2019. "Co-optimization of energy and reserve in standalone micro-grid considering uncertainties," Energy, Elsevier, vol. 176(C), pages 792-804.
    8. Roy, Nibir Baran & Das, Debapriya, 2024. "Stochastic power allocation of distributed tri-generation plants and energy storage units in a zero bus microgrid with electric vehicles and demand response," Renewable and Sustainable Energy Reviews, Elsevier, vol. 191(C).
    9. Hemmati, Reza & Ghiasi, Seyyed Mohammad Sadegh & Entezariharsini, Azam, 2018. "Power fluctuation smoothing and loss reduction in grid integrated with thermal-wind-solar-storage units," Energy, Elsevier, vol. 152(C), pages 759-769.
    10. Hyung-Joon Kim & Mun-Kyeom Kim, 2019. "Multi-Objective Based Optimal Energy Management of Grid-Connected Microgrid Considering Advanced Demand Response," Energies, MDPI, vol. 12(21), pages 1-28, October.
    11. Tabar, Vahid Sohrabi & Abbasi, Vahid, 2019. "Energy management in microgrid with considering high penetration of renewable resources and surplus power generation problem," Energy, Elsevier, vol. 189(C).
    12. Sane Lei Lei Wynn & Watcharakorn Pinthurat & Boonruang Marungsri, 2022. "Multi-Objective Optimization for Peak Shaving with Demand Response under Renewable Generation Uncertainty," Energies, MDPI, vol. 15(23), pages 1-19, November.
    13. Mehrjerdi, Hasan & Bornapour, Mosayeb & Hemmati, Reza & Ghiasi, Seyyed Mohammad Sadegh, 2019. "Unified energy management and load control in building equipped with wind-solar-battery incorporating electric and hydrogen vehicles under both connected to the grid and islanding modes," Energy, Elsevier, vol. 168(C), pages 919-930.
    14. Shaterabadi, Mohammad & Jirdehi, Mehdi Ahmadi & Amiri, Nima & Omidi, Sina, 2020. "Enhancement the economical and environmental aspects of plus-zero energy buildings integrated with INVELOX turbines," Renewable Energy, Elsevier, vol. 153(C), pages 1355-1367.
    15. Li, Longxi & Cao, Xilin & Wang, Peng, 2021. "Optimal coordination strategy for multiple distributed energy systems considering supply, demand, and price uncertainties," Energy, Elsevier, vol. 227(C).
    16. Longxi Li, 2020. "Optimal Coordination Strategies for Load Service Entity and Community Energy Systems Based on Centralized and Decentralized Approaches," Energies, MDPI, vol. 13(12), pages 1-22, June.
    17. Morteza Zare Oskouei & Ayşe Aybike Şeker & Süleyman Tunçel & Emin Demirbaş & Tuba Gözel & Mehmet Hakan Hocaoğlu & Mehdi Abapour & Behnam Mohammadi-Ivatloo, 2022. "A Critical Review on the Impacts of Energy Storage Systems and Demand-Side Management Strategies in the Economic Operation of Renewable-Based Distribution Network," Sustainability, MDPI, vol. 14(4), pages 1-34, February.
    18. Tabar, Vahid Sohrabi & Ghassemzadeh, Saeid & Tohidi, Sajjad, 2021. "Increasing resiliency against information vulnerability of renewable resources in the operation of smart multi-area microgrid," Energy, Elsevier, vol. 220(C).
    19. Ajoulabadi, Ata & Ravadanegh, Sajad Najafi & Behnam Mohammadi-Ivatloo,, 2020. "Flexible scheduling of reconfigurable microgrid-based distribution networks considering demand response program," Energy, Elsevier, vol. 196(C).
    20. Diptish Saha & Najmeh Bazmohammadi & Juan C. Vasquez & Josep M. Guerrero, 2023. "Multiple Microgrids: A Review of Architectures and Operation and Control Strategies," Energies, MDPI, vol. 16(2), pages 1-32, January.

    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:191:y:2020:i:c:s0360544219322480. 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.