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Scheduling of Air Conditioning and Thermal Energy Storage Systems Considering Demand Response Programs

Author

Listed:
  • Ali Dargahi

    (Tabriz Electric Power Distribution Company, Tabriz 5157694375, Iran
    Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz 5166616471, Iran
    These authors contributed equally to this work.)

  • Khezr Sanjani

    (Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz 5166616471, Iran
    Niroo Research Institute, Tehran 1468613113, Iran
    These authors contributed equally to this work.)

  • Morteza Nazari-Heris

    (Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz 5166616471, Iran
    Department of Architectural Engineering, Pennsylvania State University, State College, PA 16802, USA)

  • Behnam Mohammadi-Ivatloo

    (Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz 5166616471, Iran
    Institute of Research and Development, Duy Tan University, Da Nang 550000, Vietnam)

  • Sajjad Tohidi

    (Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz 5166616471, Iran)

  • Mousa Marzband

    (Faculty of Engineering and Environment, Northumbria University, Newcastle upon Tyne NE1 8ST, UK)

Abstract

The high penetration rate of renewable energy sources (RESs) in smart energy systems has both threat and opportunity consequences. On the positive side, it is inevitable that RESs are beneficial with respect to conventional energy resources from the environmental aspects. On the negative side, the RESs are a great source of uncertainty, which will make challenges for the system operators to cope with. To tackle the issues of the negative side, there are several methods to deal with intermittent RESs, such as electrical and thermal energy storage systems (TESSs). In fact, pairing RESs to electrical energy storage systems (ESSs) has favorable economic opportunities for the facility owners and power grid operators (PGO), simultaneously. Moreover, the application of demand-side management approaches, such as demand response programs (DRPs) on flexible loads, specifically thermal loads, is an effective solution through the system operation. To this end, in this work, an air conditioning system (A/C system) with a TESS has been studied as a way of volatility compensation of the wind farm forecast-errors (WFFEs). Additionally, the WFFEs are investigated from multiple visions to assist the dispatch of the storage facilities. The operation design is presented for the A/C systems in both day-ahead and real-time operations based on the specifications of WFFEs. Analyzing the output results, the main aims of the work, in terms of applying DRPs and make-up of WFFEs to the scheduling of A/C system and TESS, will be evaluated. The dispatched cooling and base loads show the superiority of the proposed method, which has a smoother curve compared to the original curve. Further, the WFFEs application has proved and demonstrated a way better function than the other uncertainty management techniques by committing and compensating the forecast errors of cooling loads.

Suggested Citation

  • Ali Dargahi & Khezr Sanjani & Morteza Nazari-Heris & Behnam Mohammadi-Ivatloo & Sajjad Tohidi & Mousa Marzband, 2020. "Scheduling of Air Conditioning and Thermal Energy Storage Systems Considering Demand Response Programs," Sustainability, MDPI, vol. 12(18), pages 1-13, September.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:18:p:7311-:d:409792
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    References listed on IDEAS

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    1. Daneshvar, Mohammadreza & Mohammadi-Ivatloo, Behnam & Zare, Kazem & Asadi, Somayeh, 2020. "Two-stage stochastic programming model for optimal scheduling of the wind-thermal-hydropower-pumped storage system considering the flexibility assessment," Energy, Elsevier, vol. 193(C).
    2. Ioannou, Anastasia & Fuzuli, Gulistiani & Brennan, Feargal & Yudha, Satya Widya & Angus, Andrew, 2019. "Multi-stage stochastic optimization framework for power generation system planning integrating hybrid uncertainty modelling," Energy Economics, Elsevier, vol. 80(C), pages 760-776.
    3. Zakaria, A. & Ismail, Firas B. & Lipu, M.S. Hossain & Hannan, M.A., 2020. "Uncertainty models for stochastic optimization in renewable energy applications," Renewable Energy, Elsevier, vol. 145(C), pages 1543-1571.
    4. Guerra, Omar J. & Tejada, Diego A. & Reklaitis, Gintaras V., 2019. "Climate change impacts and adaptation strategies for a hydro-dominated power system via stochastic optimization," Applied Energy, Elsevier, vol. 233, pages 584-598.
    5. Elhashmi, Rodwan & Hallinan, Kevin P. & Chiasson, Andrew D., 2020. "Low-energy opportunity for multi-family residences: A review and simulation-based study of a solar borehole thermal energy storage system," Energy, Elsevier, vol. 204(C).
    6. 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).
    7. Rosato, Antonio & Ciervo, Antonio & Ciampi, Giovanni & Scorpio, Michelangelo & Guarino, Francesco & Sibilio, Sergio, 2020. "Impact of solar field design and back-up technology on dynamic performance of a solar hybrid heating network integrated with a seasonal borehole thermal energy storage serving a small-scale residentia," Renewable Energy, Elsevier, vol. 154(C), pages 684-703.
    8. Hemmati, Reza & Mehrjerdi, Hasan & Bornapour, Mosayeb, 2020. "Hybrid hydrogen-battery storage to smooth solar energy volatility and energy arbitrage considering uncertain electrical-thermal loads," Renewable Energy, Elsevier, vol. 154(C), pages 1180-1187.
    9. Bostan, Alireza & Nazar, Mehrdad Setayesh & Shafie-khah, Miadreza & Catalão, João P.S., 2020. "Optimal scheduling of distribution systems considering multiple downward energy hubs and demand response programs," Energy, Elsevier, vol. 190(C).
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    Cited by:

    1. Ting Wang & Qiya Wang & Caiqing Zhang, 2021. "Research on the Optimal Operation of a Novel Renewable Multi-Energy Complementary System in Rural Areas," Sustainability, MDPI, vol. 13(4), pages 1-16, February.
    2. Mateusz Andrychowicz, 2021. "RES and ES Integration in Combination with Distribution Grid Development Using MILP," Energies, MDPI, vol. 14(2), pages 1-19, January.

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