IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v52y2013icp143-153.html
   My bibliography  Save this article

Distribution system operation supported by contextual energy resource management based on intelligent SCADA

Author

Listed:
  • Vale, Zita
  • Morais, Hugo
  • Faria, Pedro
  • Ramos, Carlos

Abstract

Future distribution systems will have to deal with an intensive penetration of distributed energy resources ensuring reliable and secure operation according to the smart grid paradigm. SCADA (Supervisory Control and Data Acquisition) is an essential infrastructure for this evolution. This paper proposes a new conceptual design of an intelligent SCADA with a decentralized, flexible, and intelligent approach, adaptive to the context (context awareness).

Suggested Citation

  • Vale, Zita & Morais, Hugo & Faria, Pedro & Ramos, Carlos, 2013. "Distribution system operation supported by contextual energy resource management based on intelligent SCADA," Renewable Energy, Elsevier, vol. 52(C), pages 143-153.
    • Handle: RePEc:eee:renene:v:52:y:2013:i:c:p:143-153
    DOI: 10.1016/j.renene.2012.10.019
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148112006647
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2012.10.019?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. Menegaki, Angeliki N., 2012. "A social marketing mix for renewable energy in Europe based on consumer stated preference surveys," Renewable Energy, Elsevier, vol. 39(1), pages 30-39.
    2. Shafiullah, G.M. & Amanullah, M.T.O. & Shawkat Ali, A.B.M. & Jarvis, Dennis & Wolfs, Peter, 2012. "Prospects of renewable energy – a feasibility study in the Australian context," Renewable Energy, Elsevier, vol. 39(1), pages 183-197.
    3. Morais, Hugo & Kádár, Péter & Faria, Pedro & Vale, Zita A. & Khodr, H.M., 2010. "Optimal scheduling of a renewable micro-grid in an isolated load area using mixed-integer linear programming," Renewable Energy, Elsevier, vol. 35(1), pages 151-156.
    4. Pinto, T. & Morais, H. & Oliveira, P. & Vale, Z. & Praça, I. & Ramos, C., 2011. "A new approach for multi-agent coalition formation and management in the scope of electricity markets," Energy, Elsevier, vol. 36(8), pages 5004-5015.
    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. Bruno Mota & Luis Gomes & Pedro Faria & Carlos Ramos & Zita Vale & Regina Correia, 2021. "Production Line Optimization to Minimize Energy Cost and Participate in Demand Response Events," Energies, MDPI, vol. 14(2), pages 1-14, January.
    2. Sousa, Tiago & Morais, Hugo & Vale, Zita & Castro, Rui, 2015. "A multi-objective optimization of the active and reactive resource scheduling at a distribution level in a smart grid context," Energy, Elsevier, vol. 85(C), pages 236-250.
    3. Amin Shokri Gazafroudi & Francisco Prieto-Castrillo & Tiago Pinto & Javier Prieto & Juan Manuel Corchado & Javier Bajo, 2017. "Energy Flexibility Management Based on Predictive Dispatch Model of Domestic Energy Management System," Energies, MDPI, vol. 10(9), pages 1-16, September.
    4. Faran Ahmed & Muhammad Naeem & Muhammad Iqbal, 2017. "ICT and renewable energy: a way forward to the next generation telecom base stations," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 64(1), pages 43-56, January.
    5. Sousa, Tiago & Vale, Zita & Carvalho, Joao Paulo & Pinto, Tiago & Morais, Hugo, 2014. "A hybrid simulated annealing approach to handle energy resource management considering an intensive use of electric vehicles," Energy, Elsevier, vol. 67(C), pages 81-96.
    6. Kostevšek, Anja & Cizelj, Leon & Petek, Janez & Pivec, Aleksandra, 2013. "A novel concept for a renewable network within municipal energy systems," Renewable Energy, Elsevier, vol. 60(C), pages 79-87.
    7. Yanine, Franco F. & Sauma, Enzo E., 2013. "Review of grid-tie micro-generation systems without energy storage: Towards a new approach to sustainable hybrid energy systems linked to energy efficiency," Renewable and Sustainable Energy Reviews, Elsevier, vol. 26(C), pages 60-95.
    8. Gutiérrez-Alcaraz, G. & Galván, E. & González-Cabrera, N. & Javadi, M.S., 2015. "Renewable energy resources short-term scheduling and dynamic network reconfiguration for sustainable energy consumption," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 256-264.
    9. Daniel Ramos & Mahsa Khorram & Pedro Faria & Zita Vale, 2021. "Load Forecasting in an Office Building with Different Data Structure and Learning Parameters," Forecasting, MDPI, vol. 3(1), pages 1-14, 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. Abbaspour, M. & Satkin, M. & Mohammadi-Ivatloo, B. & Hoseinzadeh Lotfi, F. & Noorollahi, Y., 2013. "Optimal operation scheduling of wind power integrated with compressed air energy storage (CAES)," Renewable Energy, Elsevier, vol. 51(C), pages 53-59.
    2. Sousa, Tiago & Morais, Hugo & Soares, João & Vale, Zita, 2012. "Day-ahead resource scheduling in smart grids considering Vehicle-to-Grid and network constraints," Applied Energy, Elsevier, vol. 96(C), pages 183-193.
    3. Chen, Yen-Haw & Lu, Su-Ying & Chang, Yung-Ruei & Lee, Ta-Tung & Hu, Ming-Che, 2013. "Economic analysis and optimal energy management models for microgrid systems: A case study in Taiwan," Applied Energy, Elsevier, vol. 103(C), pages 145-154.
    4. Keon Baek & Woong Ko & Jinho Kim, 2019. "Optimal Scheduling of Distributed Energy Resources in Residential Building under the Demand Response Commitment Contract," Energies, MDPI, vol. 12(14), pages 1-19, July.
    5. Toka, Agorasti & Iakovou, Eleftherios & Vlachos, Dimitrios & Tsolakis, Naoum & Grigoriadou, Anastasia-Loukia, 2014. "Managing the diffusion of biomass in the residential energy sector: An illustrative real-world case study," Applied Energy, Elsevier, vol. 129(C), pages 56-69.
    6. Rajvikram Madurai Elavarasan & G. M. Shafiullah & Nallapaneni Manoj Kumar & Sanjeevikumar Padmanaban, 2019. "A State-of-the-Art Review on the Drive of Renewables in Gujarat, State of India: Present Situation, Barriers and Future Initiatives," Energies, MDPI, vol. 13(1), pages 1-30, December.
    7. Thiaux, Yaël & Dang, Thu Thuy & Schmerber, Louis & Multon, Bernard & Ben Ahmed, Hamid & Bacha, Seddik & Tran, Quoc Tuan, 2019. "Demand-side management strategy in stand-alone hybrid photovoltaic systems with real-time simulation of stochastic electricity consumption behavior," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    8. Saher Javaid & Mineo Kaneko & Yasuo Tan, 2021. "Safe Operation Conditions of Electrical Power System Considering Power Balanceability among Power Generators, Loads, and Storage Devices," Energies, MDPI, vol. 14(15), pages 1-27, July.
    9. Llaria, Alvaro & Curea, Octavian & Jiménez, Jaime & Camblong, Haritza, 2011. "Survey on microgrids: Unplanned islanding and related inverter control techniques," Renewable Energy, Elsevier, vol. 36(8), pages 2052-2061.
    10. Prasad, Abhnil A. & Taylor, Robert A. & Kay, Merlinde, 2017. "Assessment of solar and wind resource synergy in Australia," Applied Energy, Elsevier, vol. 190(C), pages 354-367.
    11. Tang, Ruoli & Li, Xin & Lai, Jingang, 2018. "A novel optimal energy-management strategy for a maritime hybrid energy system based on large-scale global optimization," Applied Energy, Elsevier, vol. 228(C), pages 254-264.
    12. Se-Hyeok Choi & Akhtar Hussain & Hak-Man Kim, 2018. "Adaptive Robust Optimization-Based Optimal Operation of Microgrids Considering Uncertainties in Arrival and Departure Times of Electric Vehicles," Energies, MDPI, vol. 11(10), pages 1-16, October.
    13. Batas Bjelic, Ilija & Ciric, Rade M., 2014. "Optimal distributed generation planning at a local level – A review of Serbian renewable energy development," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 79-86.
    14. Soha, Tamás & Munkácsy, Béla & Harmat, Ádám & Csontos, Csaba & Horváth, Gergely & Tamás, László & Csüllög, Gábor & Daróczi, Henriett & Sáfián, Fanni & Szabó, Mária, 2017. "GIS-based assessment of the opportunities for small-scale pumped hydro energy storage in middle-mountain areas focusing on artificial landscape features," Energy, Elsevier, vol. 141(C), pages 1363-1373.
    15. Yong Zeng & Yanpeng Cai & Guohe Huang & Jing Dai, 2011. "A Review on Optimization Modeling of Energy Systems Planning and GHG Emission Mitigation under Uncertainty," Energies, MDPI, vol. 4(10), pages 1-33, October.
    16. Soares, J. & Silva, M. & Sousa, T. & Vale, Z. & Morais, H., 2012. "Distributed energy resource short-term scheduling using Signaled Particle Swarm Optimization," Energy, Elsevier, vol. 42(1), pages 466-476.
    17. Marques, António Cardoso & Fuinhas, José Alberto & Menegaki, Angeliki N., 2014. "Interactions between electricity generation sources and economic activity in Greece: A VECM approach," Applied Energy, Elsevier, vol. 132(C), pages 34-46.
    18. Shan Zhou & Douglas S. Noonan, 2019. "Justice Implications of Clean Energy Policies and Programs in the United States: A Theoretical and Empirical Exploration," Sustainability, MDPI, vol. 11(3), pages 1-20, February.
    19. Yu, Nan & Kang, Jin-Su & Chang, Chung-Chuan & Lee, Tai-Yong & Lee, Dong-Yup, 2016. "Robust economic optimization and environmental policy analysis for microgrid planning: An application to Taichung Industrial Park, Taiwan," Energy, Elsevier, vol. 113(C), pages 671-682.
    20. Niknam, Taher & Azizipanah-Abarghooee, Rasoul & Narimani, Mohammad Rasoul, 2012. "An efficient scenario-based stochastic programming framework for multi-objective optimal micro-grid operation," Applied Energy, Elsevier, vol. 99(C), pages 455-470.

    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:renene:v:52:y:2013:i:c:p:143-153. 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/renewable-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.