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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
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    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    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.
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    Citations

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    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.

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