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Distributed active demand response system for peak power reduction through load shifting

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The large variability in power consumption in electrical power systems (EPS) influences not only growth balance losses and technical losses, but also in some cases reduces energy security. Delayed restoration of power generation, combined with unpredictable weather events leading to the loss of generating power can lead to a situation in which to save the stability of the power system there must be introduced in the system a load power limit or even disconnection of end-user in a given area, which will significantly reduce the comfort of use of energy. This situation can be prevented through either the building of new intervention power units or the aggregated use of new energy technologies, such as distributed network resources (DER), which are part of an intelligent Smart Grid network. Such resources bring together virtual power plants (VPP) and demand side management (DSM). The article presents an alternative decentralized active demand response (DADR) system, that by acting on selected groups of loads reduces peak loads with minimized loss of comfort of energy in use for the end-user. The system operates without any communication. The effectiveness of the proposed solution has been confirmed, outlined in test results obtained by the authors from a developed analytical model, which also contains stochastic algorithms to decrease the negative impact of such DSM systems on the power system (power overshoot and oscillation).
Rocznik
Strony
925--936
Opis fizyczny
Bibliogr. 43 poz., rys., tab., wykr.
Twórcy
autor
  • Faculty of Electrical Engineering, Computer Science and Telecommunications, University of Zielona Góra, 9 Licealna St., 65-417 Zielona Góra
autor
  • Faculty of Electrical Engineering, Computer Science and Telecommunications, University of Zielona Góra, 9 Licealna St., 65-417 Zielona Góra
  • Faculty of Electrical Engineering, Computer Science and Telecommunications, University of Zielona Góra, 9 Licealna St., 65-417 Zielona Góra
autor
  • Faculty of Mathematics, Computer Science and Econometrics, University of Zielona Góra, 9 Licealna St., 65-417 Zielona Góra, Poland
Bibliografia
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  • [16] X. Chen, T. Wei, and S. Hu, “Uncertainty-aware household appliance scheduling considering dynamic electricity pricing in smart home”, IEEE Trans. Smart Grid 4 (2), 932–941 (2013).
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  • [18] C. Chen, J. Wang, and S. Kishore, “A distributed direct load control approach for large-scale residential demand response”, IEEE Transactions on Power Systems 29 (5), 2219–2228 (2014).
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  • [23] Y. Ozturk, D. Senthilkumar, S. Kumar, and G. Lee, “An intelligent home energy management system to improve demand response”, IEEE Transactions on Smart Grid 4 (2), 694–701 (2013).
  • [24] H. T. Haider, O. H. See, and W. Elmenreich, “A review of residential demand response of smart grid”, Renewable and Sustainable Energy Reviews 59, 166 – 178 (2016).
  • [25] G. Costanzo, G. Zhu, M. Anjos, and G. Savard, “A system architecture for autonomous demand side load management in smart buildings”, IEEE Trans. Smart Grid 3 (4), 2157–2165 (2012).
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  • [27] D. Angeli and P. Kountouriotis, “A stochastic approach to “dynamic-demand” refrigerator control”, IEEE Trans. Control Syst. Technol. 20 (3), 581–592 (2012).
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  • [34] Y. Sun, S. Wang, F. Xiao, and D. Gao, “Peak load shifting control using different cold thermal energy storage facilities in commercial buildings: A review”, Energy Conv. Manag. 71, 101 – 114 (2013).
  • [35] J. Laghari, H. Mokhlis, M. Karimi, A. Abu Bakar, and H. Mohamad, “A new under-frequency load shedding technique based on combination of fixed and random priority of loads for smart grid applications”, IEEE Trans. Power Syst. PP (99), 1–9 (2014).
  • [36] B. Shi and J. Liu, “Decentralized control and fair load-shedding compensations to prevent cascading failures in a smart grid”, Int. J. Electric Power Energy Syst. 67 (0), 582 – 590 (2015).
  • [37] M. Vedady Moghadam, R. Ma, and R. Zhang, “Distributed frequency control in smart grids via randomized demand response”, IEEE Trans. Smart Grid 5 (6), 2798–2809 (2014).
  • [38] S. Vachirasricirikul and I. Ngamroo, “Robust lfc in a smart grid with wind power penetration by coordinated v2g control and frequency controller”, IEEE Trans. Smart Grid 5 (1), 371–380 (2014).
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  • [40] K. K. W. Zhang, J. Lian, L. Marinovici, C. Moya, and J. Dagle, “Distributed smart grid asset control strategies for providing ancillary services”, tech. rep., Pacific Northwest National Laboratory Richland, 2013.
  • [41] G. Strbac, “Demand side management: Benefits and challenges”, Energy Policy 36 (12), 4419 – 4426 (2008).
  • [42] C. Zhao, U. Topcu, N. Li, and S. Low, “Design and stability of load-side primary frequency control in power systems”, IEEE Trans. Autom. Control 59 (5), 1177–1189 (2014).
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Uwagi
PL
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-db9594f9-7c92-4a7b-ada4-f8c7a0e368c5
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