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Optimal real time cost-benefit based demand response with intermittent resources

Listed author(s):
  • Zareen, N.
  • Mustafa, M.W.
  • Sultana, U.
  • Nadia, R.
  • Khattak, M.A.
Registered author(s):

    Ever-increasing price of conventional energy resources and related environmental concern enforced to explore alternative energy sources. Inherent uncertainty of power generation and demand being strongly influenced by the electricity market has posed severe challenges for DRPs (Demand Response Programs). Definitely, the success of such uncertain energy systems under new market structures is critically decided by the advancement of innovative technical and financial tools. Recent exponential growth of DG (distributed generations) demanded both the grid reliability and financial cost–benefits analysis for deregulated electricity market stakeholders. Based on the SGT (signaling game theory), the paper presents a novel user-aware demand-management approach where the price are colligated with grid condition uncertainties to manage the peak residential loads. The degree of information disturbances are considered as a key factor for evaluating electricity bidding mechanisms in the presence of independent multi-generation resources and price-elastic demand. A correlation between the cost–benefit price and variable reliability of grid is established under uncertain generation and demand conditions. Impacts of the strategies on load shape, benefit of customers and the reduction of energy consumption are inspected and compared with Time-of-Used based DRPs. Simulation results show that the proposed DRP can significantly reduce or even eliminate peak-hour energy consumption, leading to a substantial raise of revenues with 18% increase in the load reduction and a considerable improvement in system reliability is evidenced.

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    Article provided by Elsevier in its journal Energy.

    Volume (Year): 90 (2015)
    Issue (Month): P2 ()
    Pages: 1695-1706

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    Handle: RePEc:eee:energy:v:90:y:2015:i:p2:p:1695-1706
    DOI: 10.1016/
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    1. Zibelman, Audrey & Krapels, Edward N., 2008. "Deployment of Demand Response as a Real-Time Resource in Organized Markets," The Electricity Journal, Elsevier, vol. 21(5), pages 51-56, June.
    2. Ravindra, Kumudhini & Iyer, Parameshwar P., 2014. "Decentralized demand–supply matching using community microgrids and consumer demand response: A scenario analysis," Energy, Elsevier, vol. 76(C), pages 32-41.
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    5. Dhillon, Javed & Kumar, Arun & Singal, S.K., 2014. "Optimization methods applied for Wind–PSP operation and scheduling under deregulated market: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 682-700.
    6. Simoglou, Christos K. & Biskas, Pandelis N. & Vagropoulos, Stylianos I. & Bakirtzis, Anastasios G., 2014. "Electricity market models and RES integration: The Greek case," Energy Policy, Elsevier, vol. 67(C), pages 531-542.
    7. Walawalkar, Rahul & Blumsack, Seth & Apt, Jay & Fernands, Stephen, 2008. "An economic welfare analysis of demand response in the PJM electricity market," Energy Policy, Elsevier, vol. 36(10), pages 3692-3702, October.
    8. Greening, Lorna A., 2010. "Demand response resources: Who is responsible for implementation in a deregulated market?," Energy, Elsevier, vol. 35(4), pages 1518-1525.
    9. Blasques, L.C.M. & Pinho, J.T., 2012. "Metering systems and demand-side management models applied to hybrid renewable energy systems in micro-grid configuration," Energy Policy, Elsevier, vol. 45(C), pages 721-729.
    10. Paulus, Moritz & Borggrefe, Frieder, 2011. "The potential of demand-side management in energy-intensive industries for electricity markets in Germany," Applied Energy, Elsevier, vol. 88(2), pages 432-441, February.
    11. Aalami, H.A. & Moghaddam, M. Parsa & Yousefi, G.R., 2010. "Demand response modeling considering Interruptible/Curtailable loads and capacity market programs," Applied Energy, Elsevier, vol. 87(1), pages 243-250, January.
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