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The Effect of Different Non-linear Demand Response Models Considering Incentive and Penalty on Transmission Expansion Planning

Author

Listed:
  • Amir Sadegh Zakeri

    (Amirkabir University of Technology, Iran.)

  • Oveis Asgari Gashteroodkhani

    (University of Nevada, Reno)

  • Iman Niazazari

    (University of Nevada, USA.)

  • Hossein Askarian-Abyaneh

    (Amirkabir University of Technology, Iran.)

Abstract

The Transmission Expansion Planning (TEP) problem involves adding new lines to the existing electrical transmission network in order to meet the electrical demand requirements. Demand Response (DR) plays an important role in solving the TEP problem due to the delay in the investment costs. Researchers usually focus on the linear model of DR, while the focus on nonlinear models including power, exponential and logarithmic of DR is small. In this paper and in order to understand which model gives the realistic results, the linear model of DR is studied simultaneously with nonlinear models including power, exponential and logarithmic of DR. Moreover, the effect of incentive and penalty which has been neglected in the studies, is investigated. The study is investigated based on the viewpoint of different participants of the market including Independent System Operator (ISO), Customers and Utilities. In order to prioritize and select the most effective DR program, five characteristics including Peak Reduction, Energy Consumption, Load Factor, Peak to Valley and Customer’s Total Cost are extracted from the load curve. Then, using the weighting coefficients obtained by Entropy technique and implementing the TOPSIS and AHP technique, different DR programs are prioritized.

Suggested Citation

  • Amir Sadegh Zakeri & Oveis Asgari Gashteroodkhani & Iman Niazazari & Hossein Askarian-Abyaneh, 2019. "The Effect of Different Non-linear Demand Response Models Considering Incentive and Penalty on Transmission Expansion Planning," European Journal of Electrical Engineering and Computer Science, European Open Science, vol. 3(1), January.
  • Handle: RePEc:epw:ejece0:v:3:y:2019:i:1:id:19057
    DOI: 10.24018/ejece.2019.3.1.57
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