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:: Volume 1, Issue 2 (2-2013) ::
ieijqp 2013, 1(2): 49-57 Back to browse issues page
Dynamic Modeling of Investment on Generation Expansion Planning Considering Demand Response
Mahdi Samadi *1, Mohammad hossein Javidi1, Mohammad Sadegh Ghazizadeh2
1- Ferdowsi University of Mashhad
2- Power and Water University of Technology (PWUT)
Abstract:   (16844 Views)
Attention has been paid to the Demand Response (DR) programs in recent years to improve the power system operation. Demand Response affects market clearing price, which is the main motivation for investment, and thus the trend of investment on generation expansion will be affected. So far, the demand has been considered inelastic for modeling the investment on generation expansion. However, increasing the deployment of smart grid has waived this assumption. In this paper, we have used stochastic dynamic programming for modeling the generation expansion problem. We have considered both the renewable resources and demand response in modeling. In the proposed model, the uncertainty in generation and the accuracy of the price responsive demand performance are considered. In this regard, the market clearing price is determined by interaction between price and the price responsive demand. Some long-term indices are proposed and using the simulation results, they are evaluated. The achieved results, quantitatively confirm that the demand response results in decreasing the price and the outages and therefore improving the reliability.
Keywords: Demand Response, Generation Investment, Renewable energy, Stochastic Dynamic Programming
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Type of Study: Research | Subject: Special
Received: 2012/12/5 | Accepted: 2013/03/3 | Published: 2013/03/3

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Samadi M, Javidi M H, Ghazizadeh M S. Dynamic Modeling of Investment on Generation Expansion Planning Considering Demand Response. ieijqp. 2013; 1 (2) :49-57
URL: http://ieijqp.ir/article-1-43-en.html

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Volume 1, Issue 2 (2-2013) Back to browse issues page
نشریه علمی- پژوهشی کیفیت و بهره وری صنعت برق ایران Iranian Electric Industry Journal of Quality and Productivity
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