CLC number: TM715
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2013-11-18
Cited: 2
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Mahdi Samadi, Mohammad Hossein Javidi, Mohammad Sadegh Ghazizadeh. Modeling the effects of demand response on generation expansion planning in restructured power systems[J]. Journal of Zhejiang University Science C, 2013, 14(12): 966-976.
@article{title="Modeling the effects of demand response on generation expansion planning in restructured power systems",
author="Mahdi Samadi, Mohammad Hossein Javidi, Mohammad Sadegh Ghazizadeh",
journal="Journal of Zhejiang University Science C",
volume="14",
number="12",
pages="966-976",
year="2013",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.C1300008"
}
%0 Journal Article
%T Modeling the effects of demand response on generation expansion planning in restructured power systems
%A Mahdi Samadi
%A Mohammad Hossein Javidi
%A Mohammad Sadegh Ghazizadeh
%J Journal of Zhejiang University SCIENCE C
%V 14
%N 12
%P 966-976
%@ 1869-1951
%D 2013
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.C1300008
TY - JOUR
T1 - Modeling the effects of demand response on generation expansion planning in restructured power systems
A1 - Mahdi Samadi
A1 - Mohammad Hossein Javidi
A1 - Mohammad Sadegh Ghazizadeh
J0 - Journal of Zhejiang University Science C
VL - 14
IS - 12
SP - 966
EP - 976
%@ 1869-1951
Y1 - 2013
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.C1300008
Abstract: demand response is becoming a promising field of study in operation and planning of restructured power systems. More attention has recently been paid to demand response programs. Customers can contribute to the operation of power systems by deployment demand response. The growth of customers’ participation in such programs may affect the planning of power systems. Therefore, it seems necessary to consider the effects of demand response in planning approaches. In this paper, the impact of demand responsiveness on decision making in generation expansion planning is modeled. Avoidance or deferment in installation of new generating units is comprehensively investigated and evaluated by introducing a new simple index. The effects of demand responsiveness are studied from the points of view of both customers and generation companies. The proposed model has been applied to a modified IEEE 30-bus system and the results of the study are discussed. Simulation results show that reducing just 3% of the customers’ demand (due to price elasticity) may result in a benefit of about 10% for customers in the long term.
[1]Aalami, H.A., Parsa Moghaddam, M., Yousefi, G.R., 2010a. Demand response modeling considering interruptible/ curtailable loads and capacity market programs. Appl. Energy, 87(1):243-250.
[2]Aalami, H.A., Parsa Moghaddam, M., Yousefi, G.R., 2010b. Modeling and prioritizing demand response programs in power markets. Electr. Power Syst. Res., 80(4):426-435.
[3]Albadi, M.H., El-Saadany, E.F., 2008. A summary of demand response in electricity markets. Electr. Power Syst. Res., 78(11):1989-1996.
[4]Black, J.W., 2005. Integrating Demand into the United States Electricity System: Technical, Economic, and Regulatory Design for Responsive/Adaptive Load. PhD Thesis, MIT, Cambridge, MA.
[5]Choi, D.G., Thomas, V.M., 2012. An electricity generation planning model incorporating demand response. Energy Pol., 42:429-441.
[6]Greening, L.A., 2010. Demand response resources: who is responsible for implementation in a deregulated market? Energy, 35(4):1518-1525.
[7]Kannan, S., Murugan, P., 2008. Solutions to transmission constrained generation expansion planning using differential evolution. Eur. Trans. Electr. Power, 19(8):1033-1039.
[8]Kannan, S., Slochanal, S.M.R., Padhy, N.P., 2005. Application and comparison of metaheuristic techniques to generation expansion planning problem. IEEE Trans. Power Syst., 20(1):466-475.
[9]Kazerooni, A.K., Mutale, J., 2010. Transmission Network Planning under a Price Based Demand Response Program. Transmission and Distribution Conf. and Exposition, p.1-7.
[10]Kowli, A.S., Gross, G., 2009. Incorporation of Demand Response Resources in Resource Investment Analysis. IEEE PowerTech, p.1-8.
[11]Murugan, P., Kannan, S., Baskar, S., 2009. Application of NSGA-II algorithm to single-objective transmission constrained generation expansion planning. IEEE Trans. Power Syst., 24(4):1790-1797.
[12]Roh, J.H., Shahidehpour, M., Fu, Y., 2007. Security-constrained resource planning in electricity markets. IEEE Trans. Power Syst., 22(2):812-820.
[13]Shahidehpour, M., Yamin, H., Li, Z.Y., 2002. Market Operations in Electric Power Systems. Wiley, New York.
[14]Su, C.L., Kirschen, D., 2009. Quantifying the effect of demand response on electricity markets. IEEE Trans. Power Syst., 24(3):1199-1207.
[15]Tanaka, M., 2006. Real-time pricing with ramping costs: a new approach to managing a steep change in electricity demand. Energy Pol., 34(18):3634-3643.
[16]Wang, X., McDonald, J.R., 1994. Modern Power System Planning. McGraw Hill, New York.
[17]Wang, X., Li, Y.Z., Zhang, S.H., 2004. Oligopolistic equilibrium analysis for electricity markets: a nonlinear complementarity approach. IEEE Trans. Power Syst., 19(3):1348-1355.
[18]Widergren, S.E., 2009. Demand or Request: Will Load Behave? IEEE Power & Energy Society General Meeting, p.1-5.
[19]Wight, D., 2009. National Assessment of Demand Response. Federal Energy Regulatory Commission, Washington.
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