Impacts of Wind Power Integration on Generation Dispatch in Power Systems

- Journal title : Journal of Electrical Engineering and Technology
- Volume 8, Issue 3, 2013, pp.453-463
- Publisher : The Korean Institute of Electrical Engineers
- DOI : 10.5370/JEET.2013.8.3.453

Title & Authors

Impacts of Wind Power Integration on Generation Dispatch in Power Systems

Lyu, Jae-Kun; Heo, Jae-Haeng; Kim, Mun-Kyeom; Park, Jong-Keun;

Lyu, Jae-Kun; Heo, Jae-Haeng; Kim, Mun-Kyeom; Park, Jong-Keun;

Abstract

The probabilistic nature of renewable energy, especially wind energy, increases the needs for new forms of planning and operating with electrical power. This paper presents a novel approach for determining the short-term generation schedule for optimal operations of wind energy-integrated power systems. The proposed probabilistic security-constrained optimal power flow (P-SCOPF) considers dispatch, network, and security constraints in pre- and post-contingency states. The method considers two sources of uncertainty: power demand and wind speed. The power demand is assumed to follow a normal distribution, while the correlated wind speed is modeled by the Weibull distribution. A Monte Carlo simulation is used to choose input variables of power demand and wind speed from their probability distribution functions. Then, P-SCOPF can be applied to the input variables. This approach was tested on a modified IEEE 30-bus system with two wind farms. The results show that the proposed approach provides information on power system economics, security, and environmental parameters to enable better decision-making by system operators.

Keywords

Wind power integration;Correlated wind speed;Weibull distribution;Monte carlo simulation (MCS);Probabilistic security-constrained optimal power flow (P-SCOPF);

Language

English

Cited by

1.

Optimization of Wind Power Dispatch to Minimize Energy Storage System Capacity,;;

2.

Prediction of Wind Power by Chaos and BP Artificial Neural Networks Approach Based on Genetic Algorithm,;;;

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References

1.

J. Kabouris, F.D. Kanellos, "Impacts of Large Scale Wind Penetration on Energy Supply Industry", Energies, Vol. 2, No. 4, pp. 1031-1041, Nov 2009.

2.

A. Franco, P. Salza, "Strategies for optimal penetration of intermittent renewables in complex energy systems based on techno-operational objectives", Renewable Energy, Vol. 36, No. 2, pp. 743-753, Aug 2010.

3.

B. Borkowska, "Probabilistic load flow". IEEE Trans Power Appa Syst, Vol. 93, No. 3, pp. 752-755, May 1974.

4.

C.L. Su, "Probabilistic load flow computation using point estimate method", IEEE Trans Power Syst, Vol. 20, No. 4, pp. 1843-1851, Nov 2005.

5.

G. Verbic, C.A. Canizares, "Probabilistic optimal power flow in electricity markets based on a twopoint estimate method. IEEE Trans Power Sys, Vol. 21, No. 4, pp. 1883-1893, Nov 2006.

6.

H. Ahmadi, H. Ghasemi, "Probabilistic optimal power flow incorporating wind power using point estimate methods. 10th Int Conf Envir Elec Eng May 2011.

7.

A. Schellenberg, W. Rosehart, J. Aguado, "Cumulantbased probabilistic optimal power with gaussian and gamma distribution". IEEE Trans Power Syst, Vol. 20, No. 2, pp. 773-781, May 2005.

8.

X. Li, Y. Li, Y, S. Zhang, "Analysis of probabilistic optimal power flow taking account of the variation of load power", IEEE Trans Power Syst, Vol. 23, No. 3, pp. 992-999, Aug 2008.

9.

J. Wang, M. Shahidehpour, Z. Li, "Security-constrained unit commitment with volatile wind power generation", IEEE Trans Power Syst, Vol. 23, No. 3, pp. 1319- 1327, Aug 2008.

10.

J. K. Lyu, M. K. Kim, Y. T. Yoon, J. K. Park, "A new approach to security-constrained generation scheduleing of large-scale power systems with a piecewise linear ramping model", Int J Electric Power Energy Syst, Vol. 34, No. 1, pp. 121-131, Jan 2012.

11.

F. Capitanescu, J.L.M. Ramos, P. Panciatici, D. Kirschen, A.M. Marcolini, L. Platbrood, L. Wehenkel, "State-of-the-are, challenges, and future trends in security constrained optimal power flow. Elect Power Syst Res, Vol. 81, No. 8, pp. 1731-1741, Aug 2011.

12.

P. Somasundaram, K. Kuppusamy, "Application of evolutionary programming to security constrained economic dispatch", Int J Electric Power Energy Syst, Vol. 27, No. 5-6, pp. 343-351, July 2005.

13.

R. Goic, J. Krstulovic, D. Jakus, "Simulation of aggregate wind farm short-term production variations", Renewable Energy, Vol. 35, No. 11, pp. 2602-2609, Nov 2010.

14.

S. H. Isidoro, E. E. Guillermo, A. O. Manuel, "Wind farm electrical power production model for load flow analysis. Renewable Energy, Vol. 36, No. 3, pp. 1008- 1013, Mar 2011.

15.

A. Feijoo, D. Villanueva, J. L. Pazos, R. Sobolewski, "Simulation of correlated wind speeds: a review", Renewable and Sustainable Energy Reviews, Vol. 15, No. 6, pp. 2826-2832, Aug 2011.

16.

D. Villanueva, A. Feijoo, J.L. Pazos, "Probabilistic load flow considering correlation between generation, loads and wind power", Smart grid and Renewable Energy, Vol. 2, No.1, pp. 12-20, Feb 2011.

17.

F. Freris, D. Infield, "Renewable energy in power systems. New York; John Wiley and Sons: 2008.

18.

P. Ramirez, J. A. Carta, "Influence of the data sampling interval in the estimation of the parameters of the Weibull wind speed probability density distribution: a case study. Energy Conv Mana, Vol. 46, Nol. 15-16, pp. 2419-2438, Sep 2005.

19.

S.A. Akdag, A. Dinler, "A new method to estimate Weibull parameters for wind energy applications", Energy Conv Mana, Vol. 50, No. 7, pp. 1761-1766, July 2009.

20.

M.A. Abido, "Multiobjective evolutionary algorithms for electric power dispatch problem", IEEE Trans Evol Comp, Vol. 10, No. 3, pp. 315-329, June 2006.

21.

H. Wei, H. Sasaki, J. Kubokawa, R. Yokoyama, "An interior point nonlinear programming for optimal power flow problems with a novel data structure. Power Systems, IEEE Trans Power Syst, Vol. 13, No. 3, pp. 870-877, Aug 1998.