Abstract
In restructured environment, with ever-increasing demand of electricity consumption and increasing open access, transmission line congestion is quite frequent. For maximum benefit and mitigation of congestion, proper sizing and location of distributed generators are necessary. This paper presents a simple method for optimal sizing and optimal placement of distributed generators. In this paper two methods are proposed for solving congestion management problem in a day ahead electricity market. In the first method the objectives considered are the minimization of the congestion cost and transmission line loss so as to relieve congestion in the system. These two objectives: (i) the cost of installation of DG and congestion index (ii) transmission line loss and congestion index, are considered to form a single objective and the problem is solved using Real coded Genetic Algorithm. This method gives only one compromised solution considering both the objectives, which does not provide any choice to the operators. Hence in the second method, both the objectives: congestion cost and transmission line loss are considered separately and solved as a multi-objective problem, using NSGA II method. This method gives a set of pareto optimal solution, so operator has a flexibility in choosing the solution based on the need. The proposed problem is implemented on IEEE 14 bus system.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Jibiki, T., Sakakibara, E., Iwamoto, S.: Line flow sensitivities of line reactances for congestion management. In: IEEE Power Eng. Society Meeting, vol. 24, pp. 1–6 (June 2007)
Mithulananthan, N., Acharya, N.: Locating series FACTS devices for congestion management in deregulated electricity market. Elect. Power Syst. Res. 77, 352–360 (2007)
Shrestha, G.B., Fonseka, P.A.J.: Congestion-Driven transmission expansion in competitive power markets. IEEE Trans. Power Syst. 19, 1658–1665 (2004)
Kaymaz, P., Valenzuela, J., Park, C.S.: Transmission congestion and competition on power generation expansion. IEEE Trans. Power Syst. 22(1), 156–163 (2007)
Liu, J., Salama, M.M.A., Mansour, R.R.: Identify the Impact of Distributed Resources on Congestion Management. IEEE Trans. on Power Delivery 20 (2005)
Gil, H.A., Joos, G.: Models for quantifying the economic benefits of distributed generation. IEEE Trans. on Power Syst. 23(2), 327–335 (2008)
Chiradeja, P., Ramakumar, R.: An approach to quantify the technical benefits of distributed generation. IEEE Trans. Power Syst. 19(4), 764–773 (2004)
Ahmadigorji, M., Abbaspour T.F., A., Rajabi-Ghahnavieh, A., Fotuhi-Firuzabad, M.: Optimal DG placement in distribution systems using cost/worth analysis. Proceedings of World Academy of Science, Engg. and Tech. 37, 746–753 (2009)
Afkousi-Paqaleh, M., Abbaspour T.F., A., Rashidinejad, M.: Optimal locating and sizing of distributed generation for congestion management via harmony search algorithm. In: Proc. Int. Conf. on Elec. Power and Energy Conversion Syst., UAE (November 2009)
Afkousi-Paqaleh, M., Abbaspour, A., Rashidinejad, M., Lee, K.Y.: Optimal Placement and Sizing of Distributed Resources for Congestion Management Considering Cost/Benefit Analysis. In: 2010 IEEE Power and Energy Society General Meeting (2010)
Deb, K., Agrawal, S., Pratap, A., Meyarivan, T.: A Fast Elitist Non-dominated Sorting Genetic Algorithm for Multi-objective Optimization: NSGA-II. In: Deb, K., Rudolph, G., Lutton, E., Merelo, J.J., Schoenauer, M., Schwefel, H.-P., Yao, X. (eds.) PPSN 2000. LNCS, vol. 1917, pp. 849–858. Springer, Heidelberg (2000)
Zimmerman, R.D., Gan, D.: MATPOWER: A Matlab Power System, Package, Ver.3.2, Power System Engineering Research Center, Cornell University (1997), http://www.pserc.cornell.edu//Matpower
Ghosh, S., Ghoshal, S.P., Ghosh, S.: Optimal sizing and placement of distributed generation in a network system. Elect. Power and Energy Sys. 32, 849–856 (2010)
Zhao, S.Z., Suganthan, P.N., Zhang, Q.: Decomposition Based Multiobjective Evolutionary Algorithm with an Ensemble of Neighborhood Sizes. IEEE Trans. on Evolutionary Computation 16(3), 442–446 (2012)
Mallipeddi, R., Suganthan, P.N., Pan, Q.K., Tasgetiren, M.F.: Differential evolution algorithm with ensemble of parameters and mutation strategies. Applied Soft Computing 11(2), 1679–1696 (2011), doi:10.1016/j.asoc.2010.04.024
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Vijayakumar, K., Jegatheesan, R. (2012). Optimal Location and Sizing of DG for Congestion Management in Deregulated Power Systems. In: Panigrahi, B.K., Das, S., Suganthan, P.N., Nanda, P.K. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2012. Lecture Notes in Computer Science, vol 7677. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35380-2_79
Download citation
DOI: https://doi.org/10.1007/978-3-642-35380-2_79
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-35379-6
Online ISBN: 978-3-642-35380-2
eBook Packages: Computer ScienceComputer Science (R0)