Identyfikatory
Warianty tytułu
Języki publikacji
Abstrakty
In a deregulated electricity market, it is important to dispatch the generation in an economical manner and to ensure security under different operating conditions. In this study evolutionary computation based solution for optimal power flow is attempted. Social welfare optimization is taken as the objective function, which includes generation cost, transmission cost and consumer benefit function. Transmission cost is calculated using Bialek’s power flow tracing method. Severity index is applied as a constraint to measure the security. The objective function is calculated for pre and post contingency periods. Real power generations, real power loads and transformer tap settings are selected as control variables. Different bilateral and multilateral conditions are considered for analysis. A Human Group Optimization algorithm is used to find the solution of the problem. The IEEE 30 bus system is taken as a test system.
Słowa kluczowe
Czasopismo
Rocznik
Tom
Strony
227--245
Opis fizyczny
Bibliogr. 26 poz., rys., tab., wykr., wz.
Twórcy
autor
- Department of Electrical and Electronics Engineering Syed Ammal Engineering College, Ramanathapuram, Tamilnadu India-623502
autor
- Department of Electrical and Electronics Engineering Thiagarajar college of Engineering, Madurai Tamilnadu, India-625015
Bibliografia
- [1] Alsac O., Stott B., Optimal load flow with steady state security. IEEE Transactions on Power Apparatus and Systems 93: 745-751 (1974).
- [2] Aguado J. A., Quintana V.H.., Optimal power flows of interconnected power systems. IEEE Power Engineering Society Summer Meeting 2: 814-819 (2009).
- [3] Padhy N.P., Kumari L., Evolutionary Programming Based Economic Power Dispatch Solutions With Independent Power Producers. 2004 IEEE International Conference on Electric Utility Deregulation, Restructuring and Power Technologies (DRPT2004) Hong Kong 1: 172-177 (2004).
- [4] Kumar A., Chanana S., Security Constrained Economic Dispatch with Secure Bilateral Transactions in Hybrid Electricity Markets. Power System Technology and IEEE Power India Conference, pp. 1-6 (2008).
- [5] Cheng J.W.M., McGills D.T., Galiana F.D., Probabilistic security analysis of bilateral transactions in a deregulated environment. IEEE Transaction on Power systems 14(3): 1153-1159 (1999).
- [6] Raglend J., Karthikeyan P., Kothari D.P., Comparison of Intelligent Techniques to Solve Economic Load Dispatch with Bilateral and Multilateral Transactions. TENCON 2008 IEEE Region 10 Conference, Hyderabad, pp. 1-6, 19-21(2008).
- [7] Allen Wood J., Wollenberg B.F., Power Generation Operation and Control. Wiley (1996).
- [8] Udupa A.N., Purushothama G.K., Parthasarathy K., Thukaram D., A fuzzy control for network overload alleviation. Electr. Power Energy Syst. 23: 119-129 (2001).
- [9] Laurent Lenoir, Innocent Kamwa and Louis-A. Dessaint., Overload Alleviation with Preventive- Corrective Static Security Using Fuzzy Logic. IEEE Trans. Power Syst. 24(1): 134-145 (2009).
- [10] Devaraj, Yegnanarayana B., Genetic-algorithm-based optimal power flow for security enhancement. IEE Proc.-Gener. Transm. Distrib. 152(6): 899-905 (2005).
- [11] Shahidehpour M., Yamin H., Li H., Market Operation in Electric Power Systems. John Wiley & Sons Inc., New York, USA (2002).
- [12] Bialek J.W., Tracing the flow of electricity. IEE Proceedings Generation Transmission and Distribution 143 (July (4)) 313-320 (1996).
- [13] Kirschen D., Allan R., Strbac.G., Contribution of individual generations to loads and flows. IEEE Transactions on Power Systems 12 (February (1)) 52-60 (1997).
- [14] Bialek J.W., Kattuman., Real and reactive power tracking: Proof of concept and feasibility study. Electric Power Research Institute, Tech. Rep. TR112416 (1999).
- [15] Pablo Onate, Juan M. Ramirez, Carlos A. Coello Coello., An optimal power flow plus transmission costs solution. Electric Power Systems Research 79(8): 1240-1246 (2009).
- [16] Lai L.L., Yokohoma R., Zhao M., Improved Genetic Algorithm for Optimal Power Flow Under Both Normal and Contingent Operation States. International journal on Electrical Power Energy System 19: 287-291 (1997).
- [17] Abido M.A., Optimal Power Flow Using Particle Swarm Optimization. International journal on Electrical Power and Energy Systems 17(2): 563-571 (2002).
- [18] Dai, Zhu, Chen., Seeker optimization algorithm. [in:] Computational Intelligence and Security 4456 Lecture Notes in Artificial Intelligence, Y. Wang, Y. Cheung, H. Liu (Eds.) Berlin, Germany: Springer-Verlag, pp. 167-176 (2007).
- [19] Chaohua Dai, Weirong Chen, Yunfang Zhu., Seeker optimization algorithm for digital IIR filterdesign. IEEE Transactions on Industrial Electronics 57(5): 1710-1718 (2009).
- [20] Chaohua Dai, Weirong Chen, Yunfang Zhu, Xuexia Zhang., Seeker optimization algorithm for optimal reactive power dispatch. IEEE Transactions on Power Systems 24(3): 1218-1231 (2009).
- [21] Chaohua Dai, Weirong Chen, Yunfang Zhu, Xuexia Zhang., Reactive power dispatch considering voltage stability with seeker optimization algorithm Electric Power System Research 79(10): 1462- 1471 (2009).
- [22] Chaohua Dai, Weirong Chen, Lixiang Li et al., Seeker optimization algorithm for parameter estimation of time-delay chaotic systems. Physical Review E, 83, 036203 (2011).
- [23] Chaohua Dai, Weirong Chen, Lili Ran, Yi Zhang, Yu Du., Human Group Optimizer with Local Search. Lecture Notes in Computer Science 6728: 310-320 (2011).
- [24] Condren J,. Gendra T.W., Damrongkulkamjorn P., Optimal power flow with expected security costs. IEEE Transactions on Power System 21(2): 541-547 (2006).
- [25] Zimmerman R., Gan D., MATPOWER: A Matlab power system simulation package, Software package available at ttp://www.pserc.cornell.edu/matpower
- [26] Gnanadass R., Pathey N.P., Manivannan., Assessment of available transfer capability for practical power systems with combined economic emission dispatch. Electric Power Systems Research 69: 267-276 (2004).
Typ dokumentu
Bibliografia
Identyfikator YADDA
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