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Year 2018, Volume: 13 Issue: 3, 253 - 263, 23.07.2018

Abstract

References

  • 1. Salomon, K.R. and Silva Lora, E.E., (2009). Estimate of the Electric Energy Generating Potential for Different Sources of Biogas in Brazil, Biomass and Bioenergy, 33(9), 1101-1107.
  • 2. Energy Innovation. Comparing the Costs of Renewable and Conventional Energy Sources. [online] Available at: http://energyinnovation.org/2015/02/07/levelized-cost-of-energy/ (Accessed 26 Jun. 2018).
  • 3. Yenilenebilir Yaşam. Türkiye Elektrik Enerjisi Kurulu Gücünün Yıllara Göre Gelişimi. Available at: http://yenilenebiliryasam.com/2015/12/turkiye-elektrik-enerjisi-kurulu.html [Accessed 26 Jun. 2018].
  • 4. Gligor, A., Dumitru, C.D., and Grif, H.Ș., (2009). Power Quality Disturbance and Power Flow Analysis in a Hybrid Renewable Energy System using Matlab, presented at the Interdisciplinarity in Engineering International Conference, Petru Maior University of Tîrgu Mureş, Romania.
  • 5. Cristaldi, L. and Ferrero, A., (1995). Harmonic Power Flow Analysis for the Measurement of the Electric Power Quality, IEEE Transactions on Instrumentation and Measurement, 44(3), 683-685.
  • 6. Erseghe, T., (2014). A Distributed Algorithm for Fast Optimal Power Flow Regulation in Smart Grids, IEEE International Conference on Smart Grid Communications (SmartGridComm), 31-36.
  • 7. Remolino, S. and Paredes, H.F.R., (2016). An Efficient Method for Power Flow Calculation Applied to the Reconfiguration of Radial Distribution Systems, 2016 IEEE PES Transmission & Distribution Conference and Exposition-Latin America (PES T&D-LA),1-6.
  • 8. Kennedy, J. and Eberhart, R., (1995). Particle Swarm Optimization, Neural Networks, IEEE International Conference, 4, 1942-1948.
  • 9. Karaboga, D. and Basturk, B., (2007). A Powerful and Efficient Algorithm for Numerical Function Optimization: Artificial Bee Colony (ABC) Algorithm, Journal of Global Optimization, 39(3), 459-471.
  • 10. Rashedi, E., Nezamabadi-Pour, H., and Saryazdi, S., (2009). GSA: A Gravitational Search Algorithm, Information Sciences, 179(13), 2232-2248.
  • 11. Rao, R.V., Savsani, V.J., and Vakharia, D.P., (2011). Teaching–Learning-Based Optimization: A Novel Method for Constrained Mechanical Design Optimization Problems, Computer-Aided Design, 43(3), 303-315.
  • 12. Wang, M.Q., Han, X.S., Yang, M., and Wang, M.X., (2014). Dynamic Economic Dispatch with Valve Point Effect, Prohibited Operation Zones, and Multiple Fuel Option, IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC), 1-5.
  • 13. Bentouati, B., Chettih, S., and Chaib, L., (2017). Interior Search Algorithm for Optimal Power Flow with Non-Smooth Cost Functions, Cogent Engineering, 4(1), 1-17.
  • 14. Sinha, N., Chakrabarti, R., and Chattopadhyay, P.K., (2003). Evolutionary Programming Techniques for Economic Load Dispatch, IEEE Transactions on Evolutionary Computation, 7(1), 83-94.
  • 15. Özyön, S., Yaşar, C., and Temurtaş, H., (2011). Differential Evolution Algorithm Approach to Nonconvex Economic Power Dispatch Problems with Valve Point Effect, International Advanced Technologies Symposium (IATS’11), Elazığ, Turkey.
  • 16. Özyön, S., Yaşar, C., and Temurtaş, H., (2012). Solution to Nonconvex Economic Dispatch Problem with Valve Point Effect by Harmony Search Algorithm, DPÜ Fen Bilimleri Enstitüsü Dergisi, 28, 35-52.
  • 17. Irving, M.R. and Sterling, M.J.H., (1983). Economic Dispatch of Active Power with Constraint Relaxation, IEE Proceedings C - Generation, Transmission and Distribution, 130(4), 172-177.
  • 18. Nadeem Malik, T., Ul Asar, A., Wyne, M.F., and Akhtar, S., (2010). A New Hybrid Approach for the Solution of Nonconvex Economic Dispatch Problem with Valve-Point Effects, Electric Power Systems Research, 80(9), 1128-1136.
  • 19. Chowdhury, B.H. and Rahman, S., (1990). A Review of Recent Advances in Economic Dispatch, IEEE Transactions on Power Systems, 5(4), 1248-1259.
  • 20. Chaturvedi, K.T., Pandit, M., and Srivastava, L., (2009). Particle Swarm Optimization with Time Varying Acceleration Coefficients for Non-Convex Economic Power Dispatch, International Journal of Electrical Power & Energy Systems, 31(6), 249-257.
  • 21. Walters, D.C. and Sheble, G.B., (1993). Genetic Algorithm Solution of Economic Dispatch with Valve Point Loading, IEEE Transactions on Power Systems, 8(3), 1325-1332.

SOLUTION OF ECONOMIC DISPATCH PROBLEM WITH THE VALVE-POINT LOAD EFFECT BY META-HEURISTIC ALGORITHMS

Year 2018, Volume: 13 Issue: 3, 253 - 263, 23.07.2018

Abstract

Economic dispatch problem (EDP) is a balance problem between the
minimum fuel cost and demanded power within the active power limits. In this
study, economic dispatch problem was implemented by the Particle Swarm
Optimization (PSO), Artificial Bee Colony (ABC), Teaching Learning Based Optimization
(TLBO) and Gravitational Search Algorithm (GSA) on the power systems of 850 MW
including 3 active bus with valve-point load effect, 1800 MW including 13
active bus with valve-point load effect to solve the optimum fuel cost and run
time for a comparison. Minimum fuel cost in 3 active bus power system was
calculated as 8234.086 $/h in 3.28 s by the TLBO method. In 13 active bus power
system, it is calculated as 18019.15 $/h in 8.95 s by the PSO method.    

References

  • 1. Salomon, K.R. and Silva Lora, E.E., (2009). Estimate of the Electric Energy Generating Potential for Different Sources of Biogas in Brazil, Biomass and Bioenergy, 33(9), 1101-1107.
  • 2. Energy Innovation. Comparing the Costs of Renewable and Conventional Energy Sources. [online] Available at: http://energyinnovation.org/2015/02/07/levelized-cost-of-energy/ (Accessed 26 Jun. 2018).
  • 3. Yenilenebilir Yaşam. Türkiye Elektrik Enerjisi Kurulu Gücünün Yıllara Göre Gelişimi. Available at: http://yenilenebiliryasam.com/2015/12/turkiye-elektrik-enerjisi-kurulu.html [Accessed 26 Jun. 2018].
  • 4. Gligor, A., Dumitru, C.D., and Grif, H.Ș., (2009). Power Quality Disturbance and Power Flow Analysis in a Hybrid Renewable Energy System using Matlab, presented at the Interdisciplinarity in Engineering International Conference, Petru Maior University of Tîrgu Mureş, Romania.
  • 5. Cristaldi, L. and Ferrero, A., (1995). Harmonic Power Flow Analysis for the Measurement of the Electric Power Quality, IEEE Transactions on Instrumentation and Measurement, 44(3), 683-685.
  • 6. Erseghe, T., (2014). A Distributed Algorithm for Fast Optimal Power Flow Regulation in Smart Grids, IEEE International Conference on Smart Grid Communications (SmartGridComm), 31-36.
  • 7. Remolino, S. and Paredes, H.F.R., (2016). An Efficient Method for Power Flow Calculation Applied to the Reconfiguration of Radial Distribution Systems, 2016 IEEE PES Transmission & Distribution Conference and Exposition-Latin America (PES T&D-LA),1-6.
  • 8. Kennedy, J. and Eberhart, R., (1995). Particle Swarm Optimization, Neural Networks, IEEE International Conference, 4, 1942-1948.
  • 9. Karaboga, D. and Basturk, B., (2007). A Powerful and Efficient Algorithm for Numerical Function Optimization: Artificial Bee Colony (ABC) Algorithm, Journal of Global Optimization, 39(3), 459-471.
  • 10. Rashedi, E., Nezamabadi-Pour, H., and Saryazdi, S., (2009). GSA: A Gravitational Search Algorithm, Information Sciences, 179(13), 2232-2248.
  • 11. Rao, R.V., Savsani, V.J., and Vakharia, D.P., (2011). Teaching–Learning-Based Optimization: A Novel Method for Constrained Mechanical Design Optimization Problems, Computer-Aided Design, 43(3), 303-315.
  • 12. Wang, M.Q., Han, X.S., Yang, M., and Wang, M.X., (2014). Dynamic Economic Dispatch with Valve Point Effect, Prohibited Operation Zones, and Multiple Fuel Option, IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC), 1-5.
  • 13. Bentouati, B., Chettih, S., and Chaib, L., (2017). Interior Search Algorithm for Optimal Power Flow with Non-Smooth Cost Functions, Cogent Engineering, 4(1), 1-17.
  • 14. Sinha, N., Chakrabarti, R., and Chattopadhyay, P.K., (2003). Evolutionary Programming Techniques for Economic Load Dispatch, IEEE Transactions on Evolutionary Computation, 7(1), 83-94.
  • 15. Özyön, S., Yaşar, C., and Temurtaş, H., (2011). Differential Evolution Algorithm Approach to Nonconvex Economic Power Dispatch Problems with Valve Point Effect, International Advanced Technologies Symposium (IATS’11), Elazığ, Turkey.
  • 16. Özyön, S., Yaşar, C., and Temurtaş, H., (2012). Solution to Nonconvex Economic Dispatch Problem with Valve Point Effect by Harmony Search Algorithm, DPÜ Fen Bilimleri Enstitüsü Dergisi, 28, 35-52.
  • 17. Irving, M.R. and Sterling, M.J.H., (1983). Economic Dispatch of Active Power with Constraint Relaxation, IEE Proceedings C - Generation, Transmission and Distribution, 130(4), 172-177.
  • 18. Nadeem Malik, T., Ul Asar, A., Wyne, M.F., and Akhtar, S., (2010). A New Hybrid Approach for the Solution of Nonconvex Economic Dispatch Problem with Valve-Point Effects, Electric Power Systems Research, 80(9), 1128-1136.
  • 19. Chowdhury, B.H. and Rahman, S., (1990). A Review of Recent Advances in Economic Dispatch, IEEE Transactions on Power Systems, 5(4), 1248-1259.
  • 20. Chaturvedi, K.T., Pandit, M., and Srivastava, L., (2009). Particle Swarm Optimization with Time Varying Acceleration Coefficients for Non-Convex Economic Power Dispatch, International Journal of Electrical Power & Energy Systems, 31(6), 249-257.
  • 21. Walters, D.C. and Sheble, G.B., (1993). Genetic Algorithm Solution of Economic Dispatch with Valve Point Loading, IEEE Transactions on Power Systems, 8(3), 1325-1332.
There are 21 citations in total.

Details

Primary Language Turkish
Subjects Engineering
Journal Section Articles
Authors

Mehmet Fatih Tefek This is me

Mehmet Güçyetmez 0000-0003-2191-8665

Harun Uğuz

Publication Date July 23, 2018
Published in Issue Year 2018 Volume: 13 Issue: 3

Cite

APA Tefek, M. F., Güçyetmez, M., & Uğuz, H. (2018). SOLUTION OF ECONOMIC DISPATCH PROBLEM WITH THE VALVE-POINT LOAD EFFECT BY META-HEURISTIC ALGORITHMS. Technological Applied Sciences, 13(3), 253-263.
AMA Tefek MF, Güçyetmez M, Uğuz H. SOLUTION OF ECONOMIC DISPATCH PROBLEM WITH THE VALVE-POINT LOAD EFFECT BY META-HEURISTIC ALGORITHMS. Technological Applied Sciences. July 2018;13(3):253-263.
Chicago Tefek, Mehmet Fatih, Mehmet Güçyetmez, and Harun Uğuz. “SOLUTION OF ECONOMIC DISPATCH PROBLEM WITH THE VALVE-POINT LOAD EFFECT BY META-HEURISTIC ALGORITHMS”. Technological Applied Sciences 13, no. 3 (July 2018): 253-63.
EndNote Tefek MF, Güçyetmez M, Uğuz H (July 1, 2018) SOLUTION OF ECONOMIC DISPATCH PROBLEM WITH THE VALVE-POINT LOAD EFFECT BY META-HEURISTIC ALGORITHMS. Technological Applied Sciences 13 3 253–263.
IEEE M. F. Tefek, M. Güçyetmez, and H. Uğuz, “SOLUTION OF ECONOMIC DISPATCH PROBLEM WITH THE VALVE-POINT LOAD EFFECT BY META-HEURISTIC ALGORITHMS”, Technological Applied Sciences, vol. 13, no. 3, pp. 253–263, 2018.
ISNAD Tefek, Mehmet Fatih et al. “SOLUTION OF ECONOMIC DISPATCH PROBLEM WITH THE VALVE-POINT LOAD EFFECT BY META-HEURISTIC ALGORITHMS”. Technological Applied Sciences 13/3 (July 2018), 253-263.
JAMA Tefek MF, Güçyetmez M, Uğuz H. SOLUTION OF ECONOMIC DISPATCH PROBLEM WITH THE VALVE-POINT LOAD EFFECT BY META-HEURISTIC ALGORITHMS. Technological Applied Sciences. 2018;13:253–263.
MLA Tefek, Mehmet Fatih et al. “SOLUTION OF ECONOMIC DISPATCH PROBLEM WITH THE VALVE-POINT LOAD EFFECT BY META-HEURISTIC ALGORITHMS”. Technological Applied Sciences, vol. 13, no. 3, 2018, pp. 253-6.
Vancouver Tefek MF, Güçyetmez M, Uğuz H. SOLUTION OF ECONOMIC DISPATCH PROBLEM WITH THE VALVE-POINT LOAD EFFECT BY META-HEURISTIC ALGORITHMS. Technological Applied Sciences. 2018;13(3):253-6.