ISSN E 2409-2770
ISSN P 2521-2419

Economic Dispatch Solution for Generating Units through Optimization


 


Vol. 7, Issue 09, PP. 298-304, September 2020

DOI

Keywords: Optimization, ELD, GAM

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The complex nature of the modern power system is because of the interconnection of the generating units and day by day increased load demand. The main purpose of the power system is to tantalize the load needs and generate reliable and cheap energy i.e. cost of generation should be optimum i.e. operating every generating unit in such a way to optimize the cost. The cost function of every generating unit is different from other generating unit, so load has to be divided among various generating units to obtain optimum generation. The optimization of power system is done by Economic load dispatch (ELD). ELD is of immense importance in power system operation and planning (PSOP). The primary purpose of ELD is to pacify the load needs at lowest cost while satiating all kind of equality and inequality constraints. Power system has highly non-linear input output characteristics because of different generation constraints. In ELD cost function of each and every generating unit is equated as quadratic function. Numerous methods have been devised to figure out ELD problem incorporating conventional methods like Lambda iteration method and Gradient method, and artificial intelligent method like Particle Swarm Optimization, Generic Algorithms etc. In this thesis optimization of generating units is done through General Algebraic Modelling System (GAMS). GAMS is a modelling system used for mathematical programming and optimization on a large scale. It helps to develop a mathematical model similar to their corresponding mathematical expression and gives more accurate results.


  1. Muhammad Nazeer, muhammadnaxeer@gmail.com, Department of Electrical Energy System Engineering, US-Pakistan Center for Advanced Studies in Energy (US-PCASE), UET Peshawar, .
  2. Shazmina Jamil , shazminajamil@yahoo.com, Department of Electrical Energy System Engineering, US-Pakistan Center for Advanced Studies in Energy (US-PCASE), UET Peshawar, Pakistan.
  3. Mohsin Mohsin, malakmohsin5533@gmail.com, Department of Electrical Energy System Engineering, US-Pakistan Center for Advanced Studies in Energy (US-PCASE), UET Peshawar, .
  4. Jibran Ullah Khan, jibrank787@gmail.com, Department of Electrical Energy System Engineering, US-Pakistan Center for Advanced Studies in Energy (US-PCASE), UET Peshawar, .

Muhammad Nazeer Shazmina Jamil Mohsin Jibran Ullah Khan "Economic Dispatch Solution for Generating Units through Optimization" International Journal of Eng Vol. 7 Issue 09 PP. 298-304 September 2020 https://doi.org/10.34259/ijew.20.709298304


[1]         T. Phase et al., “University of Nairobi School of Engineering Department of Electrical and Information Engineering,” no. 100, 2015.

[2]         P. Systems and E. Drives, “ANALYSIS AND COMPARISON OF ECONOMIC LOAD DISPATCH USING GENETIC ALGORITHM AND Master of Engineering,” no. July, 2011.

[3]         “SOULTION TO CONSTRAINED ECONOMIC LOAD DISPATCH SOLUTION TO CONSTRAINED ECONOMIC LOAD Department of Electrical Engineering National Institute of Technology Rourkela-769008 ( ODISHA ) May-2013.”

[4]         B. Sahu, A. Lall, S. Das, and T. Manoj Kumar Patra, “Economic Load Dispatch in Power System using Genetic Algorithm,” Int. J. Comput. Appl., vol. 67, no. 7, pp. 17–22, 2013.

[5]         P. Control, “Particle Swarm Optimisation Applied To Economic,” Electr. Eng.

[6]         E. Engineering, “Economic Load Dispatch for Ieee 30-Bus System Using Pso,” pp. 1–40.

[7]         C. Kuo, “A novel string structure for economic dispatch problems with practical constraints,” Energy Convers. Manag., vol. 49, no. 12, pp. 3571–3577, 2008.

[8]         M. Nazari-heris, B. Mohammadi-ivatloo, and G. B. Gharehpetian, “A comprehensive review of heuristic optimization algorithms for optimal combined heat and power dispatch from economic and environmental perspectives,” Renew. Sustain. Energy Rev., no. April, pp. 1–16, 2017.

[9]         Y. A. Gherbi, H. Bouzeboudja, and F. Z. Gherbi, “The combined economic environmental dispatch using new hybrid metaheuristic,” Energy, vol. 115, pp. 468–477, 2016.

[10]       H. Shayeghi and A. Ghasemi, “IJTPE Journal APPLICATION OF MOPSO FOR ECONOMIC LOAD DISPATCH SOLUTION WITH TRANSMISSION LOSSES,” Int. J., no. March, pp. 27–34, 2012.

[11]       A. A. Abou El Ela, M. A. Abido, and S. R. Spea, “Differential evolution algorithm for emission constrained economic power dispatch problem,” Electr. Power Syst. Res., vol. 80, no. 10, pp. 1286–1292, 2010.

[12]       T. Yalcinoz, H. Altun, and M. Uzam, “Economic dispatch solution using a genetic algorithm based on arithmetic crossover,” 2001 IEEE Porto Power Tech Proc., vol. 2, no. 4, pp. 153–156, 2001.

[13]       D. kuo He, F. li Wang, and Z. zhong Mao, “Hybrid genetic algorithm for economic dispatch with valve-point effect,” Electr. Power Syst. Res., vol. 78, no. 4, pp. 626–633, 2008.

[14]       V. Hosseinnezhad and E. Babaei, “Electrical Power and Energy Systems Economic load dispatch using h -PSO,” Int. J. Electr. POWER ENERGY Syst., vol. 49, pp. 160–169, 2013.

[15]       B. K. Panigrahi, V. R. Pandi, and S. Das, “Adaptive particle swarm optimization approach for static and dynamic economic load dispatch,” vol. 49, pp. 1407–1415, 2008.

[16]       B. Mohammadi-ivatloo, A. Rabiee, A. Soroudi, and M. Ehsan, “Electrical Power and Energy Systems Iteration PSO with time varying acceleration coefficients for solving non-convex economic dispatch problems,” Int. J. Electr. Power Energy Syst., vol. 42, no. 1, pp. 508–516, 2012.

[17]       B. Mohammadi-ivatloo, M. Moradi-dalvand, and A. Rabiee, “Combined heat and power economic dispatch problem solution using particle swarm optimization with time varying acceleration coefficients,” Electr. Power Syst. Res., vol. 95, pp. 9–18, 2013.

[18]       B. K. Panigrahi, S. R. Yadav, S. Agrawal, and M. K. Tiwari, “A clonal algorithm to solve economic load dispatch,” vol. 77, pp. 1381–1389, 2007.

[19]       P. Chen and H. Chang, “Large-scale economic dispatch by genetic algorithm,” vol. 10, no. 4, pp. 1919–1926, 1995.

[20]       V. R. Pandi and B. K. Panigrahi, “Expert Systems with Applications Dynamic economic load dispatch using hybrid swarm intelligence based harmony search algorithm,” Expert Syst. Appl., vol. 38, no. 7, pp. 8509–8514, 2011.

[21]       A. L. Bolaji, “Tournament-based harmony search algorithm for non-convex economic load dispatch problem,” Appl. Soft Comput. J., pp. 1–11, 2016.

[22]       A. Safari and H. Shayeghi, “Expert Systems with Applications Iteration particle swarm optimization procedure for economic load dispatch with generator constraints,” Expert Syst. Appl., vol. 38, no. 5, pp. 6043–6048, 2011.

[23]       R. K. Swain, N. C. Sahu, and P. K. Hota, “Gravitational Search Algorithm for Optimal Economic Dispatch,” vol. 6, pp. 411–419, 2012.

[24]       T. A. Albert and A. E. Jeyakumar, “Hybrid PSO – SQP for economic dispatch with valve-point effect,” vol. 71, pp. 51–59, 2004.

[25]       S. Coelho and C. Lee, “Solving economic load dispatch problems in power systems using chaotic and Gaussian particle swarm optimization approaches,” vol. 30, pp. 297–307, 2008.

[26]       M. Asif, Z. Raja, U. Ahmed, and A. Zameer, “Bio-inspired heuristics hybrid with sequential quadratic programming and interior-point methods for reliable treatment of economic load dispatch problem,” 2017.

[27]       Y. Wang, B. Li, and T. Weise, “Estimation of distribution and differential evolution cooperation for large scale economic load dispatch optimization of power systems,” Inf. Sci. (Ny)., vol. 180, no. 12, pp. 2405–2420, 2010.

[28]       D. Zou, S. Li, G. Wang, Z. Li, and H. Ouyang, “An improved differential evolution algorithm for the economic load dispatch problems with or without valve-point effects,” Appl. Energy, vol. 181, pp. 375–390, 2016.

[29]       M. F. Zaman, S. Member, S. M. Elsayed, T. Ray, and R. A. Sarker, “Economic Dispatch Problems,” pp. 1–10, 2015.

[30]       B. Y. Qu, J. J. Liang, Y. S. Zhu, Z. Y. Wang, and P. N. Suganthan, “Economic emission dispatch problems with stochastic wind power using summation based multi-objective evolutionary algorithm,” pp. 1–19, 2016.

[31]       C. D. Tran, T. T. Dao, V. S. Vo, and T. T. Nguyen, “Economic Load Dispatch with Multiple Fuel Options and Valve Point Effect Using Cuckoo Search Algorithm with Different Distributions,” Int. J. Hybrid Inf. Technol., vol. 8, no. 1, pp. 305–316, 2015.

[32]       S. Rakesh and S. Mahesh, “A comprehensive overview on variants of CUCKOO search algorithm and applications,” Int. Conf. Electr. Electron. Commun. Comput. Technol. Optim. Tech. ICEECCOT 2017, vol. 2018-Janua, pp. 569–573, 2018.

[33]       G. A. Ajenikoko, O. S. Olaniyan, and J. O. Adeniran, “Cuckoo Search Algorithm Optimization Approaches for Solving Economic Load Dispatch : A Review,” vol. 1, no. 2, pp. 1–15, 2018.

[34]       A. Gautam, A. Masih, and A. Ashok, “Implementation of Smooth and Non-Smooth Fuel Cost Function for Economic Load Dispatch using Cuckoo Search Method,” vol. 8, no. 3, pp. 682–691, 2018.

[35]       R. C. A. Subramanian, K. Thanushkodi, and A. Prakash, “An Efficient Meta Heuristic Algorithm to Solve Economic Load Dispatch Problems,” vol. 9, no. 4, pp. 246–252, 2013.

[36]       P. K. Roy and S. Bhui, “A multi-objective hybrid evolutionary algorithm for dynamic economic emission load dispatch,” 2015.

[37]       D. Santra, A. Mondal, and A. Mukherjee, Study of Economic Load Dispatch by Various Hybrid Optimization Techniques. .

[38]       F. Parvez, P. Vasant, V. Kallimani, and J. Watada, “A holistic review on optimization strategies for combined economic emission dispatch problem,” Renew. Sustain. Energy Rev., no. March, pp. 1–15, 2017.

[39]       A. Y. Abdelaziz, E. S. Ali, and S. M. A. Elazim, “Electrical Power and Energy Systems Combined economic and emission dispatch solution using Flower Pollination Algorithm,” Int. J. Electr. POWER ENERGY Syst., vol. 80, pp. 264–274, 2016.

[40]       I. Ziane, F. Benhamida, and A. Graa, “Dynamic Economic Load dispatch Using Quadratic Programming : Application to Algerian Electrical Network,” no. March, 2015.

[41]       P. Tripati, U. Tomar, and A. K. Singhal, “Solving Economic Load Dispatch Problems through Moth Flame Optimization Algorithm,” no. March, 2019.

[42]       Z. C. Khalid, M. H. Muhammad, and A. Zahoor, “Design of reduced search space strategy based on integration of Nelder – Mead method and pattern search algorithm with application to economic load dispatch problem,” Neural Comput. Appl., 2017.

[43]       L. C. Kien, T. T. Nguyen, C. T. Hien, and M. Q. Duong, “A Novel Social Spider Optimization Algorithm for,” pp. 1–26, 2019.

[44]       J. J. Q. Yu and V. O. K. Li, “Neurocomputing A social spider algorithm for solving the non-convex economic load dispatch problem,” Neurocomputing, pp. 1–11, 2015.

[45]       G. Xiong and D. Shi, “SC,” Appl. Soft Comput. J., 2018.

[46]       K. Y. Lee, A. Sode-yome, and J. H. Park, “Neural Networks for Economic Load Dispatch,” vol. 13, no. 2, pp. 519–526, 1998.

[47]       N. Noman and H. Iba, “Differential evolution for economic load dispatch problems,” vol. 78, pp. 1322–1331, 2008.

[48]       M. Kia, M. S. Nazar, M. S. Sepasian, A. Heidari, and P. Siano, “Optimal day ahead scheduling of combined heat and power units with electrical and thermal storage considering security constraint of power system,” Energy, vol. 120, pp. 241–252, 2017.

[49]       B. R. Adarsh, T. Raghunathan, T. Jayabarathi, and X. Yang, “Economic dispatch using chaotic bat algorithm,” Energy, vol. 96, pp. 666–675, 2016.

[50]       M. Modiri-delshad, S. H. Aghay, E. Taslimi-renani, and N. Abd, “Backtracking search algorithm for solving economic dispatch problems with valve-point effects and multiple fuel options,” Energy, vol. 116, pp. 637–649, 2016.

[51]       T. Jayabarathi, T. Raghunathan, B. R. Adarsh, and P. Nagaratnam, “Economic dispatch using hybrid grey wolf optimizer,” Energy, vol. 111, pp. 630–641, 2016.

[52]       V. Kumar and K. S. K. Bath, “Solution of non-convex economic load dispatch problem using Grey Wolf Optimizer,” Neural Comput. Appl., 2015.

[53]       N. Ghorbani and E. Babaei, “Electrical Power and Energy Systems Exchange market algorithm for economic load dispatch,” Int. J. Electr. POWER ENERGY Syst., vol. 75, pp. 19–27, 2016.

[54]       A. Meng, J. Li, and H. Yin, “An ef fi cient crisscross optimization solution to large-scale non-convex economic load dispatch with multiple fuel types and valve-point effects,” Energy, vol. 113, pp. 1147–1161, 2016.

[55]       D. Bisen, H. M. Dubey, M. Pandit, and B. K. Panigrahi, “Solution of Large Scale Economic Load Dispatch Problem using Quadratic Programming and GAMS : A Comparative,” vol. 7, no. 3, pp. 200–211, 2012.

[56]       M. Javadi, T. Amraee, and S. Member, “Economic dispatch : A mixed-integer linear model for thermal generating units,” 2018 IEEE Int. Conf. Environ. Electr. Eng. 2018 IEEE Ind. Commer. Power Syst. Eur. (EEEIC / I&CPS Eur., pp. 1–5, 2018.

[57]       F. Benhamida, I. Ziane, B. Bouchiba, and G. Amel, “Dynamic Economic Load Dispatch Optimization with Ramp Rate Limit Using GAMS-CONOPT Solver,” no. November, 2013.