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توزیع بار اقتصادی با در نظر گرفتن آلودگی در سیستم‌های قدرت چندناحیه‌ای با استفاده از الگوریتم بهینه‌سازی فاخته | ||
| مدل سازی در مهندسی | ||
| مقاله 7، دوره 12، شماره 37، شهریور 1393، صفحه 89-104 اصل مقاله (710.94 K) | ||
| شناسه دیجیتال (DOI): 10.22075/jme.2017.1674 | ||
| نویسندگان | ||
| صابر ارمغانی* ؛ نیما امجدی | ||
| دانشگاه سمنان | ||
| تاریخ دریافت: 09 بهمن 1395، تاریخ بازنگری: 02 مهر 1396، تاریخ پذیرش: 09 بهمن 1395 | ||
| چکیده | ||
| در این تحقیق، برای حل مسئله توزیع بار اقتصادی با در نظر گرفتن آلودگی در سیستم‌های قدرت چند ناحیه‌ای، الگوریتم بهینه‌سازی فاخته پیشنهاد شده است. در سالهای اخیر، توزیع بار اقتصادی در سیستم‌های قدرت چند ناحیه‌ای، مورد توجه محققین واقع شده است، اما در هیچ‌یک از این تحقیقات، به معضل آلودگی ناشی از سوخت‌های فسیلی توجه نشده است. مدل ارائه‌شده در این تحقیق، قید آلودگی را نیز اِعمال نموده است و از این لحاظ مدلی جدید از مسالۀ مذکور به‌شمار می‌رود. الگوریتم بهینه‌سازی فاخته، یک الگوریتم جستجوی تکاملی است که در سالهای اخیر توسط محققین پیشنهاد و در زمینه های مختلف مهندسی مورد استفاده قرار گرفته است. با این وجود، قابلیت این الگوریتم برای حل مسائل بهره‌برداریِ سیستم‌های قدرت بررسی نشده است. در این مقاله، توانایی الگوریتم بهینه‌سازی فاخته، برای حل مسئله توزیع بار اقتصادی با در نظر گرفتن تابع آلودگی (مدل جدید پیشنهادی) در سیستم‌های قدرت چند ناحیه‌ای بررسی شده است. الگوریتم بهینه‌سازی فاخته در مسائل مختلف توزیع بار اقتصادی در چند سیستم‌های تک‌ناحیه‌ای (6،10و40 واحدی) و توزیع بار اقتصادی با در نظرگرفتن تابع آلودگی تحت قیود ایمنی در سیستم تک ناحیه‌ای (6 واحدی، 30 باسه) اِعمال شده است. در نهایت قابلیت الگوریتم بهینه‌سازی فاخته در حل مسئله توزیع بار اقتصادی در سیستم 4 واحدی و دو ناحیه‌ای و مسئله توزیع بار اقتصادی با در نظر گرفتن تابع آلودگی در سیستم 40 واحدی و دو ناحیه‌ای با قیود تکمیلی بررسی شده است. مقایسه عملکرد این الگوریتم با دیگر الگوریتم‌های جستجوی تصادفی، توانمندی الگوریتم بهینه‌سازی فاخته را نشان می‌دهد. | ||
| کلیدواژه‌ها | ||
| توزیع بار اقتصادی؛ قید آلودگی؛ سیستم‌های چند ناحیه‌ای؛ الگوریتم بهینه‌سازی فاخته | ||
| عنوان مقاله [English] | ||
| Multi-objective Multi-area Environmental and Economic Dispatch Using Cuckoo Optimization Algorithm | ||
| نویسندگان [English] | ||
| Saber Armaghani؛ Nima Amjady | ||
| چکیده [English] | ||
| In this paper, for solving the Multi-Objective Multi-area Environmental Economic Load Dispatch, Cuckoo Optimization Algorithm is proposed. In resent year, the economic load dispatch is considered as a multi-area power systems problem, but, in none of these studies the environmental problem is not considered. Accordingly in this paper the model of pollution constraint is imposed and the terms of issue of the new model is considered. On the other hand, the cuckoo optimization algorithm is an evolutionary search algorithm which is proposed in recent years by researchers in various fields of engineering. However, the advantage of this algorithm for solving power systems has not been investigated. So, the ability of Cuckoo Optimization Algorithm for solving environmental economic load dispatch with respect to the contamination (the proposed model) in multi-area power systems is investigated. The proposed technique is applied on different issues in many single area systems (6, 10 and 40 generation unit) and the distribution of the economic burden of pollution provisions regarding the function of the immune system in single area (6 units, 30 buses). Finally, the proposed algorithm in solving economic load dispatch in the region of 4 units and two additional constraints is investigated. The performance of this algorithm is compared with other techniques which demonstrate the superiority of this method than the others. | ||
| کلیدواژه‌ها [English] | ||
| Economic and Emission Dispatch Multi-area Cuckoo Optimization Algorithm(COA) | ||
| مراجع | ||
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[1] J.,,Nanda D.P,. Khotari K.S. Lingamurthy, (1988). “Economic-Emission Load Dispatch Through Goal Programming Techniques”, IEEE Transaction on Energy Conversion, vol.3 , pp.26–32.. [2] C.S, Chang A.C., Liew J.X., Xu X.W., Wang B.,Fan (1996). “Dynamic Security-Constrained Multi-Objective Generation Dispatch of Longitudinally Interconnected Power Systems Using Bicriterion Global Optimization”. IEEE Transaction on Power Systems vol.11, pp.1009–1016. [3] Y.H., Song G.S., Wang P.Y.,Wang A.T.,Johns, (1997). “Environmental/Economic Dispatch Using Fuzzy Logic Controlled Genetic Algorithms”. IEE Proceedings Generation, Transmission and Distribution vol.144, pp. 377–382 [4] T.,Yalcinoz H., Altun, (2002). “Environmentally Constrained Economic Dispatch Via a Genetic Algorithm with Arithmetic Crossover”. IEEE African Conference, vol. 2, , pp. 928–938. [5] T., Thakur K., Sem S., Saini S., Sharma, (2006). “Particle Swarm Optimization Solution to NO2 and SO2 Emissions For Environmentally Constrained Economic Dispatch Problem”. IEEE/PES Transmission & Distribution Conference and Exposition: Latin America, TDC’06, Caracas, 15–18 Au, pp. 1–5. [6] J.,Cai X., Ma Q., Li L., Li H., Peng, (2010). “A Multi-Objective Chaotic Ant Swarm Optimization for Environmental/Economic Dispatch”. International Journal of Electrical Power and Energy Systems vol.32, pp.337–344. [7] P.K., Hota A.K., Barisal R., Chakrabart, (2010). “Economic Emission Load Dispatch Through Fuzzy Based Bacterial Foraging Algorithm”. International Journal of Electrical Power and Energy Systems, vol.32, pp.794–803. [8] A., Bhattacharya P. K., (2011). “Chattopadhyay .Solving Economic Emission Load Dispatch Problems Using Hybrid Differential Evolution”. Soft Computing, vol.11, pp.2526-2537 [9] K.W, McEntire PL, (1982). “An Analysis of Electric Power Brokerage Systems”. IEEE Trans Power Apparatus Syst, vol.101(2), pp.96-389. [10] T., Yalcinoz MJ ,Short, (1998). “Neural Networks Approach for Solving Economic Dispatch Problem with Transmission Capacity Constraints”, IEEE Trans Power Syst, vol.13, pp.13-307. [11] P.S., Manoharan P.S., Kannan S., Baskar M., Willjuice Iruthayarajan, (2009). “Evolutionary Algorithm Solution And KKT Based Optimality Verification To Multi-Area Economic Dispatch”., Electrical Power and Energy System, vol.31, pp.365–373. [12] XS., Yang S., Deb, (2009). “Cuckoo Search Via Lévy Flights”, Proceedings of World Congress on Nature & Biologically Inspired Computing, India, vol.3, pp 210-214. [13] XS., Yang S., Deb, (2010). “Engineering Optimization by Cuckoo Search”., Int. J. Mathematical Modeling and Numerical Optimization., Vol. 1, pp 330–343. [14] R., Rajabioun, (2011). “Cuckoo Optimization Algorithm”, Soft Computing, vol.11, pp.5508-5518. [15] KT., Chaturvedi Pandit M., Srivastava, (2008). “Self-Organizing Hierarchical Particle Swarm Optimization for Non-Convex Economic Dispatch”, IEEE Trans Power Syst, vol.23, pp.1078–1087. [16] N., Amjady H.,Nasiri-Rad, )2009). “Non-Convex Economic Dispatch With AC Constraints by a New Real Coded Genetic Algorithm” , IEEE Trans Power Syst, vol. 24, pp.345-352 [17] CC., Kuo, (2008). “A Novel Coding Scheme for Practical Economic Dispatch by Modified Particle Swarm Approach”, IEEE Trans Power Syst, vol.21, pp.25–35. [18] ZL., Gaing, (2003). “Particle Swarm Optimization To Solving The Economic Dispatch Considering The Generator Constraints”, IEEE Trans Power Syst, vol.18, pp.78–95. [19] AY., Saber S. ,Chakraborty SM., Abdur-Razzak T., Senjyu, (2009). “Optimization of Economic Load Dispatch of Higher Order General Cost Polynomials and Its Sensitivity Using Modified Particle Swarm Optimization”, Electra Power Syst, vol.79, pp.98–106. [20] Ch.L., Chiang, (2005) .”Improved Genetic Algorithm for Power Economic Dispatch of Units with Valve-Point Effects and Multiple Fuels”, IEEE Trans Power Syst, vol. 20, pp.1690-1699. [21] R., Rahmani M.F, Othma R., Yusof M., Khalid, (2012). “Solving Economic Dispatch Problem Using Particle Swarm Optimization by An Evolutionary Technique for Initializing Particles”, Journal of Theoretical and Applied Information Technology, vol.46, pp 2005 – 2012. [22] N., Sinha R., Chakrabarti P.K., Chattopadhyay, (2003). “Evolutionary Programming Techniques for Economic Load Dispatch”., IEEE Trans power syst., vol.7, pp.83–94. [23] O., Abedinia N., Amjady K., Kiani H.A., Shayanfar A. Ghasemi, (2012). “Multi-objective Environmental Economic Dispatch Using Imperialist Competitive Algorithm”., IJTPE, vol.4, pp.63-70 [24] M.A., Abido, (2003). “Environmental/Economic Power Dispatch Using Multi-objective Evolutionary Algorithms”., IEEE. Trans. Power Syst , Vol.18, pp. 1529-1537. [25] Ch CL, Ch.N, (2001). “Direct Search Method for Solving Economic Dispatch Problem Considering Transmission Capacity Constraints”., IEEE Trans Power Syst, vol16, pp.764-769. [26] T.,Niknam H., Doagou Mojarrad H., Zeinoddini Meymand, (2011). “Non-Smooth Economic Dispatch Computation by Fuzzy and Self Adaptive Particle Swarm Optimization”. Soft Computing, vol.11, pp.2805-2817. [27] M., Pourakbari-Kasmaei M., Rashidi-Nejad, (2011). “An Effortless Hybrid Method to Solve Economic Load Dispatch Problem in Power Systems“. Energy Conversion and Management, vol.52, pp.2854-2860. [28] CC, Kuo, (2008). “A Novel Coding Scheme for Practical Economic Dispatch by Modified Particle Swarm approach”., IEEE Trans Power Syst , vol.21, pp.25-35. [29] C., Chokpanyasuwan S., Anantasate S., Pothiya W., Pattaraprakom P.,Bhasaputra, (2009).” Honey Bee Colony Optimization to Solve Economic Dispatch Problem with Generator Constraints”., IEEE ECTI-Con; vol.1, pp.200-203. [30] ZL., Gaing, (2003). “Particle Swarm Optimization to Solving the Economic Dispatch Considering the Generator Constraints”., IEEE Trans Power Syst, vol.18, pp.1187–1195. [31] B.K., Panigrahi V.R., Pandi S., Das, (2008). “Adaptive Particle Swarm Optimization Approach for Static and Dynamic Economic Load Dispatch”., Energy Convers Manage; vol.49, pp.1407–1415. [32] A. I., Selvakumar K., Thanushkodi, (2007). “A new Particle Swarm Optimization Solution to No-nconvex Economic Dispatch Problems”., IEEE Trans. Power Syst., vol.22, pp.42–51. [33] P. S. Manoharan, P. S. Kannan, S. Baskar, and M. W. Iruthayarajan, (2008). "Penalty Parameter-less Constraint Handling Scheme based Evolutionary Algorithm Solutions to Economic Dispatch”. IET Gen., Transm., Distrib., vol. 2, no. 4, pp. 478–490.. [34] C.-L., Chiang,(2005). “Improved Genetic Algorithm for Power Economic Dispatch of Units with Valve-point effects and Multiple fuels., IEEE Trans. Power Syst., vol. 20, pp. 1690–1699. [35] P., Chen H.,Chang, (1995). "Large-scale Economic Dispatch by Genetic Algorithm". IEEE Trans Power Syst, vol.10, pp.1919-1926. [36] S.K., Wang J.P., Chiou C.W., Liu. (2007). “Non-smooth/Non-convex Economic Dispatch by a Novel Hybrid Differential Evolution Algorithm”., IET Gener Transm Distrib; vol.1, pp.793–803. [37] L.D.S., Coelho VC., Mariani, (2006). “Combining of Chaotic Differential Evolution and Quadratic Programming for Economic Dispatch Optimization with Valve-Point Effect”., IEEE Trans Power Syst vol.21, pp.989–996. [38] A.I., Selvakumar K., Thanushkodi, (2008). “Anti-Predatory Particle Swarm Optimization: Solution to Non-Convex Economic Dispatch Problems”., Electric Power Syst Res., vol 78, pp.2–10. [39] A.I., Selvakumar K., Thanushkodi, (2007). “A New Particle Swarm Optimization Solution to Non-Convex Economic Dispatch Problems”., IEEE Trans Power Syst , vol.22, 42–51. [40] BK., Panigrahi V.R., Pandi, (2008). “Bacterial foraging Optimization Nelder–Mead Hybrid Algorithm for Economic Load Dispatch”., IET Gen Transm Distrib, vol.2, pp.556–665. [41] N., Amjady H.Sharifzadeh, (2010). “Solution of Non-Convex Economic Dispatch Problem Considering Valve Loading Effect by a New Modified Differential Evolution Algorithm". Electrical Power and Energy Systems, vol.32, pp.893-903. [42] M.A., Abido, (2006). “Multi-objective Evolutionary Algorithms for Electric Power Dispatch Problem”., IEEE Trans. Evol. Comput., Vol.10, pp.315-329. [43] M.A., Abido, (2003). “A Niched Pareto Genetic Algorithm for Multi-objective Environmental/Economic Dispatch”., Electr Power Energy Syst., Vol.25, pp.97-105. [44] M.A., Abido, (2009). “Multi-Objective Particle Swarm Optimization for Environmental/Economic Dispatch Problem”., Electr Power Syst. Vol.79, pp.1105-1113. [45] T., Jayabarathi G., Sadasiva V., Ramachandran, (2000). “Evolutionary Programming Based Multi-Area Economic Dispatch With Tie Line Constraints”., Electr Mach Power Syst, vol.28, pp.1165-1176. [46] M., Sharma, M., Pandit L.,Srivastava, (2011). “Reserve Constrained Multi-Area Economic Dispatch Employing Differential Evolution with Time-Varying Mutation”., Electrical Power and Energy Systems vol.33, pp.753-766. [47] D.C., Walters G.B., Sheble, (1993). “Genetic Algorithm Solution of Economic Dispatch with Valve Point Loading”., IEEE Trans Power Syst, Vol.8,.pp.1324-1332. [48] S.k., Soni V., Bhuria, (2012). “Multi-objective Emission Constrained Economic Power Dispatch Using Differential Evaluation Algorithm”., Int.J.of Eng.Inn. Tech, Vol.2, pp.120-125. | ||
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