WSEAS Transactions on Power Systems


Print ISSN: 1790-5060
E-ISSN: 2224-350X

Volume 13, 2018

Notice: As of 2014 and for the forthcoming years, the publication frequency/periodicity of WSEAS Journals is adapted to the 'continuously updated' model. What this means is that instead of being separated into issues, new papers will be added on a continuous basis, allowing a more regular flow and shorter publication times. The papers will appear in reverse order, therefore the most recent one will be on top.



Optimal Energy Saving of Photovoltaic Distributed Generation System with Considering Environment Condition via Hyper-Spherical Search Algorithm

AUTHORS: Mohamed Abd-El-Hakeem Mohamed, Ahmed Elnozahy, Almoataz Y. Abdelaziz

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ABSTRACT: Hyper-spherical search algorithm (HSSA) is proposed for optimal allocation and sizing of Photovoltaic Distributed Generation System (PVDGS) in the distribution network. Firstly, Power Loss Index (PLI) technique is presented to get the highest candidate buses for installing PVDGS. Secondly, the proposed HSSA is developed to decide the most optimal locations of PVDGS and their economic sizing at the elected buses by PLI. Herein, the cost objective function is designed to diminish the total cost of the system losses, and subsequently increase the annual net saving. Hourly variation of solar radiation, and temperature is taken into account in cost calculation of the PV system. In addition, the present worth value for the costs of the maintenance and the PV system components is estimated as function of interest and inflation rates. The proposed algorithm is tested on 69- IEEE and 118 IEEE radial distribution systems to ensure the effectiveness of the proposed algorithm in increasing the net saving via precise cost calculation

KEYWORDS: PV generator, HSSA, distribution network, cost objective function

REFERENCES:

[1] M. M. Haque and P. Wolfs, “A review of high PV penetrations in LV distribution networks: Present status, impacts and mitigation measures,” Renew. Sustain. Energy Rev., vol. 62, pp. 1195–1208, 2016.

[2] Alam, M. J. E., K. M. Muttaqi, and Danny Sutanto. 'A comprehensive assessment tool for solar PV impacts on low voltage three phase distribution networks.' Developments in Renewable Energy Technology (ICDRET), 2012 2nd International Conference on the. IEEE, 2012.

[3] Guerra, Gerardo, and Juan A. Martinez. 'A Monte Carlo method for optimum placement of photovoltaic generation using a multicore computing environment.' PES General Meeting Conference & Exposition, IEEE 2014.

[4] Tayjasanant, T., and V. Hengsritawat. 'Comparative evaluation of DG and PV-DG capacity allocation in a distribution system.' Harmonics and Quality of Power (ICHQP), 2012 IEEE 15th International Conference on. IEEE, 2012.

[5] Rau NS, Yih-Heui W. Optimum location of resources in distributed planning.IEEE Trans Power Syst 1994;9:2014–20.

[6] Kim JO, Park SK, Park KW, Singh C. Dispersed generation planning using improved hereford ranch algorithm. in: IEEE World Congress on Computational Intelligence, The 1998 IEEE International Conference on Evolutionary Computation Proceedings. 1998. p. 678–683.

[7] Lee S-H, Park J-W. Selection of optimal location and size of multiple distributed generations by using kalman filter algorithm. Power Syst IEEE Trans 2009;24:1393–400.

[8] Hengsritawat V, Tayjasanant T, Nimpitiwan N. Optimal sizing of photovoltaic distributed generators in a distribution system with consideration of solar radiation and harmonic distortion. Int J. Elect Power Energy Syst 2012; 39:36–47.

[9] Biswas S, Goswami SK, Chatterjee A. Optimum distributed generation placement with voltage sag effect minimization. Energy Convers Manag 2012;53:163–74.

[10] Paudyal S, El-Saadany EF, El Chaar L, Lamont LA. Optimal size of distributed generation to minimize distribution loss using dynamic programming. in: Power and Energy (PECon), 2010 IEEE International Conference on; 2010, p. 527–532.

[11] Lee SH, Park J-W. Optimal placement and sizing of multiple dgs in a practical distribution system by considering power loss. Ind Appl IEEE Trans 2013;49:2262–70.

[12] Muttaqi KM, Le AD, Negnevitsky M, Ledwich G. An algebraic approach for determination of dg parameters to support voltage profiles in radial distribution networks. IEEE Trans Smart Grid 2014;5:1351–60.

[13] Juanuwattanakul P, Masoum M. Increasing distributed generation penetration in multiphase distribution networks considering grid losses, maximum loading factor and bus voltage limits. Gener Transm Distrib IET 2012;6:1262–71.

[14] Arya LD, Koshti A, Choube SC. Distributed generation planning using differential evolution accounting voltage stability consideration. Int J Electr Power Energy Syst 2012;42:196–207.

[15] Kang Q, Zhou M, An J, Wu Q. Swarm intelligence approaches to optimal power flow problem with distributed generator failures in power networks. Automation Sci Eng IEEE Trans 2013;10:343–53.

[16] VVSN Murthy, Kumar A. Comparison of optimal dg allocation methods in radial distribution systems based on sensitivity approaches. Int J Electr Power Energy Syst 2013;53:450–67.

[17] Biswas S, Goswami SK, Chatterjee A. Optimum distributed generation placement with voltage sag effect minimization. Energy Convers Manag 2012;53:163–74.

[18] Liu Z, Wen F, Ledwich G, Ji X. Optimal sitting and sizing of distributed generators based on a modified primal-dual interior point algorithm. In: Electric Utility Deregulation and Restructuring and Power Technologies (DRPT), 2011 Proceedings of the 4th International Conference on. IEEE; 2011, p. 1360–1365.

[19] Alinejad-Beromi Y, Sedighizadeh M, Bayat M, Khodayar M. Using genetic alghoritm for distributed generation allocation to reduce losses and improve voltage profile. in: Universities Power Engineering Conference, 2007 UPEC 2007 42nd International. IEEE; 2007, p. 954–959.

[20] Hussain I, Roy AK. Optimal distributed generation allocation in distribution systems employing modified artificial bee colony algorithm to reduce osses and improve voltage profile. in: Advances in Engineering, Science and Management (ICAESM), 2012 International Conference on; 2012, p. 565–570.

[21] Injeti SK, Kumar NP. Optimal planning of distributed generation for improved voltage stability and loss reduction. Int J Comput Appl 2011;15:40–6.

[22] Sedighizadeh M, Rezazadeh A. Using genetic algorithm for distributed generation allocation to reduce losses and improve voltage profile. World Acad Sci Eng Technol, 37 2008; 2008. p. 251–6.

[23] PA-D-V Raj, Senthilkumar S, Raja J, Ravichandran S, Palanivelu T. Optimization of distributed generation capacity for line loss reduction and voltage profile improvement using pso. Elektr J Electr Eng 2008;10:41–8.

[24] Phonrattanasak P, Miyatake M, Sakamoto O. Optimal location and sizing of solar farm on japan east power system using multiobjective bees algorithm. in: Energytech, 2013 IEEE. IEEE; 2013, p. 1–6.

[25] Rider MJ, López-Lezama JM, Contreras J, Padilha-Feltrin A. Bilevel approach foroptimal location and contract pricing of distributed generation in radial distribution systems using mixed-integer linear programming. Gener Transm Distrib IET 2013;7:724–34.

[26] Ameli A, Bahrami S, Khazaeli F, Haghifam M-R. A multiobjective particle swarm optimization for sizing and placement of dgs from dg owner's and distribution company's viewpoints. IEEE Trans Power Deliv 2014;29:1831–40.

[27] Muneer W, Bhattacharya K, Canizares CA. Large-scale solar pv investment models, tools, and analysis: the ontario case. Power Syst IEEE Trans 2011;26:2547–55.

[28] Shaaban MF, Atwa YM, El-Saadany EF. DG allocation for benefit maximization in distribution networks. IEEE Trans Power Syst 2013;28:639–49.

[29] Banerjee B, Islam SM. Reliability based optimum location of distributed generation. Int J Electr Power Energy Syst 2011;33:1470–8.

[30] Algarni AAS, Bhattacharya K. Disco operation considering dg units and their goodness factors. IEEE Trans Power Syst 2009;24:1831–40.

[31]Duong Quoc H, Mithulananthan N, Bansal RC. Analytical expressions for DG allocation in primary distribution networks. IEEE Trans Energy Convers 2010; 25:814–20.

[32] Keane A, O'Malley M. Optimal allocation of embedded generation on distribution networks. IEEE Trans Power Syst 2005;20:1640–6.

[33] Esmaili M. Placement of minimum distributed generation units observing power losses and voltage stability with network constraints. IET Gener Transm Distrib 2013;7:813–21.

[34] Rider MJ, López-Lezama JM, Contreras J, Padilha-Feltrin A. Bilevel approach for optimal location and contract pricing of distributed generation in radial distribution systems using mixed-integer linear programming. Gener Transm Distrib IET 2013; 7:724–34.

[35] Paudyal S, El-Saadany EF, El Chaar L, Lamont LA. Optimal size of distributed generation to minimize distribution loss using dynamic programming. in: Power and Energy (PECon), 2010 IEEE International Conference on; 2010, p. 527–532.

[36] Algarni AAS, Bhattacharya K. Disco operation considering dg units and their goodness factors. IEEE Trans Power Syst 2009;24:1831–40.

[37] Hedayati H, Nabaviniaki SA, Akbarimajd A. A method for placement of dg units in distribution networks. IEEE Trans Power Deliv 2008;23:1620–8.

[38] Elmitwally A. A new algorithm for allocating multiple distributed generation units based on load centroid concept. Alex Eng J 2013;52:655–63.

[39] Crossland A, Jones D, Wade N. Planning the location and rating of distributed energy storage in lv networks using a genetic algorithm with simulated annealing. Int J Electr Power Energy Syst 2014;59:103–10.

[40] Nekooei K, Farsangi MM, Nezamabadi-Pour H, Lee KY. An improved multiobjective harmony search for optimal placement of dgs in distribution systems.

[41] Gandomkar M, Vakilian M, Ehsan M. A genetic-based tabu search algorithm for optimal dg allocation in distribution networks. Electr Power Compon Syst 2005;33:1351–62.

[42] Lalitha MP, Reddy V, Usha V, Reddy NS. Application of fuzzy and pso for dg placement for minimum loss in radial distribution system. ARPN J Eng Appl Sci 2010;5:32–7.

[43] Moradi MH, Abedini M. A combination of genetic algorithm and particle swarm optimization for optimal dg location and sizing in distribution systems. Int J Electr Power Energy Syst 2012;34:66–74.

[44] Gomez-Gonzalez M, López A, Jurado F. Optimization of distributed generation systems using a new discrete PSO and OPF. Electr Power Syst Res 2012;84:174–80.

[45] Mohamed A. Tolba1, Vladimir N. Tulsky2 Ahmed A. Zaki Diab3' Optimal Sitting and Sizing of Renewable Distributed Generations in Distribution Networks Using a Hybrid PSOGSA Optimization Algorithm'

[46] S. A. Ahmadi, H. Karami, M. J. Sanjari , H. Tarimoradi, G.B. Gharehpetian, 'Application of hyper-spherical search algorithm for optimal coordination of overcurrent relays considering different relay characteristics,' Int. J. of Electrical Power & Energy Systeims, vol. 83, pp. 443-449, 2016.

[47] Farag K. Aboelyousr ,Mohamed Abd-El-Hakeem Mohamed. ' Hyper-Spherical Search Algorithm for Optimal Sizing and Allocation of Capacitors in Radial Distribution Systems.' Journal of Electric Engineering jee, , accepted July 2017

[48] M. J. Sanjari, H. Karimi, A. H. Yatim, G. B. Gharehpetian, 'Application of hyper-spherical search algorithm for optimal energy resources dispatch in residential microgrids,' Applied Soft Comp., vol. 37, pp. 15-23, 2015.

[49] J. W. Large, D. F. Jones, M. Tamiz, 'Hyper-spherical inversion transformations in multi-objective evolutionary optimization,' European J. of Operational Research, vol. 177, pp. 1678-1702, 2007.

[50] H. Borhanazad, S. Mekhilef, V. G. Ganapathy, M. Modiri-Delshad, and A. Mirtaheri, 'Optimization of Micro-grid System using MOPSO,' Renewable Energy, vol. 71, pp. 295-306, 2014.

[51] Surface meteorology and Solar Energy

[on line]. Available: https://eosweb.larc.nasa.gov/sse/

[52] R. Messenger, and J. Ventre “Photovoltaic Systems Engineering,” 2nd ed., CRC Press LLC: Boca Raton, Florida, USA, 2000.

[53] A. Ajlan, C. W. Tan, and A. M. Abdilahi, “Assessment of environmental and economic perspectives for renewable-based hybrid power system in Yemen,” Renewable and Sustainable Energy Reviews, vol. 75, pp. 559–570, 2017.

[54] B. Shi , W. Wu , and L. Yan, “Size optimization of stand-alone PV/wind/diesel hybrid power generation systems,” Journal of the Taiwan Institute of Chemical Engineers, vol. 73, pp. 93–101, 2017.

[55] M.J. Sanjaria, H. Karamib, A.H. Yatima, G.B. Gharehpetianb,'Application of Hyper Spherical Search algorithm for optimal energy resources dispatch in residential microgrids,' Applied Soft Computing, vol. 37, pp. 15–23, 2015.

[56] D. Zhang, Z. Fu, L. Zhang, 'An improved TS algorithm for loss-minimum reconfiguration in large-scale distribution systems,' Electric Power System Research, Vol. 77, PP. 686-694, 2007.

[57] F.S. Abu-Mouti, M.E. El-Hawary, Optimal distributed generation allocation and sizing in distribution systems via artificial Bee colony algorithm, IEEE Trans. Power Deliv. 26 (4) (2011) 2090e2101.

[58] W. Tan, M. Hassan, M. Majid, H. Rahman, Allocation and sizing of DG using cuckoo search algorithm, IEEE Int. Conf. Power Energy (2012) 133e138.

[59] A. Abdelaziz, Y. Hegazy, W. El-Khattam, M. Othman, A multi-objective optimization for sizing and placement of voltage-controlled distributed generation using supervised Big Bang-Big Crunch method, Electr. Power Compon. Syst. 43 (1) (2015) 105e117.

[60] E.S. Ali , S.M. Abd Elazim , and A.Y. Abdelaziz, 'Ant Lion Optimization Algorithm for optimal location and sizing of renewable distributed generations,' Renewable Energy, vol. 101, pp. 1311-1324, 2017.

[61] D. Das, D. P. Kothari, A. Kalam, 'Simple and efficient method for load flow solution of radial distribution networks', Elect. Power & Energy Systems, vol. 17, pp. 335-346, 1995.

WSEAS Transactions on Power Systems, ISSN / E-ISSN: 1790-5060 / 2224-350X, Volume 13, 2018, Art. #31, pp. 311-325


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