© The Institution of Engineering and Technology
In the deregulated power market environment, distributed generation (DG) is an effective approach to manage performance, operation and control of the distribution system. Methods available in the literature for DG planning are often not able to simultaneously provide technical and economical benefits. Therefore an effective methodology is developed to improve the technical as well as economical benefits as compared with the existing approaches. This study reports the optimal installation of multi-DG in the standard 33-bus, 69-bus radial distribution systems and 54-bus practical radial distribution system. Several performance evaluation indices such as active and reactive power loss indices, voltage deviation index, reliability index and shift factor indices are used to develop a novel multi-objective function (MOF). A new set of equations is developed for representing different practical load models. A novel MOF has been solved to find optimal sizing and placement of DGs using genetic algorithm and particle swarm optimisation technique. The comparative result analysis is also discussed for both techniques. The result analysis reveals that system losses, energy not supplied, system MVA intakes are reduced, whereas available transfer capability, voltage profile, reliability and cost benefits are improved for the case with-DGs in the distribution system.
References
-
-
1)
-
22. Kansal, S., Vishal, K., Barjeev, T.: ‘Optimal placement of different type of DG sources in distribution networks’, Int. J. Electr. Power Eng. Syst., 2013, 53, pp. 752–760 (doi: 10.1016/j.ijepes.2013.05.040).
-
2)
-
2. Goldberg, D.E.: ‘Genetic algorithms in search, optimization and machine learning’ (Addison-Wesley publishers, 1989, 1st edn.).
-
3)
-
16. Price, W., Wirgau, K., Murdoch, A., et al: ‘Load modeling for power flow and transient stability computer studies’, IEEE Trans. Power Syst., 1988, 3, (1), pp. 180–187 (doi: 10.1109/59.43196).
-
4)
-
2. Singh, D., Misra, R.K.: ‘Effect of load models in distributed generation planning’, IEEE Trans. Power Syst., 2007, 22, (4), pp. 2204–2212 (doi: 10.1109/TPWRS.2007.907582).
-
5)
-
8. Zimmerman, R.D., Murillo-Sanchez, C.E.: ‘Matpower4.1’, December 2011. .
-
6)
-
27. Samui, A., Singh, S., Ghose, T., Samantaray, S.R.: ‘A direct approach to optimal feeder routing for radial distribution System’, IEEE Trans. Power Deliv., 2012, 27, (1), pp. 253–260, (doi: 10.1109/TPWRD.2011.2167522).
-
7)
-
35. Price, W.W., Casper, S.G., Nwankpa, C.O., et al: ‘Bibliography on load models for power flow and dynamic performance simulation’, IEEE Power Eng. Rev., 1995, 15, (2), p. 70.
-
8)
-
29. Naik, S.N.G., Khatod, D.K., Sharma, M.P.: ‘Analytical approach for optimal siting and sizing of distributed generation in radial distribution networks’. Proc. Inst. Eng Tech.., Gen., Transm., Distrib., 2015, 9, (3), pp. 209–220 (doi: 10.1049/iet-gtd.2014.0603).
-
9)
-
31. Kumar, A., Kumar, J.: ‘Comparison of UPFC and SEN transformer for ATC enhancement in restructured electricity markets’, Int. J. Electr. Power Energy Syst., 2012, 41, (1), pp. 96–104 (doi: 10.1016/j.ijepes.2012.03.019).
-
10)
-
38. Mishra, M.: ‘Optimal placement of DG for loss reduction considering DG models’. IEEE Int. Conf. on Electrical, Computer and Communication Technologies (ICECCT), 2015, 5–7 March 2015, pp. 1–6, .
-
11)
-
106. Hung, D.Q., Mithulananthan, N., Bansal, R.C.: ‘Analytical expressions for DG allocation in primary distribution networks’, IEEE Trans. Energy Convers., 2010, 25, (3), pp. 814–820 (doi: 10.1109/TEC.2010.2044414).
-
12)
-
41. Hung, D.Q., Mithulananthan, N., Lee, K.Y.: ‘Optimal placement of dispatchable and nondispatchable renewable DG units in distribution networks for minimizing energy loss’, Int. J. Electr. Power Energy Syst., 2014, 55, pp. 179–186 (doi: 10.1016/j.ijepes.2013.09.007).
-
13)
-
4. Kennedy, J., Eberhart, R.C.: ‘Particle swarm optimization’. IEEE Int. Conf. on Neural Networks Proc., November/December 1995, vol. 4, pp. 1942–1948, .
-
14)
-
5. Zhu, D., Broadwater, R.P., Tam, KS., et al: ‘Impact of DG placement on reliability ande fficiency with time-varying loads’, IEEE Trans. Power Syst., 2006, 21, (1), pp. 419–427 (doi: 10.1109/TPWRS.2005.860943).
-
15)
-
37. Murthy, V.V.S.N., Kumar, A.: ‘Comparison of optimal DG allocation methods in radial distribution systems based on sensitivity approaches’, Int. J. Electr. Power Energy Syst., 2013, 53, pp. 450–467 (doi: 10.1016/j.ijepes.2013.05.018).
-
16)
-
25. IEEE Task Force on Load Representation for Dynamic Performance: ‘Standard load models for power flow and dynamic performance simulation’, IEEE Trans. Power Syst., 1995, 10, (3), pp. 1302–1313 (doi: 10.1109/59.466523).
-
17)
-
1. Ackermann, T., Andersson, G., Söder, L.: ‘Distributed generation: a definition’, Electr. Power Syst. Res., 2001, 57, (3), pp. 195–204 (doi: 10.1016/S0378-7796(01)00101-8).
-
18)
-
124. Hien, N.C., Mithulananthan, N., Bansal, R.C.: ‘Location and sizing of distribution generation units for load ability enhancement in primary feeder’, IEEE Syst. J., 2013, 7, (4), pp. 797–806 (doi: 10.1109/JSYST.2012.2234396).
-
19)
-
17. Chowdhury, A., Agarwal, S.K., Koval, D.O.: ‘Reliability modeling of distributed generation in conventional distribution systems planning and analysis’, IEEE Trans. Ind. Appl., 2003, 39, (5), pp. 1493–1498 (doi: 10.1109/TIA.2003.816554).
-
20)
-
25. Al-Muhaini, M., Heydt, G.T.: ‘Evaluating future power distribution system reliability including distributed generation’, IEEE Trans. Power Deliv., 2013, 28, (4), pp. 2264–2272 (doi: 10.1109/TPWRD.2013.2253808).
-
21)
-
10. Singh, D., Singh, D., Verma, K.S.: ‘Multiobjective optimization for DG planning with load models’, IEEE Trans. Power Syst., 2009, 24, (1), pp. 427–436 (doi: 10.1109/TPWRS.2008.2009483).
-
22)
-
11. IEEE Task Force on Load Representation for Dynamic Performance: ‘Load representation for dynamic performance analysis’, IEEE Trans. Power. Syst., 1993, 8, (2), pp. 472–482 (doi: 10.1109/59.260837).
-
23)
-
22. Rao, R., Ravindra, K., Satish, K., et al: ‘Power loss minimization in distribution system using network reconfiguration in the presence of distributed generation’, IEEE Trans. Power Syst., 2013, 28, (1), pp. 317–325 (doi: 10.1109/TPWRS.2012.2197227).
-
24)
-
5. Eberhart, R.C., Kennedy, J.: ‘A new optimizer using particle swarm theory’. Proc. Sixth Int. Symp. on Micro Machine and Human Science (Nagoya, Japan), , Piscataway, NJ, 4–6 October 1995, pp. 39–43, .
-
25)
-
7. Bohre, A.K., Agnihotri, G., Dubey, M., et al: ‘A novel method to find optimal solution based on modified butterfly particle swarm optimization’, Int. J. Soft Comput. Math. Control (IJSCMC), 2014, 3, (4), pp. 1–14 (doi: 10.14810/ijscmc.2014.3401).
-
26)
-
1. Holland, J.H.: ‘Adaptation in natural and artificial systems’ (The University of Michigan Press, Ann Arbor, 1975).
-
27)
-
32. Kumar, A., Srivastava, S.C.: ‘AC power transfer distribution factors for allocating power transactions in a deregulated market’, IEEE Power Eng. Rev., 2002, 22, (7), pp. 42–43 (doi: 10.1109/MPER.2002.1016847).
-
28)
-
40. Behera, S.R., Dash, S.P., Panigrahi, B.K.: ‘Optimal placement and sizing of DGs in radial distribution system (RDS) using Bat algorithm’. Int. Conf. on Circuit, Power and Computing Technologies (ICCPCT), 2015, 19–20 March 2015, pp. 1–8, .
-
29)
-
16. Calderaro, V., Galdi, V., Lamberti, F., et al: ‘A smart strategy for voltage control ancillary service in distribution networks’, IEEE Trans. Power Syst., 2015, 30, (1), pp. 494–502 (doi: 10.1109/TPWRS.2014.2326957).
-
30)
-
9. Acharya, N., Mahat, P., Mithulananthan, N.: ‘An analytical approach for DG allocation in primary distribution network’, Int. J. Electr. Power Energy Syst., 2006, 28, (10), pp. 669–678 (doi: 10.1016/j.ijepes.2006.02.013).
-
31)
-
3. Haupt, R.L., Haupt, S.E.: ‘Practical genetic algorithms’ (John Wiley & Sons, inc., Hoboken, New Jersey, , 2004, 2nd edn.).
-
32)
-
33. Hung, D.Q., Mithulananthan, N.: ‘Multiple distributed generator placement in primary distribution networks for loss reduction’, IEEE Trans. Ind. Electron., 2013, 60, (4), pp. 1700–1708 (doi: 10.1109/TIE.2011.2112316).
-
33)
-
12. Nahman, J.M., Peric, D.M.: ‘Optimal planning of radial distribution networks by simulated annealing technique’, IEEE Trans. Power Syst., 2008, 23, (2), pp. 790–795 (doi: 10.1109/TPWRS.2008.920047).
-
34)
-
23. Celli, G., Ghiani, E., Mocci, S., et al: ‘A multiobjective evolutionary algorithm for the sizing and siting of distributed generation’, IEEE Trans. Power Syst., 2005, 20, (2), pp. 750–757 (doi: 10.1109/TPWRS.2005.846219).
-
35)
-
29. Patra, S.B., Mitra, J., Ranade, S.J.: ‘Micro-grid architecture: a reliability constrained approach’. IEEE Pmtower Engineering Society General Meeting|, , pp. 2372–2377.
-
36)
-
6. Bohre, A.K., Agnihotri, G., Dubey, M.: ‘Hybrid butterfly based particle swarm optimization for optimization problems’. First Int. Conf. on Networks and Soft Computing (ICNSC), 2014, 19–20 August 2014, pp. 172–177, .
-
37)
-
11. El-Zonkoly, A.M.: ‘Optimal placement of multi-distributed generation units including different load models using particle swarm optimization’, Swarm Evol. Comput., 2011, 1, (1), pp. 50–59 (doi: 10.1016/j.swevo.2011.02.003).
-
38)
-
14. Ochoa, L.F., Padilha-Feltrin, A., Harrison, G.P.: ‘Evaluating distributed generation impacts with a multiobjective index’, IEEE Trans. Power Deliv.,2006, 21, (3), pp. 1452–1458 (doi: 10.1109/TPWRD.2005.860262).
-
39)
-
28. Mitra, J., Patra, S.B., Ranade, S.J., et al: ‘Reliability-specified generation and distribution expansion in micro-grid architectures’, WSEAS Trans. Power Syst., 2006, 1, (8), pp. 1446–1453.
-
40)
-
30. Kumar, A., Srivastava, S.C., Singh, S.N.: ‘Available transfer capability (ATC) determination in a competitive electricity market using AC distribution factors’, Electr. Power Compon. Syst., 2004, 32, (9), pp. 927–939 (doi: 10.1080/15325000490253623).
-
41)
-
24. Hasanpour, S., Ghazi, R., Javidi, M.H.: ‘A new approach for cost allocation and reactive power pricing in a deregulated environment’, Electr. Eng., 2009, 91, (1), pp. 27–34 (doi: 10.1007/s00202-009-0113-2).
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-gtd.2015.1034
Related content
content/journals/10.1049/iet-gtd.2015.1034
pub_keyword,iet_inspecKeyword,pub_concept
6
6