Optimal placement of multiple DGs in radial distribution systems to minimize power loss using BSA
Yıl 2021,
Cilt: 17 Sayı: 2, 199 - 207, 28.06.2021
Waleed Fadel
,
Ulaş Kılıç
,
Sezai Taşkın
Öz
: Distributed generation (DG) sources are becoming more important in electrical networks due to the increase of electrical energy demands. However, DG sources can have a profound effect on network power loss. Hence, optimal placement and size of DGs are extremely important. This study presents a backtracking search algorithm (BSA) based on optimal placement and size of multiple DGs within distribution systems so to reduce power loss. The BSA is a new heuristic algorithm. Two main DGs, photovoltaic and synchronous compensator, were used in the selected systems. To demonstrate the effectiveness of the proposed method, the results obtained by BSA are compared with a genetic algorithm (GA) as well as other results in the literature.
Kaynakça
- Kansal, S., Kumar, V. and Tyagi, B., 2013. Optimal placement of different type of DG sources in distribution networks. International Journal of Electrical Power & Energy Systems, 53, pp.752-760.
- Kayal, P. and Chanda, C.K., 2013. Placement of wind and solar based DGs in distribution system for power loss minimization and voltage stability improvement. International Journal of Electrical Power & Energy Systems, 53, pp.795-809.
- Kollu, R., Rayapudi, S.R. and Sadhu, V.L.N., 2014. A novel method for optimal placement of distributed generation in distribution systems using HSDO. International Transactions on Electrical Energy Systems, 24(4), pp.547-561.
- García, J.A.M. and Mena, A.J.G., 2013. Optimal distributed generation location and size using a modified teaching–learning based optimization algorithm. International journal of electrical power & energy systems, 50, pp.65-75.
- Injeti, S.K. and Kumar, N.P., 2013. A novel approach to identify optimal access point and capacity of multiple DGs in a small, medium and large scale radial distribution systems. International Journal of Electrical Power & Energy Systems, 45(1), pp.142-151.
- Manafi, H., Ghadimi, N., Ojaroudi, M. and Farhadi, P., 2013. Optimal placement of distributed generations in radial distribution systems using various PSO and DE algorithms. Elektronika ir Elektrotechnika, 19(10), pp.53-57.
- Moradi, M.H. and Abedini, M., 2012. A combination of genetic algorithm and particle swarm optimization for optimal DG location and sizing in distribution systems. International Journal of Electrical Power & Energy Systems, 34(1), pp.66-74.
- Aman, M.M., Jasmon, G.B., Bakar, A.H.A. and Mokhlis, H., 2013. A new approach for optimum DG placement and sizing based on voltage stability maximization and minimization of power losses. Energy Conversion and Management, 70, pp.202-210.
- Murthy, V.V.S.N. and Kumar, A., 2013. Comparison of optimal DG allocation methods in radial distribution systems based on sensitivity approaches. International Journal of Electrical Power & Energy Systems, 53, pp.450-467.
- Al Abri, R.S., El-Saadany, E.F. and Atwa, Y.M., 2013. Optimal placement and sizing method to improve the voltage stability margin in a distribution system using distributed generation. IEEE transactions on power systems, 28(1), pp.326-334.
- Aman, M.M., Jasmon, G.B., Mokhlis, H. and Bakar, A.H.A., 2012. Optimal placement and sizing of a DG based on a new power stability index and line losses. International Journal of Electrical Power & Energy Systems, 43(1), pp.1296-1304.
Naik, S.G., Khatod, D.K. and Sharma, M.P., 2013. Optimal allocation of combined DG and capacitor for real power loss minimization in distribution networks. International Journal of Electrical Power & Energy Systems, 53, pp.967-973.
- Kansal, S., Kumar, V. and Tyagi, B., 2013. Optimal placement of different type of DG sources in distribution networks. International Journal of Electrical Power & Energy Systems, 53, pp.752-760.
- Kayal, P. and Chanda, C.K., 2013. Placement of wind and solar based DGs in distribution system for power loss minimization and voltage stability improvement. International Journal of Electrical Power & Energy Systems, 53, pp.795-809.
- Injeti, S.K. and Kumar, N.P., 2013. A novel approach to identify optimal access point and capacity of multiple DGs in a small, medium and large scale radial distribution systems. International Journal of Electrical Power & Energy Systems, 45(1), pp.142-151.
- Manafi, H., Ghadimi, N., Ojaroudi, M. and Farhadi, P., 2013. Optimal placement of distributed generations in radial distribution systems using various PSO and DE algorithms. Elektronika ir Elektrotechnika, 19(10), pp.53-57.
- Moradi, M.H. and Abedini, M., 2012. A combination of genetic algorithm and particle swarm optimization for optimal DG location and sizing in distribution systems. International Journal of Electrical Power & Energy Systems, 34(1), pp.66-74.
- Kansal, S., Kumar, V. and Tyagi, B., 2016. Hybrid approach for optimal placement of multiple DGs of multiple types in distribution networks. International Journal of Electrical Power & Energy Systems, 75, pp.226-235.
- Civicioglu, P., 2013. Backtracking search optimization algorithm for numerical optimization problems. Applied Mathematics and Computation, 219(15), pp.8121-8144.
- Moradi, M.H., Zeinalzadeh, A., Mohammadi, Y. and Abedini, M., 2014. An efficient hybrid method for solving the optimal sitting and sizing problem of DG and shunt capacitor banks simultaneously based on imperialist competitive algorithm and genetic algorithm. International Journal of Electrical Power & Energy Systems, 54, pp.101-111.
- Abu-Mouti, F.S. and El-Hawary, M.E., 2011. Optimal distributed generation allocation and sizing in distribution systems via artificial bee colony algorithm. IEEE transactions on power delivery, 26(4), pp.2090-2101.
- Kılıç, U., 2015. Backtracking search algorithm-based optimal power flow with valve point effect and prohibited zones. Electrical Engineering, 97(2), pp.101-110.
- Song, X., Zhang, X., Zhao, S. and Li, L., 2015. Backtracking search algorithm for effective and efficient surface wave analysis. Journal of Applied Geophysics, 114, pp.19-31.
- Duan, H. and Luo, Q., 2014. Adaptive backtracking search algorithm for induction magnetometer optimization. IEEE Transactions on Magnetics, 50(12), pp.1-6.
- Aman, M.M., Jasmon, G.B., Bakar, A.H.A. and Mokhlis, H., 2014. A new approach for optimum simultaneous multi-DG distributed generation Units placement and sizing based on maximization of system loadability using HPSO (hybrid particle swarm optimization) algorithm. Energy, 66, pp.202-215.
Yıl 2021,
Cilt: 17 Sayı: 2, 199 - 207, 28.06.2021
Waleed Fadel
,
Ulaş Kılıç
,
Sezai Taşkın
Kaynakça
- Kansal, S., Kumar, V. and Tyagi, B., 2013. Optimal placement of different type of DG sources in distribution networks. International Journal of Electrical Power & Energy Systems, 53, pp.752-760.
- Kayal, P. and Chanda, C.K., 2013. Placement of wind and solar based DGs in distribution system for power loss minimization and voltage stability improvement. International Journal of Electrical Power & Energy Systems, 53, pp.795-809.
- Kollu, R., Rayapudi, S.R. and Sadhu, V.L.N., 2014. A novel method for optimal placement of distributed generation in distribution systems using HSDO. International Transactions on Electrical Energy Systems, 24(4), pp.547-561.
- García, J.A.M. and Mena, A.J.G., 2013. Optimal distributed generation location and size using a modified teaching–learning based optimization algorithm. International journal of electrical power & energy systems, 50, pp.65-75.
- Injeti, S.K. and Kumar, N.P., 2013. A novel approach to identify optimal access point and capacity of multiple DGs in a small, medium and large scale radial distribution systems. International Journal of Electrical Power & Energy Systems, 45(1), pp.142-151.
- Manafi, H., Ghadimi, N., Ojaroudi, M. and Farhadi, P., 2013. Optimal placement of distributed generations in radial distribution systems using various PSO and DE algorithms. Elektronika ir Elektrotechnika, 19(10), pp.53-57.
- Moradi, M.H. and Abedini, M., 2012. A combination of genetic algorithm and particle swarm optimization for optimal DG location and sizing in distribution systems. International Journal of Electrical Power & Energy Systems, 34(1), pp.66-74.
- Aman, M.M., Jasmon, G.B., Bakar, A.H.A. and Mokhlis, H., 2013. A new approach for optimum DG placement and sizing based on voltage stability maximization and minimization of power losses. Energy Conversion and Management, 70, pp.202-210.
- Murthy, V.V.S.N. and Kumar, A., 2013. Comparison of optimal DG allocation methods in radial distribution systems based on sensitivity approaches. International Journal of Electrical Power & Energy Systems, 53, pp.450-467.
- Al Abri, R.S., El-Saadany, E.F. and Atwa, Y.M., 2013. Optimal placement and sizing method to improve the voltage stability margin in a distribution system using distributed generation. IEEE transactions on power systems, 28(1), pp.326-334.
- Aman, M.M., Jasmon, G.B., Mokhlis, H. and Bakar, A.H.A., 2012. Optimal placement and sizing of a DG based on a new power stability index and line losses. International Journal of Electrical Power & Energy Systems, 43(1), pp.1296-1304.
Naik, S.G., Khatod, D.K. and Sharma, M.P., 2013. Optimal allocation of combined DG and capacitor for real power loss minimization in distribution networks. International Journal of Electrical Power & Energy Systems, 53, pp.967-973.
- Kansal, S., Kumar, V. and Tyagi, B., 2013. Optimal placement of different type of DG sources in distribution networks. International Journal of Electrical Power & Energy Systems, 53, pp.752-760.
- Kayal, P. and Chanda, C.K., 2013. Placement of wind and solar based DGs in distribution system for power loss minimization and voltage stability improvement. International Journal of Electrical Power & Energy Systems, 53, pp.795-809.
- Injeti, S.K. and Kumar, N.P., 2013. A novel approach to identify optimal access point and capacity of multiple DGs in a small, medium and large scale radial distribution systems. International Journal of Electrical Power & Energy Systems, 45(1), pp.142-151.
- Manafi, H., Ghadimi, N., Ojaroudi, M. and Farhadi, P., 2013. Optimal placement of distributed generations in radial distribution systems using various PSO and DE algorithms. Elektronika ir Elektrotechnika, 19(10), pp.53-57.
- Moradi, M.H. and Abedini, M., 2012. A combination of genetic algorithm and particle swarm optimization for optimal DG location and sizing in distribution systems. International Journal of Electrical Power & Energy Systems, 34(1), pp.66-74.
- Kansal, S., Kumar, V. and Tyagi, B., 2016. Hybrid approach for optimal placement of multiple DGs of multiple types in distribution networks. International Journal of Electrical Power & Energy Systems, 75, pp.226-235.
- Civicioglu, P., 2013. Backtracking search optimization algorithm for numerical optimization problems. Applied Mathematics and Computation, 219(15), pp.8121-8144.
- Moradi, M.H., Zeinalzadeh, A., Mohammadi, Y. and Abedini, M., 2014. An efficient hybrid method for solving the optimal sitting and sizing problem of DG and shunt capacitor banks simultaneously based on imperialist competitive algorithm and genetic algorithm. International Journal of Electrical Power & Energy Systems, 54, pp.101-111.
- Abu-Mouti, F.S. and El-Hawary, M.E., 2011. Optimal distributed generation allocation and sizing in distribution systems via artificial bee colony algorithm. IEEE transactions on power delivery, 26(4), pp.2090-2101.
- Kılıç, U., 2015. Backtracking search algorithm-based optimal power flow with valve point effect and prohibited zones. Electrical Engineering, 97(2), pp.101-110.
- Song, X., Zhang, X., Zhao, S. and Li, L., 2015. Backtracking search algorithm for effective and efficient surface wave analysis. Journal of Applied Geophysics, 114, pp.19-31.
- Duan, H. and Luo, Q., 2014. Adaptive backtracking search algorithm for induction magnetometer optimization. IEEE Transactions on Magnetics, 50(12), pp.1-6.
- Aman, M.M., Jasmon, G.B., Bakar, A.H.A. and Mokhlis, H., 2014. A new approach for optimum simultaneous multi-DG distributed generation Units placement and sizing based on maximization of system loadability using HPSO (hybrid particle swarm optimization) algorithm. Energy, 66, pp.202-215.