Clean and Polluting DG Types Planning in Stochastic Price Conditions and DG Unit Uncertainties

Document Type : Research paper


Center of Excellence for power system automation and operation, Department of Electrical Engineering, Iran University of Science and Technology, Tehran, Iran


This study presents a dynamic way in a DG planning problem instead of the last static or pseudo-dynamic planning point of views. A new way in modeling the DG units’ output power and the load uncertainties based on the probability rules is proposed in this paper. A sensitivity analysis on the stochastic nature of the electricity price and global fuel price is carried out through a proposed model. Six types of clean and conventional DG units are included in the planning process. The presented dynamic planning problem is solved considering encouraging and punishment functions. The imperialist competitive algorithm (ICA) as a strong evolutionary strategy is employed to solve the DG planning problem. The proposed models and the proposed problem are applied on the 9-bus and 33-bus test distribution systems. The results show a significant improvement in the total revenue of the distribution system in all of the defined scenarios.


Main Subjects

[1]   J. Jung, A. Onen, K. Russell and R. P. Broadwater, "Local steady-state and quasi steady-state impact studies of high photovoltaic generation penetration in power distribution circuits," Renewable and Sustainable Energy Reviews, vol. 43, pp. 569-583, 2015.
[2]   V. V. S. N. Murty and A. Kumar, "Optimal placement of DG in radial distribution systems based on new voltage stability index under load growth," International Journal of Electrical Power & Energy Systems, vol. 69, pp. 246-256, 2015.
[3]   A. H. Allahnoori and S. K. M. Keyhani , "Reliability assessment of distribution systems in presence of microgrids considering uncertainty in generation and load demand," Journal of Operation and Automation in Power Engineering, vol. 2, pp. 113-120, 2014.
[4]   S. Kaur, G. Kumbhar and J. Sharma, "A MINLP technique for optimal placement of multiple DG units in distribution systems," International Journal of Electrical Power & Energy Systems, vol. 63, pp. 609-617, 2014.
[5] M. M. Aman, G. B. Jasmon, A. H. A. Bakar and H. Mokhlis, "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, vol. 66, pp. 202-215,  2014.
[6]   C. Liu, T. Tsuji and T. Oyama, "Power loss minimization considering short-circuit capacity in distribution system with decentralized distributed generation," IEEJ Transactions on Electrical and Electronic Engineering, vol. 7, pp. 471-477, 2012.
[7]   V. A. Evangelopoulos and P. S. Georgilakis, "Optimal distributed generation placement under uncertainties based on point estimate method embedded genetic algorithm," IET Proceedings on Generation, Transmission & Distribution, vol. 8, pp. 389-400, 2014.
[8]   M. Sadeghi and M. Kalantar, "The analysis of the effects of clean technologies from economic point of view," Journal of Cleaner Production, vol. 102, pp. 394-407, 2015.
[9]   C. A. Penuela Meneses and J. R. Sanches Mantovani, "Improving the grid operation and reliability cost of distribution systems with dispersed generation," IEEE Transactions on Power Systems , vol. 28, pp. 2485-2496, 2013.
[10]   B. Mohammadi-Ivatloo, A. Mokari, H. Seyedi and S. Ghasemzadeh, "An improved under-frequency load shedding scheme in distribution networks with distributed generation," Journal of Operation and Automation in Power Engineering, vol. 2, pp. 22-31, 2007.
[11]   R. Hemmati, R.-A. Hooshmand and N. Taheri, "Distribution network expansion planning and DG placement in the presence of uncertainties," International Journal of Electrical Power & Energy Systems, vol. 73, pp. 665-673, 2015.
[12]   W. Zhaoyu, C. Bokan, W. Jianhui, K. Jinho and M. M. Begovic, "Robust optimization based optimal DG placement in microgrids," IEEE Transactions on Smart Grid, vol. 5, pp. 2173-2182, 2014.
[13]   K. Sung-Yul, K. Wook-won and O. K. Jin, "Determining the optimal capacity of renewable distributed generation using restoration methods," IEEE Transactions on Power Systems , vol. 29, pp. 2001-2013, 2014.
[14]   N. R. Battu, A. R. Abhyankar and N. Senroy, "DG planning with amalgamation of economic and reliability considerations," International Journal of Electrical Power & Energy Systems, vol. 73, pp. 273-282, 2015.
[15]   S. Mallikarjun and H. F. Lewis, "Energy technology allocation for distributed energy resources: A strategic technology-policy framework," Energy, vol. 72, pp. 783-799, 8/1/ 2014.
[16]   S. Cheng, M.-Y. Chen and P. J. Fleming, "Improved multi-objective particle swarm optimization with preference strategy for optimal DG integration into the distribution system," Neurocomputing, vol. 148, pp. 23-29, 2015.
[17]   Y. M. Atwa, E. F. El-Saadany, M. M. A. Salama and R. Seethapathy, "Optimal renewable resources mix for distribution system energy loss minimization," IEEE Transactions on  Power Systems, vol. 25, pp. 360-370, 2010.
[18]   H. Siahkali and M. Vakilian, "Stochastic unit commitment of wind farms integrated in power system," Electric Power Systems Research, vol. 80, pp. 1006-1017, 2010.
[19]   E. Atashpaz-Gargari and C. Lucas, "Imperialist competitive algorithm: an algorithm for optimization inspired by imperialistic competition," in Proceedings of the IEEE Congress on Evolutionary Computation, pp. 4661-4667, 2007.
[20]   M. Abdollahi, A. Isazadeh and D. Abdollahi, "Imperialist competitive algorithm for solving systems of nonlinear equations," Computers & Mathematics with Applications, vol. 65, pp. 1894-1908, 2013.
[21]   M. A. Ahmadi, M. Ebadi, A. Shokrollahi and S. M. J. Majidi, "Evolving artificial neural network and imperialist competitive algorithm for prediction oil flow rate of the reservoir," Applied Soft Computing, vol. 13, pp. 1085-1098, 2013.
[22]   A. Zangeneh, S. Jadid and A. Rahimi-Kian, "Promotion strategy of clean technologies in distributed generation expansion planning," Renewable Energy, vol. 34, pp. 2765-2773, 2009.
[23]   M. F. Shaaban, Y. M. Atwa and E. F. El-Saadany, "DG allocation for benefit maximization in distribution networks," IEEE Transactions on Power Systems, vol. 28, pp. 639-649, 2013.
[24]   P. K. Katti and M. K. Khedkar, "Alternative energy facilities based on site matching and generation unit sizing for remote area power supply," Renewable Energy, vol. 32, pp. 1346-1362, 2007.
[25]   A. Soroudi and M. Ehsan, "A distribution network expansion planning model considering distributed generation options and techo-economical issues," Energy, vol. 35, pp. 3364-3374, 2010.
[26]   A. Zangeneh, S. Jadid and A. Rahimi-Kian, "A fuzzy environmental-technical-economic model for distributed generation planning," Energy, vol. 36, pp. 3437-3445,  2011.
[27]   Historical data of Iran Industrial power from 1980 to 1984.
[28]   N. Acharya, P. Mahat, and N. Mithulananthan, "An analytical approach for DG allocation in primary distribution network," International Journal of Electrical Power & Energy Systems, vol. 28, pp. 669-678, 2006.