Hamidreza Arasteh Mohammad Sadegh Sepasian Vahid Vahidinasab


The planning of an active distribution system is investigated in this study. This paper conducts a novel concept of smart distribution system reconfiguration and planning problem. Proposed problem uses the concept of distribution system reconfiguration (DSR) with the aim of reducing and postponing the expansion requirements, while the potential of demand response (DR) programs are considered. DR programs are modeled as virtual and distributed resources to be dealt with the distribution system expansion planning (DEP) problem in the long term time horizon. Indeed, the main purpose of this paper is to propose “demand response and distribution system reconfiguration and expansion planning (DR-DSREP)” problem to identify the impact of DSR and DR on the expansion planning of distribution systems. The 33-bus distribution system is utilized in numerical studies to investigate the performance and effectiveness of the proposed problem. The simulation results show the efficiency and advantage of the proposed methodology.

Article Details

[1] A. M. Cossi, R. Romero, and J. R. S. Mantovani, “Planning of secondary distribution circuits through evolutionary algorithms,” IEEE Trans. Power Del., vol. 20, pp. 205-213, 2005.
[2] S. Haffner, L. F. A Pereira, L. A. Pereira, and L. S. Barreto, “Multistage model for distribution expansion planning with distributed generation—Part I: Problem formulation,” IEEE Trans. Power Del., vol. 23, pp. 915-923, 2008.
[3] H. K Temraz, and V. H. Quintana, “Distribution system expansion planning models: an overview,” Electr. Power Syst. Res., vol. 26, pp. 61-70, 1993.
[4] M. Setayesh Nazar, M. Haghifam, and M. Nazˇar, “A scenario driven multiobjective Primary–Secondary Distribution System Expansion Planning algorithm in the presence of wholesale–retail market,” Electr. Power Energy Syst., vol. 40, pp. 29-45, 2012.
[5] A. Navarro, and H. Rudnick, “Large-scale distribution planning—Part I: Simultaneous network and transformer optimization,” IEEE Trans. Power Syst., vol. 24, pp. 744-751, 2009.
[6] B. R. Pereira Junior, A. M. Cossi, J. Contreras, and J. R. Sanches Mantovani, “Multiobjective multistage distribution system planning using tabu search,” IET Gener. Transm. Distrib., vol. 8, pp. 35-45, 2014.
[7] H. Xing, H. Cheng, Y. Zhang, and P. Zeng, “Active distribution network expansion planning integrating dispersed energy storage systems,” IET Gener. Transm. Distrib., vol. 10, pp. 638–644, 2016.
[8] M. Ahmadigorji, N. Amjady, “A multiyear DG-incorporated framework for expansion planning of distribution networks using binary chaotic shark smell optimization algorithm,” Energy, vol. 102, pp. 199-215, 2016.
[9] H. Falaghi, C. Singh, M. R. Haghifam, and M. Ramezani, “DG integrated multistage distribution system expansion planning,” Electr. Power Energy Syst., vol. 33, pp. 1489-1497, 2011.
[10] V. Vahidinasab, “Optimal distributed energy resources planning in a competitive electricity market: Multiobjective optimization and probabilistic design,” Renew. Energy, vol. 66, pp. 354-363, 2014.
[11] S. Najafi Ravadanegh, and R. Gholizadeh Roshanagh, “On optimal multistage electric power distribution networks expansion planning,” Electr. Power Energy Syst., vol. 54, pp:487-497, 2014.
[12] A. R. Abbasi, and A. R. Seifi, “Considering cost and reliability in electrical and thermal distribution networks reinforcement planning,” Energy, vol. 84, pp. 25-35, 2015.
[13] N. Khalesi, N. Rezaei, and M. R. Haghifam, “DG allocation with application of dynamic programming for loss reduction and reliability improvement,” Electr. Power Energy Syst., vol. 33, pp. 288-295, 2011.
[14] C. L. T. Borges, and V. F. Martins, “Multistage expansion planning for active distribution networks under demand and distributed generation uncertainties,” Electr. Power Energy Syst., vol. 36, pp. 107:116, 2012.
[15] A. M. El-Zonkoly, “Multistage expansion planning for distribution networks including unit commitment,” IET Gener. Transm. Distrib., vol. 7, pp. 766-778, 2013.
[16] H. R. Arasteh, M. Parsa Moghaddam, M. K. Sheikh-El-Eslami, and A. Abdollahi, “Integrating commercial demand response resources with unit commitment,” Electr. Power Energy Syst., vol. 51, pp. 153-161, 2013.
[17] S. M. Mazhari, H. Monsef, and Rubén Romero, “A multi-objective distribution system expansion planning incorporating customer choices on reliability,” IEEE Trans. Power Syst., vol. 31, pp. 1330-1340, 2016.
[18] P. S. Georgilakis, and N. D. Hatziargyriou, “A review of power distribution planning in the modern power systems era: Models, methods and future research,” Electr. Power Syst. Res., vol. 121, pp. 89-100, 2015.
[19] F. De Ridder, M. Hommelberg, and E. Peeters, “Demand side integration: four potential business cases and an analysis of the 2020 situation,” Euro. Trans. Electr. Power, vol. 21, pp. 1902-1913, 2011.
[20] B. Kladnik, G. Artac, and A. Gubina, “An assessment of the effects of demand response in electricity markets,” Euro. Trans. Electr. Power, vol. 23, pp. 380-391, 2013.
[21] IEA. Strategic plan for the IEA demand-side management program 2008-2012, IEA Press, 2008, [accessed 03.12].
[22] H. R. Arasteh, M. Parsa Moghaddam, and M. K. Sheikh-El-Eslami, “A Comprehensive Framework for Retailer’s Financial Policy,” Journal of Electrical Systems and Signals, vol. 1, pp. 7-18, 2013.
[23] H. Arasteh, M. S. Sepasian, and V. Vahidinasab, “Toward a Smart Distribution System Expansion Planning by Considering Demand Response Resources,” Journal of Operation and Automation in Power Engineering, vol. 3, no. 2, pp. 116-130, 2015.
[24] H. Fathabadi, “Power distribution network reconfiguration for power loss minimization using novel dynamic fuzzy c-means (dFCM) clustering based ANN approach,” Electr. Power Energy Syst., vol. 78, pp. 96–107, 2016.
[25] A. M. Tahboub, V. R. Pandi, and H. H. Zeineldin, “Distribution system reconfiguration for annual energy loss reduction considering variable distributed generation profiles,” IEEE Trans. Power Del., vol. 30, pp. 1677-1685, 2015.
[26] A. Zidan, M. F. Shaaban, and E. F. El-Saadany, “Long-term multi-objective distribution network planning by DG allocation and feeders’ reconfiguration,” Electr. Power Syst. Res., vol. 95, pp. 104-105, 2013.
[27] A. González, F. M. Echavarren, L. Rouco, T. Gómez, and J. Cabetas, “Reconfiguration of large-scale distribution networks for planning studies,” Electr. Power Energy Syst., vol. 37, pp. 86-94, 2012.
[28] K. Sathish Kumar, and T. Jayabarathi, “Power system reconfiguration and loss minimization for an istribution systems using bacterial foraging optimization algorithm,” Electr. Power Energy Syst., vol. 36, pp. 13-17, 2012.
[29] S. H. Mirhoseini, S. M. Hosseini, M. Ghanbari, and M. Ahmadi, “A new improved adaptive imperialist competitive algorithm to solve the reconfiguration problem of distribution systems for loss reduction and voltage profile improvement,” Electr. Power Energy Syst., vol. 55, pp. 128-143, 2014.
[30] A. M. Eldurssi, and R. M. O'Connell, “A Fast Nondominated sorting guided genetic algorithm for multi-objective power distribution system reconfiguration problem,” IEEE Trans. Power Syst., vol. 30, pp. 593–601, 2015.
[31] F. R. Alonso, D. Q. Oliveira, and A. C. Zambroni de Souza, “Artificial Immune Systems Optimization Approach for Multiobjective Distribution System Reconfiguration,” IEEE Trans. Power Syst., vol. 30, pp. 840-847, 2015.
[32] R. H. Fletcher, and K. Strunz, “Optimal distribution system horizon planning–Part I: Formulation,” IEEE Trans. Power Syst., vol. 22, pp. 791-799, 2007.
[33] J. Aghaei, M. K. M. Muttaqi, A. Azizivahed, and M. Gitizadeh, “Distribution expansion planning considering reliability and security of energy using modified PSO (Particle Swarm Optimization) algorithm,” Energy, vol. 65, pp. 398–411, 2014.
[34] A. M. Cossi, L.G.W. da Silva, R. A. R. La´ zaro, and J.R.S. Mantovani, “Primary power distribution systems planning taking into account reliability, operation and expansion costs,” IET Gener. Transm. Distrib., vol. 6, no. 3, pp. 274–284, 2012.
[35] A. El-Zonkoly, M. Saad, and R. Khalil, “New algorithm based on CLPSO for controlled islanding of distribution systems,” Electr. Power Energy Syst., vol. 45, no. 1, pp. 391–403, 2013.
[36] K. Zou, A. P. Agalgaonkar, K. M. Muttaqi, and S. Perera, “An analytical approach for reliability evaluation of distribution systems containing dispatchable and nondispatchable renewable DG units,” IEEE Trans. Smart Grid, vol. 5, no. 6, pp. 2657-2665, 2014.
[37] P. Wang, and R. Billinton, “Time-sequential simulation technique for rural distribution system reliability cost/worth evaluation including wind generation as alternative supply,” IET Gener. Transmiss Distrib., vol. 148, no. 4, pp. 355–360, 2001.
[38] A. A. Chowdhury, S. K. Agarwal, and D. O. Koval, “Reliability modelling of distributed generation in conventional distribution systems planning and analysis,” IEEE Trans. Ind. Appl., vol. 39, no. 5, pp. 1493–1498, 2003.
[39] I. J. Ramírez-Rosado, and J. L. Bernal-Agustín, “Reliability and costs optimization for distribution networks expansion using an evolutionary algorithm,” IEEE Trans. Power Syst., vol. 16, pp. 111-118, 2001.
[40] G. R. Aghajani, H. A. Shayanfar, and H. Shayeghi, “Presenting a multi-objective generation scheduling model for pricing demand response rate in micro-grid energy management,” Energ. Convers. Manage., vol. 106, pp. 308–321, 2015.
[41] W. Sheng, K. Y. Liu, Y. Liu, X. Meng, and Y. Li, “Optimal placement and sizing of distributed generation via an improved nondominated sorting genetic algorithm 2,” IEEE Trans. on Power Del., vol. 30, pp. 569–578, 2015.
[42] H. Mavalizadeh, A. Ahmadi, and A. Heidari, “Probabilistic multi-objective generation and transmission expansion planning problem using normal boundary intersection,” IET Gener. Transmiss. Distrib., vol. 9, pp. 560-570, 2015.
[43] S. Wen, H. Lan, Q. Fu, D. C. Yu, and L. Zhang, “Economic allocation for energy storage system considering wind power distribution,” IEEE Trans. Power Syst., vol. 30, pp. 644-652, 2015.
[44] J. C. López, M. Lavorato, and M. J. Rider, “Optimal reconfiguration of electrical distribution systems considering reliability indices improvement,” Electr. Power Energy Syst., vol. 78, pp. 837–845, 2016.
[45] E. G. Carrano, F. G. Guimarães, R. H. Takahashi, O. M. Neto, and F. Campelo, “Electric distribution network expansion under load-evolution uncertainty using an immune system inspired algorithm,” IEEE Trans. Power Syst., vol. 22, pp. 851-861, 2007.
[46] A. M. Cossi, R. Romero, and J. R. Mantovani, “Planning and projects of secondary electric power distribution systems,” IEEE Trans. Power Syst., vol. 24, pp. 1599-1608, 2009.
[47] J. H. Kim, and A. Shcherbakova, “Common Failures of Demand Response,” Energy, vol. 36, pp. 873-880, 2011.
[48] P. Ghamisi, and J. A. Benediktsson, “Feature selection based on hybridization of genetic algorithm and particle swarm optimization”, IEEE Geoscience and Remote Sensing Letters, vol. 12, no. 2, pp. 309-313, 2015.
[49] A. Stoppato, G. Cavazzini, G. Ardizzon, and A. Rossetti, “A PSO (particle swarm optimization)-based model for the optimal management of a small PV (Photovoltaic)-pump hydro energy storage in a rural dry area,” Energy, vol. 76, pp. 168–174, 2014.
[50] B. Jiang, and Y. Fei, “Smart Home in Smart Microgrid. A Cost-effective energy ecosystem with intelligent hierarchical agents,” IEEE Trans. Smart Grid, vol. 6, no. 1, pp. 3-13, 2015.
[51] P. Zhang, W. Li, and S. Wang, “Reliability-oriented distribution network reconfiguration considering uncertainties of data by interval analysis,” Elect. Power Energy Syst., vol. 34, pp. 138-144, 2012.
How to Cite
Arasteh, H., Sepasian, M. S., & Vahidinasab, V. (2015). Incorporation of Distribution System Reconfiguration and Expansion Planning Problems by Considering the Role of Demand Response Resources. Journal of Electrical Systems and Signals, 3(1), 23-36. https://doi.org/10.22067/ess.v3i1.54658
Researsh Articles