Multi-Objective Reconfiguration of Radial Distribution Systems Using Reliability Indices

This paper deals with the distribution network reconfiguration problem in a multi-objective scope, aiming to determine the optimal radial configuration by means of minimizing the active power losses and a set of commonly used reliability indices formulated with reference to the number of customers. The indices are developed in a way consistent with a mixed-integer linear programming (MILP) approach. A key contribution of the paper is the efficient implementation of the -constraint method using lexicographic optimization in order to solve the multi-objective optimization problem. After the Pareto efficient solution set is generated, the resulting configurations are evaluated using a backward/forward sweep load-flow algorithm to verify that the solutions obtained are both non-dominated and feasible. Since the -constraint method generates the Pareto front but does not incorporate decision maker (DM) preferences, a multi-attribute decision making procedure, namely, the technique for order preference by similarity to ideal solution (TOPSIS) method, is used in order to rank the obtained solutions according to the DM preferences, facilitating the final selection. The applicability of the proposed method is assessed on a classical test system and on a practical distribution system.

[1]  George Mavrotas,et al.  An improved version of the augmented ε-constraint method (AUGMECON2) for finding the exact pareto set in multi-objective integer programming problems , 2013, Appl. Math. Comput..

[2]  A. A. M. Zin,et al.  Reconfiguration of Radial Electrical Distribution Network Through Minimum-Current Circular-Updating-Mechanism Method , 2012, IEEE Transactions on Power Systems.

[3]  D.V. Nicolae,et al.  Reconfiguration and Load Balancing in the LV and MV Distribution Networks for Optimal Performance , 2007, IEEE Transactions on Power Delivery.

[4]  George Mavrotas,et al.  Effective implementation of the epsilon-constraint method in Multi-Objective Mathematical Programming problems , 2009, Appl. Math. Comput..

[5]  M. Matos,et al.  Distribution Systems Reconfiguration Based on OPF Using Benders Decomposition , 2009, IEEE Transactions on Power Delivery.

[6]  Zhengcai Fu,et al.  Joint Optimization for Power Loss Reduction in Distribution Systems , 2008, IEEE Transactions on Power Systems.

[7]  K. Ravindra,et al.  Power Loss Minimization in Distribution System Using Network Reconfiguration in the Presence of Distributed Generation , 2013, IEEE Transactions on Power Systems.

[8]  J. R. Shin,et al.  An efficient simulated annealing algorithm for network reconfiguration in large-scale distribution systems , 2002 .

[9]  A. Borghetti A Mixed-Integer Linear Programming Approach for the Computation of the Minimum-Losses Radial Configuration of Electrical Distribution Networks , 2012, IEEE Transactions on Power Systems.

[10]  S. Singh,et al.  Reconfiguration of Power Distribution Systems Considering Reliability and Power Loss , 2012, IEEE Transactions on Power Delivery.

[11]  Abdollah Kavousi-Fard,et al.  Reliability enhancement using optimal distribution feeder reconfiguration , 2013, Neurocomputing.

[12]  Weihua Zhang,et al.  A simple augmented ∊-constraint method for multi-objective mathematical integer programming problems , 2014, Eur. J. Oper. Res..

[13]  M. Raju,et al.  Optimal Network Reconfiguration of Large-Scale Distribution System Using Harmony Search Algorithm , 2011, IEEE Transactions on Power Systems.

[14]  G. Chicco,et al.  Optimal multi-objective distribution system reconfiguration with multi criteria decision making-based solution ranking and enhanced genetic operators , 2014 .

[15]  D. Shirmohammadi,et al.  Reconfiguration of electric distribution networks for resistive line losses reduction , 1989 .

[16]  Sanjib Kumar Panda,et al.  Optimization of Distribution Network Incorporating Distributed Generators: An Integrated Approach , 2013, IEEE Transactions on Power Systems.

[17]  M. J. Rider,et al.  A mixed-integer LP model for the reconfiguration of radial electric distribution systems considering distributed generation , 2013 .

[18]  Ehab F. El-Saadany,et al.  Long-term multi-objective distribution network planning by DG allocation and feeders’ reconfiguration , 2013 .

[19]  Gianfranco Chicco,et al.  Identification of the Radial Configurations Extracted From the Weakly Meshed Structures of Electrical Distribution Systems , 2008, IEEE Transactions on Circuits and Systems I: Regular Papers.

[20]  Taher Niknam,et al.  Optimal Distribution Feeder Reconfiguration for Reliability Improvement Considering Uncertainty , 2014, IEEE Transactions on Power Delivery.

[21]  C. Hwang Multiple Objective Decision Making - Methods and Applications: A State-of-the-Art Survey , 1979 .

[22]  Walter Ukovich,et al.  Minimum loss reconfiguration of electrical distribution networks with quality requirements , 2013, 2013 American Control Conference.

[23]  Carmen L. T. Borges,et al.  A Flexible Mixed-Integer Linear Programming Approach to the AC Optimal Power Flow in Distribution Systems , 2014, IEEE Transactions on Power Systems.

[24]  Shouxiang Wang,et al.  Reliability-oriented distribution network reconfiguration considering uncertainties of data by interval analysis , 2012 .

[25]  Gianfranco Chicco,et al.  Distribution system optimisation with intra-day network reconfiguration and demand reduction procurement , 2013 .

[26]  C. Su,et al.  Network Reconfiguration of Distribution Systems Using Improved Mixed-Integer Hybrid Differential Evolution , 2002, IEEE Power Engineering Review.

[27]  Felix F. Wu,et al.  Network Reconfiguration in Distribution Systems for Loss Reduction and Load Balancing , 1989, IEEE Power Engineering Review.

[28]  G. Chicco,et al.  Evaluation of the probability density functions of distribution system reliability indices with a characteristic functions-based approach , 2004, IEEE Transactions on Power Systems.

[29]  R. K. Ursem Multi-objective Optimization using Evolutionary Algorithms , 2009 .

[30]  Taher Niknam,et al.  Multi-Objective Stochastic Distribution Feeder Reconfiguration in Systems With Wind Power Generators and Fuel Cells Using the Point Estimate Method , 2013, IEEE Transactions on Power Systems.

[31]  T. Thakur,et al.  Study and Characterization of Power Distribution Network Reconfiguration , 2006, 2006 IEEE/PES Transmission & Distribution Conference and Exposition: Latin America.

[32]  M. Pipattanasomporn,et al.  Reliability benefits of distributed generation as a backup source , 2009, 2009 IEEE Power & Energy Society General Meeting.

[33]  R. Jabr,et al.  Minimum Loss Network Reconfiguration Using Mixed-Integer Convex Programming , 2012, IEEE Transactions on Power Systems.

[34]  Yuan-Kang Wu,et al.  Study of Reconfiguration for the Distribution System With Distributed Generators , 2010, IEEE Transactions on Power Delivery.

[35]  Haidar Samet,et al.  Consideration effect of uncertainty in power system reliability indices using radial basis function network and fuzzy logic theory , 2011, Neurocomputing.

[36]  M. Rider,et al.  Imposing Radiality Constraints in Distribution System Optimization Problems , 2012 .

[37]  D. Shirmohammadi,et al.  A compensation-based power flow method for weakly meshed distribution and transmission networks , 1988 .