Maximizing Available Delivery Capability of Unbalanced Distribution Networks for High Penetration of Distributed Generators

The network reconfiguration technique has been used to reduce network losses, balance transformer loading, and restore the power supply of the outage area in distribution networks. With a large number of uncontrollable distributed generators (DGs) added to distribution networks, the reconfiguration technique can be applied to enhance the available delivery capability (ADC) of distribution networks. This paper presents a two-stage methodology for determining optimal network topologies for improving the ADC of distribution networks for supporting more renewable energies. The first stage is a group-based binary particles swarm optimization (BPSO), which takes advantage of the BPSO's global capability while improving its slowness in finding optimal solutions. The second stage is a hybrid of greedy-based and domain-knowledge-based methods. When applied to multiple scenarios of DGs, the proposed methodology can effectively deal with the uncertainty of the DGs' outputs and time-varying loading conditions. As a byproduct, the optimal network topology found by the proposed methodology also decreases the network power losses due to the increase of the ADC of the distribution networks. The IEEE 123-bus test network and a practical 1001-node distribution network are used to verify the proposed methodology, and the numerical studies demonstrate the effectiveness of the proposed methodology in greatly increasing the ADC via optimal network reconfigurations.

[1]  V. Calderaro,et al.  Maximizing DG penetration in distribution networks by means of GA based reconfiguration , 2005, 2005 International Conference on Future Power Systems.

[2]  P.P. Barker,et al.  Determining the impact of distributed generation on power systems. I. Radial distribution systems , 2000, 2000 Power Engineering Society Summer Meeting (Cat. No.00CH37134).

[3]  A. Piccolo,et al.  Evaluating the Impact of Network Investment Deferral on Distributed Generation Expansion , 2009, IEEE Transactions on Power Systems.

[4]  Karen Nan Miu,et al.  Multi-tier service restoration through network reconfiguration and capacitor control for large-scale radial distribution networks , 1999 .

[5]  Tomás Gómez,et al.  Impact of distributed generation on distribution investment deferral , 2006 .

[6]  K. Tomsovic,et al.  Placement of dispersed generation systems for reduced losses , 2000, Proceedings of the 33rd Annual Hawaii International Conference on System Sciences.

[7]  A. Akbarimajd,et al.  A Method for Placement of DG Units in Distribution Networks , 2008, IEEE Transactions on Power Delivery.

[8]  M. Kitagawa,et al.  Implementation of genetic algorithm for distribution systems loss minimum re-configuration , 1992 .

[9]  M.T. Doyle,et al.  Reviewing the impacts of distributed generation on distribution system protection , 2002, IEEE Power Engineering Society Summer Meeting,.

[10]  Aboelsood Zidan,et al.  Network reconfiguration in balanced and unbalanced distribution systems with high DG penetration , 2011, 2011 IEEE Power and Energy Society General Meeting.

[11]  H. Chiang,et al.  Optimal network reconfigurations in distribution systems. I. A new formulation and a solution methodology , 1990 .

[12]  Wu Yao-wu OPTIMAL SHUNT CAPACITOR PLACEMENT USING PARTICLE SWARM OPTIMIZATION ALGORITHM WITH HARMONIC DISTORTION CONSIDERATION , 2003 .

[13]  D. Shirmohammadi Service restoration in distribution networks via network reconfiguration , 1991, Proceedings of the 1991 IEEE Power Engineering Society Transmission and Distribution Conference.

[14]  Hao Sheng,et al.  CDFLOW: A Practical Tool for Tracing Stationary Behaviors of General Distribution Networks , 2014, IEEE Transactions on Power Systems.

[15]  Yoshikazu Fukuyama,et al.  A hybrid particle swarm optimization for distribution state estimation , 2003, 2003 IEEE Power Engineering Society General Meeting (IEEE Cat. No.03CH37491).

[16]  R.E. Brown Modeling the reliability impact of distributed generation , 2002, IEEE Power Engineering Society Summer Meeting,.

[17]  H. Yoshida,et al.  A particle swarm optimization for reactive power and voltage control considering voltage security assessment , 1999, 2001 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.01CH37194).

[18]  H. Chiang,et al.  Fast service restoration for large-scale distribution systems with priority customers and constraints , 1997, Proceedings of the 20th International Conference on Power Industry Computer Applications.

[19]  P. Sensarma,et al.  A comprehensive method for optimal expansion planning using particle swarm optimization , 2002, 2002 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.02CH37309).

[20]  Rung-Fang Chang,et al.  Distributed Generation Interconnection Planning: A Wind Power Case Study , 2011, IEEE Transactions on Smart Grid.

[21]  N.D.R. Sarma,et al.  Real time service restoration in distribution networks-a practical approach , 1994 .