Distributed generation approach for single step system restoration during cold load pickup

When a system is restored after an extended outage, the demand is greater than that was before the outage due to the cold load pickup (CLPU) condition. In this paper, a particle swarm optimization (PSO) algorithm is used to find the optimal sizing and siting of distributed generation (DG) units for simultaneous single step restoration of transmission and distribution networks. The aim of the proposed DG allocation algorithm is to reduce the distribution substation transformer loss of life due to overloading and to reduce the lost load and hence the additional power demand caused by CLPU. The capacity of the DG required is determined on the basis of additional power demand and the load diversity preserved. The proposed algorithm is applied to the Egyptian 66 kV transmission network in the city of Alexandria including a 33-bus and a 69-bus, 11 kV primary distribution feeders.

[1]  Anil Pahwa.  Role of distribution automation in restoration of distribution systems after emergencies , 2001, 2001 Power Engineering Society Summer Meeting. Conference Proceedings (Cat. No.01CH37262).

[2]  Anil Pahwa,et al.  Optimal step-by-step restoration of distribution systems during excessive loads due to cold load pickup , 1995 .

[3]  R. Arseneau,et al.  Application of IEEE Standard 519-1992 Harmonic Limits for Revenue Billing Meters , 1997, IEEE Power Engineering Review.

[4]  M.M.A. Salama,et al.  An integrated distributed generation optimization model for distribution system planning , 2005, IEEE Transactions on Power Systems.

[5]  Amany M. El-Zonkol.  Optimal Placement of Multi DG Units Including Different Load Models Using PSO , 2010 .

[6]  V. Kumar,et al.  DG Integrated Approach for Service Restoration Under Cold Load Pickup , 2010, IEEE Transactions on Power Delivery.

[7]  Anil Pahwa,et al.  Distribution system design optimization for cold load pickup , 1996 .

[8]  Anil Pahwa,et al.  An analytical approach for step-by-step restoration of distribution systems following extended outages , 1994 .

[9]  James Kennedy,et al.  Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

[10]  Anil Pahwa,et al.  Ant algorithms for the optimal restoration of distribution feeders during cold load pickup , 2003, Proceedings of the 2003 IEEE Swarm Intelligence Symposium. SIS'03 (Cat. No.03EX706).

[11]  Amany El-Zonkoly.  Fault Diagnosis in Distribution Networks with Distributed Generation , 2011 .

[12]  A. Pahwa,et al.  A voltage drop-based approach to include cold load pickup in design of distribution systems , 2004, IEEE Transactions on Power Systems.

[13]  M. M. Adibi.  Distribution System Design Optimization for Cold Load Pickup , 2000 .

[14]  Chan-Nan Lu,et al.  Distribution system feeder cold load pickup model , 1996 .

[15]  Amany El-Zonkoly,et al.  Optimal placement of multi-distributed generation units including different load models using particle swarm optimisation , 2011 .

[16]  Max D. Anderson,et al.  An Analytical Method for Quantifying the Electrical Space Heating Component of a Cold Load Pick Up , 1982, IEEE Transactions on Power Apparatus and Systems.

[17]  C. Andrieu,et al.  A New Restoration Process in Power Systems with Large Scale of Dispersed Generation , 2006, 2005/2006 IEEE/PES Transmission and Distribution Conference and Exhibition.