Smart curtailment for congestion management in LV distribution network

The rapid proliferation of distributed energy resources (DERs) leads to capacity challenges, i.e. network congestions, in the low-voltage (LV) distribution networks. A number of strategies are being widely studied to tackle the challenges with direct switching actions such as load shedding or power curtailment. On the other hand, various market-based demand response (DR) programs have been developed to influence the large number of DERs to use their flexibility to deal with network congestions. However, most of the market-based solutions rely on the flexibilities of the DERs, thus cannot solve the congestion when flexibility is not available in the network. To complement the market-based solutions, a smart active power curtailment based mechanism is necessary for managing the congestions in the distribution network. In this paper, we propose a novel method for congestion management by active power curtailment based on a Mixed-Integer Programming technique. In addition, two greedy selection methods together with fair power curtailment and security constrained OPF methods have been developed for the sake of comparison. The overall performance of the proposed approach and the comparison with other methods have been verified by a simulation with a typical LV network of the Netherlands.

[1]  Dechang Yang,et al.  A new intelligent algorithm for load shedding against overload in active distribution networks , 2014, 2014 International Conference on Power System Technology.

[2]  M.R. Hesamzadeh,et al.  An optimal load shedding approach for distribution networks with DGs considering capacity deficiency modelling of bulked power supply , 2008, 2008 Australasian Universities Power Engineering Conference.

[3]  F. Milano,et al.  An open source power system analysis toolbox , 2005, 2006 IEEE Power Engineering Society General Meeting.

[4]  A. M. Ranjbar,et al.  A global Particle Swarm-Based-Simulated Annealing Optimization technique for under-voltage load shedding problem , 2009, Appl. Soft Comput..

[5]  Phuong H. Nguyen,et al.  Capacity management within a multi-agent market-based active distribution network , 2012, 2012 3rd IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe).

[6]  H. Mokhlis,et al.  Overload alleviation scheme based on real time power flow tracing in distribution network , 2014, 2014 IEEE 8th International Power Engineering and Optimization Conference (PEOCO2014).

[7]  A. N. M. M. Haque,et al.  Congestion management in smart distribution network , 2014, 2014 49th International Universities Power Engineering Conference (UPEC).

[8]  Zhao Yang Dong,et al.  Load curtailment strategy in distribution network with dispersed generations , 2011, AUPEC 2011.

[9]  Qiuwei Wu,et al.  Review of congestion management methods for distribution networks with high penetration of distributed energy resources , 2014, IEEE PES Innovative Smart Grid Technologies, Europe.

[10]  Zofia Lukszo,et al.  Renewable Energy Sources and Responsive Demand. Do We Need Congestion Management in the Distribution Grid? , 2014, IEEE Transactions on Power Systems.

[11]  Johan Löfberg,et al.  YALMIP : a toolbox for modeling and optimization in MATLAB , 2004 .

[12]  A. N. M. M. Haque,et al.  Congestion management with the introduction of graceful degradation , 2015, 2015 IEEE Eindhoven PowerTech.