A Novel Approach to DG Curtailment in Rural Distribution Networks – A Case Study of the Avacon Grid as Part of the InterFlex Field Trial

Distribution system operators in rural areas of Germany are frequently facing imminent equipment overloading caused by the feed-in of local renewable Distributed Generation (DG). A grid operator’s last resort to maintain system stability and avoid protection tripping is to temporarily curtail local feed-in until hosting capacity in the network has caught up with the demand. Due to technological limitations in today’s networks the volume of curtailed energy can be greater than what would strictly be necessary. This paper presents a case study of a 110 kV overhead line in Avacon’s network and demonstrates the limitations of today’s approach to DG curtailments, especially the relative coarse granularity of control steps. The authors develop a novel control algorithm for emergency curtailments that takes advantage of technological improvements and describes the architecture for a successful deployment at the example of Avacon’s network and SCADA. The authors compare the amount of curtailed energy under today’s best practice with the theoretical optimum and the novel approach.

[1]  Michael J. Dolan,et al.  Reducing Distributed Generator Curtailment Through Active Power Flow Management , 2014, IEEE Transactions on Smart Grid.

[2]  A. N. M. M. Haque,et al.  Smart curtailment for congestion management in LV distribution network , 2016, 2016 IEEE Power and Energy Society General Meeting (PESGM).

[3]  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.

[4]  A.N.M.M. Haque,et al.  Distributed intelligence: Unleashing flexibilities for congestion management in smart distribution networks (Invited paper) , 2016, 2016 IEEE International Conference on Sustainable Energy Technologies (ICSET).

[5]  Weerakorn Ongsakul,et al.  Online optimal power management considering electric vehicles, load curtailment and grid trade in a microgrid energy market , 2015, 2015 IEEE Innovative Smart Grid Technologies - Asia (ISGT ASIA).

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

[7]  Takashi Ikegami,et al.  Effects of home energy management systems for reduction of renewables output curtailment , 2015, 2015 IEEE Innovative Smart Grid Technologies - Asia (ISGT ASIA).

[8]  Blazej Olek,et al.  Energy storing vs. generation curtailment — The measures for controlling renewable generation , 2017, 2017 14th International Conference on the European Energy Market (EEM).

[9]  Zita Vale,et al.  Study and analysis of wind curtailment situations and developing an appropriated methodology for its management , 2015, 2015 IEEE Eindhoven PowerTech.

[10]  Jae Won Lee,et al.  Framework for determining the compensation price for output curtailment of distributed generation within active distribution network management , 2015, 2015 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC).

[11]  Graham Ault,et al.  STANDARDISATION OF CURTAILMENT ANALYSIS AND THE IMPLICATIONS FOR DISTRIBUTION NETWORK OPERATORS AND GENERATORS , 2016 .