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Impact of Inverter-Connected Generation Units on the Operations of Power Systems (jointly with Reliability and Risk Engineering)

The introduction of distributed inverter-connected renewable energy units, e.g. wind turbines and photovoltaics, has increased the share of non-synchronous generation compared to that of classical synchronous generation. This shift in operating conditions has led to a decrease of the inertia in the electric grid pushing its closer to its stability limits [1]. For the Continental European power system, system splitting scenarios have been identified as critical, in particular in view of increased transmission capacities [2]. However, system studies also indicate that inverter-connected generation can contribute to the reduction of system frequency deviations after the occurrence of a contingency. Compared to conventional synchronous machines, inverter-connected generation units feature a shorter time scale of operations enabling the provision of “synthetic inertia” [3]-[5].

The aim of the project is to further develop already existing frequency control models in order to represent inverter-connected generation units providing “synthetic inertia” [6]-[7]. In a case study, the obtained model should then be employed to assess the impact of a high penetration of inverter-connected generation units on the frequency stability of the East Australian power system. Possible measures for quantifying the magnitude and consequences of the instability event will be load shedding, binary outcomes (blackout or not), or worst-case frequency and RoCoF. The factors influencing the magnitude of the instability will be investigated and the probability of their occurrence quantified. The information will be used to estimate the risk of instability using the East Australian power system as a case study. Simulations will be carried out in Matlab.

1. Familiarization with existing frequency control models.
2. Literature review on current frequency control issues and inverter modeling.
3. Development of a control model with inverter-connected generation units.
4. Selection of the measures for quantifying the magnitude and consequences of the instability event.
5. Modification of the case study on East Australian power system to replace generators by inverter sources.
6. Simulations of various contingencies and diverse operating conditions which affect the magnitude of the instability, and quantification of the probability of the scenarios, i.e. contingency + operating conditions.
7. Quantification of the risk of instability using the East Australian power system as a case study.
8. Summary of findings in a report and a presentation

[1]. Bergen, A.R. and V. Vittal, Power systems analysis. 2000: Prentice Hall.

[2]. Frequency Stability Evaluation Criteria for the Synchronous Zone of Continental Europe - Requirements and impacting factors - RG-CE System Protection & Dynamics Sub Group March 2016.

[3]. B. Kroposki et al., "Achieving a 100% Renewable Grid: Operating Electric Power Systems with Extremely High Levels of Variable Renewable Energy," in IEEE Power and Energy Magazine, vol. 15, no. 2, pp. 61-73, March-April 2017.

[4]. Pieter Tielens and Dirk Van Hertem, The relevance of inertia in power systems, Renewable and Sustainable Energy Reviews, Volume 55, March 2016, Pages 999–1009.

[5]. W. Winter, K. Elkington, G. Bareux and J. Kostevc, "Pushing the Limits: Europe's New Grid: Innovative Tools to Combat Transmission Bottlenecks and Reduced Inertia," in IEEE Power and Energy Magazine, vol. 13, no. 1, pp. 60-74, Jan.-Feb. 2015.

[6]. Hatziargyriou, N. "Microgrids: Architectures and Control, Hoboken." (2014)

[7]. Zhong, Qing-Chang, and Tomas Hornik. Control of power inverters in renewable energy and smart grid integration. Vol. 97. John Wiley & Sons, 2012.