Application of higher order dynamic mode decomposition to modal analysisand prediction of power systems with renewable sources of energy

Concern for climate change is driving a vastly increased use of electricity and variable renewable energysupply encourages larger and evermore interconnected power systems. Stability analysis and short-termprediction of power system output has never been more urgent or more complex. Many distributed andrenewable generators contribute zero inertia to the system and increase the risk of poorly damped oscillationsleading to cascading outage. Data-driven techniques, higher order dynamic mode decomposition (HODMD)and total-least-squares higher-order dynamic mode decomposition (THDMD) are applied to modal analysisand short-term prediction of frequency and power exchange deviations. The decomposition uses multiple andrandomized sampling windows of historical measurements. Dominant THDMD and HODMD modes can beused to show the contribution of renewable generation, such as wind power, to wide-area oscillations. Thedeveloped techniques are applied to the analysis of blackouts in Europe (2006) and the UK (2019), as well asthe separation event in Australia (2018). The obtained results demonstrate that the damping of some HODMDmodes can be overestimated. Although selected HODMD modes can reconstruct and predict power systemoutput, the results are not always reliable. In turn, THDMD can predict dominant oscillations, with reductionof noise bias error in modal analysis of noisy measurements. With low noise data both techniques can producevery similar modal results.

Automated summary

Concern for climate change is driving an increased use of electricity and renewable energy supply, leading to larger and interconnected power systems. The need for stability analysis and short-term prediction of power system output is urgent and complex. Data-driven techniques such as HODMD and THDMD are applied to modal analysis and prediction of frequency and power exchange deviations. These techniques are used to analyze blackouts in Europe and the UK, as well as a separation event in Australia, demonstrating their usefulness in understanding and addressing power system issues.