Estimation Method for Power System Equivalent Inertia Based on Quasi-steady-state Data

The large-scale grid-connection of such renewable energy as wind power and photovoltaic (abbr. PV) power leads to the decreasing of power system inertial and the increasing of frequency instability risk, there is an urgent need for online assessment of equivalent inertia. However, most existing inertia estimation methods are based on the frequency change rate under large disturbance scenario so it is hard for them to meet the needs of equivalent inertia estimation under quasi-steady operating state scenario. For this reason, firstly, in allusion to the normal inertial estimation the mechanism of power system inertia response was analyzed, and the expression for the equivalent inertia under quasi-steady state operating condition was derived. Secondly, based on the theory of system identification a controlled autoregressive moving average with exogenous variable (abbr. ARMAX) model was constructed and by use of Akaike information criterion (abbr. AIC) the model order was determined, and by use of the method of least minimum square the equivalent inertia of system was estimated. Finally, the effectiveness of the proposed method was verified by WSCC 9-bus system. Verification results show that the proposed method possesses higher identification precision and can adapt to different load fluctuation forms.