  Unprecedented dynamic phenomena may appear in power grids due to higher and
higher penetration of inverter-based resources (IBR), e.g., wind and solar
photovoltaic (PV). A major challenge in dynamic modeling and analysis is that
unlike synchronous generators, whose analytical models are well studied and
known to system planners, inverter models are proprietary information with
black box models provided to utilities. Thus, measurement based
characterization of IBR is a popular approach to find frequency-domain response
of an IBR. The resulting admittances are essentially small-signal
current/voltage relationship in frequency domain. Integrating admittances for
grid dynamic modeling and analysis requires a new framework, namely modular
small-signal analysis framework. In this visionary paper, we examine the
current state-of-the-art of dynamic modeling and analysis of power grids with
IBR, including inverter admittance characterization, the procedure of component
assembling and aggregation, and stability assessment. We push forward a
computing efficient modular modeling and analysis framework via four visions:
(i) efficient and accurate admittance model characterization via model building
and time-domain responses, (ii) accurate assembling of components, (iii)
efficient aggregation, and (iv) stability assessment relying on network
admittance matrices. Challenges of admittance-based modular analysis are
demonstrated using examples and techniques to tackle those challenges are
pointed out in this visionary paper.
