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The transmission and distribution sub-systems of the electric power grid have historically been modeled and simulated in isolation from each other. While this may be sufficient in some scenarios, the growing interdependence of the sub-systems—driven by the proliferation of distributed energy resources and increasing load growth—has created a need for coupling these models. Furthermore, the separation of the two simulations often results in oversimplified representations of distribution feeders within the transmission system, often as static PQ load models. Such simplifications and isolation of simulations may lead to reduced model fidelity and potentially inaccurate planning and stability assessments. One technique to improve modeling fidelity in this scenario is to use an aggregate load model, such as the WECC Composite Load Model (CLM). This aggregate load model divides the total distribution feeder load into six different models, representing four types of motors as well as electronic and static loads. This model has been demonstrated to more accurately model power system responses, especially for fault-induced delayed voltage recovery (FIDVR) events.
The goals of this research are threefold. First, to develop a co-simulation framework capable of simulating transmission and distribution systems while enabling information exchange between them. Second, to develop an algorithm for deriving CLM component mix and feeder equivalent parameters from an existing OpenDSS circuit model. Third, to develop an algorithm for distributing CLM loads throughout an OpenDSS circuit in order to synthetically generate the CLM response at the transmission bus level—without requiring the transmission simulator to implement the model directly.
The framework is validated using the IEEE 24 Bus transmission system with PandaPower as the transmission simulator and the IEEE 34 Node distribution feeder with OpenDSS as the distribution simulator. Results from quasi-static time series co-simulations demonstrate that co-simulation captures voltage and power flow responses not observable in isolated simulations, and that the synthetic distribution of CLM components yields behavior consistent with expected load diversity and protection responses. This research lays the foundation for a scalable, open-source T&D co-simulation tool and offers a pathway for utilities and researchers to improve load modeling fidelity without reliance on commercial software.
