Distribution system segmented model simplification with independent dynamically changing end-use loads

With more emerging technologies in power distribution systems, accurately modeling the dynamic behavior of end-use load under various conditions has become important. One approach has been quasi-static time-series (QSTS) power flow simulation over short time frames. However, time and cost can be a burden for the QSTS simulation of thousands of houses with dynamic loads on large distribution feeders. This may limit sensitivity analysis, design optimization or exploration of alternatives on the distribution system. There are two main contributions of this paper in order to reduce the QSTS simulation complexity. First, the paper presents a method to stochastically model the dynamic behavior of end-use load for QSTS simulations. Second, using the stochastically modeled load behavior as part of a distribution system, and building on our previous QSTS simulation simplification/acceleration method for uniform load behavior, this paper presents a segment substitution approach for the simplification of distribution system models with multiple independent dynamically changing end-use loads. Our numerical results show that compared to GridLAB-D, a software tool that simulates end-use load behavior through physical models, the proposed stochastic modeling approach achieved an 89.3% simulation time reduction for end-use loads, while accurately capturing the temporally changing total load behavior. Moreover, the QSTS simulation of a large test distribution system through OpenDSS showed that the proposed simplification method decreased the feeder simulation time by a factor of three at less than 0.3% voltage error. Compared to our previous method, the voltage error with independent dynamic loads is reduced by a factor of four. This makes it usable for transactive system studies, including battery integration, compared to earlier methods that were tested on photovoltaic data.