UC Irvine

Growing negative impacts from climate change have increased the popularity of microgrid systems. However, novel and developing microgrid scenarios have brought uncertainty to the reliable operation and resiliency of the grid systems. This dissertation is concerned with using renewable, clean energy sources to enhance microgrid reliability and resiliency in novel grid operational scenarios.The dissertation starts with the modeling of an AC Power Flow (ACPF) model for a disadvantaged community, the Oak View Community, located in Huntington Beach, CA, based on OpenDSS. The model’s computing ability is then enhanced with a MATLAB-OpenDSS interface before the model is tested with a cross-platform comparison to confirm accuracy. The community ACPF model is then integrated with renewable and clean energy systems through four distinct operational scenarios. The initial scenario involves EV adoption within the community by employing a stochastic approach to generate and assign discrete EV charging events using the Monte Carlo algorithm. Subsequently, this scenario is extended to encompass the broader region of Southern California. The second operational scenario focuses on islanding strategies during Public Safety Power Shutoff (PSPS) events. An optimal algorithm is developed utilizing multilevel graph partitioning techniques. Then, the dissertation explores the deployment of Distributed Energy Resources (DERs) with NEM 3.0 ratings for cost optimization. A Mixed Integer Linear Programming (MILP) algorithm is employed to determine the optimal sizing and dispatch of DERs while adhering to infrastructure degradation constraints. Ultimately, the dissertation introduces a novel microgrid design framework inspired by and abstracted from the author’s work on the project. Following the power quality and degradation evaluations of the scenarios under consideration, it is shown that the current electric infrastructure in Southern California, especially distribution and transmission transformers, lacks the capacity to support the increasing electric demand driven by the EV market. Addressing this issue necessitates significant investments in transformer upgrades and/or the implementation of additional load management measures. The simulation results also find that DER/ESS solution with transformer limit constraint emerges as approximately ten times larger on average in TDV cost compared to the highest average cost incurred by infrastructure upgrade solutions.