Distributed resource integration analysis and network design of electric power distribution systems

The integration of high percentages of distributed energy resources and controllable loads into the distribution system coupled with the strict power quality and service reliability requirements at the power distribution level are necessitating a significant change in the planning, operation and control of the traditional power distribution system. The future power distribution circuits should be able to accommodate the new technologies while simultaneously providing a desired level of power quality and service reliability to the customers. This thesis aims to address the current and future grid requirements of both existing as well as new distribution systems with regard to power quality and service reliability issues. Several methods are proposed to evaluate and mitigate power quality and service reliability concerns due to the integration of smart grid technologies into both existing and new distribution circuits. Notably, for the existing distribution circuits, integration studies are simulated to analyze and mitigate the impacts of electric vehicle loads and photovoltaic generation on the distribution voltages. Furthermore, the problem of siting, sizing and deployment of distributed energy storage systems in meeting distribution planning requirements with regard to integrating distributed generation and providing contingency requirements is also addressed. A new distribution system both grid-connected and operating in islanded mode, however, could be designed to the new requirements. The new distribution circuit could be designed to meet the power quality and service reliability standards directly, thus more efficiently mitigating the concerns. In the thesis, the new distribution circuit design is approached from the perspective of maximizing the service reliability. For the new distribution circuit, approaches to reliability based distribution circuit design are proposed.Electrical and Computer Engineerin

Distributed Computing for Scalable Optimal Power Flow in Large Radial Electric Power Distribution Systems with Distributed Energy Resources

Solving the non-convex optimal power flow (OPF) problem for large-scale power distribution systems is computationally expensive. An alternative is to solve the relaxed convex problem or linear approximated problem, but these methods lead to sub-optimal or power flow infeasible solutions. In this paper, we propose a fast method to solve the OPF problem using distributed computing algorithms combined with a decomposition technique. The full network-level OPF problem is decomposed into multiple smaller sub-problems defined for each decomposed area or node that can be easily solved using off-the-shelf nonlinear programming (NLP) solvers. Distributed computing approach is proposed via which sub-problems achieve consensus and converge to network-level optimal solutions. The novelty lies in leveraging the nature of power flow equations in radial network topologies to design effective decomposition techniques that reduce the number of iterations required to achieve consensus by an order of magnitude

Sensitivity Analyses of Resilience-oriented Risk-averse Active Distribution Systems Planning

This paper presents sensitivity analyses of resilience-based active distribution system planning solutions with respect to different parameters. The distribution system planning problem is formulated as a two-stage risk-averse stochastic optimization model with conditional value-at-risk (CVaR) as the risk measure. The probabilistic scenarios are obtained using regional wind profiles, and Monte Carlo simulations are conducted to obtain failure scenarios based on component fragility models. The planning measure includes advanced distribution grid operations with intentional islanding measures. The three main parameters used in this work for sensitivity analysis are the number of scenarios, risk preference, and planning budget allocation. Such analysis can provide additional information to system operators on dispatching the planning budget and available resources properly to enhance the grid's resilience.Comment: 5 pages, 12 figures, submitted to 2023 IEEE Power and Energy Society General Meeting for revie