Power and Energy Commons^™

Consensus-Based Active And Reactive Power Control And Management Of Microgrids, Shruti Singh

Electronic Theses and Dissertations

Microgrids incorporating distributed generation and renewable energy sources offer potential solutions to the energy crisis while modernizing traditional grids. Despite cost-effectiveness in some technologies, financial support remains crucial for expensive ones like PV, fuel cells, and storage technologies. Microgrids bring economic benefits, efficiency, reduced emissions, and improved power quality. Their success hinges on cost reductions in renewables, storage, reliability, and energy management systems, enabling operation both with and without the utility grid.

Economic Dispatch optimizes system costs, considering all constraints. Various methods tackle this problem, including quadratic convex functions, Lagrangian relaxation, and quadratic programming. For microgrids with distributed generators, seamless …

Design Of Hybrid Inverters Using Wideband Gap Semiconductors For Microgrid Application, Luca Gacy

Electronic Theses and Dissertations

As the world becomes more reliant on renewable energy sources such as solar and wind power, the need for high efficiency high power inverters connected to homes is more relevant than ever. Connecting these renewable energy sources (RES) coupled with an energy storage system (ESS) to the grid through a hybrid inverter, with the highest efficiency and grid stability, is quickly becoming a necessity for the near future. This thesis explores the integration of wide band gap semiconductors for the power stage in these systems, along with the analysis of hybrid inverter topologies and structures. The goal of this thesis …

Deep Learning For Power Flow Estimation And High Impedance Fault Detection, Kun Yang

Electronic Theses and Dissertations

My thesis is divided into two parts.

The first part is: “Optimal Power Flow Estimation Using One-Dimensional Convolutional Neural Network [1]“. Optimal power flow (OPF) is an important research topic in power system operation and control decisions. Traditional OPF problems are solved through dynamic optimization with nonlinear programming techniques. For a large power system with large amounts of variables and constraints, the solving process would take a long time. This paper presents a new method to quickly estimate the OPF results using a one-dimensional convolutional neural network (1D-CNN). The OPF problem is treated as a high-dimensional mapping between the load …

Power System Dynamic Control And Performance Improvement Based On Reinforcement Learning, Wei Gao

Electronic Theses and Dissertations

This dissertation investigates the feasibility and effectiveness of using Reinforcement Learning (RL) techniques for power system dynamic control, particularly voltage and frequency control. The conventional control strategies used in power systems are complex and time-consuming due to the complicated high-order nonlinearities of the system. RL, which is a type of neural network-based technique, has shown promise in solving these complex problems by fitting any nonlinear system with the proper network structure.

The proposed RL algorithm, called Guided Surrogate Gradient-based Evolution Strategy (GSES) determines the weights of the policy (which generates the action for our control reference signal) without back-propagation process …