Search for: All records

This article studies the optimal design approach for a portable nuclear magnetic resonance (NMR) system for use in non-destructive flow measurement applications. The mechanical and electromagnetic design procedures were carried out using the Ansys Maxwell finite-element analysis (FEA) software tool. The proposed procedure considered homogeneity and strength constraints while ensuring the desired functionality of the intended device for a given application. A modified particle swarm optimization (MPSO) algorithm was proposed as a reference design framework for optimization stages. The optimally designed NMR tool was prototyped, and its functionality was validated via several case studies. To assess the functionality of the prototyped device, Larmor frequency for hydrogen atom was captured and compared with theoretical results. Furthermore, the functionality and accuracy of the prototyped NMR tool is compared to the off-the-shelf NMR tool. Results demonstrated the feasibility and accuracy of the prototyped NMR tool constrained by factors, such as being lightweight and compact. 

This paper proposes a control scheme that prevents the adverse dynamic interactions between the heterogeneously controlled grid-forming inverters (GFMI) in power electronics dominated grid (PEDG) towards a resilient self-driving grid. The primary controller of GFMIs in a grid cluster can vary based on their manufacturers such as virtual synchronous generation, droop control, power synchronization control, etc. Therefore, this can introduce heterogeneity among the network of GFMIs in PEDG. Resultantly, during the interconnection of GFMIs that are based on heterogenous primary controller poses various synchronization and dynamic interaction challenges in PEDG. For instance, severe fluctuations in frequency and voltage, high ROCOF, unintended reactive power circulation that poses a threat on the overall transient stability of the PEDG. Therefore, to mitigate these adverse dynamic interactions among the heterogeneously controlled GFMIs, a force enclaved homogenization (FEH) control is proposed in a supervisory level controller. This will autonomously adjust inertia coefficients of the each GFMI to have homogenous transient response and will enforce coherency among the heterogenous DGs. This will prevent the PEDG from the adverse dynamic interactions during an interconnection and load disturbance. Various case studies are presented that validates the effectiveness of the proposed FEH control. 

This paper proposes a control scheme to force homogeneity for heterogenous network of the grid-forming (GFM) inverters in power electronics dominated grid (PEDG) to enable their aggregation and coherent dynamic interaction. Increased penetration of the renewable energy in distributed generation (DG) fashion is moving traditional power system to a highly disperse and complex heterogenous system i.e., PEDG with fleet of grid-forming and grid-following inverters. Optimal coordination, stability assessment, and situational awareness of PEDG is challenging due to numerous heterogenous inverters operating at the grid-edge that is outside the traditional utility centric power generation boundaries. Aggregation of these inverters will not be insightful due to their heterogenous characteristics. The proposed control scheme to force enclaved homogeneity (FEH) enables an insightful aggregation of GFM that can fully mimic the given physical system dynamics. The proposed FEH scheme enables coherent and homogenized dynamic interaction of GFM inverters that enhances the PEDG resiliency. Moreover, different cluster of GFM can be merged into single cluster with minimal synchronization time and frequency fluctuations. Accurate reference models can be achieved that enables effective dynamic assessment and optimal coordination which results in resilient PEDG. Several case studies provided to validate the effectiveness of proposed FEH in network of GFM. Then, GFMs aggregation and developed reference model for the PEDG system is validated via multiple comparative case studies.