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As conventional direct connections of synchronous generators are being phased out, inverter-based resources (IBRs) with grid support functions are increasingly being integrated into power systems. This transition requires the development of accurate dynamic models for IBRs to predict how power systems will adapt to varying levels of IBRs penetration, establish grid code requirements, and ensure compliance. This study introduces an active probing signal-based data-driven modeling technique to accurately derive the dynamics model of a smart photovoltaic inverter operating in Volt-Watt and Freq-Watt modes, in compliance with the IEEE 1547–2018 standard. The paper focuses on investigating how the dynamics of the PV inverter model respond to fluctuations in solar irradiance, utilizing real-time digital simulator experimentation. The experimental analysis demonstrates that the amplitude of dynamics fluctuates with changes in irradiance across both operational modes and confirms the active power’s dependence on irradiance levels. Furthermore, the nature of inverter dynamics varies distinctly between the different modes of activation. Critically, our findings indicate that dynamic models require DC-gain adjustments to accommodate contrasting irradiance levels, highlighting a negative gradient linear relationship between the DC-gain of each model and the irradiance.

Energy storage systems (ESSs) are a flexible resource that will be vital to meet the aggressive clean energy targets of the future. However, the economic gains from ESSs can be limited due to large capital investments and monetization challenges. It is thus desirable to utilize ESSs for multiple techno-economic benefits to justify deployment costs. In this work, a framework to simultaneously dispatch ESSs for energy arbitrage and power quality applications is presented. More specifically, a model predictive control (MPC)-based framework that can dispatch energy storage to accomplish multiple techno-economic objectives is proposed. This is achieved without impacting market revenues while satisfying all power system and ESS constraints. Simulation results indicate that power quality applications such as voltage regulation and power factor correction can be stacked with arbitrage without significantly impacting arbitrage revenues and in some cases even improving the revenues. A controller-hardware-in-the-loop (CHIL) study of the proposed framework is also performed to demonstrate the practical feasibility of the framework.

Diesel generators (gensets) are often the lowest-cost electric generation for reliable supply in remote microgrids. The development of converter-dominated diesel-backed microgrids requires accurate dynamic modeling to ensure power quality and system stability. Dynamic response derived using original genset system models often does not match those observed in field experiments. This paper presents the experimental system identification of a frequency dynamics model for a 400 kVA diesel genset. The genset is perturbed via active power load changes and a linearized dynamics model is fit based on power and frequency measurements using moving horizon estimation (MHE). The method is first simulated using a detailed genset model developed in MATLAB/Simulink. The simulation model is then validated against the frequency response obtained from a real 400 kVA genset system at the Power System Integration (PSI) Lab at the University of Alaska Fairbanks (UAF). The simulation and experimental results had model errors of 3.17% and 11.65%, respectively. The resulting genset model can then be used in microgrid frequency dynamic studies, such as for the integration of renewable energy sources.

This work introduces a new broadband Class B/J power amplifier (PA) design methodology by considering the input-output waveform shaping due to nonlinear CGS-VGS profile in gallium nitride (GaN) radio frequency (RF) devices. A comprehensive time domain modeling of drain voltage and drain current as a function of input nonlinearity is presented to predict continuous Class B/J PA performance. The proposed theory shows that continuous-mode operation can no longer maintain constant PA performance with varying fundamental and second harmonic impedances as predicted by the ideal class-J theory. This paper demonstrates that continuous-mode class B/J operation with input-output waveform shaping yields a new design space with two distinct regions: one advantageous region with capacitive second harmonic load terminations in which PA performance can be enhanced significantly; and another within an inductive second harmonic load area where the performance is degraded compared to that of a classical class B/J PA. For practical validation, source pull measurements and load pull analyses are presented and a broadband Class B/J PA is designed with the proposed second harmonic load and source termination. Source/Load-pull measurements/simulations confirm the theoretical predictions in terms of performance variation across the design space. A high efficiency design space is then identified for broadband PA design. The PA protype demonstrates drain efficiency of (60-73) % with output power above 40 dBm and corrected adjacent channel power ratio (ACPR) better than −55 dBc with digital predistortion (DPD) using 10 MHz LTE signal across (2.2-3.4) GHz.

The displacement of rotational generation and the consequent reduction in system inertia is expected to have major stability and reliability impacts on modern power systems. Fast-frequency support strategies using energy storage systems (ESSs) can be deployed to maintain the inertial response of the system, but information regarding the inertial response of the system is critical for the effective implementation of such control strategies. In this paper, a moving horizon estimation (MHE)-based approach for online estimation of inertia constant of low inertia microgrids is presented. Based on the frequency measurements obtained in response to a non-intrusive excitation signal from an ESS, the inertia constant was estimated using local measurements from the ESS’s phase-locked loop. The proposed MHE formulation was first tested in a linearized power system model, followed by tests in a modified microgrid benchmark from Cordova, Alaska. Even under moderate measurement noise, the technique was able to estimate the inertia constant of the system well within ±20% of the true value. Estimates provided by the proposed method could be utilized for applications such as fast-frequency support, adaptive protection schemes, and planning and procurement of spinning reserves.

Modern data centers consume large amounts of electricity, resulting in high operational costs. The efficiency of a data center power distribution system can be increased and the operational cost reduced if the number of power conversion stages can be minimized and more efficient converters, such as wide bandgap converters, are used. This can be achieved by using dc distribution voltage at the rack level by eliminating extra conversion stages. In this paper, benchmarks for both ac and 380-V dc data centers were developed and efficiency analyses were performed for an entire year. The impact of integrating photovoltaic (PV) systems into the data centers has also been analyzed in both cases in terms of efficiency. The results show that 380-V dc data centers are more efficient than ac data centers with and without PV integration. Furthermore, the reliability of an ac system was compared with a 380-V dc architecture with Tier-IV standard. Monte-Carlo simulations were used to perform reliability analyses for different levels of redundancy in the uninterruptible power supply system for both cases. The simulation results showed that the 380-V dc distribution system had a higher level of reliability than the ac distribution system in data centers.