System dynamic models for hundreds of inverter-based generators are necessary to represent the whole behavior and to perform stability analysis at the transmission and distribution level in the electric power system. Some aggregated models, like DER_A and PVD1, have been suggested in the literature. However, these models include a considerable number of parameters, and so far, there is a lack of a formalized online method for parameterizing them. Several parameterization strategies for this particular model require the use of smooth functions. The parameters of these aggregated models may experience fluctuations and changes in the foreseeable future as the power system becomes more reliant on inverter-based generation. Consequently, an online parameter estimation will be necessary. This research proposes a way for parameter identification via online moving horizon estimation (MHE) for the grid voltage support function of the DER_A model by using a smooth mathematical representation. MATLAB/Simulink simulation shows that the proposed approach using MHE with a smooth representation of the DER_A model closely estimates the grid voltage support function parameters in the presence or absence of measurement noise. This study establishes the groundwork for the potential use in a detailed system including several inverter-based generators, with a primary focus on grid voltage support.

Diesel hybrid power systems including inverter-based generation have faster and more stochastic dynamics than traditional systems. It is necessary to develop accurate models of the system components to ensure the stability of these systems and proper controller design. The parameters of the diesel generators in hybrid power systems, such as the inertia constant, are time-varying, requiring online parameter estimation techniques. This paper presents a simplified linear model developed to represent the frequency dynamics of the detailed diesel generator system and validated the model using a moving horizon estimation (MHE) approach. The proposed optimization-based MHE algorithm is employed to accurately provide an estimation of multiple parameters of a simplified diesel generator model. The proposed method extracts the parameters minimizing a cost function with a given set of constraints on the parameters. A non-intrusive square wave excitation signal generated by step changes in load is used to perturb the system with minimal impacts on power system operation. MHE estimates the parameters based on the power and frequency from the diesel generator system measured using the phase-locked loop (PLL) and provides reasonable estimates of unknown parameters. The estimated parameters are further verified by using them back in the simplified model and comparing them with the PLL measurements to represent the frequency dynamics of the diesel genset system.

Diesel generators are an integral component of remote islanded microgrids in rural Alaska. As inverter-based generation is integrated in these microgrids, adequate transient modeling will be necessary as dynamic and transient stability issues can arise with significant contributions of inverter-based generation. A complete transient model of a diesel generator includes models of the machine, exciter, governor, and any relays or other limiting components. Few studies compare the adequacy of various types of diesel generator governor or exciter models or include a volts/hertz (V/Hz) limiting functionality commonly found in diesel generators deployed in such remote islanded microgrids. This paper introduces and compares diesel generator models in response to two load steps against responses from the ACEP PSI lab 400 kVA diesel generator which represents a realistic diesel generator found in remote islanded Alaskan microgrids. A simplified governor model is introduced and compared to the traditional DEGOV governor model, and the functionality of a V/Hz limiter added to a DC4B exciter is demonstrated.

With the advancement in power electronics technology and grid standards, traditional converters are being supplemented with the new IEEE 1547-2018 standard based grid support functions (GSFs) to support power system voltage and frequency. Inverter dynamics in power systems vary with different modes of operation, thus new modeling methods for proper system planning, operation, and dispatch are required. This work presents a data-driven approach for partitioned dynamic modeling of inverters to speed up simulation time and reduce computational complexity while ensuring acceptable accuracy. The proposed method was tested for a smart inverter with voltage support (Volt-VAr function) on a two-bus system considering dynamic residential loads, and the results showed a four-time speedup in simulation time compared to the use of the detailed model with acceptable levels of accuracy.

Virtual synchronous machine (VSM) can be used in micro-grids (MGs) for supporting virtual inertia to mitigate frequency fluctuations in the system. The performance of VSM depends on the performance of the current controlled voltage source inverter. Generally used proportional-integral (PI) controller has limited transient performance in current control. Adaptive dynamic programming (ADP) controller has been investigated, designed and tested to improve transient stability in the electric power system. In this paper, ADP controller has been proposed as a supplementary controller for fine tuning conventional PI current controller thereby improving the performance of VSM. The grid connected inverter system was simulated in MATLAB/Simulink to analyze transient stability problems. ADP as a supplementary controller not only reduced the overshoot of d-axis current at sudden load changes but also increased the speed of the current control. Furthermore, the system was tested for single phase line to ground fault and performed well based on the proposed ADP supplementary control approach.

This paper presents the development of a flexible public lighting system which aims to monitor and control electronic ballasts. The system consists of dimmable electronic ballast for high pressure sodium lamps (HPS) with power meter, and a control board with 2.4 GHz digital radios based on the IEEE 802.15.4 (ZigBee) protocol, and data transmission module using SMS. The system has bidirectional communication between the central control and the master units using SMS messaging. Further, the master units send and receive information to and from the slave units via ZigBee modules and coordinates with the central controller the operation of each lamp in their region. This system can measure and report power and energy consumption to a central controller, and to dim, turn on and turn off the lamps individually, controlling the power consumption of the illumination system.