Grid integration of solar photovoltaic (PV) systems has been escalating in recent years, with two main motivations: reducing greenhouse gas (GHG) emission and minimizing energy cost. However, the intermittent nature of solar PV generated power can significantly affect the grid voltage stability. Therefore, intermittent solar PV power generation and uncertainties associated with load demand are required to be accounted for to gain a holistic understanding on power grid voltage stability with the high penetration of PV energy sources. This article presents a framework for power grid voltage stability analysis considering uncertainties associated with PV power generation and load demand using Monte Carlo simulation. Commonly used voltage stability indicators such as critical eigenvalue, line loss, reactive power margin have been considered in the proposed framework. The proposed methodology has been verified by analyzing the voltage stability of the IEEE 14 bus test system, with the high penetration of PV energy sources and considering uncertainties associated with load demand. The results provide a clear insight into the voltage stability of power grid with different penetration levels of PV energy sources into the power grid.

This paper presents a robust nonlinear decentralized control scheme for islanded DC microgrids where the main control objectives are to maintain the desired voltage at the common DC-bus and the power balance. The proposed control scheme uses the partial feedback linearization scheme to simplify the dynamical models of different components in DC microgrids. In this paper, the DC microgrid includes a solar photovoltaic (PV) unit, fuel cell system, and battery energy storage system (BESS) along with DC loads. The robustness of the proposed controller against parametric uncertainties is ensured by the parameter, appearing in the control inputs as unknown which is then estimated through adaptation laws. The inherent noise decoupling capability of the feedback linearization scheme is used to provide robustness against external disturbances in DC microgrids. The performance of the proposed controller is evaluated on a DC microgrid through simulation and experimental studies in order to demonstrate the effectiveness and robustness under different operating conditions while considering the effects of parametric uncertainties and external disturbances. Simulation results are also compared with an existing proportional-integral (PI) controller.

In the design procedure of a PV‐based microgrid, optimal sizing of its components plays a significant role, as it ensures optimum utilization of the available solar energy and associated storage devices. This in turn ensures efficient and economic operation of the microgrid. Various approaches have been reported in the literature in order to approach the sizing problem in PV‐based microgrids. However, the existing approaches are subjective to the requirements of the microgrid and there is no unique framework for approaching the microgrid sizing problem. In this study, a comprehensive review of the existing approaches used for sizing of PV‐based microgrids with a summary of the commonly adopted design considerations has been presented. Also, the optimization problem, including the usually considered designed objectives and constraints, for PV‐based microgrid sizing have been thoroughly reviewed in this study. Furthermore, the adopted approaches for solving the optimization problem associated with the sizing of a PV‐based microgrid system available in the literature have been reviewed comprehensively. With a view to present a generic framework for the optimal sizing of a PV‐based microgrid, this study further presents a framework based on the comprehensive review of the existing literature. The developed framework will be useful for both the practising engineers and academics to understand and apply the usual practices for optimal sizing of PV‐based microgrids.

An accurate battery model is essential for precise estimation of battery performance indicators such as state of charge (SoC), state of health (SoH), etc. It helps in determining the optimum energy management and, therefore, optimum utilization of the battery capacity. Some of the battery model parameters may change with the variation of environmental conditions such as operating temperature, and, therefore, accurate temperature compensated model estimation is necessary to minimize the error in battery model and SoC estimation. This paper presents a novel parameters extraction method for the Thevenin equivalent circuit model (ECM) of Li-ion batteries considering their resiliency on temperature effect. The proposed approach represents each of the RC parallel circuits of the Thevenin based equivalent circuit battery model (ECBM) as a first-order linear time-invariant (LTI) system. The resistance and capacitance values for each of the RC circuits in the model have been identified as the parameters of a standard LTI system using the system identification theory and represented them as the temperature compensated model parameters. The proposed model can be applied to various applications such as SoC, SoH estimation, and battery energy management. In order to demonstrate the suitability of the proposed modeling approach, the model is augmented with the conventional extended Kalman filter (EKF) to enable accurate SoC estimation under varying operating temperatures. The accuracy and effectiveness of the proposed modeling approach and its suitability to enhance SoC estimation under a wide operating temperature range (-5C to 45C) have been validated through laboratory experiments in the LabVIEW platform.

This paper presents a new framework, utilizing information-gap decision theory (IGDT), for multiobjective robust security-constrained unit commitment of generating units in the presence of wind farms and gridable vehicles. Both the wind power and load demand uncertainties are considered, and modeled using a biobjective model. As the main advantage, the framework enables the system operator to take an appropriate operational decision with respect to the extremity of each uncertainty. The proposed problem is solved using a normal boundary intersection technique. Subsequently, VIsekriterijumska optimizacija i KOmpromisno Resenje (VIKOR), a decision-making tool, is utilized to choose the best Pareto optimal solution. Finally, the IGDT-based framework presented in this paper is validated using a six-bus test system, the IEEE Reliability Test System with 24 buses, and the IEEE 118-bus system.

This paper presents an adaptive rate of change of frequency (ROCOF) based passive Islanding detection technique (IDT) to overcome the non-detection zone (NDZ) issue and limitation of existing islanding detection techniques. The proposed ROCOF based passive IDT relies on the settings of the phase locked loop (PLL) closed loop control system for frequency, ROCOF and threshold ROCOF value for the PCC relay setting calculations. So, the PLL results in alternate frequency and ROCOF output value with respect to the PLL settings modification. The PLL settings can be different in different types of microgrid systems. Therefore, the proposed adaptive ROCOF based IDT provides a generic solution for islanding detection applications for the safe and reliable operation of different types of microgrid systems. The adaptive ROCOF based IDT is developed and implemented on two different types of the microgrid systems such as (I) generator based microgrid (ii) generator, PV and storage based hybrid microgrid in Matlab/Simpower System. Results showed that the proposed IDT successfully detected the islanding condition even with zero power mismatch and it is fully capable to distinguish between islanding (loss of mains and external fault) and non-islanding (internal fault, load switching, motor starting etc.) conditions with a diverse range of operating conditions.