This article introduces a data-driven approach to assessing failure mechanisms and reliability degradation in outdoor photovoltaic (PV) string inverters. The manufacturer's stated PV inverter lifetime can vary due to the impact of operating site conditions. To address limitations in degradation estimation through accelerated testing, condition monitoring, or degradation modeling, we propose a machine learning (ML) oriented approach. Utilizing data from a 1.4 MW PV power plant operational since 2016, with 46 string PV inverters tied to the grid, we employ the unsupervised one-class support vector machine ML technique to analyze inverter and sensor data, capable of classifying humidity cycling and temperature fluctuations as dominant failure mechanisms. Utilizing the anomaly alert relationship and alert details specific to the inverter, the level of PV inverter output is considered as its availability or available reliability. Subsequently, a continuous Markov model is applied to six-month alert data, revealing an average stated reliability of 20% after 20 years of continuous operation. These results support recommendations for time-bound preventive measures to enhance PV inverter reliability under diverse outdoor conditions. The approach provides a nondestructive, top–down, and generalized method for analyzing any commercial PV inverter exposed to outdoor conditions, contingent on the availability of relevant data.

The performance of PID controllers depends on the appropriate choice of its control-parameters. These parameters are chosen in order to achieve a reduced transient effects such as overshoot/undershoot, settling time and steady-state errors. This paper presents a particle swarm optimization (PSO) based PID controller design for the optimal selection of the buck converter-control PID parameters: proportional (Kp), integral (Ki) and derivative (K d). In order to address the wind-up issue with PI controllers, this paper proposes the use of an anti-windup control technique with a view to achieving very good voltage regulation in the output despite of a wide range of input voltage and load variation. The performance of the proposed controller design is verified using MATLAB/Simulink. The results demonstrates the ability of the optimization algorithm in reducing the aforementioned transient and steady state errors, thereby, reducing the output voltage fluctuations despite of input and load side fluctuations.

The rapidly increasing distributed energy resources (DERs) in power systems are now getting interconnected to set community grid structures, where power quality will be a major concern. The grid-to-grid (G2G) bidirectional power transfer among the distribution microgrid will not be considered commercially feasible unless the upstream harmonics are under the limits. The aggregation of such harmonics, measured as total harmonic distortion (THD), is feared to be beyond tolerable limits with the progression of rooftop grid-tied PV-like installations. Hence, this THD needs to be characterized with DER generation end variables. In this work, the photovoltaic (PV) DERs’ dependency on environment variables such as irradiance was profiled in the context of generating and injecting harmonics into the grid. A mathematical model of a grid-tied three-phase PV DER was developed as part of this correlation characterization, matching the fundamental unit structure of a 1.4 MW solar canopy located on the Florida International University (FIU) Miami campus. To determine the qualitative association with produced THD patterns, the model was evaluated with various irradiance settings. A real-time digital simulation (RTDS) platform was used to verify it. Following this confirmation, sets of data from power quality meters at the point of common coupling and FIU field sensors were utilized to validate further the correlation model. The results showed that the grid current’s THD exhibited a high correlation with the irradiance profile and its variation over time. The early morning and late afternoon periods of the day, associated with a low irradiance, constantly had higher harmonics generated from the PV DER. The midday THD was rather rational with partial shadings, hence a geolocation-dependent factor. These findings were verified by an RTDS and validated by real field data. In quantifying the THD injected by a single DER at a high-frequency (2–150 kHz) supraharmonics (SH) level, a 3% peak increment in magnitude was observed from the high-fixed to the low-fixed irradiance profile. The correlation characteristics depicted that the hybrid microgrid suffered from a daytime-dependent harmonic insertion from the grid-tied DER. This is a global problem unless specific measures are taken to mitigate the harmonics. The electrically notorious higher-frequency SH was found to increase proportionally. The G2G power transfer can be limited because of the higher THD in the early morning and late afternoon, which will also worsen because the numbers of grid-tied PV DERs (i.e., rooftop solar and industrial solar) are likely to increase rapidly soon. The community grid structure can thus have a controlled harmonics filtration setup purposefully designed to address the findings of this work, which also fall within the scope of our future research.

In commercial applications, the operation of DC/DC converters significantly impacts overall system performance and long-term reliability. This study introduces a data-driven digital twin ( DT ) approach for estimating critical degradation parameters of DC/DC BUCK converter under steady-state condition. Initially, a circuit-level MATLAB/Simulink digital model ( DM_C ) is refined against a hardware prototype’s switching model dataset using offline particle swarm optimization. The optimized digital model’s steady-state response is then verified with its average model response while varying the duty and load. Subsequently, degradation profiles are imposed on the inductor, capacitor, MOSFET in the DM_C . A large dataset is generated from this model, allowing training, validation, and testing of machine learning (ML) models for component health regression tasks. The proposed method employs random forest ML models, achieving impressive regression results with a squared R value as high as 0.99978 and a root mean square error of 4.2× 10 ⁻⁶ . The method is further validated on a medium power level DC/DC BUCK prototype with varying load conditions, and includes the analysis of MOSFET’s on-resistance under degradation conditions. This data-driven DT method shows promise for identifying parasitic degradation and ohmic loss parameters, enhancing converter reliability assessments in a non-invasive, generalized, and computationally efficient manner.

The modern smart grid is a development of traditional power grids that incorporates information and communication technology to deliver electricity from suppliers to consumers to improve reliability, efficiency, infrastructure, power system availability, sophisticated metering technology, and energy management approaches. Because smart grids connect millions of devices - wired and wireless, data transmission becomes increasingly complicated and exposed to hackers. In this paper, we reviewed the MITRE ATT&CK architecture, highlighted smart grid vulnerabilities, described the SCADA system, and looked at the primary attacks that may compromise the smart grid system. The security mechanisms that can be employed in smart grids to prevent attackers from gaining access to the system and to secure communications from eavesdropping and other forms of information theft are also discussed. Lastly, cryptographic method is discussed on the issue of securing data communication in smart grids.

Micro-electro mechanical system (MEMS) based oscillators are revolutionizing the timing industry as a cost effective solution, enhanced with more features, superior performance and better reliability. The design of a sustaining amplifier was triggered primarily to replenish MEMS resonator’s high motion losses due to the possibility of their ‘system-on-chip’ integrated circuit solution. The design of a sustaining amplifier observing high gain and adequate phase shift for an electrostatic clamp-clamp (C-C) beam MEMS resonator, involves the use of an 180nm CMOS process with an unloaded Q of 1000 in realizing a fixed frequency oscillator. A net 122dBΩ transimpedance gain with adequate phase shift has ensured 17.22MHz resonant frequency oscillation with a layout area consumption of 0.121 mm² in the integrated chip solution, the sustaining amplifier draws 6.3mW with a respective phase noise of -84dBc/Hz at 1kHz offset is achieved within a noise floor of -103dB_C/Hz. In this work, a comparison is drawn among similar design studies on the basis of a defined figure of merit (FOM). A low phase noise of 1kHz, high figure of merit and the smaller size of the chip has accredited to the design’s applicability towards in the implementation of a clock generative integrated circuit. In addition to that, this complete silicon based MEMS oscillator in a monolithic solution has offered a cost effective solution for industrial or biomedical electronic applications.