There are important challenges in modeling large electrical distribution circuits, especially with the presence of distributed renewable generation. Constructing simulations to assess the effect of the penetration of distributed generation on electrical distribution networks has become of great importance for Distribution Network Operators (DNOs). This paper proposes a simulation strategy based on open-source platforms and the integration of scripting tools for the rapid modeling of large-scale electrical distribution circuits with distributed renewable generation. The implementation is based on the adaptation of a tool called QGIS2OpenDSS, which creates OpenDSS distribution network models directly from an open-source geographic information system, QGIS. The plugin’s capabilities are demonstrated using a real distribution feeder with more than 60% penetration of renewable generation based on photovoltaic systems. These simulations are carried out using real data from a circuit provided by a DNO in the Dominican Republic, which is used to demonstrate how this approach provides a more accessible and flexible way to simulate and assess the effect of Distributed Energy Resources (DERs) in medium voltage (MV) and low voltage (LV) networks, enabling utilities to evaluate system performance and identify potential issues. The integration of this open-source tool within the DNO software stack enables users to apply it according to specific project needs, enhancing their capability to analyze and manage high DER penetration levels, aiding in better planning, operation, and decision-making processes related to renewable energy projects.

This paper describes research on the harmonic-distortion capacity of a single-stage photovoltaic (PV) 3.68 kWp generator in a microgrid configuration. An overview of various harmonic compensator methods used in PV generators is presented to evaluate their advantages and disadvantages. Proportional-resonant (PR) structures with harmonic compensators (HCs) are designed, modeled, and validated through real-time tests. The modeling of harmonic compensation structures for a photovoltaic inverter using MATLAB/SIMULINK R2022a is explained in detail. The harmonic compensation capacity of a PV generator inverter is studied under voltage harmonics, grid frequency variation, and voltage unbalance. The contributions of this work are, firstly a bibliographic analysis of various strategies currently used for harmonic compensation in grid-connected inverters and secondly, a detailed explanation of the modeling of harmonic compensation structures using MATLAB/SIMULINK. Finally, a demonstration of the improvement in energy quality that results from using harmonic compensation techniques in photovoltaic generators in microgrid configurations affected by grid disturbances is performed. The obtained results show that harmonic compensation strategies based on resonant filters are a good alternative for the reduction of harmonic voltage distortion in the presence of grid disturbances such as frequency variation and voltage unbalance.

There are important challenges for modeling large electrical distribution circuits, even more with the presence of distributed renewable generation. Constructing simulations for assessing the effect of the penetration of distributed generation on electrical distribution networks has become of great importance for Distribution Network Operators (DNOs). This paper proposes a simulation strategy based on open-source platforms and the integration of scripting tools for the rapid modeling of large-scale electrical distribution circuits with distributed renewable generation. The implementation is based on the adaptation of a tool called QGIS2OpenDSS, which creates OpenDSS distribution network models directly from an open-source geographic information system, QGIS. The plugin’s capabilities are demonstrated using a real distribution feeder with more than 60% penetration of renewable generation based on photovoltaic systems. These simulations are carried out using real data from a circuit provided by a DNO in the Dominican Republic, which is used to demonstrate how this approach provides a more accessible and flexible way to simulate and assess the effect of Distributed Energy Resources (DERs) in Medium Voltage (MV) and Low Voltage (LV) networks, enabling utilities to evaluate system performance and identify potential issues.

The present paper studies the current harmonic attenuation for four synchronization strategies commonly used in inverters for photovoltaic power generation. In a model of a 6kWp photovoltaic generator, the four synchronization strategies are implemented in the inverter controller. Real-time simulations are performed, for this purpose, the models of the photovoltaic generator and the utility grid were embedded in an OPAL-RT OP5707XG simulator. The distortion of the grid current for each synchronization strategy is analyzed using its corresponding frequency spectrum and a comparison is made with the IEEE Std. 519-2022 standard. The purpose of this test is to observe the effect of the synchronization strategy on the harmonic attenuation of the grid currents. The results show that one of the synchronization strategies evaluated in this work may be sufficient for the system to comply with the harmonic standard for photovoltaic generators without the use of harmonic compensation structures or active harmonic filters. The evaluation of the harmonic distortion behavior of photovoltaic generators as a function of the synchronization strategy used in the inverter controller is the principal work contribution.

Conventional validation schemes may overestimate model robustness in agricultural deep learning when spatial domain shifts are not explicitly considered. This study evaluated convolutional neural networks for pasture biomass estimation using the CSIRO Image2Biomass dataset within a multi-seed Leave-One-State-Out (LOSO) framework. A total of 24 experiments combined four Australian geographical domains, two architectures (ResNet50 and EfficientNet-B0), and three random seeds (42, 123, and 2025). Performance was assessed using WRMSLE, MAE, RMSE, and R ² . Seed-to-seed training variability was summarized using standard deviations across three random seeds, while 95% bootstrap confidence intervals for test WRMSLE were estimated by resampling the held-out test samples within each seed-level LOSO run. A metadata-based Random Forest was included as a non-image baseline. ResNet50 achieved mean test WRMSLE values ranging from 0.869 to 1.460 across held-out domains, whereas EfficientNet-B0 ranged from 0.911 to 1.519. The Random Forest baseline outperformed both CNN architectures in New South Wales and Western Australia, suggesting that structured ecological metadata can remain highly competitive when image-based models are transferred to unseen regions. To examine the visual basis of prediction errors, a systematic Grad-CAM audit was conducted using 40 activation maps derived from the five lowest- and five highest-error samples in each domain. The resulting attention patterns suggested domain-dependent model behavior and provided qualitative evidence consistent with reliance on contextual visual cues; however, the quantitative vegetation-attention measure should be interpreted as a coarse diagnostic proxy rather than a ground-truth segmentation metric. Overall, the combination of multi-seed LOSO validation, seed-level variability analysis, baseline benchmarking, and systematic XAI auditing constitutes a pre-deployment diagnostic framework for identifying generalization risks in agricultural computer-vision systems operating under spatial uncertainty.

Nonlinear loads in modern buildings are often represented using balanced or frequency-domain approximations that do not fully capture phase asymmetry and time-domain distortion observed under field operating conditions. This study aims to develop and validate a measurement-driven phase-resolved modeling framework for unbalanced three-phase nonlinear loads and to evaluate its usefulness for harmonic-mitigation assessment using shunt active power filters (SAPFs). In situ voltage and current waveforms were acquired in a university building using a Class S power-quality analyzer and embedded in MATLAB/Simulink as time-domain signals to preserve harmonic content, waveform shape, and phase-dependent behavior. Model accuracy was assessed using RMSE and range-normalized RMSE, yielding a mean RN_RMSE of 1.36% across representative loads, with simulated THD_I deviations of approximately 1–3 percentage points relative to the measurements. The measured load signatures were then used to evaluate three SAPF configurations under representative load-specific operating conditions. The results show that mean THD_I was reduced from 39.25% before compensation to 2.28% after compensation, with all the post-filter phase values remaining below 5%, consistent with IEEE Std 519-2022. The findings show that phase-resolved measurement-based load models provide a practical basis for harmonic assessment and SAPF-oriented mitigation studies in low-voltage building distribution systems with heterogeneous and unbalanced nonlinear loads.