Today the SVC (Static Var Compensator) helps to control by thyristors at the harmonics that are in the load, causing voltage fluctuations. For that the objective of this study is to determine the energy quality parameters in the TG-8 unit of the Santa Rosa Thermal Power Plant operating with Natural Gas 220 kV bus; to determine by means of measurements and calculations based on the OSINERGMIN and COES-SINAC. Procedure, the value corresponding to the flickers, voltage fluctuations and harmonics in different loads of the TG-8 generation unit, operating with Natural Gas. The method used is deductive, descriptive-explanatory; the use of thyristor-controlled SVC is a new proposal in Peru. The SVC's controlled by thyristors. They allow to improve the harmonics in the line and to stabilize to a great extent the fluctuations of tension fundamentally, those that have to do with the quality of the electrical service and increasing the reliability of the system. The thyristor control system is implemented through TACS (Transient Analysis Control Systems) of ATP / EMTP. For analysis and simulations, this article considers a 220 kV line with two units of UTI brand aviation-type turbines with a power of 105.8 MW, a Westinhouse gas turbine with a power of 123.9 MW and a Siemens brand gas turbine of 199.8 MW.

The unique challenges posed by the high altitude and extreme-irradiance variability in the Peruvian Altiplano necessitate innovative and cost-effective monitoring solutions for photovoltaic (PV) systems. This study presents a low-cost wireless monitoring system for PV systems, designed for performance analysis and with potential application in DC nanogrids. The system, based on an Arduino Nano and Raspberry Pi architecture, captures real-time data on key electrical parameters such as voltage, current, and power, as well as environmental conditions like temperature and irradiance, which are critical factors influencing PV system performance. Deployed on a 3 kW grid-connected PV system in the Peruvian Altiplano, the system reveals significant irradiance variability, with fluctuations exceeding 20% within a single day and extreme events surpassing 1500 W/m². This variability resulted in an average daily energy generation fluctuation of 15%, underscoring the importance of continuous monitoring for optimizing PV system operation. This variability impacts energy generation and underscores the importance of continuous monitoring for optimizing PV system operation. The study analyzes the system’s performance under different irradiance conditions and discusses its adaptability for use in DC nanogrids, which offer enhanced efficiency and accessibility in remote areas like the Altiplano. This research contributes a practical and versatile tool for advancing sustainable energy solutions, with implications for improving the efficiency and reliability of both grid-connected PV systems and the emerging field of DC nanogrids in remote areas.

This article analyzes the impact of the integration of large-scale wind generation in an Electric Power System, due to the fact that its intermittent nature and the type of wind turbine it uses, inject harmonic currents that cause harmonic distortions in the electrical network to which they connect. The objective is to determine the effects of the harmonic distortion of the Marcona wind farm connected to the grid with an installed power of 32 MW; produced after commissioning, analyzed in the 220 kV bus of the Tres Hermanas SE. Harmonic resonance points produced in the system were identified through frequency sweep analysis. So that later, through the analysis of the Harmonic Flow of Power, the total harmonic distortion (THD) in the 220 kV bus of the Tres Hermanas SE is known and it can be compared with the limits required by the power quality regulations.

For the safe operation and control of battery deterioration, thermal monitoring is extremely important. The performance of a battery energy system and its accuracy in State of Charge (SoC) (%) estimation for electric boats and electric vehicles are significantly influenced by ambient temperature. In this study, the battery will operate at extreme temperatures within Titicaca Lake, located at an altitude of 3850 meters above sea level. Therefore, the objective is to study a battery model that considers ambient and extreme temperatures. The cell must operate at critical values with a current of 150 A, a voltage of 3.65 V, and observe thermal aging that affects the capacity due to multiple charges and discharges. The method applied to lithium iron phosphate batteries LiFePO4 involved wear testing, considering three stress factors (time, temperature, and state of charge (SoC) (%)). Capacity measurements and resistance calculations tracked short-term degradation behaviors. The Shepherd model was established to identify battery aging using a simple but accurate two-step nonlinear regression approach; also, the thermal analysis of the battery cell was conducted to identify the most critical zone of the cell in terms of heat generation. This analysis allowed us to maximize heat dissipation with only a forced air fan mounted on the vital region. For further evaluation of the proposed strategies, a computational fluid dynamics (CFD) model was built in COMSOL Multiphysics® and validated with a thermographic camera to identify the temperature in the cells. The final arrangement of the LiFePO4 battery is the 16s1p prismatic cell type (16 cells in series and one parallel), with the cell experiencing a temperature variation of approximately 1° C higher than that of the outer parts.