Jose Manuel Ramos Cutipa

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.

In grid-connected photovoltaic systems (SFCR) in public lighting, several studies need to be carried out, in various conditions. This study in the city of Puno makes a contribution to the use and massification of distributed generation in public lighting systems in low voltage balanced systems. The objective is to analyze the performance in the connection to the grid of the photovoltaic system in public lighting and to be able to verify the electrical parameters such as: power factor, voltage and power generation to inject, considering different topologies and then carry out the treatments through simulations with The ETAP software, The study used polycrystalline photovoltaic panels (SOLAR MODULE EGE-200P-72), micro inverters (MICRO REPLUS) and luminaires with a load of 70 W. The results of three SFCR topologies were analyzed using the ETAP software. Two scenarios were carried out with different irradiance levels (1000 and 500 W/m^2), from which the results were verified for electrical parameters such as voltage drops, harmonic distortion THD and frequency. In relation to the recommended topologies to analyze the viability of implementing a 1.91 KVA public lighting system connected to the electrical grid, a feasible option for our region is presented. This study will be integrated into regulations related to power generation through grid-connected photovoltaic systems. In conclusion, the results of the study demonstrated an improvement in the reliability of the electrical power system in public lighting in the city of Puno thanks to the implementation of photovoltaic systems connected to the grid. This translates into benefits such as greater power generation, better power factor, voltage stability and energy savings.

Micro inverters, with a distributed orientation and unlike a conventional inverter that had a centralized installation approach, are installed behind each solar panel and convert direct current electricity to alternating current, just below the panel. All micro inverters can be connected directly to the home network, independently of the other micro inverters in the system. When a panel is shaded, for example, it will in no way affect the performance of the other panels. The main objective of this work is to evaluate the efficiency and regulation of the 250W grid connection micro inverter operating in the geographical and climatic conditions of 3800 meters above sea level, to improve the operation of these systems in the area. from Puno. If the evaluation and regulation of the micro inverter will be carried out, we will have better efficiency in the work of this team, which is the micro inverter. The methodology will go with the correct voltage found through a technique called Maximum Power Point Tracking or MPPT. When the maximum power point is applied at the panel level rather than a system as a whole. Performance will increase dramatically, bringing a better solution to the customer. Finally, a measurement system was used that helped us to collect data. As a result, the efficiency of our micro inverter is greater than 90 percent, at the same time it works with power factors very close to unity, if the equipment works at a capacity greater than 20%, on the date of analysis the maximum efficiency was 93.215%. One of the conclusions in this case, as the power of the micro inverter is greater than that of the photovoltaic generator, does not have limitations or what guarantees that it operates in optimal conditions.

The production of photovoltaic energy is currently of great importance; however, its use can be affected by seasonality due to the varied climatic conditions of the area. The objective of this research was to determine the comparative analysis of photovoltaic energy production in the dry and rainy seasons in the Peruvian Altiplano at high altitude. For the development of this research, a photovoltaic system was implemented to capture solar irradiation, a solar irradiation sensor connected to a programmable logic controller (PLC) for data acquisition, installed in varied climatic conditions in this area, and a principal component analysis (PCA) method was used to determine the differences in seasonal electricity production. The results of the dry season in peak sunshine hours (PSH) were 7.46 kWh/m ² /d and in the rainy season 6.05 kWh/m ² /d, being 18.86 % more in electricity production, due to climatic variability, presence of rain and days with partial cloud cover. Therefore, in the Peruvian Altiplano at high altitude in the months between July to October there is a higher energy production than in the months between November to February.

Classification green coffee beans is one of the main tasks during the quality grading process. This evaluation is normally carried out by specialist doing a visual inspection or using traditional instruments which have some limitations. This work is focused on the implementation of a computer vision system combining a hardware prototype and a software module. The hardware was made to guarantee the controlled conditions to capture the images of green coffee beans, the software is based on computer vision algorithms in order to detect defects of the coffee beans. The novelty of our proposal is the combination of algorithms to enhance the accuracy and the high number of defects detected. We applied a White Patch algorithm as an image enhancement procedure, color histograms as feature extractor and Support Vector Machine (SVM) for the classification task. It was constituted an image beans database of 1930 instances, and it was extracted 768 features, finally, the model was applied over 13 categories of defects described by the Specialty Coffee Association of America (SCAA). Results of classification achieved a 98.8% of overall accuracy detection, therefore the proposed system proved to be effective in classifying physical defects of green coffee beans. With this work we showed that the grading green coffee process can be automatized, adding a new paradigm in quality evaluation task to enhance the coffee industry.