The Effect of Average Photon Energy and Module Temperature on Performance of Photovoltaic Module under Thailand's Climate Condition

AbstractThis article present the effect of average photon energy and module temperature on performance of amorphous silicon (a-Si), polycrystalline (p-Si) and hetero-junction intrinsic thin layer (HIT) photovoltaic (PV) modules under Thailand climatic condition which located at the equator zone. The outdoor solar irradiance distribution measurements on the PV array installed at Energy Park, School of Renewable Energy Technology (SERT), Naresuan University, Thailand revealed that the field output factor of the poly-Si and HIT PV modules depended almost only on a module temperature, while that of the a-Si ones mainly depended on APE. The behaviors were reasonable considering from the operating mechanisms of the PV modules. These results demonstrate that APE is a reasonable and useful index to describe the spectral irradiance distribution for evaluating the performance of PV modules

Fuzzy Control for Smart PV-Battery System Management to Stabilize Grid Voltage of 22 kV Distribution System in Thailand

This paper presents a fuzzy logic based algorithm developed to bring smart functionality to an ordinary PV-battery system in order to maintain the grid voltage stability of the 22 kV distribution system in Thailand. This research focuses on minimizing grid voltage fluctuations by converting a typical PV system into a smart PV-battery system (SPVs-BSS). A SPVs-BSS will be able to control the electrical power from a PV system to maintain the grid voltage in case of unexpected events or emergencies. Grid support functions such as a variable reactive power control and active power control will be discussed, leading to strategies for charging and discharging the battery system in response to the status of grid voltage. Fuzzy Logic was used to develop this control algorithm, which is named the Voltage Stability Fuzzy Logic Algorithm (VSFL Algorithm). The methodology of this research consists of three parts. First, testing the grid inverter operated on grid support functions. Second, the VSFL algorithm was developed to manage both the grid inverter and the battery system. Third, a SPVs-BSS equipped with the VSFL algorithm was simulated by using DIgsilent PowerFactory software. Results showed that the SPVs-BSS equipped with the VSFL Algorithm successfully maintained grid voltage in target range

Investigations to Conduct a Study about Possibilities to Use Small Scale Solar Dish Stirling Engine System in Thailand

AbstractThis research studies the possibilities of generating electricity by using small scale solar dish Stirling engine system in Thailand. A solar dish Stirling engine system was evaluated and designed as prototypes for Thailand. The performance of system for electricity generation was also simulated under Thai climate condition. The results of the study can be structured in two parts. First is testing the existing Stirling engine and second is simulation the electricity generation by solar dish Stirling engine system prototype in Thailand. The existing Stirling engine at the Komplexlabor of the FH – Stralsund University, Germany was tested to understand the characteristics of the operating system. Stirling engine was operated at temperature of about 800 o C in the combustion chamber, being its nominal rotational speed 1,517rpm. Finally, the average Stirling engine efficiency was established in 22%. The results of simulation on solar dish Stirling engine were that the main components for a prototype of a solar dish Stirling engine system in Thailand shall consist of a Stirling engine with a nominal power of 25kW, and a 131 m2 dish concentrator. It can generate electricity about 27,946 kWh/year of electricity under Thai climate condition. During the working process, the heat lost on dish concentrator was 22% and heat lost within the Stirling engine was 60.84%. The system efficiency of this solar dish Stirling engine system was 17%

Evaluation of Machine Learning Algorithms for Supervised Anomaly Detection and Comparison between Static and Dynamic Thresholds in Photovoltaic Systems

The use of photovoltaic systems has increased in recent years due to their decreasing costs and improved performance. However, these systems can be susceptible to faults that can reduce efficiency and energy yield. To prevent and reduce these problems, preventive or predictive maintenance and effective monitoring are necessary. PV health monitoring systems and automatic fault detection and diagnosis methods are critical for ensuring PV plants’ reliability, high-efficiency operation, and safety. This paper presents a new framework for developing fault detection in photovoltaic (PV) systems. The proposed approach uses machine learning algorithms to predict energy power production and detect anomalies in PV plants by comparing the predicted power from a model and the measured power from sensors. The framework utilizes historical data to train the prediction model, and live data is compared with predicted values to analyze residuals and detect abnormal scenarios. The proposed approach has been shown to accurately distinguish anomalies using constructed thresholding, either static or dynamic thresholds. The paper also reports experimental results using the Matthews correlation coefficient, a more reliable statistical rate for an imbalanced dataset. The proposed approach leads to a reasonable anomaly detection rate, with an MCC of 0.736 and a balanced ACC of 0.863

Experimental Studies on PV Module Cooling With Radiation Source PCM Matrix

Rise in PV module temperature ( $\text{T}_{\mathrm {PV}}$ ) majorly drops the electrical output of the PV system. This research presents a novel cylindrical tube PCM matrix that is not in physical contact with the PV module back surface unlike the existing PCM based PV module cooling techniques. This contactless PCM matrix prevents the PV module from thermal and physical stress, also it blocks thermal energy re-conduction from PCM to PV module. While stored thermal energy from PCM retransferred to the PV module during off-sunshine hours and also when the PCM turns to liquid $\text{T}_{\mathrm {PV}}$ starts to rise abruptly, this contactless PCM matrix minimizes these issues as PCM matrix receives thermal energy by the mode of radiation and convection; Besides, PCM matrix surface area is not enclosed with the PV module back surface area that reduces the thermal stress and re-conduction. Developed PCM matrix is integrated beneath the PV module at particular distances of 6 mm, 9 mm and 12 mm to optimize the spacing between PV module and PCM matrix. It is found that 6 mm spacing PCM matrix reduced the $\text{T}_{\mathrm {PV}}$ maximum of 2.5 °C compared to 9 mm and 12 mm spacing. This $\text{T}_{\mathrm {PV}}$ reduction enhanced the PV module electrical output by 0.2 % than PV without PCM and it is observed that 6 mm is an optimal spacing for the radiation source PCM matrix