Stagnation and solar fraction analysis on solar thermal integration in Southeast Asia

The depletion and negative impacts of using fossil fuels have caused rapid technological growth in renewable energy sources. Southeast Asia is rich in solar resources, which makes generating thermal energy from a solar thermal system highly attractive. The objective of this article is to propose a new method for estimating solar fraction and possible occurrences of fluid stagnation based on a daily heat storage profile, reduce the possible stagnation by adjusting the storage volume, and comparing the economic performance of the proposed system among different countries in Southeast Asia. Given a solar heat system specification and irradiance data, the method involves four steps: the establishment of a daily heat storage profile, system performance analysis, reduction of the stagnation by adjusting the ratio of the storage volume to solar collector area, rsto/coll and the target heat storage percentage for night cooling, Fnc and techno-economic analysis. As a result, the proposed solar thermal system integration located in Naypyidaw, Myanmar, gives the lowest LCoH (levelised cost of heat) of 0.194 $/kWh, followed by Kuala Lumpur in Malaysia and Banyuwangi in Indonesia. As a comparison, the LCoH of a gas-fuelled heating system with a higher amount of heat demand encountered is 0.15$/kWh (Wahed et al. UPM Alam Cipta, Vol. 8, No. 3, pp. 32–43,2015)

Effect of solar utility temperature to costing and design parameters of integrated solar thermal system

The objective of this research is to evaluate the trade - off between solar utility temperature and solar collector efficiency, in the context of Malaysia, and also evaluating the proposed system efficiency and economic feasibility. Since Malaysia receives an abundance amount of solar radiation throughout the year, generating thermal energy from solar thermal energy system is highly attractive. In the illustrative case study, flat plate collector (FPC) and compound parabolic collector (CPC) were used for evaluation of integration with different temperature process . For each process, configuration with and without HEX were evaluated. Generally, solar collector cost for configuration with HEX is more than configuration without HEX , solar collector cost will be lower when solar utility temperature is lower , and effect of solar utility temperature variation affect more on FPC than on CPC. The results show that annual saving is 174,952 MYR /y . The payback period for all processes vary from 4.7 to 7.6 y

Solar Radiation Forecast Using Cloud Velocity for Photovoltaic Systems

Today, solar energy is used in a many different ways. One of the most popular technological developments for this purpose is photovoltaic conversion to electricity. However, power fluctuations due to the variability of solar energy are one of the challenges faced by the implementation of photovoltaic systems. To overcome this problem, forecasting solar radiation data several minutes in advance is needed. In this research, a methodology to forecast solar radiation using cloud velocity and cloud moving angle is proposed. Generally, a red-to-blue ratio (RBR) color model and correlation analysis are used for obtaining the cloud velocity and moving angle. Artificial neural network (ANN) forecast models with different input combinations are established. This methodology requires lower computational time since it only uses part of the pixels in the sky image. Based on R-squared analysis, it can be concluded that the ANN model with inputs of cloud velocity and moving angle and average solar radiation showed the highest accuracy among other combinations of inputs. The R-squared value was 0.59 with only a relatively small sample size of 42. The proposed model showed a highest improvement of 75.79% when compared to the ANN model based on historical solar radiation data only

Cloud optical depth retrieval via sky\u27s infrared image for solar radiation prediction

Photovoltaic (PV) system is developed to harness solar energy as an alternative energy to reduce the dependency on fossil fuel energy. However, the output of the PV system is not stable due to the fluctuation of solar radiation. Hence, solar radiation prediction in advanced is needed to make sure the tap changer in PV system has enough time to respond. In this research, the cloud base temperature is identified from the sky\u27s thermal image. From the cloud base temperature, cloud optical depth (COD) is calculated. Artificial neural network (ANN) models are established by using different combinations of current solar radiation and COD to predict the solar radiation several minutes in advanced. R-squared value is used to measure the accuracy of the models. For prediction in advanced for every minute, with COD as input, always show the highest R-squared value. The highest R-squared value is 0.8899 for the prediction for 1 minute in advanced and dropped to 0.5415 as the minute of prediction in advanced increase to 5. This shows that the proposed methodology is suitable for prediction of solar radiation for short term in advanced. © 2019 Penerbit Akademia Baru

Cloud optical depth retrieval via sky’s infrared image for solar radiation prediction

Photovoltaic (PV) system is developed to harness solar energy as an alternative energy to reduce the dependency on fossil fuel energy. However, the output of the PV system is not stable due to the fluctuation of solar radiation. Hence, solar radiation prediction in advanced is needed to make sure the tap changer in PV system has enough time to respond. In this research, the cloud base temperature is identified from the sky’s thermal image. From the cloud base temperature, cloud optical depth (COD) is calculated. Artificial neural network (ANN) models are established by using different combinations of current solar radiation and COD to predict the solar radiation several minutes in advanced. R-squared value is used to measure the accuracy of the models. For prediction in advanced for every minute, with COD as input, always show the highest R-squared value. The highest R-squared value is 0.8899 for the prediction for 1 minute in advanced and dropped to 0.5415 as the minute of prediction in advanced increase to 5. This shows that the proposed methodology is suitable for prediction of solar radiation for short term in advanced

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field