• KIPS Transactions on Software and Data Engineering
• /
• v.11 no.8
• /
• pp.339-346
• /
• 2022

Recently, the resource depletion and climate change problem caused by the massive usage of fossil fuels for electric power generation has become a critical issue worldwide. According to this issue, interest in renewable energy resources that can replace fossil fuels is increasing. Especially, photovoltaic power has gaining much attention because there is no risk of resource exhaustion compared to other energy resources and there are low restrictions on installation of photovoltaic system. In order to use the power generated by the photovoltaic system efficiently, a more accurate photovoltaic power forecasting model is required. So far, even though many machine learning and deep learning-based photovoltaic power forecasting models have been proposed, they showed limited success in terms of interpretability. Deep learning-based forecasting models have the disadvantage of being difficult to explain how the forecasting results are derived. To solve this problem, many studies are being conducted on explainable artificial intelligence technique. The reliability of the model can be secured if it is possible to interpret how the model derives the results. Also, the model can be improved to increase the forecasting accuracy based on the analysis results. Therefore, in this paper, we propose an explainable photovoltaic power forecasting scheme based on BiLSTM (Bidirectional Long Short-Term Memory) and SHAP (SHapley Additive exPlanations).

• The Journal of the Korea institute of electronic communication sciences
• /
• v.18 no.6
• /
• pp.1143-1150
• /
• 2023

The global climate crisis and the implementation of low-carbon policies have led to a growing interest in renewable energy and a growing number of related industries. Among them, solar power is attracting attention as a representative eco-friendly energy that does not deplete and does not emit pollutants or greenhouse gases. As a result, the supplement of solar power facility is increasing all over the world. However, solar power is easily affected by the environment such as geography and weather, so accurate solar power forecast is important for stable operation and efficient management. However, it is very hard to predict the exact amount of solar power using statistical methods. In addition, the conventional prediction methods have focused on only short- or long-term prediction, which causes to take long time to obtain various prediction models with different prediction horizons. Therefore, this study utilizes a many-to-many structure of a recurrent neural network (RNN) to integrate short-term and long-term predictions of solar power generation. We compare various RNN-based very short- and long-term prediction methods for solar power in terms of MSE and R² values.

• Membrane Journal
• /
• v.34 no.1
• /
• pp.70-78
• /
• 2024

A photo-crosslinked anion exchange membrane (AEM) based on quaternary-aminated polyacrylates was developed for reverse electrodialysis (RED). Although reverse electrodialysis is a clean and renewable energy generation system, the low power output and high membrane cost are serious obstacles to its commercialization. Cross-linked AEMs without any polymer supporters were fabricated through photo-crosslinking between polymer-typed acrylates with anion conducting groups, in particular, polymer-typed acrylates were synthesized based on engineering plastic with outstanding mechanical and chemical property. The fabricated membranes showed outstanding physical, chemical, and electrochemical properties. The area resistance of the fabricated membranes (CQAPPOA-20, CQAPPOA-35, and CQAPPOA-50) were ~50% lower than that of AMV (2.6 Ω cm²). Moreover, the transport number of CQAPPOA-35 wase comparable to that of AMV, despite the thin thickness (40 ㎛) of the fabricated membranes. The RED stack with the CQAPPOA-35 membrane provided an excellent maximum power density of 2.327 W m^-2 at a flow rate of 100 mL min^-1, which is 15% higher than that (2.026 W m^-2) of the RED stack with the AMV membrane. Considering easy fabrication process by UV photo-crosslinking and outstanding RED stack properties, the CQAPPOA-35 membrane is a promising candidate for REDs.

• Environmental and Resource Economics Review
• /
• v.14 no.4
• /
• pp.817-838
• /
• 2005

In this paper, the resource adequacy as well as the optimum fuel mix is obtained by the following procedures. First, the regulation body, the government agency, determine the reliability index as well as the optimum portfolio of the fuel mix during the planning horizon. Here, the resources with the characteristics of public goods such as demand-side management, renewable resources are assigned in advance. Also, the optimum portfolio is determined by reflecting the economics, environmental characteristics, public acceptance, regional supply and demand, etc. Second, the government announces the required amount of each fuel-type new resources during the planning horizon and the market participants bid to the government based on their own estimated fixed cost. Here, the government announces the winners of the each auction by plant type and the guaranteed fixed cost is determined by the marginal auction price by plant type. Third, the energy market is run and the surplus of each plant except their cost (guaranteed fixed cost and operating cost) is withdrew by the regulatory body. Here, to induce the generators to reduce their operating cost some incentives for each generator is given based on their performance. The performance is determined by the mechanism of the performance-based regulation (PBR). Here the free-riding performance should be subtracted to guarantee the transparent competition. Although the suggested mechanism looks like very regulated one, it provides two mechanism of the competition. That is, one is in the resource construction auction and the other is in the energy spot market. Also the advantages of the proposed method are it guarantee the proper resource adequacy as well as the desired fuel mix. However, this mechanism should be sustained during the transient period of the deregulation only. Therefore, generation resource planning procedure and market mechanisms are suggested to minimize possible stranded costs.

• Journal of Korean Society of Environmental Engineers
• /
• v.39 no.6
• /
• pp.356-370
• /
• 2017

The energy savings and $CO_2$ emission reductions obtainable from the situation that the Smart Grid system (SGs) is assumed to be applied in Korea up to 2030 is quantitatively analyzed with many reported data. For calculation, SGs is divided into five sectors such as Smart Transmission and Distribution (ST&D), Smart Consumer (SC), Smart Electricity Service (SES), Smart Renewable Energy (SRE) and Smart Transportation (ST). Total annual energy savings in 2030 is estimated to be approximately 103,121 GWh and this is 13.1% of total electricity consumption outlook. Based on this value, total amount of reducible $CO_2$ emissions is calculated to 55.38 million $tCO_2$, which is 17.6% of total nation's GHG reduction target. Although the contribution of energy saving due to SGs to total electricity consumption increases as years go by, that of $CO_2$ emission reduction gradually decreases. This might be because that coal fired based power generation is planned to be sharply increased and the rate of $CO_2$ emission reduction scheduled by nation is very fast. The contributable portion of five each sector to total $CO_2$ emission reductions in 2030 is estimated to be 44.37% for SC, 29.16% for SRE, 20.12% for SES, 5.11% for ST&D, and 1.24% for ST.

• The Korean Journal of Applied Statistics
• /
• v.36 no.1
• /
• pp.49-62
• /
• 2023

Solar energy, which is rapidly increasing in proportion, is being continuously developed and invested. As the installation of new and renewable energy policy green new deal and home solar panels increases, the supply of solar energy in Korea is gradually expanding, and research on accurate demand prediction of power generation is actively underway. In addition, the importance of solar radiation prediction was identified in that solar radiation prediction is acting as a factor that most influences power generation demand prediction. In addition, this study can confirm the biggest difference in that it attempted to predict solar radiation using medium-term forecast weather data not used in previous studies. In this paper, we combined the multi-linear regression model, KNN, random fores, and SVR model and the clustering technique, K-means, to predict solar radiation by hour, by calculating the probability density function for each cluster. Before using medium-term forecast data, mean absolute error (MAE) and root mean squared error (RMSE) were used as indicators to compare model prediction results. The data were converted into daily data according to the medium-term forecast data format from March 1, 2017 to February 28, 2022. As a result of comparing the predictive performance of the model, the method showed the best performance by predicting daily solar radiation with random forest, classifying dates with similar climate factors, and calculating the probability density function of solar radiation by cluster. In addition, when the prediction results were checked after fitting the model to the medium-term forecast data using this methodology, it was confirmed that the prediction error increased by date. This seems to be due to a prediction error in the mid-term forecast weather data. In future studies, among the weather factors that can be used in the mid-term forecast data, studies that add exogenous variables such as precipitation or apply time series clustering techniques should be conducted.

• Journal of the Korean Applied Science and Technology
• /
• v.34 no.1
• /
• pp.1-11
• /
• 2017

Bio-oil has attracted considerable interest as one of the promising renewable energy resources because it can be used as a feedstock in conventional petroleum refineries for the production of high value chemicals or next-generation hydrocarbon fuels. Zeolites have been shown to effectively promote cracking reactions during pyrolysis resulting in highly deoxygenated and hydrocarbon-rich compounds and stable pyrolysis oil products. In this study, catalytic pyrolysis was applied to upgrade bio-oil from yellow poplar and then fuel characteristics of upgraded bio-oil was investigated. Yellow Poplar(500 g) which ground 0.3~1.4 mm was processed into bio-oil by catalytic pyrolysis for 1.64 seconds at $465^{\circ}C$ with Control, Blaccoal, Whitecoal, ZeoliteY and ZSM-5. Under the catalyst conditions, bio-oil productions decreased from 54.0%(Control) to 51.4 ~ 53.5%, except 56.2%(Blackcoal). HHV(High heating value) of upgraded bio-oil was more lower than crude bio-oil while the water content increased from 37.4% to 37.4 ~ 45.2%. But the other properties were improved significantly. Under the upgrading conditions, ash and TAN(Total Acid Number) is decrease and particularly important as transportation fuel, the viscosity of bio-oil decreased from 6,933 cP(Control) to 2,578 ~ 4,627 cP. In addition, ZeoliteY was most effective on producing aromatic hydrocarbons and decreasing of from the catalytic pyrolysis.

• Journal of Plant Biotechnology
• /
• v.33 no.3
• /
• pp.195-207
• /
• 2006

Stem cells are the primordial, initial cells which usually divide asymmetrically giving rise to on the one hand self-renewals and on the other hand progenitor cells with potential for differentiation. Zygote (fertilized egg), with totipotency, deserves the top-ranking stem cell - he totipotent stem cell (TSC). Both the ICM (inner cell mass) taken from the 6 days-old human blastocyst and ESC (embryonic stem cell) derived from the in vitro cultured ICM have slightly less potency for differentiation than the zygote, and are termed pluripotent stem cells. Stem cells in the tissues and organs of fetus, infant, and adult have highly reduced potency and committed to produce only progenitor cells for particular tissues. These tissue-specific stem cells are called multipotent stem cells. These tissue-specific/committed multipotent stem cells, when placed in altered environment other than their original niche, can yield cells characteristic of the altered environment. These findings are certainly of potential interest from the clinical, therapeutic perspective. The controversial terminology 'somatic stem cell plasticity' coined by the stem cell community seems to have been proved true. Followings are some of the recent knowledges related to the stem cell. Just as the tissues of our body have their own multipotent stem cells, cancerous tumor has undifferentiated cells known as cancer stem cell (CSC). Each time CSC cleaves, it makes two daughter cells with different fate. One is endowed with immortality, the remarkable ability to divide indefinitely, while the other progeny cell divides occasionally but lives forever. In the cancer tumor, CSC is minority being as few as 3-5% of the tumor mass but it is the culprit behind the tumor-malignancy, metastasis, and recurrence of cancer. CSC is like a master print. As long as the original exists, copies can be made and the disease can persist. If the CSC is destroyed, cancer tumor can't grow. In the decades-long cancer therapy, efforts were focused on the reducing of the bulk of cancerous growth. How cancer therapy is changing to destroy the origin of tumor, the CSC. The next generation of treatments should be to recognize and target the root cause of cancerous growth, the CSC, rather than the reducing of the bulk of tumor, Now the strategy is to find a way to identify and isolate the stem cells. The surfaces of normal as well as the cancer stem cells are studded with proteins. In leukaemia stem cell, for example, protein CD 34 is identified. In the new treatment of cancer disease it is needed to look for protein unique to the CSC. Blocking the stem cell's source of nutrients might be another effective strategy. The mystery of sternness of stem cells has begun to be deciphered. ESC can replicate indefinitely and yet retains the potential to turn into any kind of differentiated cells. Polycomb group protein such as Suz 12 repress most of the regulatory genes which, activated, are turned to be developmental genes. These protein molecules keep the ESC in an undifferentiated state. Many of the regulator genes silenced by polycomb proteins are also occupied by such ESC transcription factors as Oct 4, Sox 2, and Nanog. Both polycomb and transcription factor proteins seem to cooperate to keep the ESC in an undifferentiated state, pluripotent, and self-renewable. A normal prion protein (PrP) is found throughout the body from blood to the brain. Prion diseases such as mad cow disease (bovine spongiform encephalopathy) are caused when a normal prion protein misfolds to give rise to PrP$^{SC}$ and assault brain tissue. Why has human body kept such a deadly and enigmatic protein? Although our body has preserved the prion protein, prion diseases are of rare occurrence. Deadly prion diseases have been intensively studied, but normal prion problems are not. Very few facts on the benefit of prion proteins have been known so far. It was found that PrP was hugely expressed on the stem cell surface of bone marrow and on the cells of neural progenitor, PrP seems to have some function in cell maturation and facilitate the division of stem cells and their self-renewal. PrP also might help guide the decision of neural progenitor cell to become a neuron.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.22 no.4
• /
• pp.312-326
• /
• 2020

Generation of weather forecasts at 100 m resolution through a statistical downscaling process was implemented by Korea Meteorological Administration Post- Processing (KMAPP) system. The KMAPP data started to be used in various industries such as hydrologic, agricultural, and renewable energy, sports, etc. Cheorwon area and Jeonbuk area have horizontal planes in a relatively wide range in Korea, where there are many complex mountainous areas. Cheorwon, which has a large number of in-situ and remotely sensed phenological data over large-scale rice paddy cultivation areas, is considered as an appropriate area for verifying KMAPP prediction performance in agricultural areas. In this study, the performance of predicting KMAPP temperature changes according to ecological changes in agricultural areas in Cheorwon was compared and verified using KMA and National Center for AgroMeteorology (NCAM) observations. Also, during the heat wave in Jeonbuk Province, solar radiation forecast was verified using Automated Synoptic Observing System (ASOS) data to review the usefulness of KMAPP forecast data as input data for application models such as livestock heat stress models. Although there is a limit to the need for more cases to be collected and selected, the improvement in post-harvest temperature forecasting performance in agricultural areas over ordinary residential areas has led to indirect guesses of the biophysical and phenological effects on forecasting accuracy. In the case of solar radiation prediction, it is expected that KMAPP data will be used in the application model as detailed regional forecast data, as it tends to be consistent with observed values, although errors are inevitable due to human activity in agricultural land and data unit conversion.

• Clean Technology
• /
• v.27 no.1
• /
• pp.1-8
• /
• 2021

Due to the negative impacts of microplastics (MPs) on the ecosystem, the investigation of its occurrence and its treatment from sewage and wastewater treatment plants (WWTPs) have received a lot of attention in the recent years. Most MPs are precipitated and removed with the sludge during the treatment process. Proper sludge management is immensely necessary to avoid MP exposure in the environment. However, the domestic research on this aspect is limited. This study reviews appropriate sludge management approaches to decrease environmental MP exposure. This can be achieved through investigating sludge generation and treatment, regulation laws and government policy trends with an emphasis on WWTPs. The ratio of sludge in sewage treatment plants has been observed to be highest in recycling followed by incineration and landfills. Recycling is the highest in fuel followed by construction materials and composting. For WWTPs, the highest ratio is in recycling followed by fuel and landfills, and recycling is confirmed in the following order: incineration > after composting > after solidification > earthworm breeding. Treatment approaches that can increase the exposure of MPs to the ecosystem are considered to be used in landfills and agricultural fields. However, this method is not appropriate given the insufficient capacity of domestic landfills and the sufficient supply of existing chemical and animal manure fertilizers. Instead, it would be rational in terms of environmental preservation to expand the use of fuel and energy in connection with the new and renewable energy policy, and to actively seek the use of sub-materials for construction materials. In order to secure the basic data for the effectiveness of future planning and revision of related laws, it is required to perform an in-depth investigation of the sludge supply and demand status along with the environmental and economic effects.