• Journal of the Korean Solar Energy Society
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• v.33 no.5
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• pp.1-8
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• 2013

Wind resource data of short-term period has to be corrected a long-term period by using MCP method that Is a statistical method to predict the long-term wind resource at target site data with a reference site data. Because the field measurement for wind assessment is limited to a short period by various constraints. In this study, 2 different MCP methods such as Linear regression and Matrix method were chosen to compare the predictive accuracy between the methods. Finally long-term wind speed, wind power density and capacity factor at the target site for 20 years were estimated for the variability of wind and wind energy. As a result, for 20 years annual average wind speed, Yellow sea off shore wind farm was estimated to have 4.29% for coefficient of variation, CV, and -9.57%~9.53% for range of variation, RV. It was predicted that the annual wind speed at Yellow sea offshore wind farm varied within ${\pm}10%$.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2009.06a
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• pp.287-288
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• 2009

In this paper we developed positioning algorithm considering distributed energy resource of ocean side by load flow calculation using Newton-Rhapson method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2063-2081
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• 2018

A resource allocation algorithm is proposed in this paper to simultaneously minimize the total system power consumption and maximize the system throughput for the downlink of multi-user multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) systems. With the Lagrange dual decomposition method, we transform the original problem to its convex dual problem and prove that the duality gap between the two problems is zero, which means the optimal solution of the original problem can be obtained by solving its dual problem. Then, we use convex optimization method to solve the dual problem and utilize bisection method to obtain the optimal dual variable. The numerical results show that the proposed algorithm is superior to traditional single-objective optimization method in both the system throughput and the system energy consumption.

• Asian Journal of Business Environment
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• v.11 no.4
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• pp.31-38
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• 2021

Purpose: This paper uses the resource-dependency theory to present the case of the Pakistan sugar industry to highlight how the industry uses a strategic alliance to gain a powerful bargaining position over its critical dependencies. The case of the Pakistan sugar industry is well-known and it is common knowledge that the alliance or the cartel within it is responsible for frequent price hikes and sugar supply shortages in the country. Research design, data and methodology: We use a case study, qualitative document analysis design to trace how the alliance overcomes its various dependencies, and in doing so, how does it harm various stakeholder interests. Results: This paper finds that the sugar industry alliance maintains its bargaining power by manipulating sugar supply through horizontal alliances, political affiliations, underselling and under-reporting sugar stocks, purchasing sugarcane from the black market, and by gaining billions of rupees in export subsidies by hoarding stock and using its political connections. Conclusion: The paper concludes by providing a summary of the measures which the government has taken to curb this anticompetitive conduct; the most important of which is the removal of protectionist measures for sugar trade and allowing market forces to control the demand and supply of sugar in the local market.

• Journal of Wind Energy
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• v.4 no.1
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• pp.39-45
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• 2013

Massive offshore wind projects of have recently been driven in full gear on the Western Offshore of Korea including the 2.5 GW West-Southern Offshore Wind Project of the Ministry of Trade, Industry and Energy, and the 5 GW Offshore Wind Project of the Jeollanamdo Provincial Government. On this timely occasion, this study performed a general wind resource assessment on the Western Offshore by using the MERRA reanalysis data of temporal-spatial resolution and accuracy greatly improved comparing to conventional reanalysis data. It is hard to consider that wind resources on the Western Sea are excellent, since analysis results indicated the average wind speed of 6.29 ± 0.39 m/s at 50 m above sea level, and average wind power density of 307 ± 53 W/m². Therefore, it is considered that activities shall be performed for guarantee economic profits from factor other than wind resources when developing an offshore wind project on the Western Offshore.

• Nuclear Engineering and Technology
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• v.56 no.8
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• pp.2923-2936
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• 2024

Modern risk management philosophy emphasizes the invulnerability of human beings to cope with all kinds of emergencies. The Nuclear Accidents Emergency Response Organization (NAERO) of Nuclear Power Plant (NPP) is the primary body responsible for nuclear accidents emergency response. The invulnerability of the organization to disturbance or attack from internal and external sources is crucial in the completion of its response missions, reduction of severity of accidents, and assurance of public and environmental safety. This paper focused on the NAERO of a certain NPP in China, and applied the complex network theory to construct the network model of the organization. The topological characteristics of the network were analyzed. Four importance evaluation indexes of network nodes including Degree Centrality (DC), Betweeness Centrality (BC), Closeness Centrality (CC) and Eigenvector Centrality (EC), along with Pearson coefficient correlation among the indexes were calculated and analyzed. Size of the Largest Connected Component (LCC) and Network Efficiency were used as measures regarding the invulnerability of the network. Simulation experiments were conducted to assess the invulnerability of network against various attack strategies. These experiments were conducted both in the absence of node protection measures and under protection measures with different node protection rates. This study evaluated the invulnerability of the NAERO network, and provided significant decision-making basis for the enhancement of the network's invulnerability.

• Environmental and Resource Economics Review
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• v.25 no.3
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• pp.449-470
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• 2016

This paper analyzes the effects of nuclear power generation on industrial growth in using the data of 22 manufacturing sectors in 14 nuclear power countries. The hypothesis that the change in the proportion of nuclear power generation in total electricity generation affects industrial value-added and industrial output through industrial electricity price reduction was tested using the dynamic panel data model. First, it was estimated that the increase in nuclear power generation by a 1% leads to a 0.8% reduction in electricity price. The results indicate that when nuclear power generation increased by a 1% point, industrial value-added and output increased by 0.16% and 0.23%,respectively, in the short-run and by 0.51% and 0.85%, respectively, in the long-run. It was also inferred that the effect of nuclear generation on industrial competitiveness working through electricity price reduction rely on institutional settings in the electricity markets. That is, the competitive effect is greater in the countries such as U.K and Japan where electricity price is high and price volatility is large. Meanwhile, in Germany which has pursued phasing out nuclear power, industrial competitiveness is promoted through stable electricity supply.

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

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.4
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• pp.385-398
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• 2009

This paper aims to find a suitable solution to joint allocation of sub-channel and transmit power for multiple users in an IEEE 802.16e OFDMA/TDD cellular system. We propose the FASA (Fairness insured Aggressive Sub-channel Allocation) algorithm, which is a dynamic channel allocation algorithm that considers all of the users' channel state information conditionally in order to maximize throughput while taking into account fairness. A dynamic power allocation algorithm, i.e., an improved CHC algorithm, is also proposed in combination with the FASA algorithm. It collects the extra downlink transmit power and re-allocates it to other potential users. Simulation results show that the joint allocation scheme with the improved CHC power allocation algorithm provides an additional increase of sector throughput while simultaneously enhancing fairness. Four frames of time delay for CQI feedback and scheduling are considered. Furthermore, by addressing the difference between uplink and downlink scheduling in an IEEE 802.16e OFDMA TDD system, we can employ the uplink channel information directly via channel sounding, resulting in more accurate uplink dynamic resource allocation.

• Journal of the Speleological Society of Korea
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• no.89
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• pp.27-33
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• 2008

Solar energy is most green and clean, unlimited and sustainable energy source on the earth. It is almost 97% of imported consumer energy in Korea. Because of resource poor nation, it is necessary to do their best to make alternative energy to allot their deficiency of the matter in hand of energy resources of petroleum. In a point of view of this problems, the natural solar energy should be improved by any methods as much, possible as we need. Photovoltaic generation with solar tracking system for obtaining optimal power is one of most benefit equipment to improve power of solar-cell panel producing clean electric power efficiently. Solar tracker is a device for orienting a solar photovoltaic panel toward the sun perpendicularly to sunlight, especially in widely separated place. For this reason, we are very interested in developing the equipment system of tracker, specially in solar cell applications, obtaining a high degree of accuracy to ensure that the optimal sunlight could be directed precisely against to the powered device. As a result, it was obtained of 12.46 volts at 90$^\circ$toward solar panel and 9.44 volts at 45$^\circ$, furthermore, improved efficiency more than 30% of average output voltage between tracker system (12.41V) and fixed system (8.55V), respectively. It is also very useful for optimum power system of widely separated cave.