• Proceedings of the Safety Management and Science Conference
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• 2012.11a
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• pp.461-471
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• 2012

Most useful statistical techniques in six sigma DMAIC are hypothesis testing and interval estimation. So this paper reviews and derives sample size formula by considering significance level, power of detectability and effect difference. The quality practioners can effectively interpret the practical and statistical significance with the rational sample sizing.

• Nuclear Engineering and Technology
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• v.46 no.6
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• pp.737-752
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• 2014

As condition-based maintenance (CBM) has risen as a new trend, there has been an active movement to apply information technology for effective implementation of CBM in power plants. This motivation is widespread in operations and maintenance, including monitoring, diagnosis, prognosis, and decision-making on asset management. Thermal efficiency analysis in nuclear power plants (NPPs) is a longstanding concern being updated with new methodologies in an advanced IT environment. It is also a prominent way to differentiate competitiveness in terms of operations and maintenance costs. Although thermal performance tests implemented using industrial codes and standards can provide officially trustworthy results, they are essentially resource-consuming and maybe even a hind-sighted technique rather than a foresighted one, considering their periodicity. Therefore, if more accurate performance monitoring can be achieved using advanced data analysis techniques, we can expect more optimized operations and maintenance. This paper proposes a framework and describes associated methodologies for in-situ thermal performance analysis, which differs from conventional performance monitoring. The methodologies are effective for monitoring, diagnosis, and prognosis in pursuit of CBM. Our enabling techniques cover the intelligent removal of random and systematic errors, deviation detection between a best condition and a currently measured condition, degradation diagnosis using a structured knowledge base, and prognosis for decision-making about maintenance tasks. We also discuss how our new methods can be incorporated with existing performance tests. We provide guidance and directions for developers and end-users interested in in-situ thermal performance management, particularly in NPPs with large steam turbines.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2446-2448
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• 2001

In addition to the stabilization of electricity supply and the quality management of electricity, load balance has been an important strategy for achieving high quality load management. Among many techniques for load management, direct load management has been actively studied and applied for increasing the efficiency of power facility and suppressing peak load. In Korea, the highest peak load is demanded in summer rather than in winter, and almost 50% of the peak load comes from cooling load. Currently, applicable systems are limited to air conditioners that have the cooling capacity less than 2kW. This paper describes the development of remote controlled air conditioners and the result of the field test of the new type air conditioner. The technical specification based on the test will be applied to the new model of the remote controlled air conditioner. The wide distribution of the air conditioners to the public will be helpful to control peak demand due to cooling load in summer time. Financial investment to generating, transmission, distribution facilities will be decreased from flatting the seasonal power load.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.58 no.4
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• pp.505-510
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• 2009

In this paper, building energy analysis and energy cost of power stand up and demand control over the power proposed to reduce power demand. Through analysis of the load power demand special day were able to apply the pattern. In addition, the existing rate of change of load forecasting to reduce the large errors were not previously available data. And daily schedules and special day for considering the exponential smoothing methods were used. Previous year's special day and the previous day due to the uncertainty of the load and the model components were considered. The maximum demand power control simulation using the fuzzy control of power does not exceed the contract. Through simulation, the benefits of the proposed energy-saving techniques were demonstrated.

• ETRI Journal
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• v.19 no.3
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• pp.98-115
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• 1997

The architecture of the CDMA mobile system (CMS) is developed based on three function groups - service resource, service control, and service management groups. In this paper, the CMS architecture is discussed from the point of view of implementing these functions. The variable length packets are used for transmission. The synchronization clock signals are derived form the GPS receiver. The open loop and closed loop techniques are used for the power control. The internationally accepted signaling and network protocols are employed. The call control for the primary services in designed to provide efficient mobile telecommunication services. The softer handoff is implemented in one card. The mobile assisted handoff and the network assisted handoff are employed in the soft and hard handoffs. The authentication is based on the secret data which includes random numbers. The management functions, which include the location management, resource management, cell boundary management and OAM management, are implemented to warrant the system efficiency, maximum capacity and high reliability. The architecture ensures that the CMS is flexible and expandable to provide subscribers with economic and efficient system configuration. The dynamic power control, adaptive channel allocation. and dynamic cell boundary management are recommended for future work.

• Journal of Korea Society of Digital Industry and Information Management
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• v.4 no.3
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• pp.77-83
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• 2008

In this paper, CPLD low power technology mapping for reuse module design under the time constraint is proposed. Traditional high-level synthesis do not allow reuse of complex, realistic datapath component during the task of scheduling. On the other hand, the proposed algorithm is able to approach a productivity of the design the low power to reuse which given a library of user-defined datapath component and to share of resource sharing on the switching activity in a shared resource. Also, we are obtainable the optimal the scheduling result in experimental results of our using chaining and multi-cycling in the scheduling techniques. Low power circuit make using CPLD technology mapping algorithm for selection reuse module by scheduling.

• Proceedings of the Korean Society for Quality Management Conference
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• 1998.11a
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• pp.393-403
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• 1998

The advent of very large scale integration(VLSI) has had a tremendous impact on the design of fault-tolerant circuits and systems. The increasing density, decreasing power consumption, and decreasing costs of integrated circuits, due in part to VLSI, have made it possible and practical to implement the redundancy approaches used in fault-tolerant computing. The purpose of this paper is to study the many aspects of designing fault-tolerant systems in a VLSI environment. First, we expound upon the opportunities and problemes presented by VLSI technology. Second, we consider in detail the importance of design mistakes, common-mode failures, and transient faults in VLSI. Finally, we examine the techniques available to implement redundancy using VLSI and the problems associated with these techniques.

• Korean Journal of Artificial Intelligence
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• v.12 no.1
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• pp.17-24
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• 2024

This paper introduces a novel approach to time-series estimation for energy load forecasting within Virtual Power Plant (VPP) systems, leveraging advanced artificial intelligence (AI) algorithms, namely Long Short-Term Memory (LSTM) and Seasonal Autoregressive Integrated Moving Average (SARIMA). Virtual power plants, which integrate diverse microgrids managed by Energy Management Systems (EMS), require precise forecasting techniques to balance energy supply and demand efficiently. The paper introduces a hybrid-method forecasting model combining a parametric-based statistical technique and an AI algorithm. The LSTM algorithm is particularly employed to discern pattern correlations over fixed intervals, crucial for predicting accurate future energy loads. SARIMA is applied to generate time-series forecasts, accounting for non-stationary and seasonal variations. The forecasting model incorporates a broad spectrum of distributed energy resources, including renewable energy sources and conventional power plants. Data spanning a decade, sourced from the Korea Power Exchange (KPX) Electrical Power Statistical Information System (EPSIS), were utilized to validate the model. The proposed hybrid LSTM-SARIMA model with parameter sets (1, 1, 1, 12) and (2, 1, 1, 12) demonstrated a high fidelity to the actual observed data. Thus, it is concluded that the optimized system notably surpasses traditional forecasting methods, indicating that this model offers a viable solution for EMS to enhance short-term load forecasting.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.820-831
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• 2015

In a deregulated electricity market, congestion of the transmission lines is a major problem the independent system operator (ISO) would face. Rescheduling of generators is one of the most practiced techniques to alleviate the congestion. However, not all generators in the system operate deterministically and independently, especially wind power generators (WTGs). Therefore, a novel optimal rescheduling model for congestion management that accounts for the uncertain and correlated power sources and loads is proposed. A probabilistic power flow (PPF) model based on 2m+1 point estimate method (PEM) is used to simulate the performance of uncertain and correlated input random variables. In addition, the impact of direct electricity purchase contracts on the congestion management has also been studied. This paper uses artificial bee colony (ABC) algorithm to solve the complex optimization problem. The proposed algorithm is tested on modified IEEE 30-bus system and IEEE 57-bus system to demonstrate the impacts of the uncertainties and correlations of the input random variables and the direct electricity purchase contracts on the congestion management. Both pool and nodal pricing model are also discussed.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.66 no.1
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• pp.33-37
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• 2017

This paper describes the modeling of the failure rate estimation technique for applying the asset management technique to electric power facilities. There are many modeling techniques to estimate the failure rate. In this paper, the characteristics of the normal distribution, exponential distribution, weibull distribution, and piecewise linear functions are discussed. When evaluating reliability, the evaluation may be less meaningful if the sample data is insufficient. Therefore, Weibull distribution and piecewise linear function are adopted as the most suitable functions for estimating the failure rate of power facilities and the resulting failure rate function is derived.