• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.63 no.7
• /
• pp.867-874
• /
• 2014

The pumped storage power plants have excellent load following characteristics. It can also be committed quickly for synchronous reserve when it is in the generating mode because it can readily increase its generating power and, consequently, increases the overall system reliability. There are strong incentives for standing the system reliability. Additionally, $CO_2$ emission can be typically impacted due to operation of pumped generators. The increase or decrease of $CO_2$ depends on the generation mix. This paper proposes evaluation of reliability, economy and environment of power system considering pumped generator. This paper describes three case studies of the reliability and economy and environment according to capacity factor and storage capacity of pumped generators. The probabilistic production simulation model is used in this paper. The practicality and effectiveness of the proposed approach are demonstrated by simulation studies for a real size power system model on the $5^{th}$ power plan in Korea.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.37 no.2
• /
• pp.21-30
• /
• 2000

If there exists a model that calculates the proper candidate position whenever the game of Go is in progress, it can be used for setting up the prototype of the candidate generation algorithm without using case-based reasoning. In this paper, we analyze Go through combinatorial game theory and on the basis of probability matrix (PM) showing the difference of the territory of the black and the white. We design and implement a candidate generation system(CGS) to find the candidates at a situation in Go. CGS designed in this paper can compute Influence power, safety, probability value(PV), and PM and then generate candidate positions for a present scene, once a stone is played at a scene. The basic strategy generates five candidates for the Present scene, and then chooses one with the highest PV. CGS generates the candidate which emphasizes more defence tactics than attack ones. In the opening game of computer Go, we can know that CGS which has no pattern is somewhat superior to NEMESIS which has the Joseki pattern.

• Structural Engineering and Mechanics
• /
• v.73 no.3
• /
• pp.339-351
• /
• 2020

Earthquakes are natural disasters that cause serious social disruptions and economic losses. In particular, they have a significant impact on critical lifeline infrastructure such as urban water transmission networks. Therefore, it is important to predict network performance and provide an alternative that minimizes the damage by considering the factors affecting lifeline structures. This paper proposes a probabilistic reliability approach for post-hazard flow analysis of a water transmission network according to earthquake magnitude, pipeline deterioration, and interdependency between pumping plants and 154 kV substations. The model is composed of the following three phases: (1) generation of input ground motion considering spatial correlation, (2) updating the revised nodal demands, and (3) calculation of available nodal demands. Accordingly, a computer code was developed to perform the hydraulic analysis and numerical modelling of water facilities. For numerical simulation, an actual water transmission network was considered and the epicenter was determined from historical earthquake data. To evaluate the network performance, flow-based performance indicators such as system serviceability, nodal serviceability, and mean normal status rate were introduced. The results from the proposed approach quantitatively show that the water network is significantly affected by not only the magnitude of the earthquake but the interdependency and pipeline deterioration.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.59 no.1
• /
• pp.26-32
• /
• 2010

This paper proposes a new effective installed reserve rate in order to evaluate reliability of power system considering renewable generators, which include uncertainty of resource supply. It is called EIRR(effective installed reserve rate) in this paper. It is developed with considering capacity credit based on ELCC by using LOLE reliability criterion. While the conventional installed reserve rate index yields over-evaluation reliability of renewable generators, the proposed EIRR describes actual effective installed reserve rate. However, it is not the probabilistic reliability index as like as LOLE or EENS but another deterministic effective reliability index. The proposed EIRR is able to evaluate the realistic contribution to the reliability level for power system considering wind turbine generators and solar cell generators with high uncertainty in resource supply. The case study in model system as like as Jeju power system size presents a possibility that the proposed EIRR can be used practically as a new deterministic reliability index for generation expansion planning or operational planning in future.

• Earthquakes and Structures
• /
• v.18 no.1
• /
• pp.45-56
• /
• 2020

The application of critical excitation method with displacement-based objective function for multi degree of freedom (MDOF) systems is investigated. To this end, a new critical excitation method is developed to find the critical input motion of a MDOF system as a synthetic accelerogram. The upper bound of earthquake input energy per unit mass is considered as a new constraint for the problem, and its advantages are discussed. Considering this constraint, the critical excitation method is then used to generate synthetic accelerograms for MDOF models corresponding to three shear buildings of 10, 16, and 22 stories. In order to demonstrate the reliability of generated accelerograms to estimate dynamic response of the structures, three target ground motions with considerable level of energy contents are selected to represent "real critical excitation" of each model, and the method is used to re-generate these ground motions. Afterwards, linear dynamic analyses are conducted using these accelerograms along with the generated critical excitations, to investigate the key parameters of response including maximum displacement, maximum interstory drift, and maximum absolute acceleration of stories. The results show that the generated critical excitations can make an acceptable estimate of the structural behavior compared to the target ground motions. Therefore, the method can be reliably implemented to generate critical excitation of the structure when real one is not available.

• Journal of Korea Game Society
• /
• v.8 no.1
• /
• pp.79-90
• /
• 2008

This paper describes a motivation-based hierarchical behavior planning framework to allow autonomous agents to select adaptive actions in simulation game environments. The combined behavior planning system is formed by four levels of specification, which are motivation extraction, goal list generation, action list determination and optimization. Our model increases the complexity of virtual human behavior planning by adding motivation with sudden and cumulative attributes. The motivation selection by probability distribution allows NPC to make multiple decisions in certain situations in order to embody realistic virtual humans. Hierarchical goal tree enhances the effective reactivity. Optimizing for potential actions provides NPC with safe and satisfying actions to adapt to the virtual environment. A restaurant simulation game was used to elucidate the mechanism of the framework.

• The Journal of Korea Robotics Society
• /
• v.16 no.2
• /
• pp.94-102
• /
• 2021

This study addresses a method for 3D reconstruction using acoustic data with heterogeneous sonar devices: Forward-Looking Multibeam Sonar (FLMS) and Profiling Sonar (PS). The challenges in sonar image processing are perceptual ambiguity, the loss of elevation information, and low signal to noise ratio, which are caused by the ranging and intensity-based image generation mechanism of sonars. The conventional approaches utilize additional constraints such as Lambertian reflection and redundant data at various positions, but they are vulnerable to environmental conditions. Our approach is to use two sonars that have a complementary data type. Typically, the sonars provide reliable information in the horizontal but, the loss of elevation information degrades the quality of data in the vertical. To overcome the characteristic of sonar devices, we adopt the crossed installation in such a way that the PS is laid down on its side and mounted on the top of FLMS. From the installation, FLMS scans horizontal information and PS obtains a vertical profile of the front area of AUV. For the fusion of the two sonar data, we propose the probabilistic approach. A likelihood map using geometric constraints between two sonar devices is built and a monte-carlo experiment using a derived model is conducted to extract 3D points. To verify the proposed method, we conducted a simulation and field test. As a result, a consistent seabed map was obtained. This method can be utilized for 3D seabed mapping with an AUV.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.45 no.1
• /
• pp.1-9
• /
• 2022

The PoN (Proof of Nonce) distributed consensus algorithm basically uses a non-competitive consensus method that can guarantee an equal opportunity for all nodes to participate in the block generation process, and this method was expected to resolve the first trilemma of the blockchain, called the decentralization problem. However, the decentralization performance of the PoN distributed consensus algorithm can be greatly affected by the network transaction transmission delay characteristics of the nodes composing the block chain system. In particular, in the consensus process, differences in network node performance may significantly affect the composition of the congress and committee on a first-come, first-served basis. Therefore, in this paper, we presented a problem by analyzing the decentralization performance of the PoN distributed consensus algorithm, and suggested a fairness control algorithm using a learning-based probabilistic acceptance rule to improve it. In addition, we verified the superiority of the proposed algorithm by conducting a numerical experiment, while considering the block chain systems composed of various heterogeneous characteristic systems with different network transmission delay.

• Journal of Korea Water Resources Association
• /
• v.32 no.3
• /
• pp.265-279
• /
• 1999

In this study, one of the techniques on the extension of low flow series has been developed, in which the daily streamflows were simulated by the Tank model with the input of extended daily rainfall series which were stochastically generated by the Markov chain model. The annual lowest flow serried for each of the given durations were formulated form the simulated daily streamflow sequences. The frequency of the estimated annual lowest flow series was analyzed. The distribution types to be used for the frequency analysis were two-parameter and three-parameter log-normal distribution, two-parameter and three-parameter Gamma distribution, three-parameter log-Gamma distribution, Gumbel distribution, and Weibull distribution, of which parameters were estimated by the moment method and the maximum likelihood method. The goodness-of-fit test for probability distribution is evaluated by the Kolmogorov-Sminrov test. The fitted distribution function for each duration series is applied to frequency analysis for developing duration-low flow-frequency curves at Yongdam Dam station. It was shown that the purposed technique in this study is available to generate the daily streamflow series with fair accuracy and useful to determine the probabilistic low flow in the watersheds having the poor historic records of low flow series.

• Journal of Korean Society on Water Environment
• /
• v.33 no.2
• /
• pp.140-148
• /
• 2017

An important factor in determining the design and treatment efficiency of wastewater treatment plants (WWTPs) is the quantity and quality of influent. These detailed and accurate information is essential for process control, diagnosis and operation, as well as the basis in designing the plant, selecting the process and determining the optimal capacity of each bioreactor. Probabilistic models are used to predict the wastewater quantity and quality of WWTPs, which are widely used to improve the design and operation of WWTPs. In this study, the optimal probability distribution of time series influent data was derived for predicting water quantity and quality, and wastewater influent data were generated using the Monte Carlo simulation analysis. In addition, we estimated various alternatives for the improvement of bioreactor operations based on present operation condition using the generated influent data and activated sludge model, and suggested the alternative that can operate the most effectively. Thus, the influent quantity and quality are highly correlated with the actual operation data, so that the actual WWTPs influent characteristics were well reproduced. Using this will improve the operating conditions of WWTPs, and a proposed improvement plan for the current TMS (Tele Monitoring System) effluent quality standards can be made.