This paper presents a novel method for satisfying the thermal comfort of indoor environment and reducing the summer peak demand power by minimizing the power consumption for an Air-conditioner within a space. Korea Electric Power Corporation (KEPCO) use the fixed duty cycle control method regardless of the indoor thermal environment. However, this method has disadvantages that energy saving depends on the set-point value of the Air-Conditioner and direct load control (DLC) has no net effects on Air-conditioners if the appliance has a lower operating cycle than the fixed duty cycle. In this paper, the variable duty cycle control method is proposed in order to compensate the weakness of conventional fixed duty cycle control method and improve the satisfaction of residents and the reduction of peak demand. The proposed method estimates the predict mean vote (PMV) at the next step with predicted temperature and humidity using the back propagation neural network model. It is possible to reduce the energy consumption by maintaining the Air-conditioner's OFF state when the PMV lies in the thermal comfort range. To verify the effectiveness of the proposed variable duty cycle control method, the case study is performed using the historical data on Sep. 7th, 2001 acquired at a classroom in Seoul and the obtained results are compared with the fixed duty cycle control method.

Generally, the training set of maximum $m{\times}L(m+f)$ patterns in the pattern recognition method is required for the real-time bus reconfiguration strategy when a main transformer fault occurs in the distribution substation. Accordingly, to make the application of pattern recognition method possible, the size of the training set must be reduced as efficient level. This Paper proposes a methodology which obtains the minimized training set by applying the pattern clustering method to load patterns of the main transformers and feeders during selected period and to obtain bus reconfiguration strategy based on it. The MaxMin distance clustering algorithm is adopted as the pattern clustering method. The proposed method reduces greatly the number of load patterns to be trained and obtain the satisfactory pattern matching success rate because that it generates the typical pattern clusters by appling the pattern clustering method to load patterns of the main transformers and feeders during selected period. The proposed strategy is designed and implemented in Visual C++ MFC. Finally, availability and accuracy of the proposed methodology and the design is verified from diversity simulation reviews for typical distribution substation.

This paper describes a simulation package for a power system using objected-oriented programming. The package includes four parts which are a power flow, a short circuit calculation, a transient simulation program, and an economic dispatch. The graphical user interface(GUI) is designed as a common platform which allows the user to create one-line diagrams of systems, specify components of power systems as well as simulation parameters, and view the output produced by the chosen application. The paper presents the data structure of the functional modules such as the draw module, power system data module, the power system simulation module, and the utility module using the object oriented programming. This package may be useful for educational and research purposes.

This paper describes the concepts of Static Line Rating (SLR) and Dynamic Line Rating (DLR) and the computational methods to demonstrate them. Calculation of the line capacity needs the heat balance equation which is also used for computing the reduced tension in terms of line aging. SLR is calculated with the data from the worst condition of weather throughout the year. Even now, the utilization ratio is obtained from this SLR data in Korea. DLR is the improved method compared to SLR. A process for DLR reveals not only improved line ratings but also more accurate allowed line ratings based on line aging and real time conditions of weather. In order to reflect overhead transmission line aging in DLR, this paper proposes the method that considers the amount of decreased tension since the lines have been installed. Therefore, the continuous allowed temperature for remaining life time is newly acquired. In order to forecast DLR, this paper uses weather forecast models, and applies the concept of Thermal Overload Risk Probability (TORP). Then, the new concept of Dynamic Utilization Ratio (DUR) is defined, replacing Static Utilization Ratio (SUR). For the case study, the two main transmission lines which are responsible for the north bound power flow in the Seoul metropolitan area are chosen for computing line rating and utilization ratio. And then line rating and utilization ratio are analyzed for each transmission line, so that comparison of the present and estimated utilization ratios becomes available. Finally, this paper proves the validity of predictive DUR as the objective index, with simulations of emergency state caused by system outages, overload and so on.

This paper describes the characteristic evaluation of 154kV lightning arrester developed by domestic technology. To prove the protective ability of lightning arrester developed, various overvoltages were analyzed for A and B arrester were being used now at 154kV air and gas insulation substation, and for arrester developed. The results obtained by the various simulations show that the developed arrester has the effective protective ability and reducing ability of the overvoltage as A and B arrester, nevertheless there are somewhat differences among three kinds of arresters. Accordingly, it is evaluated that the arrester developed by domestic technology secured reliability can be installed actually at 154kV substation. In this paper, EMTP/ATP was used for simulation.

As an electricity industry transforms into a competitive system, an electricity market revolves into a combined market consisting of generation and operating reserve. This paper presents a market model combined by an energy market and an operating reserve market. In a competitive structure, Gencos strive to choose strategic bidding parameters that maximize total profit resulting from an energy market and a reserve market. The primary goal of the paper is to analyze power transactions of generation and operation reserve based on marginal profits and capacity limits at NE(Nash Equilibrium). In case studies, the reserve market and the energy market are compared at the n from the viewpoints of marginal profits, prices and transaction quantities. It is shown that the marginal profit in an energy market is equal to that in a reserve market, and Gencos strategic bidding is greatly influenced by capacity limit.