Load forecasting is essential in the electricity market for the participants to manage the market efficiently and stably. A wide variety of techniques/algorithms for load forecasting has been reported in many literatures. These techniques are as follows: multiple linear regression, stochastic time series, general exponential smoothing, state space and Kalman filter, knowledge-based expert system approach (fuzzy method and artificial neural network). These techniques have improved the accuracy of the load forecasting. In recent 10 years, many researchers have focused on artificial neural network and fuzzy method for the load forecasting. In this paper, we propose an algorithm of a hybrid load forecasting method using fuzzy linear regression and general exponential smoothing and considering the sensitivities of the temperature. In order to consider the lower load of weekends and Monday than weekdays, fuzzy linear regression method is proposed. The temperature sensitivity is used to improve the accuracy of the load forecasting through the relation of the daily load and temperature. And the normal load of weekdays is easily forecasted by general exponential smoothing method. Test results show that the proposed algorithm improves the accuracy of the load forecasting in 1996.

As power demand increases gradually, the call for underground transmission system increases. But it is very difficult and high in cost to construct new ducts and/or tunnels for power cables in metropolitan areas. HTS (High Temperature Superconducting) cable has the several useful characteristics such as increased power density, stronger magnetic fields and/or reduced losses. Therefore HTS cable can allow more power to be moved in existing ducts, which means very large economical and environmental benefits. In these days, companies world-wide have conducted researches on HTS cable. A development project for a 22.9kV class HTS cable is proceeding at a research center and university in Korea. In this paper, we investigate the expected price of HTS cable to have a merit in viewpoint of economic aspect. First, life-cycle cost of conventional cable is calculated and based on this, the expected price of HTS cable is evaluated, which HTS cable is competitive against conventional cable.

The conventional fault location algorithms based on the travelling waves have an inherent problem. In cases of the close-up faults occurring near the relaying point and of the faults having zero degree inception angle of voltage signals, the conventional algorithms can not estimate an accurate fault distance. It is because the shapes of travelling waves are near sinusoidal in those cases. A new method solving this problem is presented in this paper. An FIR(Finite Impulse response) filter which makes high frequency components prominent and makes the power frequency component and dc-offset attenuated is used. With this method, the cross-correlation peak is to be very clear when a close-up fault or a fault having near zero-degree inception angle occurs. The cross-correlation peaks can be clearly distinguished and accurate fault location is practically possible consequently. A series of simulation studies using EMTP(Electromagnetic Transients Program) show that the proposed algorithm can calculate an accurate fault distance having maximum 2% or less error.

Fault section isolation and service restoration are very important for function of DAS. In Japan, a progressive protection method is used for the line to ground fault section isolation and service restoration. But the progressive protection method has a drawback that the customer will experience outage time and that the rate in use of the feeder is not over 50%. This paper presents a new Service Restoration Algorithm which is for the line to ground fault section isolation and service restoration method for a ungrounded distribution system. If the proposed algorithm is used, the rate in use of the feeder can improve than before because a distribution system can change multi connection of feeder and the customer's outage time can be reduced. The proposed algorithm has been successfully tested in a distribution system.

This paper presents an application of parallel Genetic Algorithm-Tabu Search(GA-TS) algorithm to search an optimal solution of a reconfiguration in distribution system. The aim of the reconfiguration of distribution systems is to determine switch position to be opened for loss minimization in the radial distribution systems, which is a discrete optimization problem. This problem has many constraints and very difficult to solve the optimal switch position because it has many local minima. This paper develops parallel GA-TS algorithm for reconfiguration of distribution systems. In parallel GA-TS, GA operators are executed for each processor. To prevent solution of low fitness from appearing in the next generation, strings below the average fitness are saved in the tabu list. If best fitness of the GA is not changed for several generations, TS operators are executed for the upper 10% of the population to enhance the local searching capabilities. With migration operation, best string of each node is transferred to the neighboring node aster predetermined iterations are executed. For parallel computing, we developed a PC-cluster system consisting of 8 PCs. Each PC employs the 2 GHz Pentium Ⅳ CPU and is connected with others through ethernet switch based fast ethernet. To show the usefulness of the proposed method, developed algorithm has been tested and compared on a distribution systems in the reference paper. From the simulation results, we can find that the proposed algorithm is efficient and robust for the reconfiguration of distribution system in terms of the solution qualify. speedup. efficiency and computation time.

This paper proposes an expert system which can enhance the accuracy of real-time bus reconfiguration strategy by adopting local minimum tree search method and minimize the spreading effect of the fault by considering totally the operating condition when a main transformer fault occurs in the automated substation. The local minimum tree search method to expand the best-first search method. This method has an advantage which can improve the performance of solution within the limits of the real-time condition. The inference strategy proposed expert system consists of two stages. The first stage determines the switching candidate set by searching possible switching candidates starting from the main transformer or busbar related to the event. And, second stage determines the rational real-time bus reconfiguration strategy based on heuristic rules for the obtained switching candidate set. Also, this paper studies the generalized distribution substation modelling using graph theory and a substation database is designed based on the study result. The inference engine of the expert system and the substation database is implemented in MFC function of Visual C++. Finally, the performance and effectiveness of the proposed expert system is verified by comparing the best-first search solution and local minimum tree search solution based on diversity event simulations for typical distribution substation.

A new real-time constrained dispatch scheduling (CDS) is needed for TWBP. The CDS needs to be performed at every dispatch period to decide generation power of scheduling generators and amounts of scheduling load. Therefore, the CDS is not based on real generation costs but on bidding data of market participants with some constraints such as power balance, generation limits, ancillary service, and transmission line limits. This paper selects linear programming(LP) as an optimization tool for the CDS and presents effective formulae for the LP application. This paper also presents the way of minimizing the number of variables and constraints of the LP to improve real-time applicability.