Recently, research activities on the fields of the power system frequency controls are increasing, especially in connection with the deregulation of power systems. The main contribution to the generation controls required for the frequency controls comes from the thermal power plants with steam boilers. This article presents the fundamental features of MW response of the thermal power plants to be considered in dynamic simulations of the frequency controls, after reviewing the basis of the frequency controls in normal conditions of power systems. The features of the MW response are described in the aspects EDC operation, LFC operation and governor speed-droop operation.
This paper presents a daily peak load forecasting method using an analyzable structured neural network (ASNN) in order to explain forecasting reasons. In this paper, we propose a new training method for ASNN in order to explain forecasting reason more properly than the conventional training method. ASNN consists of two types of hidden units. One type of hidden units has connecting weights between the hidden units and only one group of related input units. Another one has connecting weights between the hidden units and all input units. The former type of hidden units allows to explain forecasting reasons. The latter type of hidden units ensures the forecasting performance. The proposed training method make the former type of hidden units train only independent relations between the input factors and output, and make the latter type of hidden units train only complicated interactions between input factors. The effectiveness of the proposed neural network is shown using actual daily peak load. ASNN trained by the proposed method can explain forecasting reasons more properly than ASNN trained by the conventional method. Moreover, the proposed neural network can forecast daily peak load more accurately than conventional neural network trained by the back propagation algorithm.
Recently, the independent power producers (IPPs) and the distributed power generations (DGs) are increase on by the electric power system with the power system deregulation. And the power system becomes more complicated. It is necessary to carry out the electric power demand forecasting in order to the power system is operated for the high economical and the high-efficient. For the improvement of electric power demand forecasting, many methods, such as the methods using fuzzy theory, neural network and SDP data, are proposed. In this paper, we proposed the method using STROGANOFF (STructured Re-presentation on Genetic Algorithms for Non-linear Function Fitting) that approximate the value of predictive to the future data by the past data is obtained. Also, the weather condition was considered for the forecasting that is improvement, and the daily peak load forecasting in next day on Chubu district in Japan was carried out, and the effectiveness of proposed method was examined.
In this paper, we pay attention to the superior operating control function and instantaneous discharging characteristics of NAS battery systems, and propose a method for determining installation planning and operating control schemes of NAS battery systems for suppressing line overload phenomena. In the stage of planning, a target contingency is identified, and an optimal allocation and capacity of NAS battery systems and an amount of generation changes are determined for the contingency. In the stage of operation, the control strategy of NAS battery system is determined. Simulations are carried out for verifying the validity of the proposed method using the IEEJ 1 machine V system model and an example 2 machine 16 bus system model.
This paper proposes two-layered neighborhood tabu search for determining the optimal allocation and output of D-FACTS device in a distribution system with uncertain wind power generation. In recent years, wind power generation is positively introduced into distribution systems as clean and inexhaustible distributed generation. However, the distribution system with wind power generation often encounters the reverse flow due to the uncertain output performance of wind power generation. As a result, it is afraid that the voltage variation becomes much larger. In this paper, two-layered neighborhood tabu search is proposed to determine the optimal allocation and output of D-FACTS devices. To consider the uncertainty of wind power generation, this paper carries out the Monte-Carlo simulation to evaluate the probabilistic voltage assessment in the distribution system with uncertain wind power generation. The proposed method is successfully applied to a sample system.
In this paper, a new efficient feature extraction method is proposed to handle the one-step ahead daily maximum load forecasting. In recent years, power systems become more complicated under the deregulated and competitive environment. As a result, it is not easy to understand the cause and effect of short-term load forecasting with a bunch of data. This paper analyzes load data from a standpoint of data mining. By it we mean a technique that finds out rules or knowledge through large database. As a data mining method for load forecasting, this paper focuses on the regression tree that handles continuous variables and expresses a knowledge rule as if-then rules. Investigating the variable importance of the regression tree gives information on the transition of the load forecasting models. This paper proposes a feature extraction method for examining the variable importance. The proposed method allows to classify the transition of the variable importance through actual data.
In this study, the autonomous decentralized voltage control method of distribution network is described. Distribution network with distributed generation has a complicated structure and it needs to be controlled with autonomous system. For the proper control of the system, the voltage profile control method using multi agent system is discussed in this study. The proposed method is tested by simulation study on the demand area power system. It is shown that the method is effective for maintaining the voltage profile.
Due to the advancement of information technology and widespread use of power electronic devices in recent years, many customers in various fields have suffered from the voltage sag problem. In order to compensate voltage sags, sensitive loads have been primarily equipped with uninterruptible power supplies (UPS) by each consumer individually. Because consumers have many individual needs, this topic becomes an important problem to be considered by quality consultants in the electric utility industry. Based on this situation, we present the applications of UPS and dynamic voltage restorer (DVR) as compensation devices of voltage sags. By considering the need for power quality, we examine the cost-efficiency of both devices quantitatively. Simulations are carried out and the results are shown in this paper.
Service restoration problem in distribution systems is formulated as a multi-objective optimization problem which is demanded not only for minimizing the amount of unrestored total loads but also for minimizing the number of the switching operations. The solution of the multi-objective optimization problem is usually obtained with a set of Pareto optimal solutions. The Pareto optimal solutions for the service restoration problem are useful for users to obtain their desired restoration by comparing a Pareto optimal solution with the others. However, the conventional methods cannot obtain plural Pareto optimal solutions in one trial. Therefore, this paper proposes a method for obtaining a Pareto optimal set for the service restoration problem with a genetic algorithm. The genetic algorithm produces many possible solutions in its search process. By utilizing this feature, the proposed method can obtain the Pareto optimal set.
The player in deregulated electricity markets can be categorized into three groups of GENCO (Generator Companies), TRNASCO (Transmission Companies), DISCO (Distribution Companies). This research focuses on the role of Distribution Companies, which purchase electricity from market at randomly fluctuating prices, and provide it to their customers at given fixed prices. Therefore Distribution companies have to take the risk stemming from price fluctuation of electricity instead of the customers. This entails the necessity to develop a certain method to make an optimal strategy for electricity procurement. In such a circumstance, this research has the purpose for proposing the mathematical method based on stochastic dynamic programming to evaluate the value of a long-term bilateral contract of electricity trade, and also a project of combination of the bilateral contract and power generation with their own generators for procuring electric power in deregulated market.
In modern power systems, it is important to analyze various kindes of dynamic phenomena which appear in the system. When the effectiveness of new power electronics based apparatus, protective relay systems and etc. is tested, a real-time power system simulator is becoming a very effective tool. In general, however, it is very expensive and it is very difficult for beginners to understand how to use it. Therefore, studies on low-cost and easy-use real-time power system simulators have so far been done. We have developed models of power system components for the real-time power system simulator using DSP (Digital Signal Processor) combined with commercial CAD (Computer Aided Design) soft "MATLAB/SIMULINK". The use of commercial softwares can drastically decrease the development cost of the simulator. In this paper, a simplified reduction model of unbalanced three-phase transmission network with mutual impedance is proposed for analysis of various kinds of stability phenomena by use of the digital simulator. The proposed network model is constructed automatically and efficiently even for connection of both current source type models and voltage source type models of power apparatus such as generators, FACTS devices and loads.
This paper presents analyses on the penetration of polymer electrolyte fuel cells (PEFC) into a group of 10 residential houses and its effects of CO2 emission mitigation and consumers’ cost reduction in next 30 years. The price is considered to be reduced as the penetration progress which is expected to begin in near future. An experimental curve is assumed to express the decrease of the price. Installation of energy interchange systems which involve electricity, gas and hydrogen between a house which has a FC and contiguous houses is assumed to utilize both electricity and heat more efficiently, and to avoid start-stop operation of fuel processor (reformer) as much as possible. A multi-objective model which considers CO2 mitigation and consumers’ cost reduction is constructed and provided a Pareto optimum solution. A solution which simultaneously realizes both CO2 mitigation and consumers’ cost reduction appeared in the Pareto optimum solution. Strategies to reduce CO2 emission and consumers’ cost are suggested from the results of the analyses. The analyses also revealed that the energy interchange systems are effective especially in the early stage of the penetration.
Modeling was made of Ar induction thermal plasma with an injection of PTFE powder to study fundamentally the effects of polymer ablation on thermal plasma. Interactions between thermal plasma and PTFE powder such as heat conduction, melting, evaporation and radiation was simply taken into account. At the same, the behavior of particle in the plasma was also investigated. The predicted results shows that the injection of PTFE powder can cause the local cooling of Ar thermal plasma temperature field, and that increasing powder feed-rate decreases plasma temperature around torch central axis. Moreover, it was seen that smaller powder size decays plasma much more. On the other hand, it is found that particle trajectory as well as temperature history relate to powder loading, powder size and injection location of particle. This calculated result concerning plasma temperature was compared with the experimental result.
This paper will principally describe about the PV array simulation tool. This PV array simulation tool is available to estimate the output power of the PV array with difference azimuth and orientation for the maximum of four surfaces. This tool analyses the daily, monthly or annual output power with high accuracy because of using the I-V characteristic. The analysis is based on simplified I-V curve interpolation considering the characteristics of each module in the PV array. The shortest interval time of calculation is one second.
A PV system’s output is not stable and fluctuates depending on a weather condition. Using a battery is one of the feasible ways to stabilize a PV system’s output, although it requires an additional cost and provides an additional waste of the used battery. In this paper, we propose tuning a characteristic of Maxiumum Power Point Tracking (MPPT) control for smoothing a short term change of PV system’s output during a sharp insolation fluctuation, as an approach without additional equipments. In our proposed method, when an insolation increases rapidly, the operation point of MPPT control changes to the new point where the maximum power is not generated with present insolation, so that the speed of PV system’s output increase is limited to a certain value, i. e. 1%/min. In order to evaluate the effect of our proposed method in terms of reducing the additional operation task of the electric power system, we evaluated the additional LFC capacity for a large-scale installation of PV systems. As a result, it was revealed that the additional LFC capacity is not required even if a PV system is installed by 5% of utility system, when our proposed method is applied to all PV systems.
The EMTP is widely used for lightning surge analysis. As for transmission lines, they have studied lighting outage performance of transmission line by the EMTP. In the EMTP analysis, grounding resistance of a tower is usually modeled as a constant resistance model, however it is known that soil ionization sometimes occurs by high currents such as a lightning stroke. Therefore we have developed a grounding resistance model with soil ionization characteristics for the EMTP analysis. In this paper, we analyze an outage of an existing transmission line so that we investigate the effect of a grounding resistance model with soil ionization characteristics.
Fundamental properties of CO2 gas, as an alternative arc quenching medium of SF6 gas, in a puffer-type gas circuit breaker were investigated theoretically and experimentally, focusing particularly on its thermal interruption performance. It was found that utilizing arc energy for enhancing puffer pressure is a good solution to construct a CO2 gas circuit breaker due to the physical properties of CO2 gas. Based on these fundamental investigations, the 72kV-31.5kA-class CO2 gas circuit breaker model, which does not contain SF6 gas at all, was designed, manufactured, and tested. As a result, the CO2 gas circuit breaker model achieved the specified interruption performance for short line fault.
Adopting CO2 as an alternative gas of SF6 in a gas circuit breaker from the environmental viewpoint, a 72kV-31.5kA class CO2 gas circuit breaker (CO2-GCB) model, which does not contain SF6 gas at all, was designed, and produced. In the CO2-GCB model, some effective technologies for current interruption by CO2 gas were adopted; namely, puffer pressure enhancing techniques utilizing arc energy during a current interruption and ablation phenomena of a polymer element located in the puffer cylinder. As a result of current interruption and electric insulation tests, the CO2-GCB model achieved practical levels of performance. Furthermore, it was found by carrying out a life cycle assessment (LCA) that the CO2-GCB model could reduce the global warming impact by about 40% compared to the latest SF6 gas circuit breaker in the same rating for 20 years operation including one maintenance opportunity.
Since PEFC (Polymer Electrolyte Fuel Cell) can produce electricity at high power density with a simple stack constitution, PEFC is expected to be applied to electric vehicles and to distributed power sources. In these applications, PEFC may be operated at a wide range of load and may have frequent starts and stops. Therefore it is important to elucidate the transient characteristics of PEFC. In this study, we made a mathematical model to predict the transient behavior of PEFC, considering an equivalent electric circuit and a mass conservation equation. Important physical properties, such as proton conductivity and double-layer capacitance of polymer electrolyte membrane were measured to be incorporated into the model. By using the model, we calculated the response of cell potential to a rapid change of load current, and compared the numerical calculation with the experimental result. After the rapid change of load current, the cell potential varies in 10-1s accompanied by the charge and discharge of the electric double layer capacitance, and then it changes in 101s by the re-distribution of water in the polymer electrolyte membrane.
As a research aiming at obtaining basic information useful for the development of maintenance-free insulation, the status quo and trends of insulation monitoring and diagnosis methods for electric power apparatus that have been done in Japan are analyzed by reviewing about 8800 reports published for the last 50 years. It is found that the accuracy of monitoring and diagnosis has been improved well and unmanned monitoring and diagnosis have been developed significantly with the introduction of measurement systems using sophisticated computer-aided analyzing and fiber-optic monitoring techniques. Further implementation of such sophisticated methods in the whole area of insulation monitoring and diagnosis should even increase the total reliability of power apparatus, which will undoubtedly reduce the necessary personnel and costs to maintain the apparatus.