Naohiro Kusumi

Stability theory of universal learning network

Higher order derivatives of the universal learning network (ULN) has been previously derived by forward and backward propagation computing methods, which can model and control the large scale complicated systems such as industrial plants, economic, social and life phenomena. In this paper, a new concept of nth order asymptotic orbital stability for the ULN is defined by using higher order derivatives of ULN and a sufficient condition of asymptotic orbital stability for ULN is derived. It is also shown that if 3rd order asymptotic orbital stability for a recurrent neural network is proved, higher order asymptotic orbital stability than 3rd order is guaranteed.

Auto Tuning Algorithm for Vigilance Parameter in the Adaptive Resonance Theory Model and its Application to Fault Diagnosis System of Thermal Power Plants

In order to operate thermal power plants safely, early detection of equipment failure signs is one of the most important issues. To detect the signs before an alarm is issued in the existing monitoring system, we developed a fault diagnosis system based on the Adaptive Resonance Theory (ART). The vigilance parameter, which is a design parameter in the ART model, was shown to influence the diagnosis accuracy. Fixing the value of the vigilance parameter also had problems: we needed to use time-consuming trial and error, and we needed to have empirical knowledge of the parameter tuning. In this paper, using simulations we demonstrated the relationship between the vigilance parameter and diagnosis accuracy. Furthermore, to overcome the problems of the vigilance parameter tuning, we have proposed an auto tuning algorithm to make the parameter the optimum value. The performance of the proposed algorithm was evaluated in several case studies using gas turbine plant data. The effectiveness of the proposed algorithm was confirmed by the obtained results.Copyright

A new modeling method for symbiosis phenomena

Recently, a number of studies have been done to investigate complicated systems such as economical, social, ecological and living systems. And, it is well known that complicated systems can be analyzed by the concept of symbiosis which is made up of competition, exploitation and coexistence and so on. The purpose of this paper is to propose a new modeling method for complicated systems by using the concept of symbiosis. A useful modeling method is presented in order to improve the ability of representing the symbiosis phenomena using the technique of fuzzy inference.

A new concept of gas turbine system: Motor-assisted gas turbine with high-speed motor

This paper proposes a new gas turbine power generation system called the “motor-assisted gas turbine” (MAGT). The MAGT is composed of a dual-shaft gas turbine and an inverter-fed motor. The conventional dual-shaft gas turbine has two shafts that rotate at different speeds: a power turbine shaft and a compressor shaft. The power turbine shaft is connected to a synchronous generator as usual. In the MAGT, the new idea is that the compressor shaft is coupled to an inverter-fed motor. By assisting the compressor with this motor, the MAGT is able to increase the power output of the gas turbine when the intake air temperature is high. In addition, the MAGT can be used as an energy storage device like a flywheel. The inertia energy of the compressor can be charged and discharged by varying the rotation speed with the motor directly connected to the compressor. This paper also presents a method for designing motors that are suitable for MAGTs. The interior permanent-magnet synchronous motors were studied by using a joint optimization method of stress and electromagnetic analysis for megawatt-class high-speed applications.

A New Concept for Power Grid Stabilization Using a Motor-Assisted Variable Speed Gas Turbine System

As the penetration ratio of renewable energy sources becomes larger, the fluctuations of grid load also become larger and larger because of the intermittent generation of wind power and photovoltaic power. These fluctuations cause instability of voltage and frequency in the power grid.Recently, there has been considerable research into solving these challenges, leading to development such as batteries, flywheels, and improved flexibility of thermal power plants. The batteries and the flywheels are confronted with the challenge of high initial cost for the Mega-Watt class. Improving flexibility for the thermal power plants is effective, but this improvement has several limitations such as load-follow operation capability under mechanical constraints and frequency regulation within governor-free regulating capacity.To overcome these problems, we propose a new gas turbine system named Motor-assisted Gas Turbine (MAGT). MAGT is composed of a two-shaft gas turbine: one free turbine shaft is connected to a synchronous generator rotating at a constant speed, and the other compressor shaft is coupled to an inverter-fed motor controlled at variable speed. The motor and inverter capacity is appropriate: about 5–10 % that of the gas turbine. MAGT improved the reaction rate corresponding to the load fluctuation by changing the speed of the compressor. Since the motor’s shaft, which has a compressor and a high pressure turbine, rotates at high speed and those masses are considerable, it has rotational energy of about several kWh. This energy could be charged and discharged through the converter that controls the motor speed, the same as for flywheels. This response could be much faster than conventional gas turbines, which contain huge amounts of working gas. MAGT controls its rotational energy in seconds and controls gas turbine power in minutes; thereby it improves response totally. Moreover, by assisting the compressor by using motor power, MAGT can increase gas turbine power output. Since the density of air decreases with as temperature increase, the mass of working gas is reduced. Thus, the fuel input must accordingly be reduced to suppress the combustion temperature without damaging turbine blades. As a result, power output is reduced. In such cases, a motor-assisted compressor can increase working gas. That allows more fuel input.The proposed system was evaluated using numerical simulations. The results showed that frequency variations were within ±0.1Hz and the output power was recovered under high ambient temperature.Copyright

New generation system concept: Motor-assisted gas turbine with pulse width modulation interleaving motor drive

This paper introduces a new concept of power generation system called the motor-assisted gas turbine (MAGT). In the MAGT, a dual-shaft gas turbine and a motor drive are included. The conventional dual-shaft gas turbine has two shafts with different rotational speeds: a power turbine shaft and a compressor shaft. The power turbine shaft is connected to a generator and is rotated at a certain speed with respect to the grid frequency. The new idea of the MAGT is that a motor drive assists the torque of the compressor shaft. The MAGT can be used as an energy storage device, like a flywheel, by using the converter to operate the compressor at variable speeds. This paper also describes a new motor drive that reduces harmonics current in the DC-link of the frequency converter.

A Robust and Flexible Control System to Reduce Environmental Effects of Thermal Power Plants

Regulations on environmental effects due to such issues as nitrogen oxide (NOx) and carbon monoxide (CO) emissions from thermal power plants have become stricter[1]; hence the need for compliance with these regulations has been increasing. To meet this need, several technologies with respect to fuel combustion, exhaust gas treatment and operational control have been developed[2-4]. The technologies for the fuel combustion and the exhaust gas treatment include a low NOx burner and an air quality control system, and they are capable of reducing impact on the environment as physical and chemical implementation methods. The operational control technology for the thermal power plants is constantly required to receive changes in operational conditions. It is difficult to realize operational control which responds to combustion properties. To overcome this issue, the operational control must be able to reduce NOx and CO emissions flexibly in accordance with such changes. Robustness is also required in such control because the measured NOx and CO data often include noise. Therefore, a robust and flexible plant control system is strongly desired to reduce environmental effects from thermal power plants efficiently. Several studies have proposed plant control technologies to reduce the environmental effects[4-10]. These technologies are classified into two types of methods: model based and non-model based methods. The former methods include an optimization algorithm and a numerical model to estimate plant properties using neural networks (NNs)[11,12] and multivariable model predictive control[13]. The optimization algorithm searches for optimal control signals to reduce NOx and CO emissions using the numerical model. The latter methods have no models and they generates the optimal control signals by fuzzy logic[14]. A fuzzy logic controller outputs the optimal control signals for multivariable inputs using fuzzy rule bases. The fuzzy rule bases are based on a priori knowledge of plant control, and they can be tuned by parameters. These technologies require the measured plant data for initial tuning of the model properties and the parameters of rules when the technologies are installed in plants. It usually takes some time to collect enough plant data. In addition, the search for control

Smart Design System for Coal-Fired Boiler Buildings in Thermal Power Plants

To meet expanding energy requirements, supercritical sliding pressure operation has become a major trend in recent thermal power plants. The technology for this operation was developed as high efficient thermal power plants with lower emission. We have continued to develop supercritical steam plant with sliding pressure operation to meet the demand for high efficiency coal-fired power plants that has arisen due to circumstances such as high fuel prices, exacting plant site requirements, and very strict environmental requirements. Because of our accumulated expertise and practical experience, we have received orders for several coal-fired engineering, procurement, and construction (EPC) projects. We have developed a smart design system for a coal-fired boiler building using an information technology (IT) tool for a large-scale and complex system design. We call this design system the Flexible Engineering System. This system is composed of three support functions: boiler general arrangement, boiler building layout, and bill of quantity estimation. First, the boiler general arrangement support function enables us to automatically create basic engineering specifications based on the required specifications. This system generates the basic engineering required using parametric engineering practice with parameterization of several required specifications. Second, the support function of the boiler building layout planning enables us to make 3-D models of the boiler building automatically. The 3-D models of the boiler, coal silos, and air and gas ducts are generated from the boiler general arrangement. The 3-D models of the steel structures are generated from loading data. The steel structure and brace models can even reflect the results of stress analysis. The 3-D models of large components, for example, the pulverizer, forced draft fan, etc., are arranged by selecting a matching model from the data library. The 3-D piping models are generated along the optimum path routing using a search method that combines dynamic programming with a layout rule-base. The 3-D floor and head-clearance model, which means a walk space and a maintenance space, are generated taking into consideration layout rules such as those concerning installation and maintenance. This support system can check for interference between the steel structures and each component. Third, the support function of the bill of quantity estimation makes it possible to estimate the quantity of materials from the specification data and configuration data of the 3-D models. The developed system is now under operation. The results indicate that it provides high engineering accuracy and reliability.Copyright

e-chem page: A Support System for Remote Diagnosis of Water Quality in Boiling Water Reactors

It is important to control and maintain water quality for nuclear power plants. Chemical engineers sample and monitor reactor water from various subsystems and analyze the chemical quality as routine operations. With regard to controlling water quality, new technologies have been developed and introduced to improve the water quality from both operation and material viewpoints. To maintain the quality, it is important to support chemical engineers in evaluating the water quality and realizing effective retrieval of stored data and documents. We have developed a remote support system using the Internet to diagnose BWR water quality, which we call e-chem page . The e-chem page integrates distributed data and information in a Web server, and makes it easy to evaluate the data on BWR water chemistry. This system is composed of four functions: data transmission, water quality evaluation, inquiry and history retrieval system, and reference to documents on BWR water chemistry. The developed system is now being evaluated in trial operations by Hitachi, Ltd. and an electric power company. In addition diagnosis technology applying independent component analysis (ICA) is being developed to improve predictive capability of the system. This paper describes the structure and function of the e-chem page and presents results of obtained with the proposed system for the prediction of chemistry conditions in reactor water.Copyright