Author
Takashi Hiyama
Other affiliations: Clarkson University
Bio: Takashi Hiyama is an academic researcher from Kumamoto University. The author has contributed to research in topics: Electric power system & Fuzzy logic. The author has an hindex of 35, co-authored 246 publications receiving 5234 citations. Previous affiliations of Takashi Hiyama include Clarkson University.
Papers published on a yearly basis
Papers
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TL;DR: In this article, a novel maximum power point tracking (MPPT) system is proposed for partially shaded PV array using artificial neural network (ANN) and fuzzy logic with polar information controller.
Abstract: The one of main causes of reducing energy yield of photovoltaic systems is partially shaded conditions. Although the conventional maximum power point tracking (MPPT) control algorithms operate well under uniform insolation, they do not operate well in non-uniform insolation. The non-uniform conditions cause multiple local maximum power points on the power-voltage curve. The conventional MPPT methods cannot distinguish between the global and local peaks. Since the global maximum power point (MPP) may change within a large voltage window and also its position depends on shading patterns, it is very difficult to recognise the global operating point under partially shaded conditions. In this paper, a novel MPPT system is proposed for partially shaded PV array using artificial neural network (ANN) and fuzzy logic with polar information controller. The ANN with three layer feed-forward is trained once for several partially shaded conditions to determine the global MPP voltage. The fuzzy logic with polar information controller uses the global MPP voltage as a reference voltage to generate the required control signal for the power converter. Another objective of this study is to determine the estimated maximum power and energy generation of PV system through the same ANN structure. The effectiveness of the proposed method is demonstrated under the experimental real-time simulation technique based dSPACE real-time interface system for different interconnected PV arrays such as series-parallel, bridge link and total cross tied configurations.
353 citations
TL;DR: In this article, an artificial neural network (ANN) was used for the estimation of the maximum power generation from a PV module under the conditions of irradiation, temperature and wind velocity.
Abstract: This paper presents an application of an artificial neural network for the estimation of maximum power generation from PV module. The output power from a PV module depends on environmental factors such as irradiation and cell temperature. For the operation planning of power systems, the prediction of the power generation is inevitable for PV systems. For this purpose, irradiation, temperature and wind velocity are utilized as the input information to the proposed neural network. The output is the predicted maximum power generation under the condition given by those environmental factors. The efficiency of the proposed estimation scheme is evaluated by using actual data on daily, monthly and yearly bases. The proposed method gives highly accurate predictions compared with predictions using the conventional multiple regression model.
340 citations
TL;DR: The proposed neural network has a quite simple structure and provides a highly accurate identification of the optimal operating point and also ahighly accurate estimation of the maximum power from the PV modules.
Abstract: This paper presents an application of a neural network for the identification of the optimal operating point of PV modules for the real time maximum power tracking control. The output power from the modules depends on the environmental factors such as insolation, cell temperature, and so on. Therefore, accurate identification of optimal operating point and real time continuous control are required to achieve the maximum output efficiency. The proposed neural network has a quite simple structure and provides a highly accurate identification of the optimal operating point and also a highly accurate estimation of the maximum power from the PV modules. >
301 citations
Book•
15 Apr 2011
TL;DR: In this paper, a three-control area power system is used to regulate the frequency of the power system using energy-capacitor system (ECS) in a Deregulated Environment.
Abstract: Intelligent Power System Operation and Control: Japan Case Study Application of Intelligent Methods to Power Systems Application to Power System Planning Application to Power System Control and Restoration Future Implementations Automatic Generation Control (AGC): Fundamentals and Concepts AGC in a Modern Power System Power System Frequency Control Frequency Response Model and AGC Characteristics A Three-Control Area Power System Example Intelligent AGC: Past Achievements and New Perspectives Fuzzy Logic AGC Neuro-Fuzzy and Neural-Networks-Based AGC Genetic-Algorithm-Based AGC Multiagent-Based AGC Combined and Other Intelligent Techniques in AGC AGC in a Deregulated Environment AGC and Renewable Energy Options AGC and Microgrids Scope for Future Work AGC in Restructured Power Systems Control Area in New Environment AGC Configurations and Frameworks AGC Markets AGC Response and an Updated Model Neural-Network-Based AGC Design An Overview ANN-Based Control Systems Flexible Neural Network Bilateral AGC Scheme and Modeling FNN-Based AGC System Application Examples AGC Systems Concerning Renewable Energy Sources An Updated AGC Frequency Response Model Frequency Response Analysis Simulation Study Emergency Frequency Control and RESs Key Issues and New Perspectives AGC Design Using Multiagent Systems Multiagent System (MAS): An Introduction Multiagent Reinforcement-Learning-Based AGC Using GA to Determine Actions and States An Agent for ss Estimation Bayesian-Network-Based AGC Approach Bayesian Networks: An Overview AGC with Wind Farms Proposed Intelligent Control Scheme Implementation Methodology Application Results Fuzzy Logic and AGC Systems Study Systems Polar-Information-Based Fuzzy Logic AGC PSO-Based Fuzzy Logic AGC Frequency Regulation Using Energy Capacitor System Fundamentals of the Proposed Control Scheme Study System Simulation Results Evaluation of Frequency Regulation Performance Application of Genetic Algorithm in AGC Synthesis Genetic Algorithm: An Overview Optimal Tuning of Conventional Controllers Multiobjective GA GA for Tracking Robust Performance Index GA in Learning Process Frequency Regulation in Isolated Systems with Dispersed Power Sources Configuration of Multiagent-Based AGC System Configuration of Laboratory System Experimental Results
250 citations
TL;DR: Artificial neural network (ANN) is proposed as a method to improve accurate RUL prediction of bearing failure and shows that better performance is achieved in order to predict bearing failure.
Abstract: Accurate remaining useful life (RUL) prediction of machines is important for condition based maintenance (CBM) to improve the reliability and cost of maintenance. This paper proposes artificial neural network (ANN) as a method to improve accurate RUL prediction of bearing failure. For this purpose, ANN model uses time and fitted measurements Weibull hazard rates of root mean square (RMS) and kurtosis from its present and previous points as input. Meanwhile, the normalized life percentage is selected as output. By doing that, the noise of a degradation signal from a target bearing can be minimized and the accuracy of prognosis system can be improved. The ANN RUL prediction uses FeedForward Neural Network (FFNN) with Levenberg Marquardt of training algorithm. The results from the proposed method shows that better performance is achieved in order to predict bearing failure.
225 citations
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TL;DR: The many different techniques for maximum power point tracking of photovoltaic (PV) arrays are discussed in this paper, and at least 19 distinct methods have been introduced in the literature, with many variations on implementation.
Abstract: The many different techniques for maximum power point tracking of photovoltaic (PV) arrays are discussed. The techniques are taken from the literature dating back to the earliest methods. It is shown that at least 19 distinct methods have been introduced in the literature, with many variations on implementation. This paper should serve as a convenient reference for future work in PV power generation.
5,022 citations
TL;DR: A comprehensive and clear picture of the state-of-the-art technologies available, and where they would be suited for integration into a power generation and distribution system is provided in this article.
2,790 citations
TL;DR: In this paper, a comprehensive review of the MPPT techniques applied to photovoltaic (PV) power system available until January, 2012 is provided, which is intended to serve as a convenient reference for future MPPT users in PV systems. But, confusion lies while selecting a MPPT as every technique has its own merits and demerits.
Abstract: This paper provides a comprehensive review of the maximum power point tracking (MPPT) techniques applied to photovoltaic (PV) power system available until January, 2012. A good number of publications report on different MPPT techniques for a PV system together with implementation. But, confusion lies while selecting a MPPT as every technique has its own merits and demerits. Hence, a proper review of these techniques is essential. Unfortunately, very few attempts have been made in this regard, excepting two latest reviews on MPPT [Salas, 2006], [Esram and Chapman, 2007]. Since, MPPT is an essential part of a PV system, extensive research has been revealed in recent years in this field and many new techniques have been reported to the list since then. In this paper, a detailed description and then classification of the MPPT techniques have made based on features, such as number of control variables involved, types of control strategies employed, types of circuitry used suitably for PV system and practical/commercial applications. This paper is intended to serve as a convenient reference for future MPPT users in PV systems.
1,584 citations
TL;DR: All algorithms, direct and indirect, can be included in some of the DC/DC converters, Maximum power point trackings (MPPTs), for the stand-alone systems and in this article they are grouped as either direct or nondirect methods.
1,160 citations
TL;DR: A review on machinery prognostics following its whole program, i.e., from data acquisition to RUL prediction, which provides discussions on current situation, upcoming challenges as well as possible future trends for researchers in this field.
1,116 citations