A self-organizing power system stabilizer using fuzzyauto-regressive moving average (FARMA) model

This paper presents a self-organizing power system stabilizer (SOPSS) which use the fuzzy auto-regressive moving average (FARMA) model. The control rules and the membership functions of the proposed fuzzy logic controller are generated automatically without using any plant model. The generated rules are stored in the fuzzy rule space and updated on-line by a self-organizing procedure. To show the effectiveness of the proposed controller, comparison with a conventional controller for a one-machine infinite-bus system is presented     

An autonomous control system for boiler-turbine units

Achieving a more autonomous power plant operation is an important part of power plant control. To be autonomous, a control system needs to provide adequate control actions in the presence of significant uncertainties and/or disturbances, such as actuator or component failures, with minimum or no human assistance. However, a reasonable degree of autonomy is difficult to obtain without incorporating intelligence in the control system. This paper presents a coordinated intelligent control scheme with a high degree of autonomy. In this scheme, a fuzzy-logic based supervisor monitors the overall plant operation and carries out the tasks of coordination, fault diagnosis, fault isolation, and fault accommodation     

Developing a multipurpose sun tracking system using fuzzy control

The present work demonstrates the design and simulation of time controlled step sun tracking systems that include: one axis sun tracking with the tilted aperture equal to the latitude angle, equatorial two axis sun tracking and azimuth/elevation sun tracking. The first order Sugeno fuzzy inference system is utilized for modeling and controller design. In addition, an estimation of the insolation incident on a two axis sun tracking system is determined by fuzzy IF-THEN rules. The approach starts by generating the input/output data. Then, the subtractive clustering algorithm, along with least square estimation (LSE), generates the fuzzy rules that describe the relationship between the input/output data of solar angles that change with time. The fuzzy rules are tuned by an adaptive neuro-fuzzy inference system (ANFIS). Finally, an open loop control system is designed for each of the previous types of sun tracking systems. The results are shown using simulation and virtual reality. The site of application is chosen at Amman, Jordan (32° North, 36° East), and the period of controlling and simulating each type of tracking system is the year 2003.     

A fuzzy multi-criteria decision-making model for trigeneration system

The decision making for trigeneration systems is a compositive project and it should be evaluated and compared in a multi-criteria analysis method. This paper presents a fuzzy multi-criteria decision-making model (FMCDM) for trigeneration systems selection and evaluation. The multi-criteria decision-making methods are briefly reviewed combining the general decision-making process. Then the fuzzy set theory, weighting method and the FMCDM model are presented. Finally, several kinds of trigeneration systems, whose dynamical sources are, respectively stirling engine, gas turbine, gas engine and solid oxide fuel cell, are compared and evaluated with a separate generation system. The case for selecting the optimal trigeneration system applied to a residential building is assessed from the technical, economical, environmental and social aspects, and the FMCDM model combining analytic hierarchical process is applied to the trigeneration case to demonstrate the decision-making process and effectiveness of proposed model. The results show that the gas engine plus lithium bromide absorption water heater/chiller unit for the residential building is the best scheme in the five options.     

Real time control of micro-machine system using micro-computerbased fuzzy logic power system stabilizer

A microcomputer based fuzzy logic power system stabilizer is applied to a micro-machine system to investigate its efficiency in real time control. The stabilizing signal is determined by using measured speed or real power signals at every sampling time to damp the system oscillations. The results show the proposed stabilizer improves the system damping effectively subject to various types of disturbances     

A complete modeling and simulation of DFIG based wind turbine system using fuzzy logic control

The current paper talks about the variable speed wind turbine generation system (WTGS). So, the WTGS is equipped with a doubly-fed induction generator (DFIG) and two bidirectional converters in the rotor open circuit. A vector control (VC) of the rotor side converter (RSC) offers independent regulation of the stator active and reactive power and the optimal rotational speed tracking in the power maximization operating mode. A VC scheme for the grid-side converter (GSC) allows an independent regulation of the active and reactive power to exchange with the grid and sinusoidal supply currents and keeps the DC-link voltage constant. A fuzzy inference system (FIS) is adopted as an alternative of the conventional proportional and integral (PI) controller to reject some uncertainties or disturbance. The performances have been verified using the Matlab/Simulink software.     

Adaptive fuzzy logic control of a turbine generator system

This paper is concerned with the application of an adaptive, fuzzy logic controller to a synchronous generator system. Significant reductions in the amount of required calculations have been made which allow a direct analysis of the system. A novel on-line training algorithm is proposed to adapt fuzzy rule base which is shown to converge globally and provide the desired regulation for disturbances at all operating points. The sensitivity of the controller with respect to changes in design parameters is analysed. Test responses are compared with a self-tuning regulator to show the effectiveness of the proposed system. Micromachine tests further establish the possibility of developing a practical controller     

Assessing renewables-to-electricity systems: a fuzzy expert system model

The assessment of Renewables-to-Electricity Systems is a complex, time-consuming task and requires skilled, experienced engineers. This paper describes the on-going research effort that takes place in the development of a new Intelligent Approach, an efficient decision making tool in this problem based on the employment of the Expert Systems and Fuzzy Logic techniques. As far as expert knowledge representation is concerned, the proposed approach is based on Expert System techniques (rule-based methodology). Moreover, trying to assess a Renewables-to-Electricity project or several alternative ones, the analysis has to face, in general, a series of uncertainties. To handle effectively these uncertainties, a new methodology is proposed (by use of Fuzzy Sets Theory and Fuzzy Logic Techniques). The proposed Fuzzy Project Priority Index for each Renewables-to-Electricity System is very useful especially in decision-makers.     

Maximum power point tracking using adaptive fuzzy logic control for grid-connected photovoltaic system

This paper proposes a method of maximum power point tracking using adaptive fuzzy logic control for grid-connected photovoltaic systems. The system is composed of a boost converter and a single-phase inverter connected to a utility grid. The maximum power point tracking control is based on adaptive fuzzy logic to control a switch of a boost converter. Adaptive fuzzy logic controllers provide attractive features such as fast response, good performance. In addition, adaptive fuzzy logic controllers can also change the fuzzy parameter for improving the control system. The single phase inverter uses predictive current control which provides current with sinusoidal waveform. Therefore, the system is able to deliver energy with low harmonics and high power factor. Both conventional fuzzy logic controller and adaptive fuzzy logic controller are simulated and implemented to evaluate performance. Simulation and experimental results are provided for both controllers under the same atmospheric condition. From the simulation and experimental results, the adaptive fuzzy logic controller can deliver more power than the conventional fuzzy logic controller.     

Thermal comfort control on multi-room fan coil unit system using LEE-based fuzzy logic

Saving consumable energy and maintaining the thermal comfort level are two main topics in the heating, ventilating and air conditioning (HVAC) control field. The reliability of the controller is important as well. This paper proposes a least enthalpy estimator (LEE) that combines the definition of thermal comfort level and the theory of enthalpy into a load predicting way to provide timely suitable settings for a fan coil unit (FCU) fuzzy controller used in HVAC. According to the settings, including temperature and relative humidity, the fuzzy controller can make decisions and adjust the output of the FCU system. From actual experiments, the LEE-based FCU fuzzy controller can achieve the requirements of the FCU control system such as thermal comfort, energy efficiency and reliability.     

Predicting average energy conversion of photovoltaic system in Malaysia using a simplified method

This paper is about predicting the average conventional energy conversion by a photovoltaic system in Malaysia. The calculation is based on average number of days in a month. Average hourly energy flows are estimated based on knowledge of array test parameters, monthly average of hourly ambient temperature and monthly average of daily hemispherical radiation. The monthly average of diffuse component of radiation can be predicted based on hemispherical radiation, by using an appropriate empirical correlation related to the monthly average of diffuse fraction to monthly average of clearness index. The values of hourly average radiation are estimated based on a statistical model.     

PV-battery energy storage system operating of asynchronous motor driven by using fuzzy sliding mode control

This article tends on the designing of renewable-storage electrical system for asynchronous machine application. The machine requires a photovoltaic energy as a primary source of renewable energy. Such as the major drawback of solar sources are neither continuous nor regular in the time. To overcome this problem, a battery energy storage system will be added to make sure the continuity of the operation machine. Generally, electrical machine is driven by using sliding mode control where the major problem in this control technique design is chattering phenomenon which can be defeated using a sliding surface based on fuzzy logic. The proposed technique is performed with the proposed control system. A simulation test of the system for varied load motor conditions proved that the system is preferment. When, the generated power from PV is superior that the demands, the rest is stored in the battery. In the opposite condition, PV and battery required load. Moreover, the system which consists of machine and its control is enabling to produce electrical energy when it is functioning in the other sense of rotation. Four quadrant machine operations guarantee many possibilities of charging and discharging of the battery that assure the continuity of operating system.     

模糊控制在小型风电系统MPPT中的应用

根据最大功率点跟踪的基本原理及常用风力发电控制系统的特点,提出了一种基于模糊控制、具有在线参数调整的自适应占空比扰动法,该方法能迅速地感知外界的风速变化,调整发电机与负载之间的功率匹配,使风力机以最佳叶尖速比运行.通过Matlab/Simulink仿真实验表明:采用模糊控制电路,风力机的输出功率大幅提高,在风速发生突变的情况下,也能快速地找到新的最大功率点.     

A numerical model for optimal control of a heat-pump/heat-storage system

A model for optimal control of a heat-pump system with a storage tank is developed. The numerical solution is obtained by transforming the free boundary condition problem into one with fixed boundary conditions and solving for the optimal pattern of heat-pump control under varying ambient and source temperature distributions. The effects of source-temperature and mass storage on optimal cost are investigated and an approximate method of predicting energy savings is given. Simulation results suggest that, depending on the source-temperature, storage capacity and building load, significant energy savings can be made.     

An electrical modeling and fuzzy logic control of a fuel cellgeneration system

The fuel cell generation system consists of a stack, a reformer, and converters. The stack generates DC power by electrochemical reaction. For system design and analysis, it is necessary to obtain electrical models. Simplified electrical models of a fuel cell generation system for system control are proposed. Then using the electrical models, system performance of a fuel cell generation system in which power is boosted by step-up choppers is analyzed. A fuzzy controller is designed for improved system performance. Simulation and experimental results confirmed the high performance capability of the designed system     

A technique to map monthly average global illuminance from satellite data in the tropics using a simple semi-empirical model

This paper presents a technique to map monthly average hourly global illuminance from satellite data. A semi-empirical model relating monthly average global illuminance to cloud index, precipitable water, total ozone column (TOC), aerosol optical depth (AOD) and air mass was developed. Data for the cloud index, AOD and TOC were obtained from the visible imagery data of MTSAT-1R, MODIS/Terra and OMI/Aura satellites respectively, while precipitable water was extracted from NCEP/NCAR reanalysis database. The model was formulated using global illuminance measured at four stations in Thailand for a four-year period and validated with an independent one-year data set. Values of monthly average hourly global illuminance calculated from the model and those obtained from the measurements were in good agreement, with a root mean square difference (RMSD) and mean bias difference (MBD) of 8.1% and −0.8%, respectively. The model was used to calculate monthly average hourly global illuminance over Thailand and the results were displayed as illuminance maps. The maps reveal diurnal and seasonal effects mainly in response to solar zenith angle changes and cloud cover related to the southwest and northeast monsoons.     

Boiler-turbine control system design using a genetic algorithm

This paper discusses the application of a genetic algorithm to control system design for boiler-turbine plant. In particular we study the ability of the genetic algorithm to develop a proportional-integral (PI) controller and a state feedback controller for a nonlinear multi-input/multi-output (MIMO) plant model. The plant model is presented along with a discussion of the inherent difficulties in such controller development. A sketch of the genetic algorithm (GA) is presented and its strategy as a method of control system design is discussed. Results are presented for two different control systems that have been designed with the genetic algorithm     

基于模糊控制的光伏发电系统MPPT

光伏电池的输出功率随外部环境和负载的变化而变化,为充分发挥光伏器件的效能,需采用最大功率点跟踪电路。根据最大功率点跟踪的基本原理及常用光伏发电系统控制的优缺点．提出了一种基于模糊控制,具有在线参数调整的自适应占空比扰动法。该方法在不干扰系统正常工作的情况下,能迅速地感知外界的环境变化。实验结果证明,该方法能够快速、准确地跟踪太阳能电池的最大功率点。     

GA-based fuzzy logic control of a solar power plant using distributed collector fields

A novel genetic algorithm (GA) based fuzzy logic control (FLC) system has been developed for the solar power plant, Plataforma Solar de Almería (PSA) at Tabernas, in Almería, Spain. The rule base encompasses an empirical set of 49 “if-then” rules. Chromosomes consisting of 49 genes of 5-bit data are created to link to the rule base. The 5-bit data of each gene represents the stength of the corresponding ‘If-Then’ rule. The GA performs the basic operations of reproduction, crossover and mutation on a pool of chromosomes to search for the best rule base which optimises the response time of the plant to input temperature or power demand by controlling the distributed collector field of the plant. The collect field is essentially an array of parabolic mirrors and oil pipes in which the transversal of solar energy takes place. Simulation results on the plant with an optimised rule-base using the 100th generation of the chromosome show that the proposed GA-FLC scheme gives a better and more robust performance of the plant than other schemes previously implemented.