Top PDF Adaptive fuzzy control for power-frequency characteristic regulation in high-RES power systems

Hybrid Fuzzy Controller Based Frequency Regulation in Restructured Power System

frequency control in a complex and competitive environment is a tedious process, the control technique must be more intelligent and adaptive for a changing environment. More research work has been carried on Frequency control in restructured power system [1]-[7]. Possible issues in Frequency control in energy market were dis- cussed in [1]. Vertically integrated structure and bilateral based scheme modeling were discussed in [2] [3]. Different approaches like pluralistic and hierarchical methods were discussed and quoted in [4]. A decentralized approach based on control theory was formulated and analyzed in [5]. Some researchers have proposed a fre- quency control logic based on fuzzy logic controller [6], reinforcement learning [7] and artificial neural network [8] in interconnected power systems.

Load Frequency Control of Three Area Power System using Fuzzy Logic Controller

Understanding of the frequency dynamics of power systems is essential for several issues including frequency control design and estimation of the system inertia through measurements. Consider a power system with several conventional synchronous generators. If this power system is subjected to a disturbance such as a sudden outage of a generator, then dynamical changes in the system start instantaneously. These dynamics are mainly caused by the instantaneous power imbalance between the instantaneous generation and consumption of electric power. Consequently, the remaining synchronous generators are subjected to acceleration and deceleration effects. Due to the strong connection between the mechanical and electrical frequency, the changes in the rotor speed results in changes in the electrical frequency. Eventually, the power balance and the frequency are restored in the system has sufficient capacity to compensate the lost generation. This control action is called primary Automatic Load Frequency Control (ALFC). In this direction, the load-frequency control (LFC) is one of important control problems in concerning the integration of wind power turbine in a multi-area power system [2, 8, 18, 20, 21].The increasing need for electrical energy in the twenty-first century, as well as limited fossil fuel reserves, very high transportation and fuel cost and the increasing concerns with environmental issues for the reduction of carbon dioxide (CO2) and other greenhouse gasses, causes fast development in the area of renewable energy sources (RESs). One of the adaptive and nonlinear intelligent control techniques that can be effectively applicable in the frequency control design is reinforcement

Repetitive Control with Adaptive Sampling Frequency for Wind Power Generation System

The Increased power demand paved the way to invent new technologies to improve the power obtained from renewable energy sources. From various studies the hill climbing algorithms such as perturb and observe and incremental conductance is seen to be better than all other MPPT algorithms. The efficiency is high in perturb and observe and Incremental conductance methods Though soft computing techniques like fuzzy and neural networks are developing. Individual MPPT for each PV module differ in varying circuit topologies. For stand alone and grid connected systems with conventional converters perturb and observe method finds its better performance. For improvised or resonant inverters, modified P&O methods need to be included. Improved PSO is been utilized mainly in partial shaded conditions and to reduce oscillations. The different algorithms are made used in different topologies of converters. Choice of algorithms and topologies depends upon the requirement. Above all control algorithms are emerging in to field to improve the efficiency of the existing MPPT algorithms. Hybrid algorithms

Adaptive prediction, tracking and power adjustment for frequency non-selective fast fading systems

Propagation studies in a variety of environments show that the multipath signal consists primarily of a small number of discrete sinusoidal components (often 10 or fewer) [1, 4, 5]. The superposition of these components changes rapidly as the vehicle moves, producing the familiar fast- fading signal envelope observed in practice. However, the amplitude, frequency and phase of each component change on a much slower time scale, e.g. on the order of 100 times the coherence time of the signal envelope. This variation is slow enough that the fading coefficient can be predicted far beyond the coherence time. In particular, these estimates can be used to forecast signal fades before they occur. This prediction capability can provide enabling technology for adaptive coding [8-10], accurate power control, reliable transmitter and/or receiver diversity and many other components of wireless systems.

Load Frequency Control in Two Area Power Systems Integrated with SMES Combination using Fuzzy PID and ANFIS Controller

Fuzzy- PID controllers are proposed for automatic generation control (AGC) and load frequency control (LFC) of two area reheat thermal power plant in interconnected power system. Additionally, a superconducting magnetic Energy Storage (SMES) unit is considering in two areas. The implementation of SMES combination arrests the initial fall in frequency deviation and tie-line power deviation after a sudden load disturbance. The simulation result shows that the system performances are improved significantly with the proposed SMES unit. The sensitivity analysis of the system is performed by varying the parameters and operating load conditions from their nominal values. It is observed that the optimized gains of the proposed PID and fuzzy PID and ANFIS controllers are need not be reset even if the system is subjected to wide variation in loading condition and system parameters. Finally, the effectiveness of the proposed controller design is verified by considering different types of load patterns. The simulated results show that the performance of ANFIS-PID controller is better than the Fuzzy- PID and PID controllers. The simulations have been performed using Matlab software.

On chip communication architecture power estimation in high frequency high power model

analysis was made in on-chip communication system to analyze the chip into logic elements. Bus wire and bus interface element calculate the power in any part of the chip and recommend a number of power decreasing schemes [1]. In [2], the abstraction level of design-entry of hardware systems was raised from register transfer level (RTL) to electronic system level (ESL) to provide a solution for two recognizable problems - how to enable a power aware design to flow with design entry point at the ESL and how to enable power aware at a high level of synthesis to utilize RTL implementation from ESL automatically. Development in platform for power analysis and build an improved system with power analysis was suggested [5]. Another model was done featuring three important issues - power measurement, power analysis and power management. This system model helped the designers to develop a high performance in embedded system designs with low power consumption. A framework for describing the power behavior in system- level designs has been proposed in [6]. A model with a set of resources, an environmental workload specification and a power management policy serves as the heart of the system. These abilities mentioned before map this model to a simulation-based framework so as to obtain estimation to system’s power dissipation. Also, they proposed an algorithm to optimize power management policies, the optimization algorithm can be used in a tight loop with the estimation engine to derive new power-management policy algorithms for a given system-level description. OUR APPROACH

Fuzzy MPPT Control and Power Regulation for Standalone Photovoltaic Energy Conversion System

In this paper, a control system for a standalone PV system with battery storage to feed a DC load is implemented. Mamdani fuzzy control method is used to obtain the maximum power. The fuzzy control algorithm is based on minimizing the error between the estimated maximum power, as a reference, and the actual power from the PV panel. PI controllers are used to control the load power and to regulate the battery charge and discharge [7, 8].

4 – Element Spatial Power Combiner for High Frequency Communication Systems

Abstract- A solution to the insertion loss in the Distributed Amplifier configuration is presented. Wilkinson power splitter is employed at the input and wave interference characteristic is considered as the means of combining the transmitted power from active antennas. The overall result of using the power splitter and spatial combination of the signals is found to enhance the strength of the transmitted power by a factor of 16. More gain could be achieved by adding more power splitters and the corresponding active antennas.

Load Frequency Control in Deregulated Power System using Fuzzy C Means

In the power system, any sudden load change causes the deviation of frequency and tie-line power. So, that Load Frequency Control (LFC) is a very important issue in power system operation and control for supplying sufficient and reliable electric power with good quality [19]. The main aim of the LFC is to maintain zero steady state errors for frequency deviation and Tie-line power in a multi-area restructured power system. A lot of studies have been made in the last two decades about the LFC in interconnected power systems [1–7]. In most of the researchers Proportional Integral (PI) controllers have been widely used for decades as the load frequency controllers. Actually, several techniques have been proposed to design the PI controller, where the controller parameters of the PI controller are tuned using trial-and-error approach. However, it gives poor performance in the system transient response. Proportional Integral Derivative (PID) controller has been proposed to improve the performance of load frequency control problem. the mentioned technique needs to a more complex design process [10].The real world power system contains different kinds of uncertainties due to load variations, system modeling errors and change of the power system structure. Many authors have proposed fuzzy logic based controllers to power systems [9][12][14]. Fuzzy logic is a rule-based approach to decision making. This approach is used to handle imprecise knowledge and was developed in the sixties by H. Shayeghi [15]. Such knowledge can be collected and delivered by a human expert (e.g. decision-maker, designer, process planner, machine operator, etc.). Fuzzy C-Means (FCM) is a Clustering algorithms permit

Control of Renewable Power Generation Systems by using Fuzzy Logic Controller Based Synchronous Power Controller

of the primary request low-pass filter which is generally utilized just to damp the estimation clamor. The previously mentioned outlines join the swing condition innately in the power directing circle, in this manner the power synchronizing impact will be available in both grid connected or island operation. By and by, the damping impact and the power- frequency droop incline are obliged by each other. Because of this, a great parameter for the droop highlight may prompt to a deficient damping, and in the different way, damping parameter could offer ascent to an undesired droop slant. Then again, since the droop attributes are normally consolidated in the power controlling circle, a settled power control can't be specifically accomplished regardless of the possibility that it is required in a few applications. The creators propose to utilize an extra PI controller with a virtual droop to modify the damping filter to accomplish a settled power control if necessary, however the request of the shut circle switch capacity will build, in this manner the dynamic investigation and tuning of parameters turn out to be more complex.

High Power Medium Frequency Magnetics for Power Electronics Applications.

For the medium voltage solid state transformer, a three phase transformer provides the additional smoothing to transformer current and enables reduced dv/dt across the transformer input, [3]. The transformers are made with nanocrystalline material due to its low loss and high magnetizing inductance. The exact structure and design was outsourced to a professional company so the construction details are not clear. A provided equivalent model showing a three limb design is mentioned. Given the material, it is safe to assume it is some form of magnetic ribbon. However, it is known that the transformer has very low leakage inductance and requires an external inductor to meet the desired leakage for the dual active bridge. It also highlights the need for common mode chokes for blocking noise. Again, this is an ideal application space for ribbon wound cores. Finally, the authors demonstrate an auxiliary transformer in series with the original DAB. This auxiliary transformer is used to inject reactive power and enable an extension of the ZVS range. Again, in [4], magnetic ribbon cores are shown to have many design benefits. This author uses amorphous ribbon. In this work, the author uses a five limb core design to accommodate the third harmonic in a three phase transformer. In [5], the author presents a three phase axial transformer where the outer core is a magnetic ribbon nanocrystalline. This design combines the advantage of five limb and axial transformers to allow zero sequence, triplin harmonics, without nonidealities such as asymmetrical inductances.

Short term wind power forcasting using adaptive neuro fuzzy inference systems

As the global political will to address climate change gains momentum, the issues associated with integrating an increasing penetration of wind power into power systems need to be addressed. This paper summarises the current trends in wind power and its acceptance into electricity markets. The need for accurate short term wind power forecasting is highlighted with particular reference to the 5 minute dispatch interval for the proposed Australian Wind Energy Forecasting System. Results from a case study show that Adaptive Neural Fuzzy Inference System (ANFIS) models can be a useful tool for short term wind power forecasting providing a performance improvement over the industry standard “persistence” approach.

Perturbation estimation based coordinated adaptive passive control for multimachine power systems

generator excitation control is one of the most popular methods to enhance the power system stability. Many nonlinear control approaches have been used for the excitation controller (EC), such as adaptive H ∞ control [3], L-2 disturbance attenuation control [4], nonlinear adaptive control [5], adaptive dynamic programming [6], and optimal predictive control [7]. On the other hand, proper controllers of ﬂexible AC transmission systems (FACTS) can also improve the power system stability. Many studies have been undertaken on the development of nonlinear controllers for thyristor controlled series compensation (TCSC) [8], static variable compensator (SVC) [9], and static synchronous compensator (STATCOM) [10]. However, uncoordinated EC and FACTS controller may deteriorate each other or even lead to instability under large disturbances [1].

Maximum Power Point Tracking using Fuzzy Logic Control for Photovoltaic Systems

The performance of MPPT using the FLC and the simple P&O techniques is verified by operating them under the variation of irradiance. Fig. 12 shows the transient responses of the tracking power curves obtained from both control algorithms. As seen in the figure, the proposed response is much faster than that of the conventional MPPT while the overshoots of the system are almost the same. Fig.13 shows the energy obtained from the both controllers; clearly, the proposed controller gains more energy than the conventional P&O technique.

MAXIMUM POWER POINT TRACKING CONTROL FOR PHOTOVOLTAIC SYSTEMS: NEURO-FUZZY APPROACH

Solar output power of PV systems is generally influenced by atmospheric factors like variable temperature and solar irradiation. Different control techniques could be used on get rid of the miss functioning: controlling the input to the PV array and controlling the power output from the PV array. The combinations of these two may also be considered for maintaining constant output power at load [1]. The irradiance dependent input to the PV systems is controlled in order to be kept as high as possible, no matter the changes in weather conditions. Due to nonlinear I-V and P-V characteristics of the PV array, the MPPT becomes more challenging. Such non-linear and non- minimum phase characteristics further confuse the MPPT of the boost converter [5]. To overcome these problems, different conventional and intelligent MPPT algorithms have been proposed such as Incremental Conductance (IC) [6–8], Open Circuit Voltage (OCV) [9], Short Circuit Current (SCC) [10], Perturb and Observe (P&O) [11], fuzzy logic [12–15], feedback linearization [16], neural network [17– 22], neuro-fuzzy [23–25] and sliding mode [26,27]. Nevertheless, there still remains the concern of fast and accurately determining the locus of the MPP during high weather variations and external load changes occurring.

Optimization of Hybrid Power Systems Performance Based on Adaptive Neuro-Fuzzy Inference System

Large consumers of electric power need more than one source additionally to the utility grid for supplying their load demands. In many cases, the large consumers of electrical power combined between several types of power sources, which called hybrid power system. Hybrid power systems achieve the integrity of power generation sources. The main reasons of using HPSs are frequently interruptions of the utility grid and random load demands, in addition to the high generation budget of the traditional power sources. The high generation budget of the traditional power sources are high fuel cost and the periodicity maintenance requirements cost.