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

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

learning (RL). Some efforts are addressed in [3, 4, 5, 7, 16, 17]. RL based controllers learn and are adjusted to keep the area control error small enough in each sampling time of a LFC cycle. Since, these controllers are based on learning methods; they are independent of environment conditions and can learn a wide range of operating conditions. The RL based frequency control design is a model-free design and can easily scalable for large scale systems and suitable for frequency variation caused by wind turbine fluctuation. Using conventional linear control methodologies for the LFC design in a modern power system is not more efficient, because they are only suitable for a specific operating point in a traditional structure. If the dynamic/structure of system varies; they may not perform as expected. Most of conventional control strategies provide model based controllers that are highly dependent to the specific models, and are not useable for large-scale power systems concerning the integration of RES units with nonlinearities, undefined parameters and uncertain models. If the dimensions of the power system increase, then these control design may become more different as the number of the state variables also increases, significantly. Therefore, design of intelligent controllers that are more adaptive and flexible than conventional controllers is become an appealing approach. When WTGs are introduced to the power system, as they generate a part of power system loads, much portion of conventional nominal power can be available for using in supplementary control. However, as the variable wind farms power output may or may not be available during peak demand and abnormal periods, due to unpredictable nature

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

In this model shown by Fig.3, the application of fuzzy controller [3] for load-frequency control in power systems is used. For the same, interconnected power system having three control areas including same turbine units. In the system, non-reheat turbines are used for each area. So, same properties and physical constants of the areas above are considered in the simulation. In the simulation, a step load increment in the three areas of power system is considered [7]. The area control error for each area is controlled with FLC to optimize the integral coefficient and hence to achieve the zero frequency steady state error. The fuzzy model used is Mamdani and bisector is used as defuzzification method. In the decision-making stage, total twenty five rules are used, which are specified by a set of IF–THEN statements [9] define the controller behavior. The fuzzy simulation model in Simulink is shown in Fig. 3.

Fuzzy Logic Based Automatic Load Frequency Control of Multi-Area Power Systems

Since power system dynamic characteristics are complex and variable, conventional control methods cannot provide desired results. Intelligent controllers can be replaced with conventional controllers to get fast and good dynamic response in load frequency control problems [12]. If the system robustness and reliability are more important, fuzzy- logic controllers can be more useful in solving a wide range of control problems since conventional controllers are slower and also less efficient in nonlinear system applications [8, 13, 14]. Fuzzy logic controller is designed to minimize fluctuation on system outputs [15]. There are many studies on power system with fuzzy logic controller [16-18]. FLC designed to eliminate the need for continuous operator attention and used automatically to adjust some variables the process variable is kept at the reference value. A FLC consists of three sections namely, fuzzifier, rule base, and defuzzifier as shown in Fig 3.

Analysis of Load Frequency Control for a Distributed Grid System Involving Wind, Hydro and Thermal Power Plants using Conventional and Fuzzy Logic Controller

generation control (AGC) is a system for balancing the power output of multiple generators at different power plants, in response to changes in the load. In an interconnected power system, fluctuations in frequency caused due to load variations and penetration of renewable resources. Load variations occur in either one area or all areas of the system causes change in system frequency and tie line power. Due to high frequency deviation in interconnected power system could result in system collapse. Load frequency control is one of the most efficient method to solve these kinds of problems. In the proposed method a three-area system is considered i.e., area-1 with thermal power plant, area-2 with hydro power plant and area-3 with distributed generation (i.e., wind power plant, solar power plant etc.). In order to analyze the performance of a three-area system, the system responses are comparing the values of undershoot and settling time for each case using conventional control and Fuzzy logic control techniques separately for 1% disturbance in either area. Load frequency control (LFC) including conventional controller is proposed in order to suppress frequency deviations and area control error (ACE) for a power system involving wind, hydro and thermal plants. A three-area system involving thermal plants, a wind farm and a hydro plant will be modeled using MATLAB. The controller performances are simulated using MATLAB/SIMULINK simulation software.

Power Systems Load Frequency Stability Using Fuzzy Logic PI Controller

In recent years electricity has been used to power more sophisticated and technically complex manufacturing processes, and a variety of high-technology consumer goods. These products and process are sensitive not only to the continuity of power supply but also on the quality of power supply such as voltage and frequency. In power system, both active and reactive power demands are never steady they continuously change with the rising or falling trend. The changes in real power affect the system frequency, while reactive power is less sensitive to changes in frequency and is mainly dependent on Changes in voltage magnitude [1]. Load Frequency Control (LFC) as a major function of Automatic Generation Control (AGC) is one of the important control problems in electric power system design and operation. It is becoming more significant today because of the increasing size, changing structure, emerging new uncertainties, environmental constraints and the complexity of power systems. A large frequency deviation can damage equipment, corrupt load performance, reason of the overloading of the transmission lines and can interfere with system protection schemes, ultimately leading to an unstable condition for the electric power system [2]. Although the active power and reactive power have combined effects on the frequency and voltage, the control problem of the frequency and voltage can be decoupled. The frequency is highly dependent on the active power while the voltage is highly dependent on the reactive power. Thus the control issue in power systems can be decoupled into two independent problems. One is about the active power and frequency control while the other is about the reactive power and voltage control [3].Many investigations in the area of LFC of an isolated power system have been reported and a number of control schemes like integral (I), Proportional and Integral (PI), Proportional, Integral and Derivative (PID) control have been proposed to achieve improved performance [4-7].Fuzzy -PI controllers have been proposed to solve Load Frequency Control problems, and developed different fuzzy rules for the proportional and integral gains separately. in this paper three case studies of Fuzzy -PI controllers different tuning of PI controller. The comparison results suggest that the overshoots and settling time with the proposed Fuzzy -PI controllers’ controller was better.

Load Frequency Control Using Fuzzy Logic Controller of a Three Area System Consisting of a Grid Connected PV System, Hydro and Thermal Systems

ABSTRACT: In this paper the load frequency control of the three area system consisting of thermal, hydro and photovoltaic system. Using modified hill climbing algorithm, the maximum power point tracking is performed in photovoltaic. Combining fuzzy logic with hill climbing algorithm the modified hill climbing is performed. Boost converter is used for this analysis. Using single phase inverter the obtained DC output is converted to AC output. By using sinusoidal pulse width modulation the Grid connection is performed. Transfer function model of the thermal , hydro is interfaced with the photovoltaic system. Load frequency control of this three area system and simulation of the entire system is performed in the MATLAB SIMULINK.

Analysis of Load Frequency Control for a Distributed Grid System Involving Wind, Hydro and Thermal Power Plants using Conventional and Fuzzy Logic Controller

generation control (AGC) is a system for balancing the power output of multiple generators at different power plants, in response to changes in the load. In an interconnected power system, fluctuations in frequency caused due to load variations and penetration of renewable resources. Load variations occur in either one area or all areas of the system causes change in system frequency and tie line power. Due to high frequency deviation in interconnected power system could result in system collapse. Load frequency control is one of the most efficient method to solve these kinds of problems. In the proposed method a three-area system is considered i.e., area-1 with thermal power plant, area-2 with hydro power plant and area-3 with distributed generation (i.e., wind power plant, solar power plant etc.). In order to analyze the performance of a three-area system, the system responses are comparing the values of undershoot and settling time for each case using conventional control and Fuzzy logic control techniques separately for 1% disturbance in either area. Load frequency control (LFC) including conventional controller is proposed in order to suppress frequency deviations and area control error (ACE) for a power system involving wind, hydro and thermal plants. A three-area system involving thermal plants, a wind farm and a hydro plant will be modeled using MATLAB. The controller performances are simulated using MATLAB/SIMULINK simulation software.

Load Frequency Control of Multi Area Hybrid Power System Using Intelligent Controller Based on Fuzzy Logic

The Multi area hybrid controller is designed in MATLAB Simulink for load frequency control [12]. The model is shown in fig. 4. Area 1 has a thermal turbine, Area 2 has thermal turbine with re-heater and area three has hydro turbine. Value of physical constant is taken appropriately. The simulation is done for the 1.5% step load change. The fuzzy system has used “mamdani” inference and having 25 if-then rule set. The fuzzification and de-fuzzification method is shown in fig. 5. This is based on the equation (9) derived above [13]. All the simulation result is compared with the conventional PI control methodology. Area control error is processed through the fuzzy interface with appropriate derivative and proportional constant. Triangular membership function has a range from -0.4 to 0.4 for input and output which is deduced from the optimisation of controller [14]. The graph has been plotted for three area frequency deviation and the graph for comparing the resultant deviation with the intelligent controller and orthodox controller.Tie line power variation with the load frequency is important variable that effect the overall system efficiency is also considered.

Interconnected System for Grid Stability with PI and Fuzzy-PID Controller

Frequency Control is a technical requisite for the appropriate setup of an interconnected power system and it is the precondition for a stable electricity grid and guarantees secure supply at a frequency of 50Hz. An interconnected power system comprises of interconnected control areas. When load changes or abnormal conditions arises like outages of generation and varying system parameters, mismatches in frequency can be began. These incompatibilities can be improved by controlling the frequency. Automatic Generation Control is used to retain the schedule system frequency (1)(2-4)..Next importance is given to the usage of High Voltage DC transmission (HVDC)(1) link in the system instead of high Voltage Alternating Current (HVAC) transmission only. HVDC is a forecast technology due to huge growth of this transmission system and due to its economic, environmental and performance advantages over the other options. Therefore it is planned to have a dc link in parallel with HVAC link interconnecting control areas to get an enhanced system dynamic performance. Those studies are conceded out considering the nominal system parameters. Practically system parameters vary considerably with changing operating conditions. Intelligent controllers can be hired to elucidate this problem. The conventional control technique does not provide control problems including AGC of interconnected power system. Fuzzy logic based controller can be implemented to scrutinize the load frequency control of three area interconnected power system with HVAC and HVDC parallel link taking parameter uncertainties into account. In the system working under deregulated environment, a Wind Turbine Generator(WTG) or other locally generating plants can be replicated using in the to carry out all the planned operations and to control the frequency of the system using AGC and fuzzy Controller with PID(7-9)

Load Frequency Control of Interconnected Hydro-Thermal Power System Using Conventional PI and Fuzzy Logic Controller

Conventional Proportional plus Integral controller (PI) provides zero steady state frequency deviation, but it exhibits poor dynamic performance (such as number of oscillation and more settling time), especially in the presence of parameters variation and nonlinearity [10].In PI Controller Proportionality constant provides simplicity, reliability, directness etc. The disadvantage of offset in it is eliminated by integration but this system will have some oscillatory offset. The control signals can be written as:

Design of Fuzzy Logic Controller for a PV Grid Connected Two Area Load Frequency Control System

Fig -4: Change of frequency of both areas (for the system with integral controller only) for reasonable load. It is observed that without using the integral controller the steady state frequency error does not disappear, which is undesirable. When including the integral controller, the steady state error requirement is met, however the settling time is much larger than the required 3s (it is more than 18s in both cases) and the undershoot is also much larger than the required 0.02 Hz. The second case of a sudden increase in load equal to 50% is an extreme case. However, even in the first case (i.e. reasonable change in load power), neither the undershoot nor the settling time criteria were met with integral controller only. Thus, FL controller is designed to enhance the system performance in terms of system frequency.

Frequency Error and Voltage Control by using PI and Fuzzy Logic Controllers for Multi Area Inter Connected Power System

Fuzzy logic controller has been used in both the thermal- thermal and hydro-thermal inter connected areas. Attempt has been made to examine with five number of triangular membership functions (MFs) which provides better dynamic response with the range on input (error in frequency deviation and change in frequency deviation) i.e. universe of discourse is -0.25 to 0.25. The number of rules is 25. The dynamic response are obtained and compared to those obtained with conventional integral controllers [3]. Further, several inputs have been tried out and dynamic responses are examined in order to decide suitable inputs to the fuzzy logic controller (FLC).

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

generation control scheme in electric power systems. Among the various types of load frequency controllers, the most widely employed is the conventional proportional integral (PI) controller. The PI, PID and Fuzzy-PID and ANFIS controllers are very simple for implementation and gives better dynamic response, but their performance deteriorate when the complexity in the system increases due to disturbance like load variation . Therefore, there is need of controllers which can overcome these problems. The artificial intelligent controllers like fuzzy and neural control approaches are more suitable in this respect. Literature survey shows that most of earlier work in the area of LFC pertains to interconnected reheat thermal power system. In this paper, the performance evaluation based on ANFIS, Fuzzy-PID and conventional PID for two area thermal interconnected system.

Comparison of Multi-Area Load Frequency Control by PI and Fuzzy Logic Controller Using SMES

To be effective in load frequency control application, the energy storage system should be fast acting i.e. the time lag in switching from receiving (charging) mode to delivering (discharging) mode should be very small. For damping the swing caused by small load perturbations the storage units for LFC application need to have only a small quantity of stored energy, though its power rating has to be high, since the stored energy has to be delivered within a short span of time. However, due to high cost of superconductor technology, one can consider the use of non-superconducting of lossy magnetic energy storage (MES) inductors for the same purpose. Such systems would be economical maintenance free, long lasting and as reliable as ordinary power transformers.

Load Frequency Control in an Interconnected Hydro Power System with SMES and SCES Units

The Fig.2 shows the basic configuration of a SMES unit in the power system. The superconducting coil can be charged to a set value (which is less than the full charge) from the utility grid during normal operation of the grid. The DC magnetic coil is connected to the AC grid through a Power Conversion System (PCS) which includes an inverter/rectifier. Once charged, the superconducting coil conducts current, which supports an electromagnetic field, with virtually no losses. The coil is maintained at extremely low temperature (below the critical temperature) by immersion in a bath of liquid helium.

ABSTRACT : The paper proposes a high step up boost converter. The proposed converter has used a coupled inductor

Due to energy crisis and environmental issues such as pollution and global warming effect, photovoltaic (PV) systems are becoming a very attractive solution. Unfortunately the actual energy conversion efficiency of PV module is rather low. So to overcome this problem and to get the maximum possible efficiency, the design of all the elements of the PV system has to be optimised. In order to increase this efficiency, MPPT controllers are used. Such controllers are becoming an essential element in PV systems. A significant number of MPPT control schemes have been elaborated since the seventies, starting with simple techniques such as voltage and current feedback based MPPT to more improved power feedback based MPPT such as the perturbation and observation (P&O) technique or the incremental conductance technique [1-2]. Recently intelligent based control schemes MPPT have been introduced. Some converters operate at very high frequency with fast transient response. The main switch is fabricated from an integrated power process, the layouts can be changed to vary the parasitic, however design of switch layout is complex, fixed frequency and constant duty ratio must be maintained [5]. This converter provides high voltage gain and can be employed for high power applications however the duty ratio is limited to 0.85 [4]. In this, the energy of the leakage inductor is recycled to the output load directly, limiting the voltage spike on the main switch. To achieve a high step-up gain, it has been proposed that the secondary side of the coupled inductor can be used as boost and buck-boost converters [3-4].

Three Area Power System Control System Design using PSO with PID for Load Frequency Control

For large scale power systems which normally consist of interconnected control areas, load frequency control (LFC) is important to keep the system frequency and the inter-area tie power as near to the scheduled values as possible. Because loading of a given power system is never constant and to ensure the quality of power supply, a load frequency controller is needed to maintain the system frequency at the desired nominal value. In a deregulated power system, each control area contains different kinds of uncertainties and various disturbances due to increased complexity, system modeling errors and changing power system structure Therefore, a control strategy is needed that not only maintains constancy of frequency and desired tie-power flow but also achieves zero steady state error and inadvertent interchange. Among the various types of load frequency controllers, the most widely employed is the conventional proportional integral (PI) controller.

Design of Fuzzy PI Load Frequency Controller for Hybrid Wind Diesel system with SMES unit

Damping torque is produced to overcome rotor oscillation. To achieve better performance fuzzy logic can be implemented in a more effective way for load frequency controller. The fuzzy controller considered, has two phases, first being the fuzzy system unit where the Area Control Error (ACE) and its derivative (dACE) are set as input parameters. Before being connected to the output a rule base is created in the Mamdani controller. It is a common practice to build a rule base from terms such as s, z, and b representing labels of fuzzy sets. An input family may consist of those three terms. Consequently, with two inputs it is possible to build 3 x 3 = 9 rules. Nine rules is a manageable amount often used in practice, and the same is used here. The fuzzy codes are written in the .fis file in MATLAB using AND function in the Mamdani inference using triangular membership functions. The rules highly depend on the membership function, the rules are set in appropriate collection of input and output parameters. The fuzzy controller is implemented with and without an SMES unit. Both the results are separately shown in the results section.

Fuzzy controlled SMES System for load leveling

Fuzzification: The fuzzification procedure consists of finding appropriate membership functions to describe crisp data. For the design of the proposed FLC, power mismatch, ∆p, and firing angle of thyristor, α, are selected as the input and output, respectively. Triangular membership functions for are shown in Figure 3, in which the linguistic variables N, Z, and P stand for negative, zero, and positive, respectively. The membership functions have been determined by the trial and error approach in order to obtain the best system performance. The equation of the triangular membership function used to determine the grade of membership values is as follows 3 :

Comparative Study of Load Frequency Control using PID and Fuzzy PID Controller in Power System

------------------------------------------------------------------------***------------------------------------------------------------------------- Abstract - In this paper, load frequency control is one of the efficient ways to solve various problems in power system. The different configuration of models and control techniques are applied for load frequency control have been addressed which are applicable for generation system. An interconnected system for two areas is designed and simulated by using fuzzy logic controller for improved performance parameter. Like:-setting time, overshoot value, and undershoot value and maximum range over the conventional PID controller. The control methodology assures that the steady state error of frequency and exchange of tie-line power of area maintain within prescribed limit. The working of the two area system incorporating these controllers are simulated using MATLAB/Simulink packages.