7,598 research outputs found

    A new scaled fuzzy method using PSO segmentation (SePSO) applied for two area power system

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    The balance of the power supply and demand (frequency control) is one of the most ancient approaches for the power systems, which is considered as a highly complex system.The power systems frequency response is a perfect indicator of the resilience to the multi-disturbances. In this work, the fuzzy logichas been scaledusing PSO segmentation (SePSO) and suggested to get high performance of frequency stability. PSO has participated into multi-segments for calculating the scald-fuzzy membership with basic rules. Two identical interconnectedpower areas wereselected to exam the new scaled fuzzy method. The time response of the results has undertaken the effectiveness of the controller reactionusing the MATLAB Simulink. The work feed back proved that the proposed SePSO optimization for the controlhas significantly faster with low undershot concerningthe classical controllers in differenttime schedules and disturbance values

    Chaotic multi-objective optimization based design of fractional order PI{\lambda}D{\mu} controller in AVR system

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    In this paper, a fractional order (FO) PI{\lambda}D\mu controller is designed to take care of various contradictory objective functions for an Automatic Voltage Regulator (AVR) system. An improved evolutionary Non-dominated Sorting Genetic Algorithm II (NSGA II), which is augmented with a chaotic map for greater effectiveness, is used for the multi-objective optimization problem. The Pareto fronts showing the trade-off between different design criteria are obtained for the PI{\lambda}D\mu and PID controller. A comparative analysis is done with respect to the standard PID controller to demonstrate the merits and demerits of the fractional order PI{\lambda}D\mu controller.Comment: 30 pages, 14 figure

    Review on load frequency control for power system stability

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    Power system stability is the capability of power systems to maintain load magnitude within specified limits under steady state conditions in electrical power transmission. In modern days, the electrical power systems have grown in terms of complexity due to increasing interconnected power line exchange. For that, an inherent of controllers were essential to correct the deviation in the presence of external disturbances. This paper hence aims to review the basic concepts of power system stability in load frequency control. Various control techniques were analyzed and presented. Power system stability can be classified in terms of method to improve power system stability, which are rotor angle stability, frequency stability and voltage stability. It is found that each method has different purpose and focus on solving different types of problem occurred. It is hoped that this study can contribute to clarify the different types of power system stability in terms of where it occurs, and which is the best method based on different situation

    AGC of a multi sources power system with natural choice of power plants

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    This paper presents an application of optimal control theory in multi sources power system by considering natural choice of power plants participating in automatic generation control (AGC) scheme. However, for successful operation of large power system, the natural choices of generation suitable for AGC system are hydro and thermal power plants since gas and nuclear power plants are rarely participates in the AGC scheme. Therefore, this work presents design and implementation of proportional integral (PI) structured optimal AGC controller in the presence of hydro and thermal power plants by using state vector feedback control theory. Moreover, various case studies are identified to obtain: (i) Cost aspects of physical realization of optimal AGC controller, (ii) Closed loop system stability margin through patterns of eigenvalues and (iii) System dynamic performance. Further, results have shown that when optimal AGC scheme is implemented in power system, the dynamic performance of power system is outstanding over those obtained with genetic algorithms (GAs) tuned PI structured AGC controller. Besides, with optimal AGC controller, cheaper cost of control structure, increased in system closed loop stability margin and outstanding dynamic performance of power system have been found when lessening in hydro generation is replaced by generation from thermal power plants for various case studies under investigation

    Introducing LQR-fuzzy for a dynamic multi area LFC-DR model

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    It is well known that Load Frequency Control (LFC) model plays a vital role in electric power system design and operation. In the literature, much research works has stated on the advantages and realization of DR (Demand Response), which has proved to be an important part of the future smart grid. In an interconnected power system, if a load   demand changes randomly, both frequency and tie line power varies. LFC-DR model is tuned by standard controllers like PI, PD, PID controllers, as they have constant gains. Hence, they are incapable of acquiring desirable dynamic performance for an extensive variety of operating conditions and various load changes. This paper presents the idea of introducing a DR control loop in the traditional Multi area LFC model (called LFC -DR) using LQR- Fuzzy Logic Control. The effect of DR-CDL i.e. (Demand Response Communication Delay Latency) in the design is also considered and is linearized using Padé approximation. Simulation results shows that the addition of DR control loop with proposed controller guarantees stability of the overall closed-loop LFC-DR system which effectively improves the system dynamic performance and is superior over a classical controller at different operating scenarios

    Self-adaptive fuzzy-PID controller for AGC study in deregulated Power System

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    The aim of this paper elucidates the AGC issues in a large scale interconnected power system incorporating HVDC link under the deregulated environment. The performance of the system is degraded under the influence of abrupt load change, and parameter variation. To perceive a reliable and quality power supply, secondary robust controllers are essential. A novel self-adaptive Fuzzy-PID controller is proposed to ameliorate the dynamic performance of both the conventional PID and Fuzzy-PID controller, employed in the restructured power system. In self-adaptive Fuzzy-PID controller unlike the Fuzzy-PID controller, the output scaling factors are tuned dynamically while the controller is functioning. These three controllers are designed by enumerating different gains and scaling factors, applying a budding nature-inspired algorithm known as Wild Goat Algorithm (WGA). The superior dynamic performance of frequency and tie-line power deviation under self-adaptive Fuzzy-PID controller in comparison to its' counterparts is investigated by dispatching the scheduled and unscheduled power under different contracts such as poolco based transaction, bilateral transaction and contract violation based transaction through different tie-lines. The dynamic response under parameter variation and random load perturbation confers the robustness of the proposed controller

    Load frequency controllers considering renewable energy integration in power system

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    Abstract: Load frequency control or automatic generation control is one of the main operations that take place daily in a modern power system. The objectives of load frequency control are to maintain power balance between interconnected areas and to control the power flow in the tie-lines. Electric power cannot be stored in large quantity that is why its production must be equal to the consumption in each time. This equation constitutes the key for a good management of any power system and introduces the need of more controllers when taking into account the integration of renewable energy sources into the traditional power system. There are many controllers presented in the literature and this work reviews the traditional load frequency controllers and those, which combined the traditional controller and artificial intelligence algorithms for controlling the load frequency

    Load frequency control scheme for a microgrid system with the application of hTLO-DE algorithm

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    Load frequency control (LFC) is a crucial feature of electric power systems to maintain a balance between power supply and load demand, thus avoiding a deviation of the grid frequency. The present work aims to implement an effective LFC scheme for a microgrid system consisting of a diesel generator (DEG), a wind turbine generator (WTG) and a battery storage system. Proportional-integral-double-derivative (PIDD) controllers are used to implement the proposed LFC scheme. The controller parameters are computed using an innovative hybrid teaching-learning-optimization differential-evaluation (hTLO-DE) algorithm. The main scope of the work lies in application of hTLO-DE optimized PIDD controllers in DEG-WTG-battery storage based MG system. The results obtained with PIDD controllers are compared with those obtained with the traditional PI and PID controllers. A critical analysis shows that the PIDD controller can provide better dynamic responses in terms of settling time and magnitude of oscillations compared to PI and PID controllers. The frequency responses of the system are studied under different scenarios of generation and load variations, which establishes the robustness of the proposed PIDD-based LFC scheme

    A novel hybrid many optimizing liaisons gravitational search algorithm approach for AGC of power systems

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    A hybrid Many Optimizing Liaisons Gravitational Search Algorithm (hMOL-GSA)-based fuzzy PID controller is proposed in this work for Automatic Generation Control problem. MOL is a simplified version of particle swarm optimization which ignores the particle best position consequently simplifying the algorithm. The proposed method is employed to tune the fuzzy PID parameters. The outcomes are equated with some newly proposed methods like Artificial Bee Colony (ABC)-based PID for the identical test systems to validate the supremacy of GSA and proposed hMOL-GSA techniques. Further, the design task has been carried out in a three-area test system and the outcomes are equated with newly proposed Firefly Algorithm (FA) optimized PID and Teaching Learning-Based Optimization (TLBO) tuned PIDD controller for the identical system. Better system response has been observed with proposed hMOL-GSA method. Finally, sensitivity study is being carried out and robustness of the proposed method is established
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