Abstract— In this paper the Artificial Neural Network (ANN) Controller for **load** **frequency** **control** of Multi area power system is presented. The performances of ANN Controller and conventional PI controllers are compared for Single area and Multi area power system with non-reheat turbines. The effectiveness of the proposed controller is compared by applying **load** disturbances. The dynamic response of the **load** **frequency** **control** problem is studied using MATLAB Simulink package. The results indicate that ANN Controller exhibits better performance.

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The detailed block diagram modeling of two area thermal-thermal power system for **load** **frequency** **control** investigated is shown in figure 1. Each area is assumed to have only one equivalent generator and is equipped with governor- turbine system. The **load** flow controller shown in Fig. 1 is based upon tie-line bias **control**, where each area tends to reduce the Area **Control** Error (ACE) to zero. The ACE given in Eq. (1) for each area consists of a linear combination of **frequency** and tie-line power deviation [1]

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the reactive power is shorted susceptive to change in the **frequency** and is mainly subordinate on the motility of the voltage magnitude. Therefore, the **control** of active and reactive power in the electrical power system is trade separately. So weight **frequency** **control** is mainly related to system **frequency** and actual power **control**, while the automatic voltage regulator loop controls is used to change in the reactive power and voltage appearance and magnitude. **Load** **Frequency** **control** is an elevated level of many promotions and advanced concepts, which governs the dimensions of the electrical power system. **Load** **Frequency** **Control** (LFC) has a basic **control** structure or arrangement, of parts of the machine and similar devices in term of power system operation and **control**. **Load** **Frequency** **Control** use to keep the uniform **frequency** during changing **load**. When system **frequency** is changed, the main problem is that the system output of generating units cannot be controlled with in specified limit is called **load** **frequency** **control** (LFC) [6-8]. The speed depends on the **frequency** of the alternative current power supply. These are the main situation when speed permanence is required to be higher order. Electrical chronometers are operated by synchronous motors. The precision of the chronometer do not depend only on the **frequency** but the integral part of the **frequency** error. If the normal **frequency** of any network is 50 hertz, and the network **frequency** falls below 48.5 hertz, and goes to high level 51.5

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ANN is implemented to the process which is under **control**. Nguyen and Widrow have shown in a novel approach the use of this method for backing up a trailer in a two dimensional plane. Kong and Koskotried also the same approach, but used the truck kinematic equation instead of truck emulator as used by Nguyen. Beau- fays et al. have used this method for **load** **frequency** **control** in power systems. Generally, the off-line method is applicable to a process with explicit mathematical formulation.

Fig.1. shows the schematic diagram for automatic **load** **frequency** **control** (ALFC). In this structure turbine is fed by steam or water input. The input of the turbine can be controlled by valve. A turbine is a rotating mechanical device that extracts energy from a fluid flow and converts it into mechanical energy. A turbine is a turbo machine with at least one rotating part called a rotor, which is a shaft or drum with blades attached. Moving fluid acts on the blades so that they move and impart rotational energy to the rotor. This turbine may be a water turbine, steam turbine, gas turbine or wind turbine. The turbine shaft is mechanically coupling to the alternator. The alternator converts mechanical energy into electrical energy. This electrical energy can be given to grid through an interfacing transformer.

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Abstract: This paper describes about **load** **frequency** **control** problem in power systems by using multi-verse optimization algorithm (MVO). This paper compares the controlling of LFC with PID and PID+MVO controllers. In this paper four area hydrothermal networks was represented.MVO algorithm was introduced in this paper for tuning the secondary controllers. The concept of MVO is runs on white hole, black hole and warm hole. Inflation rates of universe can be calculated and implemented in PID. This paper was implemented in simulator (MATLAB/SIMULINK) software.

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This paper deals with the Particle Swarm Optimisation (PSO) tuned **Load** **Frequency** **Control** (LFC) of single area power system, with diversified power sources. The diversified generating units considered for the purpose of LFC study are thermal, hydro and gas power plants. Hybrid power system increases the reliability of the supply and instigates economic/feasible system operation. System **frequency** gets affected due to real power changes, this is regulated using **Load** **Frequency** **Control** (LFC). The hybrid interconnected power system with various generating units imposes additional complexity in the tuning of controllers. Thus in this paper PSO based tuning is imposed to obtain sophisticated **control** parameters for LFC of Hybrid power system.

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Abstract: With the increasing penetration of renewables in power systems, **frequency** regulation is proving to be a major challenge for system operators using slower conventional generation units, and alternative means to provide faster regulation are being actively sought. The participation of demand side management in ancillary service provision is proven in a number of energy markets, yet its full potential to benefit **frequency** regulation, including the exploitation of fast power ramping capability of some devices, is still undergoing research. In this paper, a novel approach to improve the speed of response of **load** **frequency** **control**, a secondary **frequency** **control**, approach is proposed. The proposed **control** is enabled by an effective location identification technique, is highly resilient to anticipated system changes such as reduction of inertia, and enables fully decentralized power system architectures. The effectiveness of the approach is demonstrated and compared to that of present day regulation **control**, by means of real-time simulations incorporating appropriate time delays conducted on a five-area reduced model of the Great Britain power system. The applicability of the method is further proven under realistic communications delays and measurements experimentally using a controller and power hardware-in-the-loop setup, demonstrating its critical support for enabling the stable operation of future power systems.

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Abstract: Recently several robust **control** designs have been proposed to the **Load**- **Frequency** **Control** (LFC) problem. However, the importance and difficulties in the selection of weighting functions of these approaches and the pole-zero cancellation phenomenon associated with it produces closed loop poles. Also the order of robust controllers is as high as the plant. This gives rise to complex structure of such controllers and reduces their applicability in industry. In addition conventional LFC systems that use classical or trial-and-error approaches to tune the PI controller parameters are more difficult and time-consuming to design. In this paper, a bisection search method is proposed to design well-tuned PI controller in a restructured power system based on the bilateral policy scheme. The new optimized solution has been applied to a 3-area restructured power system with possible contracted scenarios and the results evaluation shows the proposed method achieves good performance compared with recently powerful robust controllers. Keywords: Bisection Search, Deregulated Environment, **Load**-**Frequency** **Control**.

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A Proportional-Integral-Derivative(PID) tuning method of Power system **load** **frequency** **control** was proposed on a Ziegler-Nichols, Tyrens-Luyben, Internal Model **Control** and Direct Synthesis method. The simulation results shown in fig 5 and table 3. It confirms that the Direct Synthesis controller with simple design approach and smaller rule can provide better performance comparing with the Ziegler-Nichols tuned PID controller, Tyrens-Luyben and IMC based PID controller. In this paper **load** **frequency** **control** was proposed order reduction technique to reduce higher order to second order plus dead time(SOPDT) and first order plus dead time(FOPDT) and reduced model order has been obtained by resembling the coefficient from Taylor series approximation. The performance of the closed loop system has effectively improved with second order reduced system model instead of full order system with PID controller with different type of tuning techniques(Internal

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Small power changes mainly depends on or f . Moreover, **frequency** is also a major stability criterion for large-scale stability in multi area power systems. To provide the stability, a constant **frequency** is required which depends on active power balance. If any change occurs in active power demand/ generation in power systems, **frequency** cannot be hold as its rated value. Hence, oscillations increase in both power and **frequency**[7-8]. Thus, the system is subjected to a serious instability problem. To improve the stability 34 of the power networks, it is necessary to design **load** **frequency** **control** (LFC) systems that **control** the power generation and active power at tie lines of interconnected system. In interconnected power networks with two or more areas, the generation within each area has to be controlled to maintain the scheduled power interchange. **Load** **frequency** **control** scheme has two main **control** loops. These are primary **control** and secondary **control** loops. This action has been realized by using a turbine-governor system in the plant[9- 10] .

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The continuous growth in size and complexity of interconnected power systems, along with both area **frequency** and tie-line power interchange. The main purpose of **load** **frequency** **control** (LFC) is to sustain **frequency** of the system under prescribed limits and check the fluctuations on tie-line loading in case of multi area power system. Past year Automatic generation **control** (AGC) system specifies an applicable way to hold a **control** over the **frequency** and tie line power flow. Different methods have been suggested for **Load** **Frequency** **Control**. The best common technique which is commonly used around world since few years is based Proportional Integral (PI) controllers, but with exponentially increasing electricity market essential for more progressive **control** techniques arises for correct effective of large numbers of interconnected multi area generating units. The **control** of **load** **frequency** and the operational aspect of automatic generation **control** for a multi area hybrid interconnected power system In the large interconnected power system the risk of network failure is increased many times as the system **frequency** is related to Active power. The two predictable controllers are based on the theories of PI and artificial neural network which is being tested on the three area interconnected hybrid power system which embraces thermal power plant with and without re-heater and hydro power plant with different loading. As it is apparent that **frequency** **control** is laggard **control** when paralleled against voltage **control** so it is necessary to reduce the transient time in **load** **frequency** **control** to boost the overall power system performance. Both the proposed controller is discussed in details with respect to their working and implementation in interconnected power system network completely replacing the present day PI controller. An iterative linear estimate built matrix algorithm is framed to linearize the system. Modern **control** technique based on network Fuzzy Logic based Controller (FLC),Artificial Neural Network (ANN), and genetic algorithm crafted are assessed for LFC problem. Yet bountiful exertion have been made for optimizing predictable LFC but very less exertion for designing intelligent controller for multi area power system.

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In this paper, a new technique for **load** **frequency** **control** is adopted in general the **frequency** is controlled by using a dump **load**, whose rating is equal to the rated power output of the plant. The new scheme proposed reduces the size of the dump **load** by controlling input power of the hydro power plant using on/off controls. The water ﬂowing through the penstock is rerouted in smaller pipes, two or three ﬁtted with motor operated valves. The opening or closing of the valves is achieved by on/off controls. The on/off **control** linearly raises or lowers the generation. A transfer function model for the system is developed with an on/off **control** logic. Finally, system transient’s performance is compared for the case of two –pipe (50% dump **load**) and the three-pipe (30% dump **load**).

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GWO is one of the recently obtained meta-heuristic procedures. In this paper GWO and GWO-BFO are used to explain **load** **frequency** **control** problem for two area thermal system. The simulation conclusion shows that gains of hybrid technique GWO- BFO are better to resolve **Load** **frequency** problem in power scheme. The algorithm is planned in MATLAB (R2009b) software package.

Abstract - In this paper an extensive literature review on **load** **frequency** **control** (LFC) problem in power system has been highlighted. The various configuration of power system models and **control** techniques/strategies that concerns to LFC issues have been addressed in conventional as well as distribution generation based power systems. Further, investigations on LFC challenges incorporating storage devices BESS/SMES, FACTS devices, wind–diesel and PV systems etc. have been discussed too.

[4] Ndubisi Samuel .N., “A single area **load** **frequency** **control**: a comparative study based on pi, optimal and fuzzy logic controllers”, American Journal Of Scientific And Industrial Research, pp. 748-754, Vol. - 2(5), 2011. [5] Surya Prakash and S.K. Sinha, “**Load** **frequency** **control** of three area interconnected hydro-thermal reheat power system using artificial intelligence and PI controllers”, International Journal of Engineering, Science and Technology, pp. 23-37, Vol. 4, No. 1, 2011.

Fig.1 shows two area non reheat thermal power systems and their rating are 2000 MW (area-1 and area-2) with a nominal **load** of 1000 MW. Two area non-reheat thermal system is extensively used in the literature for design and investigation of automatic **load** **frequency** **control** of interconnected areas [25]. Fig.1 shows different parameter classifies as B1& B2-**frequency** bias parameters; ACE1 & ACE2 -area **control** errors; u1&u2 -**control** outputs from controller; R1 &R2 - governor speed regulation parameters(p.u.); TG1 &TG2-speed governor time constants(seconds); ∆PV1 &∆PV2 -change in governor valve positions (p.u.); ∆PG1& ∆PG2 - governor output command (p.u.); TT1 & TT2 - turbine time constant(seconds); ∆PT1 & ∆PT2 - change in turbine output powers; ∆PD1 & ∆PD2-**load** demand changes; ∆Ptie -incremental change in tie line power (p.u.); KP1 &KP2 -power system gains; TP1 &TP2 - power system time constant(seconds); T12 - synchronizing coefficient and ∆F1 &∆F2 -system **frequency** deviations(Hz). The generation of power by Thermal power plants can be modified or changed at a specific maximum rate (2-5% per min) and this is Generation Rate Constraint (GRC). Both areas of the power system consist of the speed governing system, turbine and generator. Both areas have three inputs and two outputs. The inputs are the controller input ∆Pref (also denoted as u), **load** disturbance ∆PD and tie-line power error ∆Ptie the outputs are the generator **frequency** ∆F and Area **Control** Error (ACE).

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In this paper, the Adaptive Neuro Fuzzy Inference System based **Load** **Frequency** **Control** is proposed for a two area power system in each **control** area. The results have been compared with conventional PI controller. The results proved that the Adaptive Neuro Fuzzy Inference System based LFC gives better response as compared to conventional controller in terms of peak overshoot, settling time and steady sate error. Proposed ANFIS controller is not only simple to design but also easy to implement. Moreover, the ability to adapt to disturbances makes the proposed controller more effective. Also the learning ability of ANFIS architecture can be used to generate mature membership functions and fuzzy rules based on training data when the human export knowledge is not reliable.

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If there is a small change in **load** power in a single area power system operating at set value of **frequency** then it creates mismatch in power both for generation and demand. This mismatch problem is initially solved by kinetic energy extraction from the system, as a result declining of system **frequency** occurs. As the **frequency** gradually decreases, power consumed by the old **load** also decreases. In case of large power systems the equilibrium can be obtained by them at a single point when the newly added **load** is distracted by reducing the power consumed by the old **load** and power related to kinetic energy removed from the system. Definitely at a cost of **frequency** reduction we are getting this equilibrium. The system creates some **control** action to maintain this equilibrium and no governor action is required for this. Each output **frequency** finds the information about its own area and the tie line power deviation finds the information about the other areas. Thus the **load** **frequency** **control** of a multi area power system generally incorporates proper **control** system, by which the area frequencies could brought back to its predefined value or very nearer to its predefined value so as the tie line power, when the is sudden change in **load** occurs.

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Large scale power systems were normally composed of **control** areas or regions representing coherent groups of generators. An interconnected power system is basically a large power system consisting of a number of power systems. These power systems or areas were connected by tie lines[1]. The objectives of a **control** strategy is to generate and deliver power to an interconnected power system as economically and reliably as possible, while maintaining the voltage and **frequency** within permissible limit. The **Load** **Frequency** **Control** (LFC) loop controls the real power and **frequency**, while the Automatic Voltage regulator (AVR) loop controls the reactive power and voltage. With the growth of interconnected power system, LFC has gained more importance. It should be noted that in this linearized model of the AGC, hence is based on an assumption that the **frequency** and tie line power deviations are small as referred in [2].

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