239 research outputs found

    Co-ordinated Design of PSS and TCSC Damping Controllers in Multi-machine Power System using PSO

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    Transmission networks of modern power systems are becoming increasingly stressed because of growing demand and restrictions on building new lines. One of the consequences of such a stressed system is the threat of losing stability following a disturbance. Transient stability improvement is essential for maintaining system security that is the incidence of a fault should not lead to tripping of generating unit due to loss of synchronism. Flexible ac transmission system (FACTS) devices are found to be every effective in stressing a transmission network for better utilization of its existing facilities without sacrificing the desired stability margin. Amongst the available FACTS devices for transient stability enhancement, the TCSC is the most versatile one and it is a series FACTS device which allows continuous changes of the transmission line impedance. It has great application and potential in accurately regulating the power flow on a transmission line, damping inter-area power oscillations and improving the transient stability. Power System Stabilizer (PSS) which detects changes in the generator output power and by controlling the excitation value it reduces the power swings in the system. This Report presents coordinated control tuning of PSS with TCSC. The design of proposed coordinated damping controller is formulated as an optimization problem and the controller gains are optimized instantaneously using particle swarm optimization (PSO). Here single machine infinite bus system and the multi-machine power system employed with PSS and TCSC is considered. The coordinated tuning among the damping controllers is performed on the non-linear power system dynamic model. Finally, the proposed coordinated controller performance is discussed with time domain simulations. Different loading conditions are employed on the test system to test the robustness of proposed coordinate controller and the simulation results are compared with four different control schemes

    Enhancing the performance of flexible AC transmission systems (FACTS) by computational intelligence

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    The thesis studies and analyzes UPFC technology concerns the management of active and reactive power in the power networks to improve the performance aiming to reach the best operation criteria. The contributions of the thesis start with formatting, deriving, coding and programming the network equations required to link UPFC steady-state and dynamic models to the power systems. The thesis derives GA applications on UPFC to achieve real criteria on a real world sub-transmission network. An enhanced GA technique is proposed by enhancing and updating the working phases of the GA including the objective function formulation and computing the fitness using the diversity in the population and selection probability. The simulations and results show the advantages of using the proposed technique. Integrating the results by linking the case studies of the steady-state and the dynamic analysis is achieved. In the dynamic analysis section, a new idea for integrating the GA with ANFIS to be applied on the control action procedure is presented. The main subject of the thesis deals with enhancing the steady-state and dynamics performance of the power grids by Flexible AC Transmission System (FACTS) based on computational intelligence. Control of the electric power system can be achieved by designing the FACTS controller, where the new trends as Artificial Intelligence can be applied to this subject to enhance the characteristics of controller performance. The proposed technique will be applied to solve real problems in a Finnish power grid. The thesis seeks to deal, solve, and enhance performances until the year 2020, where the data used is until the conditions of year 2020. The FACTS device, which will be used in the thesis, is the most promising one, which known as the Unified Power Flow Controller (UPFC). The thesis achieves the optimization of the type, the location and the size of the power and control elements for UPFC to optimize the system performance. The thesis derives the criteria to install the UPFC in an optimal location with optimal parameters and then designs an AI based damping controller for enhancing power system dynamic performance. In this thesis, for every operating point GA is used to search for controllers' parameters, parameters found at certain operating point are different from those found at others. ANFISs are required in this case to recognize the appropriate parameters for each operating point

    Voltage Stability Assessment and Enhancement in Power Systems

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    Voltage stability is a long standing issue in power systems and also is critical in the power system. This thesis aims to address the voltage stability problems. When wind generators reach maximum reactive power output, the bus voltage will operate near its steady-state stability limit. In order to avoid voltage instability, a dynamic L-index minimization approach is proposed by incorporating both wind generators and other reactive power resources. It then verifies the proposed voltage stability enhancement method using real data from load and wind generation in the IEEE 14 bus system. Additionally, power system is not necessary to always operate at the most voltage stable point as it requires high control efforts. Thus, we propose a novel L-index sensitivity based control algorithm using full Phasor measurement unit measurements for voltage stability enhancement. The proposed method uses both outputs of wind generators and additional reactive power compensators as control variables. The L-index sensitivity with respect to control variables is introduced. Based on these sensitivities, the control algorithm can minimise all the control efforts, while satisfying the predetermined L-index value. Additionally, a subsection control scheme is applied where both normal condition and weak condition are taken into account. It consists of the proposed L-index sensitivities based control algorithm and an overall L-index minimisation method. Threshold selection for the subsection control scheme is discussed and extreme learning machine is introduced for status fast classification to choose the method which has less power cost on the transmission line. Due to the high cost of PMUs, a voltage stability assessment method using partial Phasor measurement unit (PMU) measurements is proposed. Firstly, a new optimisation formulation is proposed that minimizes the number of PMUs considering the most sensitive buses. Then, extreme learning machine (ELM) is used for fast voltage estimation. In this way, the voltages at buses without PMUs can be rapidly obtained based on the PMUs measurements. Finally, voltage stability can be assessed by using L-index

    Study and Analysis of Power System Stability Based on FACT Controller System

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    Energy framework soundness is identified with standards rotational movement and the swing condition administering electromechanical unique conduct. In the exceptional instance of two limited machines, the basis of equivalent territory security can be utilized to ascertain the basic clearing point in the force framework, It is important to look after synchronization, in any case the degree of administration for customers won't be accomplished. This term steadiness signifies "looking after synchronization." This paper is an audit of three kinds of consistent state. The main sort of adjustment, consistent state steadiness clarifies the most extreme consistent state quality and force point chart. The transient solidness clarifies the wavering condition and the idleness steady while dynamic soundness manages the transient security time frame. There are a few different ways to improve framework soundness a portion of the techniques are clarified. Versatile AC Transmission Frameworks (FACTS) Flexible AC Transmission System (FACTS) regulators have been utilized frequently to comprehend the different issues of a non-variable force structure. Versatile AC Transmission Frames or FACTS are devices that permit versatile and dynamic control of intensity outlines. Improving casing respectability has been explored with FACTS regulators. This examination focuses to the upsides of utilizing FACTS apparatuses with the explanation behind improving electric force tire activity. There has been discussion of an execution check for different FACTS regulators

    Facts-based stabilizers for power system stability enhancement

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    Facts-based stabilizers for power system stability enhancement

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    Power system damping controllers design using a backstepping control technique

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    The objective of this dissertation is to design and coordinate controllers that will enhance transient stability of power systems subject to large disturbances. Two specific classes of controllers have been investigated, the first one is a type of supplementary signals added to the excitation systems of the generating units, and the second is a type of damping signal added to a device called a Static Var Compensator that can be placed at any node in the system. To address a wide range of operating conditions, a nonlinear control design technique, called backstepping control, is used. While these two types of controllers improve the dynamic performance significantly, a coordination of these controllers is even more promising. Control coordination is presented in two parts. First part concerns simultaneous optimization of selected control gains of exciter and SVC in coping with the complex nature of power systems. Second part proposes a combination of reinforcement learning and a backstepping control technique for excitation control system. The reinforcement learning progressively learns and adapts the backstepping control gains to handle a wide range of operating conditions. Results show that the proposed control technique provides better damping than conventional power system stabilizers and backstepping fixed gain controllers

    Improvement of active distribution systems with high penetration capacities of shunt reactive compensators and distributed generators using Bald Eagle Search

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    This work proposes an intelligent allocation of distributed generation (DG) units and shunt reactive compensators (SRC) with high penetration capacities into distribution systems for power loss mitigation using the Bald Eagle Search (BES) optimization algorithm. The intelligent allocation causes a reduction in voltage variations and enhances the voltage stability of the systems. The SRC units include shunt capacitors (SC), Static Var Compensators (SVC), and Distribution Static Compensators (DSTATCOM), which are determined according to their capacities. The optimization study includes the 33-bus and the 118-bus distribution systems as medium to large systems. Performance parameters, including the reactive power loss, Total Voltage Deviation (TVD), and Stability Index (SI), besides the power loss, are recorded for each optimization case study. When the BES algorithm optimizes 1, 2, and 3 DG units operating at optimal power factor (OPF) into the 33-bus systems, percentage reductions of power loss reach 67.84%, 86.49%, and 94.44%, respectively. Reductions of 28.26%, 34.47%, 35.24%, and 35.44% are achieved in power loss while optimizing 1, 3, 5, and 7 SRC units. With a combination of DG/SRC units, the power loss reductions achieve 72.30%, 93.89%, and 97.49%, optimizing 1, 3, and 5 pairs of them. Similar reductions are achieved for the rest of the performance parameters. With high penetration of compensators into the 118-bus system, the percentage reductions of power loss are 29.14%, 73.27%, 83.72%, 90.14%, and 93.41% for optimal allocations of 1, 3, 5, 7, and 9 DG units operating at OPF. The reduction reaches 11.15%, 39.08% with 1 and 21 devices when optimizing the SRC. When DG SRC units are optimized together, power loss turns out to be 32.83%, 73.31%, 83.32%, 88.52%, and 91.29% with 1, 3, 5, 7, and 9 pairs of them. The approach leads to an enhanced voltage profile near an acceptable range of bus voltages, reduces the voltage fluctuation substantially, and enhances the system stability. The study also ensures the BES algorithm’s capability to solve these nonlinear optimization problems with high decision-variable numbers
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