Unified Power Flow Controller: A Brief Review on Tuning and Allocation for Power System Stability

The Power System can become unstable due to disturbances. To enhance system stability the Unified Power Flow Controller (UPFC) is tuned and allocated in the System. In this paper, a brief review of UPFC tuning and allocation studies for power systems stability is presented. The databases consulted for literature are the IEEE Xplore, ScienceDirect, Google Scholar and IOP Publications. The search terms used are Allocation, Tuning, UPFC, Power System and Stability to find the literature used in this review. A total of 26 Journal articles and conference papers were found and reviewed based on tuning and allocation studies. The Researchers applied Fuzzy coordination, Genetic Algorithm (GA), Particles Swarm Optimization (PSO), Grey Wolf Optimization (GWO) and Linear Quadratic Tracker (LQT) to tune the UPFC for enhancing power system stability. For studies on UPFC allocation in power systems, the Researchers applied frequency response of power system transfer function, power flow, Tabu Search (TS), PSO and GA. For allocation based on optimization, the Researchers minimized power losses, voltage index and investment costs considering equality and inequality constraints

Application of whale algorithm optimizer for unified power flow controller optimization with consideration of renewable energy sources uncertainty

Purpose. In this paper an allocation methodology of Flexible Alternating Current Transmission Systems (FACTS) controllers, more specifically, the Unified Power Flow Controller (UPFC) is proposed. As the penetration of Renewable Energy Sources (RESs) into the conventional electric grid increases, its effect on this location must be investigated. Research studies have shown that the uncertainty of RESs in power generation influences the reactive power of a power system network and consequently its overall transmission losses. The novelty of the proposed work consists in the improvement of voltage profile and the minimization of active power loss by considering renewable energy sources intermittency in the network via optimal location of UPFC device. The allocation strategy associates the steady-state analysis of the electrical network, with the location and adjustment of controller parameters using the Whale Optimization Algorithm (WOA) technique. Methodology. In order to determine the location of UPFC, approaches are proposed based on identification of a line which is the most sensitive and effective with respect to voltage security enhancement, congestion alleviation as well as direct optimization approach. The optimum location of UPFC in the power system is discussed in this paper using line loading index, line stability index and optimization method. The objective function is solved using the WOA algorithm and its performance is evaluated by comparison with Particle Swarm Optimization (PSO) algorithm. Results. The effectiveness of the proposed allocation methodology is verified through the analysis of simulations performed on standard IEEE 30 bus test system considering different load conditions. The obtained results demonstrate that feasible and effective solutions are obtained using the proposed approach and can be used to overcome the optimum location issue. Additionally, the results show that when UPFC device is strategically positioned in the electrical network and uncertainty of RES is considered, there is a significant influence on the overall transmission loss and voltage profile enhancements of the network.Мета. У статті пропонується методологія розподілу контролерів гнучких систем передачі змінного струму (FACTS), зокрема уніфікованого контролера потоку потужності (UPFC). Оскільки проникнення відновлюваних джерел енергії (ВДЕ) у звичайну електричну мережу збільшується, необхідно досліджувати їхній вплив на це. Наукові дослідження показали, що невизначеність ВДЕ у виробленні електроенергії впливає на реактивну потужність мережі енергосистеми і, отже, на її загальні втрати під час передачі. Новизна запропонованої роботи полягає в покращенні профілю напруги та мінімізації втрат активної потужності за рахунок обліку перемежування відновлюваних джерел енергії в мережі за рахунок оптимального розташування пристрою UPFC. Стратегія розподілу пов'язує стаціонарний аналіз електричної мережі з розміщенням та налаштуванням параметрів контролера з використанням методу алгоритму оптимізації кита (WOA). Методологія. Для визначення розташування UPFC пропонуються підходи, засновані на виявленні лінії, яка є найбільш чутливою та ефективною з точки зору підвищення безпеки за напругою, зменшення навантажень, а також прямий підхід до оптимізації. Оптимальне розташування UPFC в енергосистемі обговорюється в цій статті з використанням індексу завантаження лінії, індексу стійкості лінії та методу оптимізації. Цільова функція вирішується з використанням алгоритму WOA, а її продуктивність оцінюється шляхом порівняння з алгоритмом оптимізації рою частинок (PSO). Результати. Ефективність запропонованої методології розподілу перевірена за допомогою аналізу моделювання, виконаного на тестовій системі стандартної шини IEEE 30 з урахуванням різних умов навантаження. Отримані результати демонструють, що за допомогою запропонованого підходу виходять здійсненні та ефективні рішення, які можна використовувати для подолання проблеми оптимального розташування. Крім того, результати показують, що коли пристрій UPFC стратегічно розташований в електричній мережі і враховується невизначеність ВДЕ, це значно впливає на загальні втрати при передачі і поліпшення профілю напруги в мережі

An optimal allocation of UPFC and transient stability improvement of an electrical power system: IEEE-30 buses

Recently, the expansion process of electrical networks has become crucial with the development of electrical systems. One of the active solutions to progress the performance of an electrical system is the usage of flexible AC transmission system (FACTS). As a new generation of telecommunications and power electronics technology, FACTS has provided a new viewpoint to increase the bearing capacity, better control the grid, and reduce costs. The unified power flow controller had a multi-purpose unit that could command the scenario of providing or consuming the power components and maintaining the bus voltage. The study's novelty resided in presenting a modified particle swarm optimization algorithm-based software system and applied a Newton-Raphson load flow solution to get the best solutions for optimal allocation of unified power flow controllers (UPFC). This study has focused on the functions of the UPFC electrical system with corresponding effects on transient stability. MATLAB software (Simulink/code) and excel sheet were performed on IEEE 30 buses as a case study. It has been shown the effectiveness of UPFC with fast response and autonomous command on the flow of power components. The dynamic response for stability improvement for some network buses had been verified to ensure the robustness of UPFC during a sudden disturbance in electrical load. The case study results illustrate that the number of UPFC increased with load increased by (14% and 21%)

Full body harness

The full body safety harness is a key part of an active fall arrest system. The harness serves two purposes, first, distributing fall forces safely across a worker's body in the event of a free fall, and second, providing freedom of movement sufficient to allow the worker to effectively perform his or her job. The complete body harness incorporates the characteristics of a sit harness that supports the hips and upper legs as well as a chest harness that supports the chest and shoulders. The complete body structure includes the human torso when correctly used and helps to keep it upright during a fall case

Artificial Intelligence-based Control Techniques for HVDC Systems

The electrical energy industry depends, among other things, on the ability of networks to deal with uncertainties from several directions. Smart-grid systems in high-voltage direct current (HVDC) networks, being an application of artificial intelligence (AI), are a reliable way to achieve this goal as they solve complex problems in power system engineering using AI algorithms. Due to their distinctive characteristics, they are usually effective approaches for optimization problems. They have been successfully applied to HVDC systems. This paper presents a number of issues in HVDC transmission systems. It reviews AI applications such as HVDC transmission system controllers and power flow control within DC grids in multi-terminal HVDC systems. Advancements in HVDC systems enable better performance under varying conditions to obtain the optimal dynamic response in practical settings. However, they also pose difficulties in mathematical modeling as they are non-linear and complex. ANN-based controllers have replaced traditional PI controllers in the rectifier of the HVDC link. Moreover, the combination of ANN and fuzzy logic has proven to be a powerful strategy for controlling excessively non-linear loads. Future research can focus on developing AI algorithms for an advanced control scheme for UPFC devices. Also, there is a need for a comprehensive analysis of power fluctuations or steady-state errors that can be eliminated by the quick response of this control scheme. This survey was informed by the need to develop adaptive AI controllers to enhance the performance of HVDC systems based on their promising results in the control of power systems. Doi: 10.28991/ESJ-2023-07-02-024 Full Text: PD

Multi-objective tabu search for the location and sizing of multiple types of FACTS and DG in electrical networks

Flexible AC transmission systems and distributed generation units in power systems provide several benefits such as voltage stability, power loss minimization, thermal limits enhancement, or enables power system management close to the limit operation points; and by extension, economic benefits such as power fuel cost and power loss cost minimization. This work presents a multi-objective optimization algorithm to determine the location and size of hybrid solutions based on a combination of Flexible AC transmission systems devices and distributed generation. Further, the work expands the types of FACTS usually considered. The problem is solved by means of a Tabu search algorithm with good results when tested in a network of 300 nodes

Nonlinear optimization approach for UPFC power flow control and voltage security: Sufficient system constraints for optimality

This dissertation provides a nonlinear optimization algorithm for the long term control of Unified Power Flow Controller (UPFC) to remove overloads and voltage violations by optimized control of power flows and voltages in the power network. It provides a control strategy for finding the long term control settings of one or more UPFCs by considering all the possible settings and all the (N-1) topologies of a power network. Also, a simple evolutionary algorithm (EA) has been proposed for the placement of more than one UPFC in large power systems --Abstract, page iv

Enhancement of voltage stability in an interconnected network using unified power flow controller

In this paper, the optimal placement of Unified Power Flow Controllers (UPFC) in a large-scale transmission network in order to improve the loadability margin was considered. In other to achieve this aim, the Line Stability Factor (LQP) as a technique for the optimal location of UPFC in the IEEE 14-bus network and 56-bus Nigerian national grid was adopted. The power injection model for the UPFC was employed to secure improvements in the loading margin of the IEEE 14-bus network and 56-bus Nigerian national grid system. Continuation power flow was used to assess the effect of UPFC on the loadability margin. Steady-state simulations using Power System Analysis Toolbox (PSAT) on MATLAB was applied to determine the effectiveness of placing UPFC between bus 13 and bus 14 in the IEEE 14-bus network and between bus 44 (Ikot-Ekpene) and bus 56 (Odukpani) in the 56-bus Nigerian national grid system. The results showed that the loadability margin increased by 8.52 % after UPFC was optimally placed in the IEEE 14-bus network and increased by 195.5 % after UPFC was optimally placed in the 56-bus Nigerian national grid system. Thus, these enhance the voltage stability of both network and utilizing the network efficiently