Transformer Tap Research Articles

Improved state transition algorithm for hybrid power system reactive power optimization using filter techniques

Abstract Reactive power optimization in power systems is crucial for their normal and efficient operation. However, with the increasing prevalence of active current and direct current (AC-DC) hybrid power grids, existing optimization methods face issues such as poor adaptability, low efficiency, insufficient accuracy, and inadequate convergence. To address these problems, this paper proposes a reactive power optimization model based on an improved state transition algorithm (STA) utilizing filter techniques. The optimization model considers operational costs associated with adjusting transformer tap positions, switching reactive power compensation capacitors, regulating generator terminal voltages, and adjusting active power in DC transmission. Simulation results demonstrate that this method can reduce system losses and voltage control costs while ensuring stable system operation, thus improving the reactive power distribution in AC-DC hybrid transmission systems.

Optimal Reactive Power Dispatch and Demand Response in Electricity Market Using Multi-Objective Grasshopper Optimization Algorithm

Optimal Reactive Power Dispatch (ORPD) is a power system optimization tool that modifies system control variables such as bus voltage and transformer tap settings, and it compensates devices’ Volt Ampere Reactive (VAR) output. It is used to decrease real power loss, enhance the voltage profile, and promote stability. Furthermore, several issues have been faced in electricity markets, such as price volatility, transmission line congestion, and an increase in the cost of electricity during peak hours. Programs such as demand response (DR) provide system operators with more control over how small customers participate in lowering peak-hour energy prices and demand. This paper presents an extensive study on ORPD methodologies and DR programs for lowering voltage deviation, limiting cost, and minimizing power losses to create effective and economical operations systems. The main objectives of this work are to minimize costs and losses in the system and reduce voltage variation. The Grasshopper Optimization Algorithm (GOA) and Dragonfly Algorithm (DA) have been implemented successfully to solve this problem. The proposed technique has been evaluated by using the IEEE-30 bus system. The results obtained by the implementation of demand response systems show a considerable reduction in costs and load demands that benefit consumers through DR considerations. The results obtained from the GOA and DA are compared with those generated by other researchers and published in the literature to ascertain the algorithm’s efficiency.

Simulation research on generator leading phase test and main transformer tap selection

Simulation research on generator leading phase test and main transformer tap selection

Power efficiency improvement in reactive power dispatch under load uncertainty

Nowadays, there is a significant rise in electricity demand, posing challenges for power grid operators due to inaccurate forecasting, leading to excessive power losses and voltage instability. This paper addresses these issues by focusing on solving optimal reactive power dispatch (ORPD) while considering load demand uncertainty. The main objective of solving ORPD is to reduce power losses by adjusting generator voltage ratings, transformer tap ratio, and shunt capacitors' reactive power. Monte Carlo simulation (MCS) is employed to generate load scenarios using the normal probability density function, while a reduction-based technique is implemented to decrease the number of those scenarios. The improved gray wolf optimization (I-GWO) algorithm is introduced for the first time to address the stochastic ORPD problem. Experimentation is conducted on an IEEE-30 bus system when results are contrasted with conventional gray wolf optimization (GWO) and five other algorithms as stated in the literature. The I-GWO algorithm's performance is assessed with and without considering load demand uncertainty. Through Friedman's statistical tests, a significant decrease of 20.96% in active power losses and 63.06% in the summation of expected power losses is observed. The I-GWO algorithm's results on the ORPD problem demonstrate its effectiveness and robustness.

An iterative approach to grid topology and redispatch optimization in congestion management

The selection of Remedial Actions (RA) to ensure system security is a highly complex task performed by Transmission System Operators (TSOs). Phase shifting transformer (PST) tap changes and active power changes of generation units (redispatch) are some RA available in Security Constrained Optimal Power Flow (SCOPF) simulations within the operational planning processes. Topological RA are not part of these SCOPF yet, as the optimization thereof adds high complexity to the existing optimization problem. To overcome this complexity, this paper introduces an iterative approach that decouples topology optimization from redispatch & PST optimization. Linearized models of RA are used to meet computation time requirements. Exemplary investigations of the presented method were performed based on modified IEEE 39-Bus, 118-Bus and PEGASE-1354-Bus grid models. Within the scope of these investigations, the method shows good results and a great potential for the reduction of congestions and required redispatch through topological RA. In order to eliminate inaccuracies of the approach and to further improve its suitability for use in grid operation, a need for future investigations and possible further developments were identified.

Nonlinear Impact of Topological Configuration of Coupled Inverter-Based Resources on Interaction Harmonics Levels of Power Flow

The increasing level of harmonics in the power grid, driven by a substantial presence of coupled inverter-based energy resources (IBRs), poses a new challenge to power grid transient stability. This paper presents the findings from experiments and analytical studies on the impact of the topological configuration of coupled IBRs on the level of power flow harmonics in a distribution grid: (i) our findings report that the impact of grid topology on harmonics is nonlinear, which is in contrast to the common perception that the power grid operates as a large linear low-pass filter for harmonics; (ii) importantly, this study highlights that the influence of the topological configuration of inverters on the reduction of system-level harmonics is more substantial than the effect of line impedance, emphasizing the significance of grid topological configuration; (iii) furthermore, the observed reduction in harmonics is attributed to a harmonic cancellation effect achieved through self-compensation by all the coupled inverters without affecting the active power flow in the power grid. These findings propose a new approach to limit the penetration of complex IBR harmonics in the power grid from a system-wide perspective. This approach significantly differs from the component-level or localized solutions used today, such as inverter control, power filtering, and transformer tap changes.

Gaussian Mutation Based Teaching-Learning Optimization for reactive power dispatch

This paper develops the Gaussian Mutation Based Teaching-Learning Optimization (GMBTLO) to solve different reactive power dispatch problems. In GMBTLO, Gaussian random variables are instituted, which includes both the ‘Teacher phase’ as well as ‘Learner phase’ helps to improve the efficiency of searching. Simultaneously, it ensures more feasibility to obtain the global optimal. Gaussian random variables are presented in GMBTLO, where both the ‘Teacher phase’ as well as ‘Learner phase’ is considered. This advances searching competence and guarantee a great possibility of achieving global optimum without affecting the convergence speed. In this paper, GMBTLO is implemented to enhance solution quality as well as convergence speed. Developed GMBTLO is exploited for obtaining the control variables settings including terminal voltages of a generator, transformer taps, as well as output power of shunt VAR compensators (reactive) for achieving a reduced loss in real power transmission and enhanced voltage profile. GMBTLO is validated by taking IEEE 30-bus, 57-bus along with 118-bus test systems. Also, test outcomes are matched with the results already acquired from other implemented evolutionary techniques. It is concluded that the suggested GMBTLO extends a better solution.

Influence of the Load Models in the Dynamic Voltage Stability of an Electric Power System

Voltage stability plays a very important role during the planning and design stages of an electric power network as well as during the system operation. In the last years in various countries worldwide, several power network collapses (blackouts) caused by voltage problems have been reported. This can be produced by a lack of sufficient reactive power reserve during heavy load or by the occurrence of severe contingencies. In this paper it is studied and analysed the influence of the load models in the dynamic voltage stability assessment of an electric power system. It was used the BPA test power network. A severe contingency situation was simulated to perform the study. The automatic voltage regulators of the generating units and the turbine speed governors were modelled as well as the transformer taps. The simulation results were obtained using the commercial transient software package EUROSTAG. Finally some conclusions that provide a better understanding of the voltage collapse phenomena are pointed out.

Performance assessment and impact of electric vehicles penetration in active distribution grids

Because of the ongoing discussion about global warming, many nations have developed several approaches to address this problem. Some strategies are: renewable energy integration, agricultural robotic solutions, and electric vehicle penetration. The last strategy, the electric vehicle (EV), has gained considerable attention due to the paradigm shift in the transport sector driven by internal combustion engines and EV penetration can also achieve efficient operation of power grids. However, there are numerous challenges associated with the penetration of these technologies within active distribution networks. It is necessary to analyze the increased amount of electricity consumption in these grids, the degradation in the voltage profile in these networks and the hosting capacity assessment of electric vehicle integration in these grids. This paper analyzes the influence of EV penetration on a 34-bus active distribution system through five EV stations and proposes two alternatives for improving the introduction of these technological elements. Specifically, it analyzes the voltage levels at the system nodes and proposes an intelligent management of resources through capacitor banks and transformer taps. From the results, the effects on the network were voltage drop on some bus bars and an increase or decrease of the loading on lines depending on the EV penetration. It is also evident that 9% of the bus bars were not working under acceptable voltage ranges in the worst-case scenario.

FACTS placement for reactive power planning with weak node constraints using an improved symbiotic search algorithm

In this paper, an economically feasible and reliable operation of the IEEE 57 bus system for Optimal Power Flow (OPF) is proposed. The Improved Symbiotic Organisms Search (ISOS) algorithm is proposed for effective reactive power planning as an OPF issue. Further, the optimal position of Flexible AC Transmission Systems (FACTS) is taken into consideration, by including the existing system controlling variables like reactive power generators output, transformer tapping and capacitors connected at shunt. The objective of the work is two-fold; i.e., to reduce the energy loss and to enhance the voltage profile within the prescribed limit by ensuring the economic operation and investment cost of FACTS in the system. In this work, two FACTS devices like Static Var Compensator (SVC) and Thyristor-Controlled Series Controller (TCSC) have been taken into consideration. Voltage sensitivity indicator and reactive power flow are two tools that are utilised in order to locate weak nodes for the implementation of FACTS. Finally, the performance of the ISOS algorithm is compared with that of three other state- of-the -art optimization techniques, such as, Symbiotic Organisms Search (SOS), Differential Evolution (DE) and Teaching Learning Based Optimization (TLBO). A Non-parametric statistical analysis is also performed to investigate the dominance of the ISOS algorithm over others.

Current balancing of scalar-controlled induction motors with long imbalanced cables for artificial lift systems

Induction motor current imbalance increases losses, torque ripple and vibrations. Current imbalance is known to appear in artificial lift systems, where motors are driven over long imbalanced cables. Power hardware modifications, namely transposition of cable phases in the wellbore, adjustment of the step-up transformer taps, and addition of balancing inductors have so far been proposed to suppress the imbalance. However, these solutions compromise the system's reliability or involve costly additional equipment, which must be customized according to the cable characteristics. This paper proposes a control method for current balancing of induction motors driven by scalar-controlled variable speed drives. In the proposed method, Second-Order Generalized Integrators (SOGIs) are used to extract the negative-sequence component of the motor currents, which is then suppressed by a Synchronous Reference Frame (SRF) current controller. The frequency and angle information required by the SOGIs and the SRF controller are obtained directly from the scalar algorithm, without needing a position sensor or observer, thus offering a novel, simple, robust and computationally effective implementation, which is also independent of the cable characteristics. The paper presents MATLAB/Simulink simulation results to illustrate the method's operating principles and performance in a variety of transient conditions. Experimental results obtained using full-scale equipment are also provided to demonstrate its effectiveness.

Low threshold DC–AC power converter with optimized standby power consumption

The quest for universal energy access continues to be a major concern globally. Renewable energy technologies such as solar PV are viable options to meet this energy poverty with DC–AC power converters playing a major role in solar PV systems. Current designs of these converters suffer from high standby energy consumption and high input threshold voltage. This paper presents the design and implementation of a single-phase DC–AC power converter with low threshold input voltage and optimized standby power consumption. A multivibrator, pulse width modulation signal generator, MOSFETs, and a multiple secondary winding center tap transformer were used in the system design. The results show an optimized power converter having a low input threshold voltage of 10.5V and power consumption of 9.49W.

An integrated decision-making approach for managing transformer tap changer operation while optimizing renewable energy storage allocation using ANP-entropy and TOPSIS

An integrated decision-making approach for managing transformer tap changer operation while optimizing renewable energy storage allocation using ANP-entropy and TOPSIS

Addressing Power Loss and Voltage Profile Issues in Electrical Distribution Systems: A Novel Approach Using Polar Bear Gradient-Based Optimization

Energy is an essential commodity for everyone, with electrical energy being the most preferred form. Unfortunately, non-renewable energy resources are gradually depleting, and renewable energy sources take several years to establish. To mitigate this problem, technology has shifted from non-renewable energy sources to electrical devices and machines, including household appliances like washing machines and air conditioners. However, the generation of electricity is still inadequate to meet the growing demand. This leads to two major problems: high power loss and poor voltage profile, making it difficult for power distribution companies to ensure a consistent and reliable power supply. This paper aims to address the reduction and minimization of power losses by adjusting distribution side transformer tap settings using the polar bear gradient-based optimization. The proposed approach uses the 14-bus system as a reference and calculates losses for this system using the backward-forward sweeping technique. The results are compared with standard PSO algorithm; the proposed strategy shows superior results.

The importance of reconfiguration of the distribution network to achieve minimization of energy losses using the dragonfly algorithm

In this article, a method for reconfiguring the distribution network with the presence of production sources to minimize energy losses is presented. Also, besides the reconfiguration issue, the Super distribution tap transformers and the power factor of resources in the network will have their optimal values based on the amount of energy consumption as factors affecting the number of losses. According to the stated parameters, the optimization problem in this article is a non-linear problem with a large search space, for which the dragonfly optimization algorithm was used. To make the results realistic, all types of loads, including commercial, residential and office, have been considered in 24 h and two seasons of the year, cold and hot. The program was prepared with the help of MATLAB software on a sample network of 16 buses, and its applications and results have been evaluated. The obtained results show that determining the optimal reconfiguration is very effective in reducing network losses because, with this method, the amount of losses and unsupplied energy of network subscribers has been reduced significantly. Also, by coordinating the reconfiguration with tap transformers and the power factor of distributed generation resources, the loss reduction rate can be made more effective. The results obtained are compared with the genetic algorithm and the results show the superiority of the dragonfly optimization method.

Reactive Capability Sizing of HPR1000 NPP in the UK Grid

To address the voltage profile, the reactive power requirements in the UK Grid Code have risen due to increasing power flows and the wind turbine system volume. This study strives to figure out the reactive capability of HPR1000 NPP in the UK grid and presents ETAP-based modeling and simulation of the demonstration. The paper first introduces the UK grid’s reactive capability requirements, then analyses the theory of synchronous generator reactive capability and unit transformer tap changer sizing, and finally demonstrates the sizing of reactive generator capability and unit transformer tap changer via load flow studies. The reactive capability requirements of the UK grid are more severe than China, causing the synchronous generator with a larger reactive capability [0.83PF(lagging), 0.98PF(leading)] and the unit transformer with a larger range of on-load tap changer[-10×1.25% / +4×1.25%], which should be concerned during HPR1000 NPP exportation.

Reactive power planning with the help of multi-objective genetic algorithm and flexible AC transmission systems devices

In this paper power quality of 3-bus solar-based hybrid system has been presented (where one or more than one distribution generator unit is connected to the grid). The injection of solar power into grid-connected systems creates power quality problems such as current consistency, electrical fluctuations, and inefficient power demand. A power quality control strategy based on a real-time self-regulation method for autonomous microgrid operation has been presented. In this paper solar farm design and satisfactory performance tests such as PV-static synchronous compensator (STATCOM) to improve the power quality of grid-based systems have been presented using the MATLAB/Simulink environment. Pulse width modulator (PWM) with proportional-integral derivative (PID) controller used for frequency control, reactive var compensation is used to control voltage profile. Multi-objective genetic algorithm (MOGA) for reactive power planning (RPP) with the objective of reactive power minimization is introduced. The optimization variables are generator voltage, transformer tap changer, and various operational constraints.

A Novel Co-phase Traction Power Supply System in Electrified Railway

The electrified railway has power quality problems such as three phases seriously unbalanced, large harmonics, and reactive power. In addition, the neutral section exists at each power supply section, which restricts the development of the high-speed and heavy-haul railway. This paper proposes a novel co-phase traction power supply system (TPSS) based on a YNvd balanced transformer, which can not only solve the above problems but also save one single-phase coupling step-down transformer, thus reducing the cost and space of the whole system. In addition, the voltage level of the converter switching device can be reduced by the rational design of the transformer tap position, which enhances the reliability and feasibility of the system. The compensation principle and control strategy of the co-phase TPSS based on the novel YNvd balanced transformer are analyzed in detail in this paper, and the compensation current detection and integrated power flow controller (IPFC) control methods are given. Simulation and analysis show that the proposed topology structure and control method are correct and feasible.

Reactive power planning with the help of multi-objective genetic algorithm and flexible AC transmission systems devices

In this paper power quality of 3-bus solar-based hybrid system has been presented (where one or more than one distribution generator unit is connected to the grid). The injection of solar power into grid-connected systems creates power quality problems such as current consistency, electrical fluctuations, and inefficient power demand. A power quality control strategy based on a real-time self-regulation method for autonomous microgrid operation has been presented. In this paper solar farm design and satisfactory performance tests such as PV-static synchronous compensator (STATCOM) to improve the power quality of grid-based systems have been presented using the MATLAB/Simulink environment. Pulse width modulator (PWM) with proportional-integral derivative (PID) controller used for frequency control, reactive var compensation is used to control voltage profile. Multi-objective genetic algorithm (MOGA) for reactive power planning (RPP) with the objective of reactive power minimization is introduced. The optimization variables are generator voltage, transformer tap changer, and various operational constraints.

Reduction of Power Losses in the Distribution System by Controlling Tap Changing Transformer using the PSO Algorithm

Energy is an essential commodity for everyone, with electrical energy being the most preferred form. Unfortunately, non-renewable energy resources are gradually depleting, and renewable energy sources take several years to establish. To mitigate this problem, technology has shifted from non-renewable energy sources to electrical devices and machines, including household appliances like washing machines and air conditioners. However, the generation of electricity is still inadequate to meet the growing demand. This leads to two critical issues: Excessive power loss and inadequate voltage stability, making it difficult for power distribution companies to ensure a consistent and reliable power supply. The objective of this study is to tackle the issue of reduction and minimization of power dissipation By employing the PSO technique, adjusting the transformer tap settings. The proposed approach uses the 14-bus system as a reference and calculates losses for this system using the backward-forward sweeping technique.