Tap Ratio Research Articles

Inline fiber optic power sensor featuring a variable tap ratio based on a tightly focused femtosecond laser inscription.

We propose and demonstrate an inline fiber optic power sensor (IFPS) resorting to an embedded waveguide tap, which is formed to traverse across the cladding and core of a standard single-mode fiber. The tap was produced via a single-step inscription based on the femtosecond laser direct-writing method. A tightly focused pulsed laser beam has been particularly exploited to suppress the elongation along the laser propagation direction, thereby improving the cross-sectional symmetry of the created tap waveguide. The fabricated fiber optic tap has been stably combined with a photodiode via a compact package. The achieved tap ratio could be tuned from 1.0% to 5.9% at the wavelength of 1550 nm by adjusting the applied laser power, while the induced excess loss was kept below 0.6 dB. The proposed IFPS will be highly suitable for real-time power monitoring in a variety of applications, including optical communication networks and systems.

Transformer Tap Position Estimation Improvement Using the Hypothesis Testing for a Population Mean

This article presents an efficient method for power transformer tap position estimation based on the Hypothesis Testing for a Population Mean. To have a good performance, energy management system requires a precise model of the modern power networks. This makes the parameter estimation to be a vital part, and the transformer tap position is a crucial parameter in the networks. Therefore, this article focuses on the transformer tap position estimation. To this aim, the power system states are estimated for all tap positions using the measurements and the weighted least-squares (WLS) method. Then, the estimated measurements are calculated by the estimated states. Finally, the mean of every measurement is compared with its estimated value by employing the Hypothesis Testing for a Population Mean, and the tap ratio with the largest correct responses is identified as the correct one. Simulations are done on both the IEEE 14-bus system and a power network of Iran, showing the reliability and efficiency of the proposed method over the most recent ones.

Minimisation of active power losses and number of control adjustments in the optimal reactive dispatch problem

Trade-offs between power system's optimal operational performance and the minimal number of control adjustments necessary to attain a desired operating point make optimal reactive dispatch (ORD) solutions practical to system operators. In this study, a multi-objective ORD model that provides, in terms of weighting factors, trade-offs between minimal active power losses in transmission systems and minimal number of control adjustments in generator voltages, tap ratios and shunt controls is featured. This multi-objective ORD is formulated as a mixed-integer non-linear programming (MINLP) problem, and the proposed resolution methodology is based on translating the original MINLP problem into non-linear programming (NLP) problem deploying a sigmoid function, enabling the use of NLP solvers. Both original MINLP and translated NLP models are implemented in GAMS and numerical tests with IEEE test-systems with up to 300 buses are conducted using DICOPT, KNITRO and CONOPT solvers to validate the proposed ORD model and its resolution methodology. Results demonstrate the relation between active power losses and the number of adjustments in control variables, which is valuable information for operation planning. Another fundamental result is the high computational performance of the method when compared to specialized MINLP solvers.

Distributed generation allocation with on-load tap changer on radial distribution networks using adaptive genetic algorithm

This paper presents a distribution generation (DG) allocation strategy along with on-load tap changer (OLTC) for radial distribution networks using adaptive genetic algorithm (AGA). The optimal locations for DG units and OLTC, the optimal generation for the DG units, and the OLTC tap ratio are determined by minimizing a weighted objective function comprising of network power loss and maximum bus voltage deviation. A planning model incorporating DG and OLTC models is devised. Three different types of DG units, i.e., DG operating at lagging, leading, and unity power factor are used in the planning. Two new AGA variants based on adaptively varying crossover and mutation probabilities are proposed and used in this work as solution strategies and their performances are compared with some of the existing similar type of AGA variants using the results of multiple runs. The performances of the proposed AGA variants are found to be better in terms of quality of the solutions and consistency. The results also show that the combined operation of DG and OLTC reduces significant amount of power loss and bus voltage deviation. A direct performance comparison with some of the similar approaches shows that the solutions obtained with the proposed approach provide similar amount of power loss reduction and bus voltage improvement with lesser amount of DG penetration level. The approach is demonstrated on a 69-bus test distribution network and a 52-bus Indian practical distribution network.

Clustered adaptive teaching–learning-based optimization algorithm for solving the optimal generation scheduling problem

In the present paper, the optimum generation scheduling problem of deregulated power system is solved considering the non-smooth and non-convex generator fuel cost characteristics using the clustered adaptive teaching–learning-based optimization (CATLBO) technique. In CATLBO technique, the entire class is separated into many sections and assigned different teacher to each section depending on the performance of that particular section. This sectioning of the class makes proposed algorithm less prone to trapping in local optima and more robust. In this paper, three different objective functions are formulated, and they are total generation cost minimization considering the practical constraints, system loss minimization and L-index/ voltage stability enhancement index (VSEI). In this optimization problem, the generator active power outputs, generator bus voltage magnitudes, transformer tap ratios and bus shunt susceptances are selected as the control variables including the various equality and inequality constraints. The effectiveness and suitability of the proposed algorithm is examined on standard IEEE 30 bus, 57 bus, 118 bus and 300 bus systems, and the simulation results obtained using the proposed algorithm are also compared with many other optimization techniques reported in the literature.

Multi-objective Optimization of Afghanistan Kabul City Distribution Network for Real-time Voltage Control and Power Loss Reduction

Afghanistan Kabul City Distribution System (KDS) is functioning in adverse condition, and there is always programmed or un-programmed load shedding imposed by the Power Distribution Company. There are four indicators to be optimized for the sustainability of KDS, power loss reduction, stability, reliability, preservation and protection. In this paper, the optimization of power loss reduction and optimal voltage control of Kabul Distribution System (KDS) in the presence of Distributed Generation (DG) and Step-Voltage Regulator (SVR) connected to the network is proposed. In particular, Kabul city has plentiful sources of renewable energy such as Photovoltaic (PV) and wind power as a countermeasure for diminishing the losses of the system. The Multi-Objective Particle Swarm Optimization (MOPSO) based on two objective functions regarding hourly power loss reduction and voltage profile improvement of the distribution network is considered. The application of PV as DG in distribution system regarding their optimal number, size, and location justifies as loss reduction, reducing the entire grid peak demand and minimizing the congestion of the network. However, the optimized tap ratios and position of SVR are treats to enhance and stabilize the voltage prole and to control the violation of the system voltage according to load conditions. The 24 hours technical data of the practically functioning Kabul city Distribution System Junction Station II are used as a case study. Finally, the proposed algorithm has been simulated using MATLAB® software, and the results are presented.

Optimal Reactive Power Dispatch with Static VAR Compensator Using Harmony Search Algorithms

One of the major optimization problems in power systems is the optimal reactive power dispatch (ORPD) problem. ORPD plays an important role for secure and reliable operation of power systems. The main purpose of ORPD is to find the settings of control variables such as voltage rating of generators, reactive power injection of VAr compensators and tap ratios of the tap setting transformers in order to minimize the total active power losses of the network while satisfying a given set of constraints. The whole ORPD problem is considered as a non-linear multi-modal optimization problem with a combination of discrete and continuous variables. Along with the conventional control variables in ORPD the optimal location and the Var settings of SVC are included in the optimization problem for additional active power loss reduction. In this paper, two versions of harmony search algorithms namely basic Harmony Search Algorithm (HSA) and Improved Harmony Search algorithm (IHSA) are applied to solve conventional ORPD, as well as ORPD with the FACTS device Static Var Compensator (SVC), to minimize the total active power loss of the power system. The harmony search algorithms for ORPD, as well as ORPD considering SVC are implemented on IEEE 14 and 57 bus systems. Comparison of simulation results reveals the effectiveness of harmony search algorithms over other well established population based optimization techniques.

General optimal substation coverage algorithm for phasor measurement unit placement in practical systems

The primary objective of the conventional optimal phasor measurement unit (PMU) placement problem is the minimisation of the number of PMU devices that, when placed in a power system, measure all bus voltages. However, due to advancements in the field of relay technology, digital relays can now act as PMUs. This has significantly reduced device costs. Moreover, although the goal is to observe all the buses, the devices themselves can only be placed in substations, whose upgrade costs are much higher than those of the devices. Considering these factors, the approach proposed here simultaneously optimises the number of substations where traditional PMUs and dual-use line relay PMUs can be placed. The general optimal substation coverage (GOSC) algorithm presented in this study is also able to incorporate practical requirements such as redundancy in the measurement of critical elements of the system, and estimation of the tap ratios of the transformers present. Simulation results indicate that the GOSC algorithm provides significant techno-economic benefits.

Optimal reactive-power dispatch using differential search algorithm

Optimal reactive-power dispatch (ORPD) is one of the most difficult optimization problems regarding to power-system operation which is heavily related to system stability. To overcome ORPD problem, in general, the total real-power loss is reduced by determining the power-system control parameters, such as generator voltages, tap ratios of tap-changer transformers, and compensated reactive power, optimally. In this paper, a simple and efficient heuristic search method based on the differential search algorithm (DSA) has been presented and used to solve the ORPD problem in power systems. The ORPD problem was overcome on the IEEE 30 bus and IEEE 57 bus test systems by achieving optimal solution sets of system control variables for the objective functions regarding to power-loss minimization, voltage-profile improvement, and voltage-stability enhancement. By comparing with the several optimization methods, the performance of DSA is tested and verified on the aforementioned power system. Optimization results of different cases and objective functions indicate the implementability of the proposed algorithm in terms of solving the ORPD problem as well as other single- and multi-objective optimization problems regarding to power systems.

Group Search Optimization for Solution of Different Optimal Power Flow Problems

This article presents group search optimization for the solution of different optimal power flow problems of a power system with generators that may have either convex or non-convex fuel cost characteristics. Different operational constraints, such as generator capacity limits, power balance constraints, line flow, and bus voltages limits, have been considered. Settings of transformer tap ratio and reactive power compensating devices have also been included as the control variables in the problem formulation. Group search optimization, inspired by the animal searching behavior, is a biologically realistic algorithm. Group search optimization has been implemented to solve four different objectives such as fuel cost minimization, emission minimization, voltage profile improvement, and voltage stability enhancement with the optimal power flow embedded on IEEE 30-bus, 57-bus, and 118-bus test systems. The results of the proposed approach are compared with those obtained by other evolutionary methods reported in the literature. It is found that the proposed group search optimization based approach is able to provide a better solution.

MODELO DE IMPEDANCIA SIMPLIFICADO PARA TRANSFORMADORES CON REGULACIÓN EN CARGA CON UN FLUJO DE CARGAS ÓPTIMO

This paper presents a multi-objective optimization methodology for power systems including on-load tap changing (OLTC) transformers. A simple model for OLTC is developed based on impedance approach. In this model, the OLTC transformer with the connected transmission line are represented as a modified p equivalent circuit as a function in tap ratio. The admittance matrix of system is amended to include this new equivalent circuit. A multi-objective optimization related to generation cost and transmission losses for power systems including OLTC transformer is developed. Finally, the developed OLTC transformer model in optimal load flow has been validated using the standard IEEE 30-bus and IEEE 118-bus test systems. Key Words: Multi-Objective, Optimal Power Flow, OLTC Transformers

A Three-phase Hybrid Power Flow Algorithm for Meshed Distribution System with Transformer Branches and PV Nodes

Aiming at analyzing the power flow of the distribution systems with distribution transformer (DT) branches and PV nodes, a hybrid three-phase power flow methodology is presented in this paper. The incidence formulas among node voltages, loop currents and node current injections have been developed based on node-branch incidence matrix of the distribution network. The method can solve the power flow directly and has higher efficiency. Moreover, the paper provides a modified method to model DT branches by considering winding connections, phase shifting and off-nominal tap ratio, and then DT branches could be seen like one transmission line with the proposed power flow method. To deal with the PV nodes, an improved approach to calculate reactive power increment at each PV node was deduced based on the assumption that the positive-sequence voltage magnitude of PV node is fixed at a given value. Then during calculating the power flow at each iteration, it only needs to update current injection at each PV node with the proposed algorithm. The process is very simple and clear. The results of IEEE 4 nodes and the modified IEEE 34 nodes test feeders verified the correctness and efficiency of the proposed hybrid power flow algorithm.

Optimal Tap Setting of Voltage Regulation Transformers in Unbalanced Distribution Systems

In this paper, we propose a method to optimally set the tap position of voltage regulation transformers in distribution systems. We cast the problem as a rank-constrained semidefinite program (SDP), in which the transformer tap ratios are captured by 1) introducing a secondary-side “virtual” bus per transformer, and 2) constraining the values that these virtual bus voltages can take according to the limits on the tap positions. Then, by relaxing the non-convex rank-1 constraint in the rank-constrained SDP formulation, one obtains a convex SDP problem. The tap positions are determined as the ratio between the primary-side bus voltage and the secondary-side virtual bus voltage that result from the optimal solution of the relaxed SDP, and then rounded to the nearest discrete tap values. To efficiently solve the relaxed SDP, we propose a distributed algorithm based on the alternating direction method of multipliers (ADMM). We present several case studies with single- and three-phase distribution systems to demonstrate the effectiveness of the distributed ADMM-based algorithm, and compare its results with centralized solution methods.

A Two-Stage Robust Reactive Power Optimization Considering Uncertain Wind Power Integration in Active Distribution Networks

Traditional reactive power optimization aims to minimize the total transmission losses by control reactive power compensators and transformer tap ratios, while guaranteeing the physical and operating constraints, such as voltage magnitudes and branch currents to be within their reasonable range. However, large amounts of renewable resources coming into power systems bring about great challenges to traditional planning and operation due to the stochastic nature. In most of the practical cases from China, the wind farms are centrally integrated into active distribution networks. By the use of conic relaxation based branch flow formulation, the reactive optimization problem in active distribution networks can be formulated as a mixed integer convex programming model that can be tractably dealt with. Furthermore, to address the uncertainties of wind power output, a two-stage robust optimization model is proposed to coordinate the discrete and continuous reactive power compensators and find a robust optimal solution that can hedge against any possible realization within the uncertain wind power output. Moreover, the second order cone programming-based column-and-constraint generation algorithm is employed to solve the proposed two-stage robust reactive power optimization model. Numerical results on 33-, 69- and 123-bus systems and comparison with the deterministic approach demonstrate the effectiveness of the proposed method.

Improvement of voltage profile and reactive power using genetic algorithm

Abstract. Electrical power network is the biggest hand make of human and this network growth every day. The electrical power network has many sections and variables. In this network, the voltage profile is the most important issue to be considered. The voltage profile is hardly associated with management of reactive power. For this purpose, this paper proposes an intelligent system to improve the voltage profile using reactive power management. The proposed system uses genetic algorithm to select the best parameters of power network. In the proposed method, we consider some important variables of electrical power network such as compensator location, compensators value, on line tap changeable transformers tap ratio. Also the proposed optimization algorithm is compared with other nature based optimization algorithms such as particle swarm optimization algorithm and imperialist competitive algorithm. The proposed system is tested on twenty five buses system and the obtained results show that the proposed system has good performance.

A Study on Integrated Performance of Tap-Changing Transformer and SVC in Association with Power System Voltage Stability

Abstract—Electricity market activities and a growing demand for electricity have led to heavily stressed power systems. This requires operation of the networks closer to their stability limits. Power system operation is affected by stability related problems, leading to unpredictable system behavior. Voltage stability refers to the ability of a power system to sustain appropriate voltage levels through large and small disturbances. Steady-state voltage stability is concerned with limits on the existence of steady-state operating points for the network. FACTS devices can be utilized to increase the transmission capacity, the stability margin and dynamic behavior or serve to ensure improved power quality. Their main capabilities are reactive power compensation, voltage control and power flow control. Among the FACTS controllers, Static Var Compensator (SVC) provides fast acting dynamic reactive compensation for voltage support during contingency events. In this paper, voltage stability assessment with appropriate representations of tap-changer transformers and SVC is investigated. Integrating both of these devices is the main topic of this paper. Effect of the presence of tap-changing transformers on static VAR compensator controller parameters and ratings necessary to stabilize load voltages at certain values are highlighted. The interrelation between transformer off nominal tap ratios and the SVC controller gains and droop slopes and the SVC rating are found. P-V curves are constructed to calculate loadability margins.

Phasor-Measurement-Based State Estimation for Synchrophasor Data Quality Improvement and Power Transfer Interface Monitoring

Validation and data quality improvement of phasor data through state estimation is the first step in ensuring that the synchrophasor data is useful for applications in monitoring, visualization, and control. This paper presents a phasor-measurement-based state estimator (PSE) for improving data consistency by identifying angle biases and current scaling errors in the phasor data using the augmented state vector approach. These errors can arise from issues with the Global Positioning Signal (GPS), timing circuits, instrument channels, and/or data channel scaling. The PSE is demonstrated using several sets of disturbance data from the Central New York Power System. The PSE can also provide estimates of line parameters and transformer tap ratios with sufficient measurement redundancy. Finally, the PSE allows the computation of interface power flows for disturbance and stability monitoring.

Magnetically Controlled Reactor Tap Ratio Optimization Research

The tap ratio of magnetic controllable reactor (MCR) has an important influence on the response speed and active power loss. With various applications of MCR, the focuses of MCRs response speed and active power loss are different, which makes the design of the tap ratio different. According to MCRs most widely application--- power system reactive power voltage control---the effect of the tap ratio on the response speed and active power loss was considered. The tap ratio of magnetic controllable reactor was optimized based on the dynamic optimal algorithm of MATLAB, which made the response speed and the active power loss of MCR stay in the equilibrium optimal state, and a general formula was given. Through the simulations of ANSYS and PSCAD software, the feasibility of this theory is verified, and a solid theoretical foundation for the wider practical application of magnetic controllable reactor is provided.

A modified Primal–Dual Logarithmic-Barrier Method for solving the Optimal Power Flow problem with discrete and continuous control variables

The aim of solving the Optimal Power Flow problem is to determine the optimal state of an electric power transmission system, that is, the voltage magnitude and phase angles and the tap ratios of the transformers that optimize the performance of a given system, while satisfying its physical and operating constraints. The Optimal Power Flow problem is modeled as a large-scale mixed-discrete nonlinear programming problem. This paper proposes a method for handling the discrete variables of the Optimal Power Flow problem. A penalty function is presented. Due to the inclusion of the penalty function into the objective function, a sequence of nonlinear programming problems with only continuous variables is obtained and the solutions of these problems converge to a solution of the mixed problem. The obtained nonlinear programming problems are solved by a Primal–Dual Logarithmic-Barrier Method. Numerical tests using the IEEE 14, 30, 118 and 300-Bus test systems indicate that the method is efficient.

Hybrid Control Model of Under Load Tap Changers

This paper proposes a hybrid control model of under load tap changer transformers. The proposed model is based on the well-known discrete and continuous control models of such device, and is designed so that it preserves the discrete behavior of the tap ratio while allowing solving small-signal stability and eigenvalue analysis. The proposed model is tested through the IEEE 14-bus test system and a real-world 1488-bus model of a sub-transmission and distribution system.