Tap Changing Transformers Research Articles

Static Analysis and Optimization of Voltage and Reactive Power Regulation Systems in the HV/MV Substation with Electronic Transformer Tap-Changers

The quality of electricity is a very important indicator. The durability and reliable operation of all connected devices depend on the quality of the network voltage. Rapid changes in loads, changes in network connections and the presence of uncontrolled energy sources require the development of new voltage regulation systems. This requires voltage regulation systems capable of responding quickly to sudden voltage changes. In substations with control transformers, it is possible thanks to the use of semiconductor tap changers. Moreover, voltage regulation and reactive power compensation systems should be built as one system. This is due to the close dependence of voltage and reactive power in the network node. Therefore, it was proposed to use artificial intelligence methods to build a new voltage regulation and reactive power compensation system using all measurement voltages of network nodes. In the first stage of the research, active and reactive powers, as well as the voltage of the reference node, were selected for 6420 periods of the mains voltage. The simulation results were compared for the classic voltage regulation system with semiconductor tap changers and the evolution algorithm based on voltage measurements from the entire MV network. A significant improvement in the quality of voltage regulation with the use of an evolutionary algorithm was demonstrated. Then, a second set of input data with increased values of reactive power was generated. The results of the evolutionary algorithm after the application of the classic, independent reactive power compensation system and two-criteria optimization were compared. It has been shown that only the two-criteria optimization algorithm keeps both |tgφ| within the acceptable range and the quality of voltage regulation is the best. The article compares different working algorithms for semiconductor tap changers.

Multiobjective Optimization of Power Flow Distribution in EPS with RES under Minimum Number of Transformer’s On-Load Tap Changing

The incorporation of renewable energy sources (RES) such as wind and solar power plants into traditional power systems offers numerous technical and environmental benefits. However, improper operation of power grids with RES may lead to high operating costs and higher system losses, as well as voltage fluctuations. To solve these problems, in this paper a formulation of the dynamic optimal power flow (DOPF) problem has been proposed with the integration of RES in the grid. The maximum allowable number of switching operations in a day for on-load tap-changer (OLTC) of transformers is taken into consideration as practical constraint. For 24 hours, the objective functions were to minimize the total operating cost (including fuel cost and cost of power loss), minimize power loss and the daily number of tap operations for transformer's OLTC. The minimization of the daily number of operations for transformers was taken as the goal to preserve the service life of transformers, reduce maintenance and depreciation. The objectives were minimized by coordination between control variables such as the output power of generators, the voltage of generators, transformer tap changer, and shunt capacitor. The improved practical swarm optimization (PSO) algorithm has been employed successfully to solve DOPF with discrete and continuous decision variables in the electric power system.

Solving Unit Commitment Including Wind Power Generation Using PSS®E

Operating the power system in an optimal way and keeping it safe and reliable is very important in power systems planning and operation. The power system currently has a large variety of power plants that operate with different kinds of fossil fuel or use renewable energy to produce power. As the demand on electricity is fluctuated, utilities are obligated to provide consumers with power at any time during a day. Power system operators try to supply electricity in an economic operation by turning on the cheapest generating units and turning off the most expensive ones at off-peak value of the load. Finding the optimal combination of units to supply forecasting load is called unit commitment problem (UC). The second step of the optimization problem is finding the optimal output power from each committed unit, which known as economic dispatch (ED). The main benefits of solving the unit commitment problem and economic dispatch are to minimize generation cost over the objective period horizon while applying all system constraints that come from generating units’ limits and the transmission system’s characteristics, as well as to verify the balance between power generation and power demand. While, the optimal power flow (OPF) tries to find the optimal dispatch for the whole power system, but by taking into account all systems constrain, such as voltage security and transmission line limit. The optimal power flow can control many variables to find the optimal operation of the system, like a transformer tap changer, phase shifter, switched shunt, and load adjustment. In this paper, power system simulator for engineering (PSS®E) is used to solve unit commitment, economic dispatch, and optimal power flow. The implementation is performed on IEEE 30-bus system for a 24-hour period. In the first stage, the UC, ED, and OPF were solved for the systems without including wind power generation. In the second stage, UC, ED, and OPF were solved by including a wind-power farm with 100 MW rated power connected to the system. The solution is based on 24-hour wind data forecasting, and 24-hour power demand's prediction.

Nb-doped PtS2 monolayer for detection of C2H2 and C2H4 in on-load tap-changer of the oil-immersed transformers: A first-principles study

First-principles calculations are conducted to investigate the Nb-doped PtS2 (Nb-PtS2) monolayer for sensing C2H2 and C2H4 in the on-load tap-changer of the oil-immersed transformers. The adsorptions of two gases on the Nb-PtS2 monolayer are verified as chemisorption with adsorption energies of −2.47 and −1.0.91 eV, as confirmed by Hirshfeld analysis, charge density difference and orbital density of state. The band structure indicates the good sensing response of 1206.7% and −4717.4%, for C2H2 and C2H4 detections, suggesting its strong potential as a resistance-type gas sensor for their detections. This work paves the ways to explore novel PtS2-based gas sensor effectively.

Enhanced Transmission and Distribution Network Coordination to Host More Electric Vehicles and PV

Distributed energy resources (DERs) installed at electric distribution networks create different opportunities and challenges for the distribution system operator (DSO). By increasing the penetration level of DERs, the impacts of these technologies are also sensed by the transmission system operator (TSO). The focus of this paper is on investigating and managing the impacts of the Electric Vehicle (EV) charging and solar Photo-Voltaic (PV) generation considering TSO-DSO interaction constraints. These constraints include the driving point impedance that reflects the impact of the DER-rich distribution system on the upstream HV network and voltage profile control through the on-load tap changing (OLTC) transformer's operation. The aim is to optimally utilize the existing assets and flexibilities to have more EVs and PVs at the distribution level without violating constraints at both transmission and distribution levels. The proposed model could readily be used by policymakers to design and implement the proper time-of-use tariffs for improved handling of the increasing EVs and PVs penetrations in emerging distribution networks. The proposed method is implemented on the IEEE 69-bus standard MV distribution network to demonstrate the applicability.

A novel control technique for on‐load tap changer to enlarge the reactive power capability of wind power plants

This paper suggests a new control algorithm for On-Load Tap Changer (OLTC) of wind farm main transformer that is responsible for voltage regulation of collector network. The conventional control scheme adjusts the voltage of LV side of transformer without considering the wind turbine voltages. The voltage of end-string wind turbines may reach the upper or lower limits of Over or Under-Excited operation regions. Voltages close to upper or lower limits bounds the reactive power capability (generation or consumption) of wind farm due to dependency of wind turbine reactive power capability to voltage. Operation of wind turbine at extreme voltages may stress its power electronic devices. Furthermore, minor disturbances at either grid or power plant may trigger the protection system and interrupt generation due to vicinity of operation point to protection thresholds. The suggested technique integrates the OLTC control into the power plant controller and considers both LV side voltage of transformer and wind turbine voltages. By monitoring the wind turbine voltages, the voltage setpoint of OLTC is adjusted to provide voltages closer to middle of range for wind turbines that prevents the wind turbines from reaching the voltage limits. Dynamical simulations conducted in DigSILENT PowerFactory software for both Under-Excited and Over-Excited operation regions demonstrate desired performance for the suggested technique.

Efficient Operations of Micro-Grids with Meshed Topology and Under Uncertainty through Exact Satisfaction of AC-PF, Droop Control and Tap-Changer Constraints

Micro-grids’ operations offer local reliability; in the event of faults or low voltage/frequency events on the utility side, micro-grids can disconnect from the main grid and operate autonomously while providing a continued supply of power to local customers. With the ever-increasing penetration of renewable generation, however, operations of micro-grids become increasingly complicated because of the associated fluctuations of voltages. As a result, transformer taps are adjusted frequently, thereby leading to fast degradation of expensive tap-changer transformers. In the islanding mode, the difficulties also come from the drop in voltage and frequency upon disconnecting from the main grid. To appropriately model the above, non-linear AC power flow constraints are necessary. Computationally, the discrete nature of tap-changer operations and the stochasticity caused by renewables add two layers of difficulty on top of a complicated AC-OPF problem. To resolve the above computational difficulties, the main principles of the recently developed “l1-proximal” Surrogate Lagrangian Relaxation are extended. Testing results based on the nine-bus system demonstrate the efficiency of the method to obtain the exact feasible solutions for micro-grid operations, thereby avoiding approximations inherent to existing methods; in particular, fast convergence of the method to feasible solutions is demonstrated. It is also demonstrated that through the optimization, the number of tap changes is drastically reduced, and the method is capable of efficiently handling networks with meshed topologies.

A Novel Multiline Fast Electromagnetic Unified Power Flow Controller Topology for Distribution Network

In order to promote the consumption of distributed generations and meet the power flow regulation requirements of the distribution network, a novel multiline fast electromagnetic unified power flow controller for the distribution network (D-MFEUPFC) is proposed. It has the advantages of compact structure, fast response, good economy, and high reliability with the traditional regulation mode. Besides, based on multiwinding transformer and hybrid on-load tap changer, D-MFEUPFC can quickly adjust the multiline power flow of the distribution network and absorb the output of new energy. The operating principles and characteristics of the D-MFEUPFC are analyzed to verify the deductions. Then, the multiline power flow equation considering D-MFEUPFC is derived with the comprehensive load model and power injection method, and its control strategy is studied. Finally, the effectiveness of the proposed D-MFEUPFC is proved by simulations and a prototype experiment. The results show that D-MFEUPFC can quickly adjust the multiline power flow within 60 ms, reasonably absorb the output of new energy, and improve the section transmission capacity. Moreover, D-MFEUPFC can realize decoupling control with high compensation accuracy, and the maximum errors of the active power and reactive power are 8.33% and 3.71%, respectively.

Intelligent transformer tap controller for harmonic elimination in photovoltaic interfaced micro-grid network

The photovoltaic (PV) system is interfaced to the microgrid through an on-load tap changer (OLTC) transformer. Pulse width modulation (PWM) AC choppers are used to control these OLTC but create harmonics owing to their non-optimal firing angles. In this paper, Differential Evolution (DE) and Grey Wolf Optimizer (GWO) techniques are used for optimal control of an AC chopper to keep the harmonic distortion of voltage and current within limits. An IEEE-13 node network is adapted as a micro-grid with PV integration through transformers. The simulated results are validated by a laboratory set-up. A dSPACE experimental set-up is used for the real-time implementation of optimization algorithms. The results show that the DE gives firing angles that improve power quality, particularly a reduction in total harmonic distortion and improvement in the root mean square voltage profile. The research is particularly useful for the on-line power quality improvement in PV interfaced microgrid networks.

Salp swarm algorithm for solving optimal power flow problem with thyristor-controlled series capacitor

In this paper, a salp swarm algorithm (SSA) is proposed for solving the optimal power flow (OPF) problem of a power system with the incorporation of the thyristor-controlled series capacitor (TCSC). The proposed methodology is implemented for determining the optimal setting of control variables for the OPF problem, which includes the real power of generators buses, voltages of generator buses, reactive power injected by shunt compensators, and tap changing transformer ratios. The performance of the proposed approach is validated and tested on the standard IEEE-30 bus system and single-objective functions, including transmission line losses. The severity factor has been minimized and the result obtained is compared with the existing algorithms. Simulation results achieved with the proposed SSA approach demonstrate that it results in an effective and better solution for the OPF problem.

Multi-objective-based reactive power planning and voltage stability enhancement using FACTS and capacitor banks

Reactive power planning (RPP) and voltage stability improvement (VSI) consider two of the most important problems to meet a major challenge of the power system. In this work, a multi-objective genetic algorithm (MOGA) for RPP with objectives of cost minimization of the power losses, new reactive power (VAR) sources, maximization of the VSI, and enhancement of total transfer capacity (TTC) is introduced. Different optimization variables are considered including generator voltages, transformer tap changers besides load, and different operational constraints. The best compromise solution is determined through a fuzzy min–max approach. Comparison studies among capacitor banks, flexible ac transmission systems (FACTS) or both as new VAR support sources to achieve better performance are explored. Moreover, the optimal allocations of switchable VAR sources are not determined in advance; instead, they are treated as control variables to improve the techno-economic operation of the network. Added to that many voltage stability indicators are presented, and their results are compared. The effectiveness of the proposed algorithm is examined on a modified IEEE 30-bus test system and South Egypt Electricity network where felicitous results have been acquired. The results expound on the effectiveness of the proposed approach compared with other optimization methods.

ОСОБЛИВОСТІ ДЕКОМПОЗИЦІЇ БАГАТОРІВНЕВИХ ВИПРЯМЛЯЧІВ ЗА УМОВИ ЗАДАНОГО ОБМЕЖЕННЯ ДІАПАЗОНУ РЕГУЛЮВАННЯ ВИХІДНОЇ НАПРУГИ

Harmonization of the requirements of certain groups of electrical and electrotechnological consumers of electricity with the current supply conditions requires in many cases the use of converters. Prominent among the systems designed to purposefully change the supply voltage of such consumers (regulation, stabilization) are converters with transformer-and-switches executive structure or tap changing (smart) transformers, which use discrete-time control, in particular so-called multi-level AC rectifiers (MLR). In the synthesis of MLR the main problem is to determine the optimal law of sectioning of the secondary envelope of its transformer. The paper analyzes the features of MLR decomposition into two functionally identical blocks under the given limitation of the output voltage control range and its difference from the decomposition of wide-range MLRs. The a priori variety of circuit technical solutions of such MLRs is determined. New MLRs with high efficiency of semiconductor switch elements use are offered. References 15, figures 7, tables 3.

A Bilevel Voltage Regulation Operation for Distribution Systems With Self-Operated Microgrids

The emerging of microgrids in distribution systems has significantly enhanced the resilience of power grids. However, the operators of a distribution system and microgrids therein can be different and have accessibility to different devices. To model the operation of such a grid, this paper proposes a bilevel formulation and probes into the voltage regulation operation, considering the interaction between different systems. The proposed bilevel formulation considers the cooperation of active energy resources (AER), transformer tap-changers, and capacitor banks that are controlled by different operators. To facilitate the solution time of the target bilevel optimization, the lower-level problems with different objectives are modeled using deep neural networks (DNNs) which are then converted into a set of constraints. Hence, the bilevel problem can be reformed to a single-level problem. Lastly, the proposed solution procedures are validated using a customized joint system constructed by the IEEE 123-bus system and a real distribution system in Iowa. According to the numerical validation results, the solution time of the proposed nonlinear activation function based DNN model is 69 times faster than other methods in solving voltage regulation with a bilevel structure.

Optimal Reactive Power Dispatch Using a Chaotic Turbulent Flow of Water-Based Optimization Algorithm

In this study, an optimization algorithm called chaotic turbulent flow of water-based optimization (CTFWO) algorithm is proposed to find the optimal solution for the optimal reactive power dispatch (ORPD) problem. The ORPD is formulated as a complicated, mixed-integer nonlinear optimization problem, comprising control variables which are discrete and continuous. The CTFWO algorithm is used to minimize voltage deviation (VD) and real power loss (P_loss) for IEEE 30-bus and IEEE 57-bus power systems. These goals can be achieved by obtaining the optimized voltage values of the generator, the transformer tap changing positions, and the reactive compensation. In order to evaluate the ability of the proposed algorithm to obtain ORPD problem solutions, the results of the proposed CTFWO algorithm are compared with different algorithms, including artificial ecosystem-based optimization (AEO), the equilibrium optimizer (EO), the gradient-based optimizer (GBO), and the original turbulent flow of water-based optimization (TFWO) algorithm. These are also compared with the results of the evaluated performance of various methods that are used in many recent papers. The experimental results show that the proposed CTFWO algorithm has superior performance, and is competitive with many state-of-the-art algorithms outlined in some of the recent studies in terms of solution accuracy, convergence rate, and stability.

Multi-agent based sine–cosine algorithm for optimal integration of DERs with consideration of existing OLTC in distribution networks

In this work, a modified version of the sine–cosine algorithm (SCA) has been developed to solve complex optimization problems. This proposed modified algorithm integrates the multi-agent system and sine–cosine algorithm and is termed as multi-agent sine–cosine algorithm (MA-SCA). This work also proposes a simplified strategy for the self-learning operator and modification in inversion operator. These proposed modifications have been validated by implementing the proposed MA-SCA algorithm on standard functions and comparing results with other reported optimization methods. Furthermore, in this work, MA-SCA algorithm has also been applied to optimally deploy the distributed energy resources (DERs) and shunt capacitors (SCs) in the distribution network with and without consideration of the existing on-load tap changing transformer (OLTC). The considered objectives in this optimization problem are reduction of cost of annual energy loss (CAEL) and minimization of voltage deviation under different loading conditions. To demonstrate the efficacy of the MA-SCA algorithm, it has been implemented on IEEE 33 bus radial distribution network (DN) and real-life Indian 108 bus radial DN. The comparison of obtained results with the results obtained by using other optimization methods has been carried out, and it indicates that MA-SCA algorithm provides the improved solution.

A new swarm intelligence optimization approach to solve power flow optimization problem incorporating conflicting and fuel cost based objective functions

Optimization of Power Flow (OPF) is a notable key tool pertinent to power system process, in both setting up and working phases and it is structured for a specific objective to optimize over power system variables, based on definite constraints. A new method of optimization based on swarm intelligence named Sparrow Search Algorithm (SSA), is proposed in this article to resolve the OPF problem in a most efficient way. The different equipped constraints like power balance, generator capacity, bus voltage limit and line flow, were taken into account. Shunt reactive power compensating elements and tap changing transformer settings were also incorporated in the problem formulation as control variables. The proposed SSA based OPF was constructed by several constraints, formulations and objective functions, scrutinized with higher number of cases (33 cases), for the first time, on the three well-liked IEEE networks (IEEE 30-, 57- and 118-bus) via single and weighted amount multi-objectives. The simulation result was examined and the performance and preeminence of the obtainable method was evaluated against other well-constructed recent optimization studies, reported in the literature. The percentage reduction of fuel rate, active transmission loss and deviation in voltage, were examined and compared with some most important recent studies, specified in the literature. Percentage improvement of voltage stability was also evaluated with recent studies, accounted in the literature.

Optimized Voltage-Led Customer Load Active Service Using Genetic Algorithm in Distribution Networks

To mitigate the low frequency problem in a transmission system in an event of a power station failure or during low renewable generation production, UK National Grid (NG) Electricity System Operator has balancing mechanism in place with generators to provide temporary extra power, or with large energy users to reduce load demand or so call fast reserve services. This paper presents an alternative method to aggregately control the existing distribution network primary on load transformer tap changers as a voltage-led customer load active service. The main benefits of the proposed method are (i) to unlock the distribution network load demand flexibility without causing any negative impact on customers, and (ii) to provide the lowest cost of fast reserve service from a distribution network to transmission network. In this paper an optimal control strategy based on genetic algorithm is proposed and developed to achieve an optimized voltage-led customer load active service with the aim of finding the optimal dispatch of on load transformer tap changers by minimizing each transformer tap switching operation as well as network losses. Two practical 102 buses and 222 buses UK distribution networks have been modelled and used to demonstrate and compare the effectiveness of the proposed control methods under different operating conditions. The performances of the proposed method are also compared with both the rule-based and the branch-and-bound methods. The results show that the proposed optimal control strategy based on the genetic algorithm is more effective by achieving more accuracy and a faster solution for a large distribution network than other two methods. These are important findings as the fast reserve service by transmission network requires the accuracy of the load demand reduction delivery within 2 minutes.

Estimation of Line Parameters, Tap Changer Ratios, and Systematic Measurement Errors Based on Synchronized Measurements and a General Model of Tap-Changing Transformers

A primary requirement for the transmission system operator is an accurate knowledge of grid parameters. Moreover, the availability of effective and accurate monitoring tools allows the proper operation of power transmission grids. However, in spite of the now widespread possibility of having monitoring systems based on synchronized measurements, the monitoring applications can be affected not only by the inevitable uncertainty sources but also by the simplified or incomplete modelling of the network components. For this reason, the impact on power system monitoring and control applications of tap-changing transformer models is a key point. In this scenario, this paper presents a method to estimate simultaneously line parameters, tap changer ratios and systematic measurement errors associated with the instrument transformers. The method exploits a flexible model of the tap-changing transformer based on a parameter representing the ratio between the two winding impedances of the transformer. The proposal is based also on the suitable modelling of the measurement chain and on the constraints introduced by the equations of involved transmissions lines and transformers. The validation has been carried out by means of tests performed on the IEEE 14 Bus Test Case.

Approximating multi-purpose AC Optimal Power Flow with reinforcement trained Artificial Neural Network

Solving AC-Optimal Power Flow (OPF) problems is an essential task for grid operators to keep the power system safe for the use cases such as minimization of total generation cost or minimization of infeed curtailment from renewable DERs (Distributed Energy Resource). Mathematical solvers are often able to solve the AC-OPF problem but need significant computation time. Artificial neural networks (ANN) have a good application in function approximation with outstanding computational performance. In this paper, we employ ANN to approximate the solution of AC-OPF for multiple purposes. The novelty of our work is a new training method based on the reinforcement learning concept. A high-performance batched power flow solver is used as the physical environment for training, which evaluates an augmented loss function and the numerical action gradient. The augmented loss function consists of the objective term for each use case and the penalty term for constraints violation. This training method enables training without a reference OPF and the integration of discrete decision variable such as discrete transformer tap changer position in the constrained optimization. To improve the optimality of the approximation, we further combine the reinforcement training approach with supervised training labeled by reference OPF. Various benchmark results show the high approximation quality of our proposed approach while achieving high computational efficiency on multiple use cases.

Enhancing PV Hosting Capacity Using Voltage Control and Employing Dynamic Line Rating

Photovoltaic (PV) system installation has encouraged to be further expedited to minimize climate change and thus, rooftop solar PV systems have been sparkled in every corner of the world. However, due to technological constraints linked to voltage and currents, the PV hosting capacity has been substantially constrained. Therefore, this paper proposes a competent approach to maximize PV hosting capacity in a low voltage distribution network based on voltage control and dynamic line rating of the cables. Coordinated voltage control is applied with an on-load tap changing transformer, and reactive power compensation and active power curtailment of PV inverters. A case study with probabilistic and deterministic assessments is carried out on a real Sri Lankan network to show how the PV hosting capacity is constrained. The findings revealed the capability of integrated voltage control schemes and dynamic line rating in maximizing hosting capacity. The study is expanded by incorporating the PV rephasing approach in conjunction with the aforementioned control techniques, and the effectiveness of PV-rephasing is clearly demonstrated. When compared to voltage control and conductor static rating, the combined rephasing, voltage control, and DLR yielded a 60% increase in PV hosting capacity.