Load Tap Changer Research Articles

Distributed energy storage planning in soft open point based active distribution networks incorporating network reconfiguration and DG reactive power capability

The integration of high-penetration distributed generators (DGs) with smart inverters and the emerging power electronics technology of soft open points provide increased controllability and flexibility to the operation of active distribution networks. Existing works on distributed energy storage planning have not fully considered the coordinated operation of these new power electronic devices with distributed energy storage systems, leading to less economic investment decisions. This paper proposes an optimal planning model of distributed energy storage systems in active distribution networks incorporating soft open points and reactive power capability of DGs. The reactive power capability of DG inverters and on load tap changers are considered in the Volt/VAR control. Moreover, soft open points are modeled to provide flexible active and reactive power control on the associated feeders. Hourly network reconfiguration is conducted to optimize the power flow by changing the network topology. A mixed-integer second-order cone programming model is formulated to optimally determine the locations and energy/power capacities of distributed energy storage systems. Finally, the effectiveness of the proposed model is validated on a modified IEEE 33-node distribution network. Considering soft open points, DG reactive power capability, and network reconfiguration, the results demonstrate the optimal distributed energy storage systems planning obtained by the proposed model achieves better economic solution.

Voltage Stability Monitoring From a Transmission Bus PMU

This paper examines the problem of monitoring long-term voltage instability from a phasor measurement units installed at any transmission bus. It is shown that the well-known impedance matching condition on a radially connected load bus, as well as the local identification of voltage emergency situations (LIVES) method based on load tap changing transformers can be generalized into a New LIVES Index suitable for any transmission bus feeding a weak area of a system. Results on an IEEE voltage stability test system validate the dependability and security of the new index for the early detection of voltage instability. Moving average, as well as a new filtering method based on short-time Fourier transform are employed to reduce the effect of noise and short-term transients.

Electronics Solid State Voltage Regulating Relay for on Load Tap Changer Distribution Transformer for AVR (Automatic Voltage regulation)

Electronics Solid State Voltage Regulating Relay for on Load Tap Changer Distribution Transformer for AVR (Automatic Voltage regulation)

Convex probabilistic allocation of wind generation in smart distribution networks

This study introduces a probabilistic optimisation model for allocation of renewable distributed generations (DGs) in radial distribution networks. The methodology is based on a probabilistic generation – load model that combines all possible operating conditions of the wind-based DG units as well as load levels with their probabilities. A multiobjective performance index is extracted that is formulated as a combination of two indices, namely energy losses reduction and voltage improvement. Besides, a probabilistic AC optimal power flow is used to determine the optimal allocation of wind DG and maximise the multiobjective performance index. Two alternative control approaches of the future smart grids, i.e. area based under load tap changer control and adaptive power factor control, are assessed to maximise potential benefits and expand the penetration level of DGs. At first, this problem is formulated as a mixed-integer non-linear programming (MINLP) which leads to a computationally NP-hard problem. Accordingly, the obtained MINLP problem is relaxed and reformulated in the form of a well-suited second-order cone programming problem which is computationally efficient scheme to be solved. The implementation of the proposed framework on 4-bus and IEEE 33-bus radial distribution systems shows the performance of the proposed optimisation mechanism.

The challenges of estimating the impact of distributed energy resources flexibility on the TSO/DSO boundary node operating points

The increasing penetration of renewable energy sources characterized by a high degree of variability and uncertainty is a complex challenge for network operators that are obligated to ensure their connection while keeping the quality and security of supply. In order to deal with this variable behavior and forecast uncertainty, the distribution networks are equipped with flexible distributed energy resources capable of adjusting their operating point to avoid technical issues (voltage problems, congestion, etc.). Within this paradigm, the flexibility that, in fact, can be provided by such resources, needs to be estimated/forecasted up to the transmission network node (primary substation) and requires new tools for TSO/DSO coordination. This paper addresses this topic by developing a methodology capable of finding the flexibility area while taking into account the technical grid constraints. The proposed approach is based on the formulation of a single optimization problem which is run several times, according with the expected precision for the flexibility area estimation. To each optimization problem run, a different objective function belonging to a family of straight lines is assigned. This allows exploring the active and reactive power flow limits at the TSO/DSO boundary nodes – which define the flexibility area. The effectiveness of the proposed model has been evaluated on two test networks and the results suggest a step forward in the TSO/DSO coordination field. Nevertheless, further investigations to study the effect of assets with discrete control nature (e.g., on load tap changers – OLTC, capacitor banks) on the occurrence of disjoint flexibility areas should be carried.

Two‐layer volt/var/total harmonic distortion control in distribution network based on PVs output and load forecast errors

A two-layer control method is proposed for voltage and reactive power control in harmonic polluted distribution network with penetration of photovoltaic (PV) systems. Optimal scheduling of load tap changer and shunt capacitors for minimising energy losses and improving the power quality simultaneously are performed using P-particle swarm optimisation (PSO) optimisation method. Here, the minimising cost of real power losses and improving the power quality criteria have been pursued as the goals of an optimisation problem. Considering load and PVs output forecast, the first-layer control determines the optimal reactive power and control settings for all mechanical controllers. Hourly errors of load and power forecasts and mechanical control setting of the first layer are used to estimate optimised reactive power of PV in order to achieve maximum voltage regulation, reduce network losses and total harmonic distortion (THD). These data are trained a neural network (NN) to estimate optimised PV reactive power. This NN in the second layer is used to optimise the online reactive power setting based on online PV power. For more practical applications of the proposed method, simulation is carried out in a large distorted 37-bus distribution system. The algorithm will increase use of renewable energies, reduce voltage fluctuations, THD, and wear and tear of mechanical equipment.

Optimal coordination of voltage controllable devices in distribution systems using power‐based models and quadratic programming

The incorporation of photovoltaic (PV) inverters makes the management of voltage difficult for power system operators. One solution is to consider these inverter‐based devices as controllable reactive power (VAr) sources and to coordinate them with other voltage regulating devices in the distribution system. This paper proposes some acceptable approximations to quickly formulate and solve a mixed‐integer quadratic programming problem to periodically determine the optimal voltage coordination of a load tap changer, voltage regulators, capacitor banks, and PVs on a smart grid platform. The solution to the optimization problem is aided by an iteration‐based algorithm. By using the MATLAB software to carry out the simulation and computation, the method is well verified by comparing its generated result with a trustworthy solution obtained from examining all possible coordinating combinations of voltage regulating devices and PVs in a modified IEEE 34‐bus system. The effectiveness and features of the method are clearly illustrated on that test system by considering a time‐varying load and PV generation. The obtained results demonstrate the practical application of this work to medium‐voltage systems. © 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

Thyristor Switched Smart Transformer for Active Power Flow Control in Multi Micro grid System

An intentional active power flow control between microgrids in a multi micro grid system in the grid connected mode is achieved at the point of common coupling. The thyristor controlled on load tap changing transformer at the point of common coupling is equipped with voltage based power flow controller where different tapping are switched according to the required power flow condition to be satisfied and the amount of power to be transmitted. Accordingly, the voltage based droop control associated with the distributed generation units in each of the micro grid changes their active power generation. Thus, without much communication to other elements of the micro grids, the Smart Transformer at the point of common coupling allows active power exchange. The simulations performed in MATLAB/ SIMULINK for both three phase and single phase system follows that active power flow control is achieved in a multi micro grid system using the thyristor switched Smart Transformer. Hardware implementation has also been initiated to analyze the concept of power flow control with thyristor switched Smart Transformer and results are studied. The proposed system shows its operational effectiveness, which can be employed to solve grid emergencies in real time.

Optimal Reactive Power Dispatch With Accurately Modeled Discrete Control Devices: A Successive Linear Approximation Approach

In this paper, a novel solution to the optimal reactive power dispatch (ORPD) problem is proposed. The nonlinearity of the power flow equations is handled by a new successive linear approximation approach. For the voltage magnitude terms, a mathematical transformation that improves the accuracy and facilitates the linear modeling of shunt capacitors is used. Without loss of accuracy, the load tap changers and shunt capacitors are both modeled by linear constraints using discrete variables, which facilitates the linearly constrained mixed-integer formulation of the proposed ORPD model. An efficient iterative solving algorithm is introduced. The obtained solution strictly satisfies the power flow equations. Case studies on several IEEE benchmark systems show that the proposed algorithm can efficiently provide near-optimal solutions with the error of the objective functions of less than 0.1%. Compared with several commercial solvers, the proposed method shows distinct advantages in terms of both robustness and efficiency. Moreover, based on the round-off results, a heuristic method that reduces the optimization ranges of the discrete control variables is proposed. This method can further improve the computational efficiency with small losses in accuracy.

Distributed Computing Architecture for Optimal Control of Distribution Feeders With Smart Loads

This paper presents a distributed computing architecture for solving a distribution optimal power flow (DOPF) model based on a smart grid communication middleware (SGCM) system. The system is modeled as an unbalanced three-phase distribution system, which includes different kind of loads and various components of distribution systems. In this paper, fixed loads are modeled as constant impedance, current and power loads, and neural network models of controllable smart loads are integrated into the DOPF model. A genetic algorithm is used to determine the optimal solutions for controllable devices, in particular load tap changers, switched capacitors, and smart loads in the context of an energy management system for practical feeders, accounting for the fact that smart loads consumption should not be significantly affected by network constraints. Since the number of control variables in a realistic distribution power system is large, solving the DOPF for real-time applications is computationally expensive. Hence, to reduce computational times, a decentralized system with parallel computing nodes based on an SGCM system is proposed. Using a “MapReduce” model, the SGCM system runs the DOPF model, communicates between master and worker computing nodes, and sends/receives data among different parts of parallel computing system. Compared to a centralized approach, the proposed architecture is shown to yield better optimal solutions in terms of reducing energy losses and/or energy drawn from the substation within adequate practical run-times for a realistic test feeder.

Local identification of voltage instability from load tap changer response

Abstract This paper presents a local long-term voltage instability monitoring method, which is suitable for on-line applications. The proposed extended-time Local Identification of Voltage Emergency Situations (eLIVES) method is a significantly modified version of the previously presented LIVES method. The new method is not bound to assessing system response over a predefined LTC tapping period. This allows handling LTCs with variable delays, as well as events taking place during the tapping sequence impacting the distribution voltages. For that purpose, eLIVES applies recursive least square fitting to acquired distribution voltage measurements and a new set of rules to detect a voltage emergency situation. The effectiveness of the eLIVES method is presented on the IEEE Nordic test system for voltage stability and security assessment.

Volt/VAr Optimization of Distribution System with Integrated Distributed Generation

This paper addresses the issues of VVO (Volt/VAr Optimization) such as loss minimization, acceptable voltage profiles and optimized number of switching operations. Basic function of the DMS (Distribution Management System) is to upgrade system intelligence so that it can make dynamic decisions and control the network in realtime. Distributed generators can cause the system to operate above and below the desired limits due to their variable nature. Therefore, devices like SC (Shunt Capacitors) and OLTC (On Load Tap Changers) are used in distribution system as control devices. Main focus of this paper is to inspect effects of DG (Distributed Generation) on switching states of control devices while considering Volt/VAr standards. An optimization search algorithm is employed to search the optimal solution considering the system constraints. The GA (Genetic Algorithm) is used for the optimization process of the system and the simulation is done in MATLAB using IEEE-30 bus system with DG under 24 hour changing load profiles. By setting up constraints of distribution system’s voltage limits, capacitor bank and OLTC, losses are minimized up to 50%. Merits of the proposed optimized method are demonstrated through simulation results .The result achieved from the proposed technique has proven to be beneficial for switching optimization of control devices under variant conditions of loads and distributed generation

Analysis of the vibration modes in the diverter switch of load tap changer

Analysis of the vibration modes in the diverter switch of load tap changer

Contribution of Distribution Network Control to Voltage Stability: A Case Study

A case study dealing with long-term voltage instability in systems hosting active distribution networks (DN) is reported in this paper. It anticipates future situations with high penetration of dispersed generation (DG), where the latter are used to keep distribution voltages within desired limits, in complement to load tap changers. The interactions between transmission and active DN are investigated on a 3108-bus test system. It involves transmission grid, large generators, and 40 DN, each with DG steered by a controller inspired by model predictive control. The reported simulations show the impact of distribution network voltage restoration, as well as the benefit of load voltage reduction actuated by the dispersed generators.

OLTC를 활용한 도시철도 최대전력 감축에 관한 연구

논문에서는 도시철도의 변전소의 최대수요전력을 줄이기 위한 새로운 방법으로 OLTC(:On Load Tap Changer)를 갖는 변압기의 사용을 제안한다. 국내의 대부분의 도시철도는 전동차에 필요한 전력을 다이오드 방식으로 정류하며 DC 1500[V]로 공급한다. 변전소가 병렬로 연결되어 있기 때문에 수전전압이 상승하면 정류기 전압도 상승하게 되고 변전소의 최대전력도 증가하게 된다. 시뮬레이션 결과를 통해 본 논문에서 제안하는 방법이 최대수요전력의 증가를 상당히 제한할 수 있음을 보인다. This paper proposes a new method reducing the maximum demand power of substations at urban railway by using transformer with OLTC(:On Load Tap Changer). Most of the domestic urban railway is rectified by a diode scheme, and supplies the electric vehicles in dc 1500[v]. Because the substations are connected in parallel, if an input voltage of a substation is increased, then the voltage of rectifiers is also increased, and which leads to an increase in the maximum demand of the substation. Simulation results show that increment of maximum demand power can significantly be limited using the method proposed in this paper.

Embedding OLTC nonlinearities in predictive Volt Var Control for active distribution networks

This paper presents an original procedure to embed the On Load Tap Changer (OLTC) nonlinearities in a predictive real-time Volt Var Control (VVC) for distribution systems. These commonly disregarded nonlinearities are namely the OLTC time-delays, the dead-band and the discrete nature of tap change. It is shown that using a continuous approximation can lead to control failures. The proposed nonlinear controller accurately anticipates the response of the system and the costs associated with control efforts. Demonstrations are performed in a 20kV network to assess the performance of such a procedure compared to a predictive VVC using an OLTC continuous approximation.

Optimal power flow using moth swarm algorithm

This work presents a novel Moth Swarm Algorithm (MSA), inspired by the orientation of moths towards moonlight to solve constrained Optimal Power Flow (OPF) problem. The associative learning mechanism with immediate memory and population diversity crossover for Lévy-mutation have been proposed to improve exploitation and exploration ability, respectively, in addition to adaptive Gaussian walks and spiral motion. The MSA and four heuristic search algorithms are carried out on the IEEE 30-bus, 57-bus and IEEE 118-bus power systems. These approaches are applied to optimize the control variables such as real power generations, load tap changer ratios, bus voltages and shunt capacitance values under several power system constraints. Fourteen different cases are executed on different curves of fuel cost (e.g., quadratic, valve-loading effects, multi-fuels options), environmental pollution emission, active power loss, voltage profile and voltage stability for contingency and normal conditions, in single and multi objective optimization space. Furthermore, the impacts of the updating mechanism of optimizers on those objective functions are investigated. The effectiveness and superiority of the MSA have been demonstrated in comparison with many recently published OPF solution

On Coordinated Control of OLTC and Reactive Power Compensation for Voltage Regulation in Distribution Systems With Wind Power

Active management strategies such as coordinated on load tap changer (OLTC) voltage control and reactive power compensation (RPC) are frequently suggested for voltage regulation in a distribution system with a high level of distributed generation (DG). This paper proposes a control and coordination algorithm for these two active management strategies. Voltage control through OLTC is achieved by using state estimation (SE) to determine the voltage in the network. To lower the implementation cost of the proposed control strategy, pseudo-measurements are used together with real-time measurement data in the SE. Moreover, the deadband of the automatic voltage control (AVC) relay is relaxed so that the AVC relay acts on the network’s maximum or minimum voltage obtained through the SE. This is found to be simpler to realize than adjusting the set point of the AVC relay. Voltage control through RPC is actualized by using integral controllers implemented locally at the wind turbine site. Furthermore, RPC from the local wind turbine is also used to mitigate an overvoltage at a remote bus on the same feeder when the remote wind turbine reaches its regulation limit. The applicability of the proposed voltage regulation algorithm is successfully demonstrated using a case study system.

Determining the Power and Energy Capacities of a Battery Energy Storage System to Accommodate High Photovoltaic Penetration on a Distribution Feeder

The integration of distributed energy generation systems has begun to impact the operation of distribution feeders within the balancing areas of numerous electrical utilities. Battery energy storage systems may be used to facilitate greater integration of renewable energy generation. This paper describes a method for determining the power and energy capacities a battery energy storage system would need in order to accommodate a particular photovoltaic penetration level within a distribution feeder, or conversely, the amount of photovoltaic that could be installed on a feeder with a minimal investment in power and energy battery energy storage system (BESS) capacities. This method determines the BESS capacities required to compensate both intra-hour and inter-hour load and photovoltaic fluctuations to achieve a flat feeder power profile. By managing the feeder power, the voltage drop along the length of feeder may be managed, thereby mitigating the voltage fluctuation induced by the stochastic nature of both renewables generation and load. Doing so facilitates system benefits, such as conservation voltage reduction, fewer operations of load tap changers, and voltage regulators, and allows for deferment of capital expenditures.

Distributed Generation Hosting Capacity Evaluation for Distribution Systems Considering the Robust Optimal Operation of OLTC and SVC

With the rapidly increasing penetration of renewable distributed generation (DG), the maximum hosting capacity (MHC) of a distribution system has become a major concern. To effectively evaluate the ability of a distribution system to accommodate DGs, this paper proposes an MHC evaluation method while considering the robust optimal operation of on load tap changers (OLTCs) and static var compensators (SVCs) in the uncertain context of DG power outputs and load consumptions. The proposed method determines the DG hosting capacities corresponding to different conservative levels. Furthermore, this paper discusses how to find out the most critical technical constraint that may limit the MHC by adjusting parameters of the proposed robust formulation. The effectiveness of the proposed method is demonstrated using a modified IEEE 33-bus distribution system.