Systematic modelling and analysis of TAPP voltage control schemes

Voltage control is considered one of the basic operational requirements of electrical power systems both at distribution and transmission levels. It continues to attract the attention of workers to improve and/or develop new voltage control techniques particularly to accommodate distributed generation. The most popular voltage control equipment includes on- load tap changer (OLTC) transformer controlled by automatic voltage control (AVC) relay, which is mostly used in 11 kV networks. In recent years, a growing number of distributed/embedded generators are connected to distribution networks. Conventional AVC relay usually equipped with compounding whose setting are chosen to compensate for the voltage drop along the feeder(s) emanating from source substation. However, the integration of distributed/embedded generators (DG/EGs) including wind farms into distribution systems causes voltage regulation problems due to the interference with the performance of AVC relay. It has been found that the presence of DGs causes the voltage measured by conventional AVC relay to be shifted upwards or downwards compared depending on the power factor of the current through OLTC transformer. It also depends on the power factor of DG and system load. As a result, a proper voltage control of distribution network can not be achieved. Therefore, a new voltage control scheme of supply system with DG will be developed. This paper presents an attempt to design an AVC relay based on fuzzy logic (FL). In this paper the structure of the proposed FL based AVC relay is presented and the results that show its performance with and without embedded generation in distribution network are also presented and discussed.

Voltage control in distribution networks becomes increasingly important with an increasing penetration of distributed generation (DG). As distribution networks are much more resistive than transmission networks, the conventional technique of reactive power compensation in order to control the voltage cannot be applied very well. For that reason other voltage control techniques have to be applied. In this contribution several options for voltage control in distribution networks are analyzed and related to important grid parameters such as the short-circuit ratio and the X/R ratio of the grid. For networks with a high X/R ratio reactive power can be used for voltage control. For networks with a low X/R ratio several new voltage control techniques are proposed. These techniques are voltage control with active power, inserting a controllable inductance in the grid and series compensation by DG unit converters.

Distribution networks have been experiencing significant changes under the pressure of the energy transition. The high integration of renewable energy sources combined with the electrification process introduces new challenges in managing distribution networks. Innovative solutions aimed at optimizing the control of complex problems, starting from historical data instead of a detailed system model, have been growing due to rapid development in artificial intelligence and machine learning. This paper proposes a Q-learning algorithm to control the tap setting of the on-load tap changer installed in primary substation transformers. The ultimate goal is to maintain voltage magnitudes at all busses of the medium-voltage distribution network within a safe range, simultaneously optimizing on-load tap changer operations. As a case study, the effectiveness of the proposed algorithm is assessed using a real medium-voltage distribution network with high penetration of renewable energy sources that supplies more than 2500 users/prosumers. The ability of the proposed algorithm to control bus voltages is tested in several scenarios characterized by significant variability and uncertainty. Outcomes show that the proposed algorithm is suitable for optimizing voltage control in distribution networks using a data-driven approach.

This paper studies the participation of doubly-fed induction wind generator (DFIG), as a continuous variable, in dynamic optimization of reactive power and voltage control in the distribution network by obtaining the reactive power capability through controlling the power electronic interfaces and taking DFIG rated parameters into accounts. Given the fluctuation in the DFIG output active power, a time partition method based on the variance of the DFIG output active power has been proposed. According to the results of the time partition method, the operational requirements and the characteristics of the control variables in the distribution network, different dynamic optimization algorithms have been applied in different optimization time. The simulation based on the improved IEEE 33-bus system has been conducted to validate the effectiveness of the proposed optimization strategy.

A new and efficient methodology for optimal reactive power and voltage control of distribution networks with distributed generators based on fuzzy adaptive hybrid particle swarm optimisation (PSO) is proposed. The objective is to minimise comprehensive cost, consisting of power loss and operation cost of transformers and capacitors, and subject to constraints such as minimum and maximum reactive power limits of distributed generators, maximum deviation of bus voltages and maximum allowable daily switching operation number. PSO is used to solve the corresponding mixed integer non‐linear programming problem and the hybrid PSO (HPSO) method, consisting of three PSO variants, is presented. In order to mitigate the local convergence problem, fuzzy adaptive inference is used to improve the searching process and the final fuzzy adaptive inference‐based HPSO is proposed. The proposed algorithm is implemented in VC++ 6.0 program language and the corresponding numerical experiments are finished on the modified version of the IEEE 33‐node distribution system with two newly installed distributed generators and eight newly installed capacitors banks. The numerical results prove that the proposed method can search a more promising control schedule of all transformers, all capacitors and all distributed generators with less time consumption, compared with other listed artificial intelligent methods.

A bi-level optimization method for voltage control in distribution networks using batteries and smart inverters with high wind and photovoltaic penetrations

This paper proposes a multi-agent control scheme in order to coordinate between distributed battery energy storage systems (BESS) and renewable distributed generation (DG) units in distribution networks. The proposed control scheme aims to utilize BESSs as distributed voltage controllers across the distribution network, in such a way to overcome the intermittent high-ramp rate of renewable DG units. To that end, the voltage control in distribution networks is formulated as a distributed constraint satisfaction problem (DisCSP). An asynchronous weak commitment approach is utilized to solve the formulated problem. Several case studies are carried out to test the effectiveness and performance of the proposed algorithm under different operating conditions.

This paper proposes a distributed coordinated voltage control scheme for distribution networks with distributed generation (DG) and on-load tap changer (OLTC). In this scheme, static synchronous compensators (STATCOMs), DG units and OLTC are coordinated to regulate voltages of all buses to be close to the nominal value in the distribution network, mitigate voltage fluctuations, and minimize the number of operations of OLTC while considering different temporal characteristics of voltage regulation devices. The optimization problem of coordinating DG units and STATCOMs is decomposed by the gradient projection (GP) method. The local controller optimizes the reactive power outputs of DGs and STATCOMs according to local voltage and reactive power measurements, and still achieves the optimal coordination of DG units and STATCOMS in a decentralized manner without a central controller or communication between local controllers. The OLTC control scheme is designed to correct the long-term voltage deviations based on model predictive control (MPC) while minimizing the number of operations. The local controllers send the calculated reactive power references of DG and STATCOMs to the OLTC controller, which achieves distributed coordinated voltage control and mitigates the computation burden.

Network partition-based hierarchical decentralised voltage control for distribution networks with distributed PV systems

Large-scale integration of renewable generation has changed the way that distribution networks are operated, posing significant challenges to voltage control. To address this challenge, system operators need to exploit the potential of inverter-based renewable generation for reactive power regulation. However, the distribution network parameters are usually inaccurate or incomplete, making conventional centralized or model-dependent distributed control methods difficult for fast voltage tracking and optimal reactive power distribution. This paper proposes a model-free distributed Newton method for voltage control based on data-driven lift-dimension linear power flow which does not reply on accurate and complete network parameters. By using matrix splitting to calculate Hessian matrix, the proposed method possesses a super-linear convergence and exhibits superiority in fast response over existing linear methods. Furthermore, a Koopman-based state space mapping method is proposed to obtain global sensitivity and tune the iteration direction in an off-line manner, which can realize model-free voltage control. The convergence and optimality of the proposed method are validated by case studies. Especially, the parameter independence feature of the model-free scheme provides decided superiority in scenarios of incomplete model. Even under communication failures, the proposed method still can maintain voltage stability at a suboptimal point.

This paper shows that the smart loads could be effective in mitigating voltage problems caused by photovoltaic (PV) generation and electric vehicle (EV) charging in low voltage (LV) distribution networks. Limitations of the previously reported smart load configuration with only series reactive compensator (SLQ) (one converter) is highlighted in this paper. To overcome these limitations, an additional shunt converter is used in back-to-back (B2B) configuration to support the active power exchanged by the series converter, which increases the flexibility of the smart load without requiring any energy storage. Simulation results on a typical UK LV distribution network are presented to compare the effectiveness of a smart load with B2B converters (SLBC) against an SLQ in tackling under- and over-voltage problems caused by EVs or PV. It is shown that SLBCs can regulate the mains voltage more effectively than SLQs especially, under over-voltage condition. Although two converters are required for each SLBC, it is shown that the apparent power capacity of each converter is required to be significantly less than that of an equivalent SLQ.

This paper proposes a hierarchical multi-stage approach based on a distributed level phasor measurement unit (µPMU) at local controllers and a phasor data concentrator (PDC) at the central control unit to restore system voltage when it exceeds the limits recommended by the IEEE 1547-2018 standard. The proposed algorithm does not need an accurate system model or employ optimization solutions. Therefore, it has less implementation complexity and would be popular among distribution network service providers (DNSPs) and distribution network operators (DNOs) as it does not suffer from cost and computational complexity limitations. A PMU-PDC-based communication platform has been developed as a more efficient alternative to the supervisory control and data acquisition (SCADA) system, and provides superior characteristics, including a higher sample rate, higher data resolutions, and faster communication. The proposed coordinated algorithm aims to postpone power generation curtailment in distributed energy resources (DERs) with overvoltage problems (local DERs) by incorporating all the DERs that are not subjected to voltage violation (remote DERs) by absorbing their maximum reactive power capacity. If the system voltage has not recovered after absorbing all of the reactive power capacity of all the DERs, a reduced active power curtailment proposed by the algorithm is then applied to the system to control the voltage. The proposed strategy has been simulated in MATLAB and applied to IEEE 13-bus and IEEE 33-bus radial distribution benchmark systems to validate the performance of the system, in terms of its ability to coordinate voltage control and the accuracy of the PMU-PDC-based communication interface.

With the high penetrated photovoltaics (PVs) accessing distribution networks (DNs) in the future, the overvoltage of distribution network will be more serious, and the voltage control will be more complex. To solve this problem, a cluster partition-based zonal voltage control method for DN is proposed in this study. First, a cluster partition method using a comprehensive performance index is proposed: in terms of DN structure, a global density quality function index is introduced to measure the coupling degree of nodes in clusters. In terms of cluster function, the inconsistency coefficient index is presented to reflect the PV output characteristics, and a node membership function index is presented to limit the scale of the cluster. Then, the DN cluster partition is carried out under the fast Newman (FN) algorithm. Second, a second-order cone programming (SOCP) model of voltage control is established to maximize the PV consumption in each cluster. To achieve the coordinated optimization of clusters, an iterative optimization strategy among clusters is proposed. Finally, the effectiveness and rationality of the proposed method are verified in a 10 kV actual feeder system in Zhejiang Province, China.

Optimal voltage control in distribution network in the presence of DGs

Along with the advancement of renewable energy development strategy, photovoltaic (PV) power technology has gained rapid progress in recent years. Due to the rapid growth of PV power penetration in power system, the research with PV power grid integration are drawing more and more attention, such as low voltage ride through (LVRT), automatic voltage control (AVC), voltage stability and so on. This paper investigates on voltage and reactive power control characteristic of grid-connected solar PV plant based on simulation. The voltage and reactive power control strategy uses the grid-connected inverters and static VAR compensation (SVC) device as flexible and controllable source of reactive power to regulate the voltage and reactive power of large-scale PV power plants. The PV inverters and SVC both have a variety of control mode generally, such as constant voltage control mode, constant reactive power control mode, constant power factor (PF) control mode and so on. The coordination control characteristic between PV inverter and SVC is analyzed in this paper. Through in-depth study of the characteristics of different combinations of control modes, the operating characteristics of PV power plants are summarized. The research results of this paper are helpful to the development of AVC sys tem.