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

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.

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.

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.

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.

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.

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 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.

It is the responsibility of the distribution network operator (DNO) to maintain voltage profiles within statutory limits across a range of conditions such as varying load or intermittent output of distributed generation. An effective device for voltage control in distribution networks is the on-load transformer tap changer equipped with automatic voltage control (AVC) relays. In order to increase security of supply, it is common practise for the DNO to parallel transformers. A number of factors that can influence the optimum tap position are primary voltage level, load level, power factor, distributed generation and circulating current. This paper presents, firstly, an overview of automatic voltage control methods for paralleled transformers and related standard DNO practice. Secondly, a detailed description of the established transformer automatic paralleling package (TAPP) schemes is presented. Finally, modelling and analysis of the TAPP scheme is performed for a range of distribution network case studies in order to determine and evaluate the effect of the above factors on optimum tap position. Results from the modelling and analysis of the TAPP scheme and conclusions are also presented.

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

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 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.

With the accelerating penetration of photovoltaics (PVs) and electric vehicles (EVs), distribution networks face the risks of voltage violations and fluctuations. On the one hand, conventional voltage regulation resources like OLTC transformers and capacitor banks feature slow response and limited lifetime duration, making them incapable of quickly responding to the temporary voltage issues created by PVs and EVs. On the other hand, EVs and PVs interact with the power grid via fully controllable power electronic converters capable of real-time adjusting their operating settings, making them ideal voltage support resources. To exploit the voltage support capability of PVs and EVs, this paper proposes a two-stage control scheme for the voltage regulation of distribution networks, consisting of the day-ahead and intraday control stages. The day-ahead control mitigates potential voltage violations via day-ahead scheduling of the operation settings for OLTC transformers and capacitor banks. The intraday control further alleviates voltage deviations and voltage fluctuations based on the reactive power support of PV systems and the rational EV charging/discharging scheduling. A rolling optimization-based control technique is proposed in the intraday control stage to achieve real-time control of EVs and PVs with the stochastic nature of EV charging behaviors inherently considered. The proposed two-stage voltage regulation scheme is validated via case studies performed on the IEEE 123-node test feeder integrated with PVs and EVs.

With increasing connection of distributed generations (DGs), the power flow in electric distribution network is no longer unidirectional and the network has become active distribution network. Thus, the connection of DGs in electric distribution networks has created a challenge for distribution network operators due to bidirectional power flow. One of the main technical challenges of an active distribution network is to maintain an acceptable voltage level in the system. This has initiated efforts in using various voltage control strategies to regulate the network voltage profile so that the voltage is maintained at its allowable voltage limits. A number of voltage control methods have been applied to solve voltage control problems associated with the connection of DGs in a distribution system. These voltage control strategies may be classified as decentralized or distributed and centralized or coordinated voltage control. From the literature, a number of coordinated voltage control strategies have been implemented to provide better and faster control to the system. This chapter presents an improved coordinated voltage control method in active electric distribution network by coordinating the three voltage control methods, namely, power factor control, on load tap changer control and generation curtailment control. These voltage control methods are coordinated using fuzzy logic by considering the load bus voltages and DG power as inputs and the voltage control actions as the outputs. The fuzzy logic if-then control rules which are generated to build the fuzzy logic control system are based on the simulations results as well as from the previous works. Results obtained using the fuzzy logic based coordinated voltage control has shown that the voltages are able to be kept within its permissible limits.

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.

Distributed photovoltaic (PV) in the distribution network accounted for an increasing proportion of the distribution network, and the power quality of the distribution network of the power quality problem is more and more significant. In this paper, the voltage regulation methods for low-voltage distribution networks containing high-penetration PV are investigated. First, the working principles of the four voltage control methods are introduced: energy storage system configuration, regulating the reactive power output of PV inverters, restricting the active power output of PV, adjusting the switching positions of on-load regulator trap changer and distribution network reconfiguration, and then, in combination with the recent related research, the optimization of each method is compared horizontally with its respective concerns and characteristics. The optimization of each method is compared horizontally with the recent studies to find out the focus and characteristics of each method, and the shortcomings of each method are explored. Coordinated voltage control through multiple flexibility resources has become the mainstream voltage regulation scheme, and distribution network voltage regulation is considered from the perspective of flexibility resources. The three types of flexibility resources, namely, source, network, and storage, have been widely used in distribution network voltage regulation. Although load-side resources have become one of the main regulation resources of the new type of power system, the current study introduces less about the participation of load-side flexibility resources in voltage regulation of LV distribution networks and advancing the application of load-side resources in voltage regulation of LV distribution networks is the focus of future research. Then, the important role of load-side flexibility resources in voltage regulation is described in three parts, namely, the important role of load-side resources, the development trend, and the suggestions for promoting the coordination of source-network-load-storage flexibility resources, aiming to promote the application of load-side resources in voltage regulation in LV distribution networks, and the suggestions and programs are proposed for the technological challenges faced by voltage regulation. In the context of today’s new power system emphasizing the interaction of source, network, load, and storage, new technologies and methods for solving voltage problems in LV distribution networks are prospected, with a view to providing certain reference value for the actual operation and optimization of distribution network systems.