Voltage Regulation In Distribution Systems Research Articles

배전계통 전압 측정오차가 분산전원 출력 제어에 미치는 영향 분석

In this paper, effect of error in voltage measurement on output control of distributed generations(DGs) for voltage regulation in distribution systems is analyzed. Volt-Var and Volt-Watt control of a smart inverter which is regarded as one of the typical voltage regulation algorithms based on voltage measurement is considered and characteristics of active/reactive power control and performance of voltage regulation are theoretically evaluated. For verification of the analyzed effect, simulations based on the Korean distribution system are performed by using MATLAB/Simulink. Based on the simulation results, we can confirm that output control of DGs based on the voltage measurement at point of common coupling (PCC) is highly affected by even small error in voltage measurement.

Voltage regulation in unbalanced power distribution systems with residential PV systems

Increased integration of rooftop photovoltaic (PV) power generation in a low-voltage power distribution system poses significant challenges due to the severity of voltage unbalance problems and complexities in regulating the voltage. Conventional regulation methods are insufficient to address these challenges due to their inability to deal with the voltage unbalance. This paper proposes an advanced supervisory control methodology, with the reactive power control and voltage regulation at residential PV inverters, as an effective means of addressing unbalanced voltages in a power distribution system. The uniqueness of the approach is that it simultaneously controls voltage magnitude and voltage unbalance at affected nodes by precise dispatching of reactive power. Several cases were studied by simulating realistic operating conditions on the unbalanced IEEE 37-node test feeder, and results suggest that the proposed approach can manage the voltage magnitude at nodes within voltage unbalance thresholds. Further cases suggest that the application of the proposed methodology could also reduce the operational stress of residential PV inverters significantly, facilitating distribution system with an increased capacity of PV power generation.

Detection of Cyber Attacks on Voltage Regulation in Distribution Systems Using Machine Learning

Several wired and wireless advanced communication technologies have been used for coordinated voltage regulation schemes in distribution systems. These technologies have been employed to both receive voltage measurements from field sensors and transmit control settings to voltage regulating devices (VRDs). Communication networks for voltage regulation can be susceptible to data falsification attacks, which can lead to voltage instability. In this context, an attacker can alter multiple field measurements in a coordinated manner to disturb voltage control algorithms. This paper proposes a machine learning-based two-stage approach to detect, locate, and distinguish coordinated data falsification attacks on control systems of coordinated voltage regulation schemes in distribution systems with distributed generators. In the first stage (regression), historical voltage measurements along with current meteorological data (solar irradiance and ambient temperature) are provided to random forest regressor to forecast voltage magnitudes of a given current state. In the second stage, a logistic regression compares the forecasted voltage with the measured voltage (used to set VRDs) to detect, locate, and distinguish coordinated data falsification attacks in real-time. The proposed approach is validated through several case studies on a 240-node real distribution system (based in the USA) and the standard IEEE 123-node benchmark distribution system. The results show that the proposed approach can detect low margin attacks (as low as 1% of actual measurements) with up to 99% accuracy. All of the developed source codes of the proposed solution are publicly available at Github. https://github.com/nbhusal/Data-Attack-on-Voltage-Regulation.

Optimal coordination between PV smart inverters and different demand response programs for voltage regulation in distribution system

Optimal coordination between <scp>PV</scp> smart inverters and different demand response programs for voltage regulation in distribution system

A Multi-Agent Deep Reinforcement Learning Based Voltage Regulation Using Coordinated PV Inverters

This paper proposes a multi-agent deep reinforcement learning-based approach for distribution system voltage regulation with high penetration of photovoltaics (PVs). The designed agents can learn the coordinated control strategies from historical data through the counter-training of local policy networks and centric critic networks. The learned strategies allow us to perform online coordinated control. Comparative results with other methods show the enhanced control capability of the proposed method under various conditions.

Enhancement of voltage regulation using a 7-Level inverter based electric spring with reduced number of switches

Electric Springs has been testified recently to enhance voltage regulation in distribution systems using demand side management. In this paper, a 7-level Multilevel Inverter (MLI) with a resonant switched capacitor Converter based on sinusoidal PWM, is implemented to analyze the performance of an electric spring under voltage variations at PCC. By the proposed MLI based ES, voltage regulation of critical load voltage is studied for voltage sag and swell conditions. Remarkable features of the proposed topology are maintaining voltage balance in input capacitors and reduction of power components. Simulations have been done in MATLAB/Simulink on distribution system with DGs equipped with MLI based ES under line voltage anomalies. Tested results are analyzed with THD% in critical load voltage.

Technical Issues of Voltage Regulation in Distribution System with Large Reverse Power Flow from Photovoltaic Systems and its Solutions

Technical Issues of Voltage Regulation in Distribution System with Large Reverse Power Flow from Photovoltaic Systems and its Solutions

A Model Predictive Control Strategy for Distribution Grids: Voltage and Frequency Regulation for Islanded Mode Operation

In the last few years, one of the most important challenges of power technologies has been the integration of traditional energy production systems and distributed energy resources. Large-scale photovoltaic systems and wind farms may decrease the quality of the electrical grid service, mainly due to voltage and frequency peaks and fluctuations. Besides, new functionalities, such as the operation in islanded mode of some portions of the medium-voltage grid, are more and more required. In this respect, a model predictive control for voltage and frequency regulation in interconnected local distribution systems is presented. In the proposed model, each local system represents a collection of intelligent buildings and microgrids with a large capacity in active and reactive power regulation. The related model formalization includes a linear approximation of the power flow equations, based on stochastic variables related to the electrical load and to the production from renewable sources. A model predictive control problem is formalized, and a closed-loop linear control law has been obtained. In the results section, the proposed approach has been tested on the Institute of Electrical and Electronics Engineers(IEEE) 5 bus system, considering multiple loads and renewable sources variations on each local system.

Optimal Operation of Electric Springs for Voltage Regulation in Distribution Systems

In this article, we propose an optimal voltage control method for critical buses in an active distribution system using electric springs (ESs). The proposed optimization model relies on both an accurate ES and a load model. The real-time load parameters are determined using the nonintrusive load monitoring (NILM) technique, which provides a flexible and convenient power profile disaggregation. The optimization problem is solved in both a centralized and distributed manner with the minimum ES voltage outputs. A control center communicates with all ESs and collects system information in a centralized scheme, while a multiagent concept is built into the distributed scheme to manage the communication, optimization, and control of ESs located in different areas. The proposed voltage optimal control methods with ESs are verified and compared on a modified IEEE 15-bus distribution network. The results are promising; voltage regulation capability is verified, indicating advantages in the proposed optimal operation strategy over the previous ES control strategy.

Use of demand response for voltage regulation in power distribution systems with flexible resources

In low-voltage power distribution systems with high penetration of photovoltaics (PVs) generation and electric vehicles (EVs), the over-voltage problem arises at times because of large PV generation, and under-voltage problem also arises sometimes because of simultaneous charging of massive EVs. Over- and under-voltage problems lead to more difficulties in achieving voltage regulation. Demand response (DR) is expected to be promising and cost-effective in promoting smart grids, and hence, the utilisation of flexible resources (FRs) through DR can be helpful for distribution system voltage regulation. This study introduces a hierarchical control structure of a community energy management system (CEMS) and multiple sub-CEMSs to apply an FR-based two-stage voltage regulation technique. In the first stage, i.e. the day-ahead scheduling stage, each sub-CEMS optimises the FRs' schedules for minimising customers' electricity cost and network voltage violation times. In the second stage, i.e. the real-time operation stage, the voltage sensitivity-based FRs' shifting method is proposed to eliminate network voltage violations caused by errors of estimated day-ahead data. The proposed models and methods are verified based on a realistic distribution system in Japan, where voltage violations, customer electricity cost and a number of on-load tap changer tap operations are proved to be reduced.

Non-Isolated Fourth-Order Boost DC-DC Converter for Power Management in Low Voltage Low Power DC Grids: Design and Interaction Analysis

In this paper, a minimum-phase response fourth-order boost dc-dc converter (FBDC) exhibiting continuous input and output current is proposed. A voltage-mode controller is adopted to this converter to perform bus voltage regulation in a low voltage low power dc distribution system (LVPDS). FBDC supports additional load demand by interconnecting a second power source/battery. A systematic steady-state analysis for FBDC is established and the ripple content and other L-C design expressions are derived. The LVPDS is an integration of solar photovoltaic (PV) source using a conventional dc-dc boost converter (CBDC), and constant power load using a conventional dc-dc buck converter (CBuC). In this LVPDS, the FBDC primarily ensures dc bus voltage regulation, CBDC ensures the maximum power point tracking (MPPT) while CBuC regulates the load voltage. Various transfer function models, formulated through small-signal analysis, are used to address the controller design aspects and interconnected LVPDS stability issues. A generalized small-signal model of LVPDS is also developed to analyze the sub-system interactions arising during the coherent operation of BRC in this multi-converter system. The impact of connecting FBDC, as BRC, with other converters in the LVPDS is also analyzed. The laboratory prototype of a 48 V LVPDS is developed for experimental validation of bus voltage regulation and sub-system interactions. The theoretical and experimental results are found to be in close correlation with each other.

Robust model predictive control based voltage regulation method for a distribution system with renewable energy sources and energy storage systems

With the integration of high penetration renewable energy sources (RESs) in distribution networks, the uncertainty of RES outputs brings a great challenge for the voltage regulation of distribution systems. This paper proposes a method based on robust model predictive control (RMPC) for voltage regulation by optimally coordinating the reactive power outputs of the RESs, energy storage systems and on-load tap changers (OLTCs). By considering the prediction error of the RES active outputs, the voltage regulation problem is formulated as a multitime period robust optimization model to obtain the optimal control actions in the prediction horizon. The control actions for the first time period are applied to the distribution network. Since the RMPC-based optimization model is nonlinear, it is linearized and transformed into a quadratic programming model that can be solved effectively by commercial software. The effectiveness of the proposed method is demonstrated in a real Finnish distribution network model.

Coordinated control method of active and reactive power for voltage regulation in distribution systems with high-penetration PV

Owing to the intermittent and randomness of solar radiation, high-penetration photovoltaic (PV) energy injected into power distribution systems will inevitably change the magnitude and direction of the power flow, thus causing problems such as voltage violation of the point of common coupling (PCC) and further having a hazardous influence on consumers’ electricity quality. And the communication construction of China’s distribution systems is now relatively weak, difficultly integrating multiple voltage regulation equipment. To improve consumers’ voltage quality at the PCC, a coordinated control method based on active and reactive power of local inverter is proposed. This method can realize the economic regulation of the voltage at the PCC through reactive compensation and active reduction, which can maximumly assure the voltage magnitude at the PCC within limits (including upper and lower limits) and maximize the utilization capacity of PV inverter. Based on Matlab/Simulink, simulation results in different scenarios show the effectiveness of the proposed method.

Optimal Voltage Control Strategy for Voltage Regulators in Active Unbalanced Distribution Systems Using Multi-Agents

The rapid increase in the installation of renewable energy sources, particularly solar photovoltaic (PV) sources associated with unbalanced features of distribution systems (DS), disturbs the classic control strategy of voltage regulation devices and causes voltage violation problems. This paper proposes an effective control strategy for voltage regulators in the DS based on the voltage sensitivity using a multi-agent system (MAS) architecture. The features of the unbalanced distribution system (UDS) with the PV and different types and configurations of voltage regulators are considered in the proposed strategy. The novelty of the proposed method lies in realizing both the control optimality of minimizing voltage violations and the flexibility to accommodate changes in the DS topology using an MAS scheme. An advantageous feature of using the MAS scheme is the robust control performance in normal operation and against system failure. Simulation studies have been conducted using IEEE 34-node and 123-node distribution test feeders considering high PV penetration and different sun profiles. The results show that the proposed voltage control strategy can optimally and effectively manage the voltage regulators in the UDS, which decrease their operation stresses and minimize the overall voltage deviation.

Optimal Electric Spring Allocation for Risk-Limiting Voltage Regulation in Distribution Systems

This paper addresses the optimal allocation of the electric spring (ES) smart load device in radial distribution systems for voltage regulation. An ES can transform a connected noncritical load into a smart load providing voltage support and voltage suppression functions. A risk-limiting ES planning method is proposed to obtain the optimal ES configuration (number, locations, capacities, and types) to mitigate the voltage violations caused by uncertainties in renewable distributed generation. The forecasting uncertainties are placed into multi-state discrete levels to reduce scenario numbers. The voltage regulation capability of different types of ES are quantified and compared to determine the optimal allocation model. The optimal ES installation plan is identified as per the minimal total cost and lowest voltage violation risk. The proposed optimal allocation method is validated on a modified IEEE 15-bus distribution network.

Real-Time Model-Free Coordination of Active and Reactive Powers of Distributed Energy Resources to Improve Voltage Regulation in Distribution Systems

This paper proposes and implements a model-free optimal strategy to regulate the voltage in distribution systems by effective control of Inverter-Interfaced Distributed Energy Resources (I-DERs) output power. In distribution systems, where the ratio of R/X is considerable, reactive power control is not always an optimum solution for voltage regulation. With the aim of improving voltage regulation, this paper proposes an alternative method to optimally coordinate active and reactive power of I-DERs in the grid. The proposed method does not need to have a system model and phase measurement, which are barriers in control and operation of behind-the-meter assets. The paper formulates the problem of voltage regulation in form of equilibrium-map-with-optimum, without any restriction on system configuration, amount of reverse power flow and losses. Using the extremum seeking control technique and without an explicit model of distribution circuit, the ratio of active and reactive power is coordinated in real time. The amount of exchanged apparent power is also adjusted simultaneously. Simulation results for a typical distribution circuit verify the effectiveness of the proposed approach in improving the voltage regulation performance. The experimental results also show a 20 percent reduction in use of system capacity to provide the desired voltage regulation performance.

Coordinated Voltage Control Strategy for Voltage Regulators and Voltage Source Converters Integrated Distribution System

This paper presents a situational-aware, data-driven, and agnostic-coordinated control methodology for voltage regulation in the active distribution systems (DS) considering voltage source converters (VSCs) as reactive power sources that work in conjunction with the existing legacy controllers. The approach uses time-scale coordination based on regulator warnings such that the voltage support from regulators is time separated from the reactive power support using VSCs. Two type of voltage changes are considered; a slow changing one based on the feeder load and a fast-changing one based on sudden changes in load or PV output. The reactive support for both these changes is then designed based on the voltage to reactive power sensitivities. The combined reactive support is then used as a set-point to dispatch reactive power from the VSCs. The proposed control technique has been tested in the field verified model of a real feeder and the scalability is verified on an 8500-node real feeder. Results show that the proposed coordination approach has major economic as well and power quality benefits in the operation of DS. It has also been shown that this can be achieved without major changes in the communication framework currently utilized by the utility.

Coordinated Voltage Regulation by On-Load Tap Changer Operation and Demand Response Based on Voltage Ranking Search Algorithm

The growing penetration of photovoltaic (PV) systems may cause an over-voltage problem in power distribution systems. Meanwhile, charging of massive electric vehicles may cause an under-voltage problem. The over- and under-voltage problems make the voltage regulation become more challenging in future power distribution systems. Due to the development of smart grid and demand response, flexible resources such as PV inverters and controllable loads can be utilized for voltage regulation in distribution systems. However, the voltage regulation needs to calculate the nonlinear power flow; as a result, utilizing flexible resources for voltage regulation is a nonlinear scheduling problem requiring heavy computational resources. This study proposes an intelligent search algorithm called voltage ranking search algorithm (VRSA) to solve the optimization of flexible resource scheduling for voltage regulation. The VRSA is built based on the features of radial power distribution systems. A numerical simulation test is carried out on typical power distribution systems. The VRSA is compared with the genetic algorithm and voltage sensitivity method. The results show that the VRSA has the best optimization effect among the three algorithms. By utilizing flexible resources through demand response, the tap operation times of on-load tap changers can be reduced.

Power system effects and mitigation recommendations for DER cyberattacks

Extensive deployment of interoperable distributed energy resources (DER) is increasing the power system cyber security attack surface. National and jurisdictional interconnection standards require DER to include a range of autonomous and commanded grid-support functions, which can drastically influence power quality, voltage, and bulk system frequency. Here, the authors investigate the impact to the cyber-physical power system in scenarios where communications and operations of DER are controlled by an adversary. The findings show that each grid-support function exposes the power system to distinct types and magnitudes of risk. The physical impact from cyber actions was analysed in cases of DER providing distribution system voltage regulation and transmission system support. Finally, recommendations are presented for minimising the risk using engineered parameter limits and segmenting the control network to minimise common-mode vulnerabilities.

Optimal Tap Setting of Voltage Regulation Transformers Using Batch Reinforcement Learning

In this paper, we address the problem of setting the tap positions of load tap changers (LTCs) for voltage regulation in radial power distribution systems under uncertain load dynamics. The objective is to find a policy to determine the tap positions that only uses measurements of voltage magnitudes and topology information so as to minimize the voltage deviation across the system. We formulate this problem as a Markov decision process (MDP), and propose a batch reinforcement learning (RL) algorithm to solve it. By taking advantage of a linearized power flow model, we propose an effective algorithm to estimate the voltage magnitudes under different tap settings, which allows the RL algorithm to explore the state and action spaces freely offline without impacting the system operation. To circumvent the "curse of dimensionality" resulted from the large state and action spaces, we propose a sequential learning algorithm to learn an action-value function for each LTC, based on which the optimal tap positions can be directly determined. The effectiveness of the proposed algorithm is validated via numerical simulations on the IEEE 13-bus and 123-bus distribution test feeders.