Voltage Distribution System Research Articles

End-to-end deep learning on classification of neutral-to-ground voltage in secondary distribution systems

Neutral-to-ground voltage (NTGV) abnormalities in secondary distribution systems (SDS) pose significant power quality (PQ) challenges, including safety hazards, power losses, and equipment damage. Despite their importance, these abnormalities remain relatively understudied. Accurate classification of NTGV events is crucial for effective mitigation strategies. Existing research primarily relies on machine learning (ML) models trained on manually extracted features from simulated or real-world signals. This paper introduces a novel end-to-end deep learning approach that leverages Gate Recurrent Units (GRU) to bypass manual feature extraction, directly utilizing real-world signals from three NTGV event categories: ground fault, lightning strike, and normal conditions. This is first time that GRU has been used for NTGV classification using raw data. The model's generalizability is assessed through 5-fold cross-validation. A comparative analysis with baseline models and traditional ML techniques demonstrates the proposed model's superior performance and computational efficiency due to its ability to directly process raw data.

Distributed energy storage participates in reactive power optimization strategy research of new distribution system

Abstract We studied the reactive power control strategy of distributed energy storage in distribution systems, improved reactive power support capacity, and enhanced system reliability and new energy carrying capacity. Firstly, the principles and methods of reactive power optimization in distribution networks are studied. Then, the principles and mechanisms of distributed energy storage participating in reactive power control in distribution networks are studied. Finally, the genetic algorithm optimization method for reactive power optimization in distribution networks is studied, including parameter setting, target selection, and genetic strategy improvement, providing support for fine control of reactive power and voltage in distribution systems and efficient operation. Through simulation analysis of the IEEE33 node system, it is shown that distributed energy storage can improve the reactive voltage level of the distribution system and promote the consumption of new energy.

Performance evaluation of solar-PV integrated hybrid fuzzy-logic controlled multi-functional UPQC for enhancing PQ features

To improve distribution system voltage and current quality, a newly built solar-PV system connected multi-functional universal power quality compensator (MFUPQC) has been extensively used. The proposed MFUPQC mitigates both load and source-side concerns in a three-phase distribution system. Furthermore, as part of the distributed generation scheme, active power from solar PV is injected into the grid or source when solar PV is available. In this context, the proposed MFUPQC was tested in both PQ enhancement and DG integration modes using a feasible control scheme. The proportional-integral controller is used for shunt- voltage-source inverter (VSI) DC-link control, which is not suitable for regulating DC-link voltage at the desired level due to incorrect gain value selection. In this work, an intelligent hybrid-fuzzy-logic DC-link control of MFUPQC evidences the intelligent knowledge base for better regulation of power-quality issues. The suggested hybrid fuzzy-logic controlled MFUPQC device's performance for both power quality (PQ) improvement and DG integration is validated using the MATLAB/Simulink software tool, and simulation results are provided with an appealing comparison analysis.

Assessing the efficiency of measures to enhance electric power quality in variable-frequency drive for scraper conveyors

The intensive implementation of variable-frequency drive machines and installations in underground mining processes necessitates addressing several issues, with a primary focus on ensuring the quality of electric power. Elevating the energy resource of mining machines and enhancing the energy efficiency of mining operations requires maintaining the rated indicators of electric power quality in mine power distribution systems. Achieving this involves assessing the level and composition of higher harmonic components in voltage and current within power circuits equipped with variable-frequency drives (VFD). Key objectives encompass the development of a simulation model based on the equivalent diagram of the power distribution system substitution with a scraper conveyor VFD to scrutinize the spectral composition of higher harmonic components in the power circuits of the mine power distribution system (MPDS). Additionally, the study involves analyzing the impact of harmonic filters (HFs), reactors, and sine filters on the quality of electric power in the VFD system of a scraper conveyor. Further analysis extends to the spectral composition of higher harmonic components in circuits related to insulation leakage and metering circuits of the residual-current device. Practical recommendations for improving electric power quality in the VFD system of a scraper conveyor are then developed based on the research findings. The established model of a variable-frequency drive system for scraper conveyors facilitates the assessment of the effectiveness of electric power quality improvement measures. The harmonic composition of voltage and current in the mine power distribution system is determined under maximum distortion conditions and in the presence of HFs, reactors, and sine filters. Research methods are chosen to unveil the spectral composition of voltage and current in symmetrical and single-phase modes of insulation leakage, as well as in metering circuits of residual-current devices (RCDs). It is noted that the harmonic composition of leakage voltage and current is primarily influenced by the parameters of the output voltage modulated by the autonomous frequency converter inverter. Considering the high level of harmonic components in voltage and current, adjustments to RCD settings, capacitive current compensator, and the protective shunting unit are recommended for electrical safety. The study emphasizes the importance of scientifically substantiating the rated indicators of higher harmonic components for leakage circuits and further exploring the physiological effects of higher current harmonics on the human body. The feasibility of installing a harmonic filter (HF) directly on the low-voltage supply section of a scraper conveyor should be technically justified. Interestingly, the presence of HFs, reactors, and sine filters does not significantly impact the harmonic composition or the magnitudes of coefficients of the harmonic components in the phase voltage of the system concerning ground and leakage currents through insulation. However, higher harmonic components induced in leakage current circuits may pose a potential hazard, leading to a violation of magnetic compatibility and posing risks in case of contact with live parts of electrical equipment.

Distributionally Robust Optimization of Photovoltaic Power With Lifted Linear Decision Rule for Distribution System Voltage Regulation

Distributionally Robust Optimization of Photovoltaic Power With Lifted Linear Decision Rule for Distribution System Voltage Regulation

Optimal Location of EV Charging Stations in the Distribution System Considering GWO Algorithm

Objectives: The transition from conventional vehicles to electric vehicles (EVs) has been significantly influenced by the current scarcity of fossil fuels and the environmental concerns surrounding greenhouse gas emissions. The exploration of the optimal location of electric vehicle charging stations has been prompted by the electrification of the transportation system and the increasing demand for EVs. Methods: One of the main challenges is the detrimental impact of improper positioning of charging stations on the power distribution network. The Grey Wolf Optimization (GWO) approach is used to determine the effective Charging Stations (CS) locations to minimize the losses, which is the major objective of the proposed technique. An IEEE 33 bus system is used to implement the suggested technique. Findings : The proposed method finds the suitable deployments for EVCS within the distribution system, which is of utmost importance due to the constraints imposed by limited battery capacity and prolonged charging periods. This article proposes the optimal location for EVCS to minimize losses inside the distribution network. Novelty: The effectiveness of the proposed GWO is evaluated by comparing it with the PSO optimal algorithm. Finally, a comparison of system voltage and nominal voltage is presented and the probability comparison of EV location with the base case and the proposed algorithms is presented. Keywords: Electric Vehicle Charging Station, Distribution System, GWO, System and Nominal Voltage

A Voltage-Aware P2P Power Trading System Aimed at Eliminating Unfairness Due to the Interconnection Location

P2P power trading is necessary for efficiently using consumer electricity not subject to FIT. However, the execution rules for P2P power trading do not include restrictions on voltage, and there is a trade-off between the activation of the P2P power trading market through the mass introduction of PV and the optimization of the voltage of the power distribution system. In addition, there is a tendency for output curtailment to be biased toward consumers connected to the end of the grid. Since consumers cannot choose the interconnection location, there are concerns about unfairness. In this study, we investigate a new P2P model that includes voltage constraints for the execution rules of P2P power trading to avoid voltage deviation while ensuring benefits and fairness for the participants. In the proposed model, to increase the incentive to participate in the P2P power trading market, we consider compensating consumers who receive output curtailment signals due to voltage constraints. In addition, the profit is secured by differentiating the compensation cost unit price depending on the contract’s availability. A case study was conducted on this model using the IEEE 33 bus system. The results show that the proposed model is superior.

Assessment of the Performance of Frequency Domain Models Based on Different Reference Points for Linearization

Power electronic-based loads are increasingly used in modern distribution systems. Such appliances inject harmonic currents into the power system and thus, they can have serious impacts on the power quality of the system. Therefore, it is necessary to find suitable frequency domain models of these loads to predict their contribution to the harmonic voltage levels. So far, various modeling approaches have been proposed in the relevant literature. Usually, they are parameterized based on laboratory measurements. In this paper, however, a circuit-based time domain model of a Compact Fluorescent Lamp (CFL) is implemented in MATLAB®/Simulink® and used for the parameter identification of three different frequency domain models. These models usually rely on a linearization of their emission characteristic and therefore, it is required to choose an appropriate reference voltage. As the supply voltage in real distribution systems is already distorted, the commonly made assumption of a sinusoidal reference voltage may increase the inaccuracy of models for strongly non-linear devices. Therefore, different reference points for the model parameterization are specified and their impact on the model performance under typical voltage distortions is studied.

Applying Sensor-Based Phase Identification With AMI Voltage in Distribution Systems

Applying Sensor-Based Phase Identification With AMI Voltage in Distribution Systems

Localized structure in secondary distribution system voltage sensitivity matrices

Localized structure in secondary distribution system voltage sensitivity matrices

SVR Control Method Adapted to Three‐Phase Unbalanced Voltage in Distribution Systems with Photovoltaics and Electric Vehicles

This paper proposes a control method for step voltage regulators (SVRs) to avoid voltage violations in distribution systems with unbalanced voltages due to photovoltaic (PV) generation and electric vehicle (EV) charging. Distribution system operators must effectively address voltage problems resulting from the widespread installation of distributed energy resources under the optimizing the utilization of existing voltage regulators to establish an efficient and rational infrastructure. Therefore, this study focused on advancements in voltage control using SVR based on line‐drop compensator (LDC) control, which is widely used in actual operations. We propose a method that utilizes voltage data from information technology switches to detect and address voltage unbalances in the control section, allowing for the sequential adjustment of the monitoring target in LDC control to maintain appropriate voltage limits under unbalanced conditions. We conducted power flow calculations using a distribution system model that represents an actual distribution system in the Hokuriku area. The effectiveness of the proposed method was evaluated in terms of its impact on PV and EV hosting capacity, as well as the frequency of tap operations. © 2023 The Authors. IEEJ Transactions on Electrical and Electronic Engineering published by Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

Risk assessment of voltage overrun probability of photovoltaic access distribution system voltage based on quasi-Monte Carlo method

With the rapid development of renewable energy, distributed PV access to the distribution grid has become a common form. However, distributed PV access to the distribution network (DN) may cause voltage overrun problems, which brings challenges to the stability and reliability of the DN. In order to reasonably assess the impact of PV grid connection, the paper proposes a probabilistic trend calculation based on the quasi-Monte Carlo mode method to obtain the node voltage overrun probability under the premise of considering the stochastic nature of PV power generation and load fluctuation, and combines with the utility preference exponential function to characterize the overrun severity, to construct a comprehensive assessment model of voltage overrun probability risk. Taking the IEEE33 node system as an example, the simulation results show that the rational selection of access points effectively reduces the risk of overrun of the whole DN, and improves the safety of the distribution network.

Optimization of distribution network operating parameters in grid tied microgrid with electric vehicle charging station placement and sizing in the presence of uncertainties

ABSTRACT The power generated by renewable sources is prone to uncertainties which encourages to perform effective modelling to ensure the reliable operation of the grid-connected microgrid (MG) system. This work focuses on the uncertainty modelling of primary sources of solar power, wind power and electric vehicle (EV) load considering three factors battery capacity, state of charge (SoC) and type of EVs charged by employing Monte-Carlo Simulation (MCS) to minimize the distribution system's voltage stability, reliability and power loss (VRP) index. The objective function is tested on the modified IEEE-33 bus distribution system under three diverse scenarios with optimum sizing and placement of RESs and EVCS. To obtain optimal solutions for the proposed problem in a reasonable computation time, modified version of teaching and learning-based optimization (TLBO) and the JAYA algorithm are applied as the rate of convergence is superior to other existing methods in the literature and does not require any precise control parameters. For all the scenarios, it can be seen that the modified JAYA algorithm outperforms TLBO and other existing approaches. The findings of the results reveal the efficacy of uncertainty modelling in a proposed grid-connected DC MG to curtail the VRP index.

Optimal Voltage Control Method for a Step Voltage Regulator Considering the Under-Load Tap Changer in a Distribution System Interconnected with a Renewable Energy Source

The voltage in distribution systems is controlled by the under-load tap changer of the substation and the pole transformer of the primary feeders. Recently, as one of the main countermeasures, a step voltage regulator is being introduced to solve voltage problems such as overvoltage phenomena in a distribution feeder interconnected with a renewable energy source and under voltage in a long-distance feeder. However, the tap of the step voltage regulator may be frequently operated due to its interdependent relationship with the under-load tap changer in the distribution system. Furthermore, given the existing operating characteristics of the step voltage regulator, it is difficult to perfectly maintain the customer voltage within an allowable limit using existing methods such as the line drop compensation method for a step voltage regulator. In addition, the existing line drop compensation method, considering the distributed generators, may be not able to control the proper voltage within an allowable limit. Therefore, in order to solve such voltage problems, this paper proposes a voltage control method for a step voltage regulator by considering the output voltage of an under-load tap changer that is operated via the line drop compensation method. In other words, to overcome the limitations of existing voltage control methods for step voltage regulators, this paper proposes an optimal control method to determine the optimal compensation rate for a step voltage regulator by considering the reverse power flow from a renewable energy source and the output voltage of the under-load tap changer of the main transformer.

APPLICATION OF ASCA TO SOLVE THE PROBLEMS OF HARMONIC DISTORTIONS SOURCES IDENTIFICATION

One of the most important components of the electricity market is its instrumental support, which is a set of systems, instruments, devices, communication channels, algorithms, etc. To control and manage the parameters of energy consumption and energy supply. The basis for the formation and development of instrumental support is the automated systems of commercial account of electric power (ASCA). In addition to the tasks of monitoring energy consumption and power supply, it is also advisable to use ASCA to solve the tasks of monitoring the power quality, identifying the culprits of harmonic distortions and determination the degree of participation of each element of the distribution system in the distribution of higher harmonics power in order to improve the quality and reliability of power supply consumers and adjust the amount of payment for consumed electricity. This paper discusses the issues of the possibility of ASCA for monitoring the harmonic set of voltage and current curves in distribution systems in order to identify and assess of harmonic distortion sources. The block diagram of an industrial facility ASCA and its main components are considered. An algorithm for expanding the functionality of electricity meters is proposed, which makes it possible to control the harmonic composition of the supplied power, to register the power and energy of higher harmonics. Considered are the issues of using counters with recording the power and energy of higher harmonics as part of the ASCA.

Multi-Task Reinforcement Learning for Distribution System Voltage Control With Topology Changes

This letter proposes a multi-task deep reinforcement learning (DRL) approach for distribution system voltage regulation considering topology changes via PV smart inverter control. The key idea is to encode the topology as an additional state for the DRL and leverage the multi-task learning scheme for joint learning of all task control policies. Unlike other DRL-based methods, our approach is robust to different topologies. Comparison results on the modified IEEE 123-node system demonstrate the enhanced robustness of the proposed method.

Two-stage voltage regulation in power distribution system using graph convolutional network-based deep reinforcement learning in real time

The model-based voltage control is widely used to mitigate quick voltage fluctuations caused by renewable energy uncertainties. However, the accurate and complete parameters of the distribution system are rarely available in practice. A two-stage voltage regulation framework based on a mixed-integer second order cone optimization programming (MISOCP) model and graph convolutional network-based deep reinforcement learning (GCN-DRL) is proposed for active distribution system voltage regulation. Specifically, in the day-ahead stage, a MISOCP is proposed for hourly voltage regulation optimization with capacitor banks (CBs), on-load tap changers (OLTC), and energy storage systems (ESS). Then, a GCN-DRL method is proposed in the real-time stage for dispatching reactive power from the intelligent inverters connected to the photovoltaic systems to alleviate the voltage fluctuations. The proposed grid topological graph convolutional network (GTGCN) leverages the distribution system’s graph structure information and the convolutional operation to capture and embed the graphical features among nodal measurements. Then, the deep deterministic policy gradient (DDPG) is innovatively proposed for GCN-DRL to learn the high-efficiency voltage regulation policies, which can be implemented in a real-time manner in practice. The proposed voltage regulation model is investigated on a modified IEEE 33-node distribution system and a 25-node unbalanced distribution system. The numerical results illustrate the high effectiveness and efficiency of the proposed adaptive robust operating model.

Charging Management of Electric Vehicles on Loading Capability of Distribution System Equipment, Voltage Quality, and Energy Loss by Monte Carlo Simulation and Linear Programming

This paper presents the impact of uncoordinated and coordinated charging management of electric vehicles (EVs) on the loading capability of major distribution system equipment, voltage quality, and energy loss in a distribution system. The main emphasis is given to the overloading of distribution transformers, primary feeders, and a substation transformer. The voltage quality of load points along the feeders and the system energy loss are also underlined. The load profile for uncoordinated EV charging is simulated by a Monte Carlo method with several deterministic and stochastic variables involved. To mitigate the overloading of the system components, a coordinated charging (also known as smart charging) model formulated as a linear programming problem is proposed with the objective of maximizing the total amount of energy consumption by EVs and the sum of all individual final states of charge (SoCs), and minimizing the sum of the absolute deviation of individual SoCs from the overall average SoC. The optimization problem is subject to equipment capability loading and planning criteria constraints with low, medium, and high EV penetration levels. The voltage quality problem and energy loss are also analyzed by an unbalanced three-phased power flow model. A case study of a real and practical 115/22 kV distribution system of the Provincial Electricity Authority (PEA) with a 50 MVA substation transformer, 5 feeders, and 732 distribution transformers shows that the possibility of overloaded system components, voltage drops along the feeders, and the system energy loss can be identified in the uncoordinated charging scenario and offer the readiness for equipment replacement and network reinforcement planning. The proposed smart charging model allows the distribution system to accommodate more EVs by appropriately managing the power and the start times of charging for the individual EVs over the timeslots of a day. The study results confirm no violation of the system components and voltage regulation imposed by the system planning guidelines. In addition, the system peak demand and the system energy loss are significantly lower in the smart charging scenario, thus deferring investment upgrades, offering better asset utilization, and retaining network security and service quality.

Hybrid control mechanism-based DVR for mitigation of voltage sag and swell in solar PV-based IEEE 33 bus system

<p><span lang="EN-US">The power quality issues are raised due to sag/swell, which affects the overall performance of the grid-connected system. This study introduces the hybrid control mechanism based on a dynamic voltage restorer (DVR) to mitigate the sag and swell issues in the solar PV-based IEEE 33 bus system. The hybrid controller improves the dynamic performance and boosts the overall efficiency of the DVR system. The proposed work is also used to address the distribution system's voltage quality issues with minimal energy drawn out from the utility grid and effectively use solar energy. The sag and swell are introduced at the grid side and compensated at the load side by injecting DVR voltage. The proportional-integral (PI) controller followed by the fuzzy logic controller (FLC) is used to create the hybrid control mechanism for DVR. In this work, the solar PV system with DVR system is connected to the 29<sup>th </sup>location in the IEEE 33 bus system for performance realization. The hybrid control mechanism-based DVR provides 1.06% and 1.05% total harmonic distortion (THD) at sag and swell conditions for load voltage. The proposed work meets the IEEE 519 standards in terms of THD calculation. The proposed design compares with existing work and shows better THD reduction for load voltages.</span></p>

Optimising the size and placement of embedded energy generators for distribution system loss reduction and voltage improvement

Optimising the size and placement of embedded energy generators for distribution system loss reduction and voltage improvement