Power Quality Of Distribution Network Research Articles

TLBO trained an ANN-based DG integrated Shunt Active Power Filter to Improve Power Quality

In terms of power quality, the rising number of nonlinear loads in modern use has caused warning signs for power system and power engineering professionals. Every day, utilities have to deal with harmonic distortion caused by a growing number of non-linear power electronic equipment. To keep the system's power supply in good condition, a shunt active filter is used to filter out unwanted harmonics in the signal. This study presents a practical and low-cost method for reducing harmonics and enhancing distribution network power quality by means of the use of PV-integrated Shunt Active Power Filters (SAPF). With a teaching-learning-based optimized artificial neural network controller (TLBO-ANN) and the required DC power is extracted from the PV module. SAPF's TLBO-ANN algorithms are intended to increase system performance by reducing total harmonic distortion (THD). Here, the research work was performed in three stages to mitigate grid current harmonics. The first-stage SAPF system comprises a three-prong voltage source converter and uses DC power derived from photovoltaic panels. The P&O algorithm is used to get the maximum power out of a photovoltaic array. In the second stage, the BBO algorithm is used to fine-tune a conventional PI controller, resulting in values for and that increase the controller's performance. Furthermore, it is intended to use the BBO-PI controller's input and output values as training data for the ANN controller. This ANN controller is currently being tuned with the TLBO algorithm to find optimal values for the weight and bias parameters. In the third stage, the converter in PV-SAPF will inject the active power required by the load by using active current control theory, which means the inverter of SAPF is working like DG as well as the active power filter. Employing MATLAB simulations, we concluded that the proposed method is extremely adaptable and highly efficient in lowering harmonic currents that are brought on by non-linear loads.

Voltage and Reactive Power-Optimization Model for Active Distribution Networks Based on Second-Order Cone Algorithm

To address the challenges associated with wind power integration, this paper analyzes the impact of distributed renewable energy on the voltage of the distribution network. Taking into account the fast control of photovoltaic inverters and the unique characteristics of photovoltaic arrays, we establish an active distribution network voltage reactive power-optimization model for planning the active distribution network. The model involves solving the original non-convex and non-linear power-flow-optimization problem. By introducing the second-order cone relaxation algorithm, we transform the model into a second-order cone programming model, making it easier to solve and yielding good results. The optimized parameters are then applied to the IEEE 33-node distribution system, where the phase angle of the node voltage is adjusted to optimize the reactive power of the entire power system, thereby demonstrating the effectiveness of utilizing a second-order cone programming algorithm for reactive power optimization in a comprehensive manner. Subsequently, active distribution network power quality control is implemented, resulting in a reduction in network loss from 0.41 MW to 0.02 MW. This reduces power loss rates, increases utilization efficiency by approximately 94%, optimizes power quality management, and ensures that users receive high-quality electrical energy.

Probabilistic and Harmonic Assessment of Power Quality Parameters from Distributed Energy Resources in a Distribution Network

Distributed energy resources (DERs) are leading actors in energy transition worldwide. Despite the environmental benefits, DERs are intermittent (consumption/generation power changes according to the input variables), and the use of power electronic devices affects the power quality in distribution networks. Typically, models and simulations (deterministic or probabilistic) are proposed to estimate such impacts. However, previous studies have analyzed the main effects caused by one or two DERs during a day. These studies had a reduced level of detail in the applied methodology in modeling and impact evaluation, or they did not consider that the harmonic distortion level depends on input variables. The aim of this article was to develop a probabilistic harmonic simulation approach to characterize the hourly effect of photovoltaic systems (PVS), battery energy storage systems, and electric vehicle charging stations in a 34-node IEEE test feeder. The individual and collective effect estimation of the DERs consists of the hourly quantification of the effective voltage value, voltage unbalance, power factor, and harmonic distortion, with data obtained using Python and PowerFactory co-simulation for 23 operation scenarios. These impacts were assessed through indicators proposed in the literature and hypothesis tests (inferential statistics). Each DER generally operates at a specific time, making it easy to identify the individual effects of network parameters. The PVS increased the effective voltage value and total harmonic distortion. However, electric vehicles and batteries increase the voltage unbalance and power factor due to the two-phase connection in some network nodes.

Design of Online Intelligent Detection System for Power Quality and Fault Identification in Distribution Networks

Abstract This paper lays the foundation for the subsequent analysis of power quality in distribution networks by briefly describing the indicators of power quality. Utilizing the zero sequence voltage mutation detection fault of a small current routing algorithm, the instantaneous values of voltage and current of each phase of the three-phase circuit are quickly calculated based on the electrical parameters of instantaneous reactive power and the online intelligent detection system is established. The effectiveness and feasibility of the designed detection system and detection algorithm in detecting electrical energy parameters have been verified through experiments. The results show that the error of voltage measurement is within 0.0003-0.002, the frequency error of the system is up to 0.0117%, the measurement error of three-phase unbalance is distributed between 0.001 and 0.1, and the error of negative sequence and zero sequence is between ±0.003, which meet the system design requirements. It shows that the use of online intelligent detection systems can improve the quality of distribution network operation and fault identification accuracy, improve power quality, and effectively improve the reliability of power supply.

Prospective Analysis of Massive Integration of Electric Vehicle Chargers and Their Impact on Power Quality in Distribution Networks

The increasing presence of electric vehicles (EVs) requires a thorough understanding of their impact on distribution assets. EV chargers are characterized as nonlinear and multi-state loads due to their unique electrical consumption patterns. This paper presents a comprehensive study focused on modelling diverse EV charging units deployed in the industrial, commercial, and residential sectors. To conduct this analysis, a simulation environment utilizing the ETAP tool is employed, taking into account time variations. This approach facilitates the comprehension and anticipation of the effects that EV charging may impose on distribution networks, thereby supporting well-informed decision-making for the adaptation and enhancement of the electrical system. Detailed data on current and voltage from operational EV charging stations were collected to create consumption, current, voltage, and harmonic profiles for these charging units. Subsequently, general models or libraries applicable to Level 1, Level 2 and Level 3 EV chargers available in Colombia were developed. These models underwent rigorous validation and were subjected to a comprehensive analysis using the IEEE 13-bus test system. The research yielded valuable insights and conclusions regarding the integration of EV chargers into the current Colombian distribution systems, as well as the potential impact of adopting these devices on power quality issues within the distribution grid. This study contributes to the improved management of distribution assets, thereby facilitating the integration of sustainable electric mobility in the national electrical system.

A New Control Strategy of Hybrid Reactive Power Compensation System in Distribution Network

Reactive power compensation is an important measure to improve the power quality of distribution networks, especially with the increasing connection of distribution transformers, heavy industrial electrical equipment, and asynchronous motors, which generate a large amount of reactive power demand. Traditional reactive power compensation devices, such as fixed capacitors (FC) and thyristor switched capacitors (TSC), have some drawbacks, such as low response speed, harmonic generation, and switching shock. A static synchronous compensator (STATCOM) is a flexible AC transmission system (FACTS) device that can provide fast and continuous reactive power compensation, but it also has some limitations, such as high cost, large capacity requirement, and low utilization rate. Therefore, hybrid reactive power compensation systems that combine FC or TSC with STATCOM have attracted much attention in recent years. Many researchers have proposed and studied different topologies and control methods of hybrid systems to overcome the disadvantages of single devices and achieve better performance. However, most of the existing hybrid systems are designed for low or medium-voltage distribution networks, and their performance under high-voltage distribution networks is still unclear. Moreover, the coordination control strategy of the hybrid system and its subsystems is also a key issue that affects the effectiveness and efficiency of reactive power compensation. In view of this, this paper aims to propose a TSC+STATCOM hybrid reactive power compensation system for high-voltage distribution networks, which optimizes the shortcomings of traditional reactive power compensation devices. The system uses the synergistic effect of TSC and STATCOM to achieve large-scale static reactive power and small-scale dynamic reactive power compensation and adopts a switching strategy based on an expert decision system. This paper introduces the working principle of each subsystem of the hybrid reactive power compensation system in detail and builds a simulation model of the hybrid reactive power compensation system under a high voltage distribution network on Matlab/Simulink platform. The simulation results verify the feasibility and excellent performance of the system control method in reactive power compensation and improving power quality.

Comprehensive early warning of power quality in distribution network based on deep learning

Comprehensive early warning of power quality in distribution network based on deep learning

Research and Governance of Power Quality of the Distribution Network Based on Large-Scale Distributed PV Access

The continuously increasing distributed photovoltaic installations have a great impact on power grid operation, which shows a trend of “local to global development and distribution network to the main network extension”. The situation puts forward higher requirements for power grid power balance, reactive power regulation, and power quality control. Based on the measured data of a regional power grid, this paper analyzes the new problems brought by the large-scale access of distributed photovoltaic to the power quality of distribution network from the aspects of voltage deviation, harmonics, three-phase imbalance, voltage fluctuation, low voltage ride through, and reactive power support in detail. Besides, it describes a series of management and control measures that the local government and grid companies can take to reduce the operation risk of the distribution network against these adverse effects. The purpose is to provide technical guidance for exploring the new mode of distributed photovoltaic grid connection service and regulation operation management in the whole county.

PSO Trained Feed Forward Neural Network Based SAPF for Power Quality Enhancement in Distribution Networks

Power distribution infrastructure is being harmed by the advent of nonlinear devices, which cause harmonics to enter into the power system networks and distort the voltage and current signals. Shunt Active Power Filter (SAPF) is a new power electronics-based technology that can reduce harmonics and improve the power quality in distribution networks. This research provides an efficient and inexpensive strategy to minimizing harmonics and improving the power quality in power distribution networks by employing Shunt Active Power Filter’s (SAPF), which uses the Particle Swarm Optimized Artificial Neural Network Controller (PSO-ANN). The goal of the PSO-ANN algorithms have been developed for SAPF is to improve system performance by lowering the amount of Total Harmonic Distortion (THD). In this work, the standard PI controller is initially tuned using the PSO algorithm to obtain the optimal gain values (Ki, Kp) for the PI controller. After that, these values of the PSO-PI controller's input and output will serve as a dataset for the ANN controller. Now, the PSO algorithm is being used to tune this ANN controller in order to acquire the optimal values for the weight and bias. Using the MATLAB/SIMULINK tool, the proposed algorithm's performance is evaluated and compared to that of a PSO-PI based SAPF and the conventional PI based SAPF. The results of the simulation demonstrate that a SAPF which is based on a PSO-ANN controller is capable of achieving superior THD in the drawing source current while maintaining minimum levels and which are acceptable in accordance with the IEEE-519 standard for harmonics.

Research on Comprehensive Control of Power Quality of Port Distribution Network Considering Large-Scale Access of Shore Power Load

In view of the problem of power quality degradation of port distribution network after the large-scale application of shore power load, a method of power quality management of port distribution network is proposed. Based on the objective function of the best power quality management effect and the smallest investment cost of the management device, the optimization model of power quality management in the distribution network after the large-scale application of large-capacity shore power is constructed. Based on the balance between the economic demand of distribution network resources optimization and power quality management capability, the power quality of distribution network is considered comprehensively. The proposed optimization algorithm for power quality management based on Matlab and OpenDSS is proposed and analyzed for port distribution networks. The simulation results show that the proposed optimization method can maximize the power quality management capability of the port distribution network, and the proposed optimization algorithm has good convergence and global optimization finding capability.

An Overview on Power Quality Issues and Control Strategies for Distribution Networks With the Presence of Distributed Generation Resources

Power systems based on centralized production are facing two limitations: the lack of fossil fuels and the need to reduce pollution; Therefore, the importance of distributed generation resources (DGs) has increased by connecting renewable energy systems to the network. With the increasing penetration of renewable energies in the network, power quality challenges in low voltage and medium voltage distribution systems have become one of the main fields of studies. Since most of the renewable energy systems are connected to the network with the help of electronic power converters devices and the main purpose of these converters is to connect DGs to the network in compliance with power quality standards; Therefore, if the switching frequency of inverters is not implemented properly, major power quality problems will be created. On the other hand, the reduction in power quality causes acute problems in power networks, which include lack of proper performance, reduction in useful life and efficiency of electrical and electronic devices in the network, creation of series and parallel resonance in some harmonics due to the presence of inductors and the capacitor, and as a result, more distortion in the voltage of the distribution network. This paper actually provides a road-map for researchers to investigate power quality issues. In other words, the mentioned cases show the importance of research and providing the solutions to improving power quality in distribution networks.

Distribution Network Power Quality Insights With Optimally Placed Micro-PMUs Incorporating Synthetic and Real Field Data

Distribution Network Power Quality Insights With Optimally Placed Micro-PMUs Incorporating Synthetic and Real Field Data

Study on the influence of grid connected capacity difference of photovoltaic power generation on power grid performance

Due to the integration of photovoltaic power generation system, the structure of traditional distribution network will change, and then the grid system after grid connection is in an abnormal working state. If relevant measures are not taken, the operation quality of grid cannot be guaranteed. Therefore, based on the working principle of photovoltaic cells, this paper studies its equivalent model and output characteristics, builds a single-stage three-phase photovoltaic grid connected system on PSCAD platform, verifies the correctness of power control strategy, analyses the impact of photovoltaic grid connection on distribution network loss and voltage, establishes a 33 node model for example analysis, and simulates the grid connection of photovoltaic power generation system under different capacities and locations for many times, the calculation example of determining the location and capacity of photovoltaic grid connected power generation system is analysed, and a multi-objective mathematical model is proposed based on DG cost and active power loss. The installation quantity, capacity and location of DG are deeply studied, and the optimization function is carried out based on genetic algorithm, so as to realize the minimum impact condition of photovoltaic grid connected power generation on power quality of distribution network, and then realize the optimal configuration of photovoltaic power generation system.

Two‐phase BESS optimization methodology to enhance the distribution network power quality and mitigate violations

AbstractThis paper proposes a two‐phase optimization methodology to optimally dispatch the active/reactive power of battery energy storage systems (BESS) installed on the medium voltage distribution network to manage the violations and enhance the power quality and security. The first phase is look‐ahead scheduling that aims to flatten the grid power curve and optimize the network power factor over the scheduling horizon using forecasted demand and generation. The second phase is a real‐time model predictive control (MPC) introduced to adjust the BESS real power setpoints against network violations due to high uncertainties associated with the renewable generation and low carbon technologies as well as other unexpected events. Simulations were carried out for an actual 11 kV, 53‐node distribution network located in Northern Ireland for two case studies representing the winter and summer. The results demonstrate the effectiveness of the proposed methodology in enhancing the network operation through optimizing the power factor, reducing line losses, and mitigating stresses. Sudden over/under voltage events were solved through the real‐time phase efficiently without affecting the power factor or the line losses in a fast manner with a computation time of 0.52 s/time‐point which makes it suitable for real‐time control implementation.

The impact of events in the Slovene high – voltage network on the power quality in the distribution networks

This work analyses the impact of different events in Slovene high-voltage network on power quality in the 20 kV and 0.4 kV distribution networks. In order to perform the analysis a simplified dynamic model of the Slovene power system was build in the program package Matlab/Simulink, using toolbox PowerSys. The obtained model is appropriate for simulation of electromagnetic transients in duration up to a few seconds. It contains simplified dynamic models of all main generators and power transformers installed in the Slovene power system, detailed models of 400 kV, 220 kV and 110 kV networks, simplified models of the neighboring power systems and models of important consumers. The 20 kV and 0.4 kV distribution networks are modeled in the details only in the area of interests. Everywhere else, they are represented as constant loads connected to the 110 kV network. The aforementioned dynamic model was applied to analyze the impact of different events in the Slovene power system on power quality in the 0.4 kV distribution network during transients and in steady states. The power quality in distribution network was analyzed on 0.4 kV busbars in five substations (Cerkno, Škofja Loka, Vevče, Šentjur, Rače) for the following set of events: a switch-off of a 300 MVA (400 kV/110 kV) power transformer in the substation Okroglo; a three-phase short circuit on 110 kV busbars in the substation Kleče; a three-phase short circuit on 20 kV busbars in the substation Rogaška Slatina and a switch-on in a pumping regime of pump-turbine plants Avče and Kozjak which are currently at the design stage. The results obtained show that aforementioned events in some points of Slovene distribution network can cause power quality distortion over that allowed by the power quality standards.

A Novel 31 Level Inverter with Level Boosting Network to Improve Power Quality in Distribution Network

A Novel 31 Level Inverter with Level Boosting Network to Improve Power Quality in Distribution Network

Optimal allocation of energy storage systems, wind turbines and photovoltaic systems in distribution network considering flicker mitigation

Renewable energies have introduced themselves as efficient resources for power production but their integration into power grid makes some challenges during operation. One of these challenges is the negative impact of wind turbines (WTs) on power quality. Flicker produced by WTs is one of the most important parameters which significantly affects power quality of distribution networks. In this paper, to mitigate flicker produced by WTs, distribution network planning problem is solved by considering power quality issue. For this aim, in the objective function, in addition to power losses and energy storage system (ESS) cost, flicker emission and voltage deviation are also minimized. Due to the complexity of the planning problem, crow search algorithm with differential operator (CSAd) is proposed to optimally site and size WTs and ESSs. In CSAd, new solutions are generated by using the information of high-quality solutions. To investigate the impact of various factors on the network performance, the planning problem is solved at different scenarios: (1) Siting and sizing ESSs, (2) Siting ESSs, WTs and PVs as well as sizing ESSs and (3) Siting ESSs, WTs and PVs as well as sizing ESSs and WTs. Simulation results show that optimal siting and sizing of ESSs and WTs can considerably improve the distribution network parameters in terms of power losses and flicker emission. Moreover, the proposed approach produces more accurate and robust results than the other studied methods.

Influence of electric vehicle distributed energy storage access on safety and stability of distribution network

This paper proposes a distributed energy storage control strategy for electric vehicles to improve the security and stability of distribution network when electric vehicles are connected. Firstly, the load characteristics of electric vehicles are investigated, and the optimal power flow model including energy storage power station, electric vehicle charging station considering V2G and distribution network is established. The objective function is established to minimize network loss, voltage deviation and load peak to peak. The problem is transformed into a mixed integer second-order cone optimization problem for solution, and based on the analysis of distributed energy storage model and constraints, the distributed energy storage control strategy of electric vehicle is established. Through the solution analysis in IEEE33 node system, it can be concluded that using this strategy can improve the power quality of distribution network and effectively improve the security and stability of distribution network.

A Two-Step Horizon Optimum Switching Vector-Model Predictive Control with a Novel Shunt Active Filter Reference Current Extraction

Shunt active filters (SAFs) can be used for harmonic mitigation, reactive power compensation and power factor control in electrical distribution networks. Model predictive controller (MPC) can be used to give optimum performance for SAF’s due to its inherent cost function optimization. The SAF’s reference current extraction technique in finite control set-MPC (FCS-MPC) plays a vital role in the effectiveness of the SAF’s operation. The advantage of FCS-MPC is that it closely tracks the reference and injects the required compensating currents by optimizing the SAF’s switching vector and it does not require an external modulator for pulse generation. FCS-MPC can be implemented as either an optimal switching vector MPC (OSV-MPC) or an optimal switching sequence MPC (OSS-MPC) technique. The OSV-MPC technique is simple and efficient for SAF applications. In this paper, a novel reference current extraction technique, the inverse matrix average pq-synchronous reference frame (SRF) (IMApq-SRF) technique, is proposed along with the OSV-MPC technique. Practically a two-step delay compensation is essential in the implementation of the technique for the control of an SAF. Hence in this paper a two-step horizon OSV-MPC technique is proposed along with an IMApq-SRF reference current extraction technique to improve the power quality in distribution networks. The presented results show that the proposed methodology gives optimum SAF performance under a large range of supply and load conditions.

Research on power quality comprehensive control device under the situation of medium voltage and high power based on H-bridge cascade converter

This paper proposes a power quality control device based on H-Bridge cascade converter, to solve the problems in current decentralised power quality control, such as huge investment in equipment, expensive operation and maintenance cost, hard to coordinate, and low global technical-economic ratio. It provides a novel for the comprehensive management of power quality in distribution networks. This paper has three parts. In the first part, the topology structure and working principle of the power quality comprehensive control device based on H-Bridge cascade converter are analysed, and its key parameters are analysed and designed. In the second part, corresponding coordinated control strategy is proposed according to the function of power quality comprehensive control device. Finally, a 10kV/1MVA medium-voltage and high-power power quality comprehensive control device is designed. The simulation through MATLAB Simulink proves that the parameter design is correct and the coordinated control strategy is effective.