Power Quality Indices Research Articles

Power Quality Improvement Using a Novel Simplified Adaptive Control of Solar PV Integrated Shunt Active Power Filter

ABSTRACTPower quality improvement in grid‐tied solar photovoltaic (PV) system is one of the emergent current research trends. To address the power quality concern, shunt active power filters (SAPF) are widely deployed and researched in grid‐tied PV systems. This paper presents a simplified adaptive transversal (SAT)‐filter control scheme for the two‐stage PV‐SAPF system. The proposed control has the ability to improve different power quality indices. Also, it features faster operation under steady‐state and under dynamic conditions, better dc‐offset rejection ability due to estimation of the accurate fundamental component of the load current. To justify the effectiveness of the proposed control scheme, a thorough comparison is carried out with different conventional and adaptive control schemes. Simulations and extensive experimental analysis are carried out under severe transient conditions such as balanced‐unbalanced supply, sudden load, and irradiation change scenario.

Experimental investigation of adaptive multi-generalized integrator-based controller for electronically interfaced hybrid microgrid system

This research work explores the conceptualization and evaluation of a hybrid microgrid that taps into the potential of solar photovoltaic systems, wind energy conversion systems, and battery energy storage systems. In practice, nonlinear loads pose power quality issues that significantly impact the performance of hybrid microgrids. To tackle these challenges, an adaptive multi-generalized integrator (MGI) filter is proposed. This filter extracts the fundamental signal from the distorted utility grid voltages. It features a pre-filter with a DC-off set rejection loop, effectively minimizing the DC-offsets from the distorted grid voltages. This facilitates the distribution of active power generated by the hybrid microgrid's sources while simultaneously addressing various power quality problems. In addition, a dynamic power management control approach enhances grid resilience by operating the hybrid microgrid in grid-connected and islanding modes. It provides uninterrupted and high-quality power supply to consumers during grid outages. The performance of this filter is comprehensively assessed through numerical simulations in MATLAB®/Simulink® environment. A real-time laboratory prototype is developed with WAVECT® WUC300 FPGA controller, demonstrating the practical application of the proposed filter. It ensures the minimum DC-offsets of 0.02V, fast convergence, and minimum oscillations. The grid synchronization and power quality index of the grid currents simultaneously achieve a THD of 2.82 %, complying with the IEEE-1547 and IEEE-519 standards. Importantly, the proposed adaptive-MGI filter outperforms the conventional SOGI and LMF filters in terms of nonlinear load tracking capabilities, with a response speed of less than 200μs, thereby highlighting its practical relevance and importance.

Hybrid Deep Neural Network Approaches for Power Quality Analysis in Electric Arc Furnaces

In this research, we investigate the power quality of the grid where an Electric Arc Furnace (EAF) with a very high load operates. An Electric Arc Furnace (EAF) is a highly nonlinear load that uses very high and variable currents, causing major power quality issues such as voltage sags, flickers, and harmonic distortions. These disturbances produce electrical grid instability, affect the operation of other equipment, and require strong mitigation measures to reduce their impact. To investigate these issues, data are collected from the Point of Common Coupling where the Electric Arc Furnace is fed. The following three main factors are identified for evaluating power quality: apparent power, active and reactive power, and distorted power. Along with these powers, Total Harmonic Distortion, an important indicator of power quality, is calculated. These data are collected during the full process of producing a complete steel batch. To create a Deep Neural Network that can model and forecast power quality parameters, a network is developed using LSTM layers, Convolutional Layers, and GRU Layers, all of which demonstrate good prediction performance. The results of the prediction models are examined, as well as the primary metrics characterizing the prediction, using the following: MAE, RMSE, R-squared, and sMAPE. Predicting active and reactive power and Total Harmonic Distortion (THD) proves useful for anticipating power quality problems in an Electric Arc Furnace (EAF). By reducing the EAF’s impact on the power system, accurate predictions will anticipate and minimize disturbances, optimize energy consumption, and improve grid stability. This research’s principal scientific contribution is the development of a hybrid deep neural network that integrates Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU) layers. This deep neural network was designed to predict power quality metrics, including active power, reactive power, distortion power, and Total Harmonic Distortion (THD). The proposed methodology indicates an important step in improving the accuracy of power quality forecasting for Electric Arc Furnaces (EAFs). The hybrid model’s ability for analyzing both time-series data and complex nonlinear patterns improves its predictive accuracy compared to traditional methods.

Assessment of Quasi-Stationary Power Quality Phenomena in DC Power Systems

The adoption of dc architectures for electricity distribution has been increasingly considered to reduce the number of energy conversions and to exploit their inherent ability to cope with peaks in energy supply and demand. Furthermore, dc systems have been commonly and widely adopted for high-voltage transmission systems and public transport for many years. Despite this, the Power Quality (PQ) assessment in dc power networks is still unstandardized. In the scientific literature, various indices have been proposed for the quantification of dc PQ. However, not all the aspects encountered in practical applications are adequately accounted for, and their effects regarding the impact on the measurement results are not fully analysed. This paper focuses on signal processing for the analysis of PQ of dc networks in stationary or quasi-stationary conditions aimed at compatibility level assessment. The influence quantities that affect the measurement results of the most commonly adopted procedures for determining the PQ index determination are identified and modelled, and their impact is analytically calculated. Advanced signal processing methods, suitable to be adopted in standards for dc PQ compatibility level surveys, are proposed to improve the accuracy and reliability of results. The rationality and effectiveness of the proposed procedures are shown with analytical calculations and in real measurement situations.

Analysis and improvement of power quality in the onboard electrical power systems within a self-propelled floating crane

This research addresses electromagnetic compatibility and power quality (EMC and PQ) challenges in shipboard electric power systems (SEPS) with dynamic positioning (DP) capabilities, focusing on the self-propelled floating crane (SPFC) “EXPERT 3.” Our goal is to enhance methodologies for evaluating power quality indicators (PQI) related to voltage and current waveform distortions, specifically in converter-based propulsion complexes (CBPCs) featuring variable-frequency regulated asynchronous drives (VFDs). We investigate harmonic current and voltage distortions, reactive power generation, and power factor (PF) in SEPS “EXPERT 3″ during the operation of VFDs with conventional semiconductor power converters (SPCs). A refined MATLAB model considers equipment and cable network parameters, validating distortion indicators at ship synchronous generators (SGs). PQI compliance with international maritime standards is verified at the point of common coupling (PCC) for various VFD configurations with pulse width modulated (PWM) SPCs and filter-compensating devices (FCDs). We propose an improved controlled FCD (CFCD) incorporating a resonance filter (RF) and a controllable reactor compensator (CRC). CFCD efficiency in various VFD configurations is experimentally validated. We analyze harmonic distortions of voltage and current, including high-frequency (HF) commutations in VFDs with input thyristor-based rectifiers (TBRs), considering parasitic ”phase-hull“ capacitances of cable line segments (CLS). Our study examines harmonics in CBPC-based SEPS in two sub-frequency ranges: low-frequency (LF) − 0 to 2 kHz and high-frequency (HF) − 2 kHz to 500 kHz.© 2017 Elsevier Inc. All rights reserved.

A multifunctional inverter power quality coordinated optimization strategy based on comprehensive evaluation

The large-scale integration of renewable energy sources and power electronic devices has led to increasingly dispersed and networked characteristics of power quality disturbances in distribution systems. Traditional control devices, limited by their fixed-point control, no longer meet the development needs of modern distribution systems. Considering the distribution and structural characteristics of the current new-type sources and loads, a multifunctional inverter power quality coordinated control strategy based on comprehensive evaluation is proposed. This strategy aims to achieve power quality coordinated control by utilizing optimal compensation capacity while the grid-connected inverter provides active power output. Firstly, the traditional ipiq power quality detection method is analyzed and improved to enable detection of harmonics, reactive power, and three-phase imbalance currents in single-phase systems or three-phase four-wire systems. Secondly, in the power quality assessment, a balanced algorithm is employed to obtain the comprehensive evaluation index of power quality, thereby improving the deficiencies of single-weight evaluation. Next, to ensure the grid-connected inverter achieves optimal power quality coordinated control with minimal compensation capacity, an optimization compensation function is established between compensation capacity and comprehensive power quality index. This function is optimized using non-dominated sorting genetic algorithm to enhance equipment utilization and system economy. Finally, the feasibility and effectiveness of the proposed method are validated through simulations, demonstrating the achievement of optimal capacity configuration for power quality coordinated control while ensuring active power output by the grid-connected inverter.

A Grid-Wide Comprehensive Evaluation Method of Power Quality Based on Complex Network Theory

To achieve a hierarchical and quantitative evaluation of grid-wide power quality in the distribution network, reflecting the overall power quality level of the distribution network, a comprehensive evaluation method for power quality in a grid-wide system based on complex network theory is proposed. Firstly, based on the propagation characteristics of power quality disturbances, a power quality evaluation index system is constructed. Secondly, to reflect the constraint effect of the local power quality level of nodes on the overall power quality level of the distribution system, corresponding indices such as improved node degree, improved node electrical betweenness, and node self-healing capability are proposed based on complex network theory, and the power quality influence degree of nodes is calculated. Then, the GRA-ANP (Grey Relational Analysis–Analytic Network Process) subjective weight calculation method is improved by introducing grey relational analysis to address the impact of differences in different decision-making results. Based on power quality monitoring data, the entropy weight method is used for objective weighting. To avoid the partiality of a single weight evaluation result, the game equilibrium algorithm is employed to calculate the comprehensive weight of each power quality index. Subsequently, considering the correlation and dependency among indices, the VIKOR (VIseKriterijumska Optimizacija I Kompromisno Resenje) method is used to obtain the power quality grade of each node. Combining this with the calculation of the power quality influence degree of nodes, the overall power quality grade of the distribution network is determined, achieving a hierarchical and quantitative evaluation of power quality in the entire distribution system. Finally, through a case study analysis of an improved 13-node distribution network, it is verified that the proposed method can fully extract data information and produce comprehensive and accurate power quality assessment results by comparing it with other methods. This provides strong support for the safe and stable operation of the distribution system and the subsequent optimization and management of power quality.

Application of hilbert transform for power quality indicators monitoring in general purpose grids

During the operation of power grids, abnormal modes occur that lead to a decrease or increase in the grid voltage beyond permissible values, the appearance of high-frequency noise components and grid signal fading’s, which fading’s the power quality and can lead to the failure of electrical equipment. This requires constant monitoring of power quality indicators. The methods of measuring power quality indicators have been examined and analyzed in the article, their advantages and limitations have been considered, and the inefficiency of using the Fourier transform for estimating of power quality indicators in time domain has been justified. The application of Hilbert transform has been suggested for monitoring the indicators of power quality in general-purpose grids, which include measuring the duration and magnitude of voltage dips, the duration of voltage fading, localization and determination of the duration of high-frequency noise interference in the power grid, determination of phase shift during voltage dip. A simulation of the process of determining the indicators of power quality in time domain and the time intervals during which these indicators exceed the established limits has been performed, which confirmed the effectiveness of using the Hilbert transform in the systems of their monitoring. Keywords: general purpose power grid, power quality indicators, Hilbert transform.

A risk warning method for steady-state power quality based on VMD-LSTM and fuzzy model

The risk warning for steady-state power quality in the power grid is essential for its prevention and management. However, current risk warning methods fall short in predicting the power quality trend while accounting for potential risks. Consequently, this study introduces a novel steady-state power quality risk warning method utilizing VMD-LSTM and a fuzzy model. Firstly, a power quality index prediction method based on variational mode decomposition (VMD) and long short-term memory (LSTM) is proposed. This approach significantly enhances prediction accuracy. Secondly, a power quality risk warning method incorporating kernel density estimation (KDE) and a fuzzy model is proposed, which systematically addresses the uncertainty associated with power quality risks. To validate the effectiveness and practicality of the proposed method, experiments are conducted using field monitoring data from a residential load in southern China. The results affirm the reliability and applicability of the proposed method. The simulation results show that the median error of prediction of power quality indexes by the proposed method is 5.03 % during the evaluated time period, and the prediction accuracy is mostly maintained above 90 %.

Single-Phase Robust Charger with High Power Quality for Electric Vehicle Application

The widespread use of electric vehicles (EVs) necessitates the development of a robust charging infrastructure. The goal of this research paper is to create a high-quality, single-phase charger for electric cars. The purpose of this design is to provide a charger that is both fast and efficient but also protects against power quality problems including harmonics, power factor correction, and voltage variations. A single-phase–single-stage improved power quality EV charger for small and medium power applications has been designed and simulated. A single DC-DC converter is utilized for constant charging and improved power quality operation. The charger presented exhibits improved power quality as sinusoidal current is drawn from the utility grid supply with the total harmonic distortion (THD) in compliance with the IEEE 519 and IEC 61000-3-2 standards. In order to charge the battery of an electric vehicle, most two-stage converters first use a boost converter for power factor correction (PFC), and then they use a DC-DC converter that can accept any input voltage. These two-stage conversions are inefficient and use more parts than necessary. This work proposes a PFC converter based on a single-stage switching inductor Cuk converter, which has the advantages of high step-down gain, low current stress, high efficiency, and a small number of components. The suggested converter’s operational analysis and design equations are performed in continuous current mode. The proposed converter is the subject of extensive mathematical modelling, analysis, simulation, and experimentation presented in this study. With both constant voltage (CV) and constant current (CC) loads, the proposed converter’s performance is analysed with regard to power quality indices like voltage total harmonic distortion (THD), current THD, and total power factor. Additionally, in CV mode and CC mode, the suggested converter’s dynamic performance with battery charging is evaluated in relation to the extensive supply changes. The developed charger presents a reliable and efficient solution for EV charging, fostering the transition to a cleaner and more sustainable transportation system.

An intelligent fuzzy enabled parent node selection approach in low power networks

The Internet of Things lies in establishing low-power and lossy networks created by interconnecting many wireless devices with limited resources. Fascinatingly, an IPv6 routing protocol for low-power and lossy networks has become a common practice for these applications. Even though this protocol addresses the challenges of low-power networks, many issues concerning the quality of service and energy consumption are open to the research community. The protocol relies on a destination-oriented directed acyclic graph, and the root selection depends on some constraints and metrics associated with an objective function (OF). The conventional OFs select parents based on a single metric, such as the expected transmission count or the number of nodes to travel. The current paper proposes an enhancement to the OF metric, aiming to decrease node energy and enhance the quality of service. This improvement is achieved by the factors, including the received signal strength indicator, node distance, power, link quality indicator, and expected transmission count, to select reliable communication links. The minimum power needed for reliable communication is predicted from the received signal strength indicator, node distance, receiver power, and link quality indicator using a nonlinear support vector machine. The OF value of the candidate node is computed from the power level and expected transmission count combined using the Takagi-Sugeno fuzzy model. The proposed OF is implemented in the Cooja simulator and compared against minimum rank with hysteresis OF and OF zero. A considerable improvement in the packet delivery ratio and a 37.5% reduction in energy consumption is obtained.

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.

ENERGY MANAGEMENT: NEW PRIORITIES OF THE 21ST CENTURY

The development of management methodology and the concept of energy management in modern conditions of transforming the energy sector by the requirements of the carbon-free economy are considered. New qualitative features and new areas of application of energy management and energy management systems (EMS) in the implementation of the energy transition and implementation of the Smart Grid concept have been revealed. It has been established that modern energy management is a proactive, organized, and systematic coordination of the purchase, transformation, distribution, and use of energy to meet requirements, taking into account environmental and economic goals. In contrast to the formation of the EMS according to the ISO 50000 series of standards, today the construction of the EMS is becoming more relevant, which provides systemic (complex) optimization of the parameters, structure, and modes of various technical objects according to a set of technical, economic and environmental criteria. It is shown that EMS is much more than a simple technical solution for monitoring the parameters and state of energy systems. With comprehensive forecasts of energy demand and supply, this system takes energy management to a completely new level, allowing operators of facilities (enterprises, buildings, and smart networks and systems) to determine the strategic direction of energy management, implement it, and achieve both energy efficiency and energy availability and environmental (social) acceptability. The components of EMS for Smart Grid are characterized, in particular: monitoring (actual energy production, actual energy demand, state of charge of energy storage, price uncertainty); forecast (energy production, energy demand, mobile data storage, uncertainty); power quality management (loss minimization, power quality indicators, and reliability/comfort); planning/dispatch/cost (operating costs, reduction of GHG emissions, profit maximization). It is proposed that a promising direction is to consider the SEM as a system of information and communication technologies, which at the system level is combined with power energy processes used by operators of electric power systems and networks to monitor, control, and optimize the productivity of production, transmission, and consumption of energy resources in systems of various hierarchical levels. level (as UES of Ukraine, regional and local systems, on specific energy facilities or individual energy technologies, etc.). Based on the analysis of prospective areas of application of EMS at energy sector facilities, modern areas of scientific and technical research in the construction of energy management systems for energy, electric power, and electrotechnical systems, which are practical to carry out in Ukraine, have been determined.

A Novel Methodology for Developing an Advanced Energy-Management System

Current targets, which have been set at both the European and the international level, for reducing environmental impacts and moving towards a sustainable circular economy make energy efficiency and digitization key elements of all sectors of human activity. The authors proposed, developed, and tested a complex methodology for real-time statistical analysis and forecasting of the following main elements contributing to the energy and economic performance of an end user: energy performance indicators, power quality indices, and the potential to implement actions to improve these indicators, in an economically sustainable manner, for the end user. The proposed methodology is based on machine learning algorithms, and it has been tested on six different energy boundaries. It was thus proven that, by implementing an advanced energy management system (AEMS), end users can achieve significant energy savings and thus contribute to the transition towards environmental sustainability.

Soft Computing Technique for Harmonic Mitigation of Enhancing Grid-Integrated Photovoltaic (PV) System Power Quality

This abstract explores the use of soft computing techniques for harmonic mitigation in renewable energy integration, particularly for photovoltaic (PV) systems in power grids. Traditional methods often fail to effectively mitigate harmonics, leading to system performance compromise and grid instability. Soft computing's adaptability and ability to handle complex systems offer promising solutions. The study explores the use of soft computing techniques like artificial neural networks, fuzzy logic, and genetic algorithms to mitigate harmonics in PV systems. ANNs learn complex patterns, fuzzy logic handles uncertain data, and genetic algorithms optimize mitigation strategies for varying grid conditions and system dynamics. The study demonstrates the effectiveness of soft computing-based harmonic mitigation techniques in improving power quality indices like total harmonic distortion and voltage stability. It emphasizes the importance of integrating advanced computational approaches in PV systems for seamless grid integration and promoting sustainable renewable energy integration. Key Word: Renewable Energy sources, PV systems, harmonics, fuzzy logic controller, ANNs

Research on Building Power Quality Assessment and Control Technology Based on Online Monitoring

This study is to improve the assessment accuracy and control efficiency of building power quality by adopting online monitoring and integrating multiple technical indicators and control methods. A whole set of power quality technical index system is developed in the study, involving voltage deviation, harmonic voltage/current limit, and so on. The power quality indicators are quantitatively evaluated through standardization and weight determination. The assessment results show that the measured power quality indicators vary within the interval of 0 to 9, which verifies the effectiveness of the assessment system. In terms of control technology, this paper discusses in depth the static reactive power compensation (SVC) device and its role in improving building power quality, and confirms its efficacy in optimizing power quality through simulation experiments. This work not only successfully evaluates the building power quality, but also proposes practical control strategies, which provide theoretical and practical guidance for the stable operation of power systems and the further improvement of power quality.

Testing and Analysis of Harmonics at utility Substation

This paper is about auditing electrical quality in substations. A Fluke 1748 Energy Analyze is used for power quality audits. The quality audit will be performed according to IEEE Standard 519 2022. The specific purpose of power quality is the cleanliness of the power supply, including voltage fluctuations and waveform distortion. Harmonics occurs whenever non-sinusoidal currents and/or voltages are generated in a power system. This is commonly referred to as harmonic distortion. The main conditions that cause harmonic problems in power systems are non-linear loading, phase imbalance, high input voltage or current, and resonance. Electrical energy is key to industry, commerce and development, so maintaining the quality of electricity flow is important. Having power quality indicators is very important when identifying hazards and possible defects in electrical installations. Keywords: IEEE 519 2022, Harmonics, Power Quality

Estimation of an Extent of Sinusoidal Voltage Waveform Distortion Using Parametric and Nonparametric Multiple-Hypothesis Sequential Testing in Devices for Automatic Control of Power Quality Indices

Deviations of power quality indices (PQI) from standard values in power supply systems of industrial consumers lead to defective products, complete shutdown of production processes, and significant damage. At the same time, the PQI requirements vary depending on the industrial consumer, which is due to different kinds, types, and composition of essential electrical loads. To ensure their reliable operation, it is crucial to introduce automatic PQI control devices, which evaluate the extent of distortion of the sinusoidal voltage waveform of a three-phase system. This allows the power dispatchers of grid companies and industrial enterprises to quickly make decisions on the measures to be taken in external and internal power supply networks to ensure that the PQI values are within the acceptable range. This paper proposes the use of an integrated indicator to assess the extent of distortion of the sinusoidal voltage waveform in a three-phase system. This indicator is based on the use of the magnitude of the ratio of complex amplitudes of the forward and reverse rotation of the space vector. In the study discussed, block diagrams of algorithms and flowcharts of automatic PQI control devices are developed, which implement parametric and nonparametric multiple-hypothesis sequential analysis using an integrated indicator. In this case, Palmer’s algorithm and the nearest neighbor method are used. The calculations demonstrate that the developed algorithms have high speed and high performance in detecting deviations of the electrical power quality.

Reconfiguration of distribution network for improving power quality indexes with flexible lexicography method

Reconfiguration is a low-cost method to reduce power loss in distribution network (DN). Harmonics and unbalancing cause additional losses in DNs. Therefore, it is necessary to consider these two factors in distribution network reconfiguration (DNR). In this paper, the effect of reconfiguration in two harmonic polluted medium and large scale DN is evaluated. In addition, the effect of harmonic injection of distributed generation (DG) is studied. Moreover, the effect of reconfiguration in unbalanced DN in the presence of single-phase DGs is investigated, and it is concluded that distribution system operator (DSO) should consider network unbalance in DNR to more reduction of power losses. Furthermore, a new flexible lexicography method is introduced to solve multi-objective problems, especially in DNR. In the proposed method, the DSO determines the priority of each goal in comparison to the other goals, instead of using weighing factors of them. This method is effective for power quality goals which cannot be illustrated as cost function. In this paper, validation of the proposed method in IEEE 69 bus and 95 bus practical harmonic polluted DN and 25 bus unbalanced DN in presence of three-phase and single-phase PVs are investigated. Results show the effectiveness of the method in increasing the flexibility of DSO in DNR to improve power quality goals such as harmonics and unbalance, as well as reduce power losses.

System Power Quality Analysis under Wind–Hydro Complementary Generation Mode

The highly random and characteristics of wind power generation challenge the power quality of the wind–hydro complementary generation system (WHCGS). Herein, the transient characteristics of power quality under the complementary generating mode are studied. First, a nonlinear hydropower system (HPS) model is innovatively established considering the dynamic characteristics of hydrounits under part load operation, and then a wind power system model including wind speed model, wind turbine and its controller, generator and converter is established. Finally, the applicability of WHCGS model in power quality evaluation is established and verified by IEEE‐9 node model. Combined with active power, frequency, and voltage power quality indicators, the effects of wind–hydro capacity ratio and voltage sag on the system are quantified. The results show that the increase in wind power penetration will deteriorate the power quality of WHCGS. Moreover, when the wind power capacity reaches 60 MW, it will damage the voltage and frequency stability of HPS. Besides, the larger the voltage sag amplitude, the worse the power quality of WHCGS. The longer the voltage sag lasts, the higher the risk of WHCGS instability. This article provides a technical reference for the safe and stable operation of WHCGS.