Unbalanced Load Research Articles

Modified Adaptive Filter Based UPQC for Battery Supported Hydro Driven PMSG System

The standalone three phase system for power quality improvement of both the load side voltages as well as the currents of the machine terminal is presented in this paper. This standalone system consists of a three-phase permanent magnet synchronous generator (PMSG) driven by governor-less hydro turbine as a three-phase source feeding the sensitive/non-linear/linear loads, connected via a unified power quality conditioner (UPQC). The UPQC consists of a back-to-back connected voltage source converters (VSCs) sharing a common DC bus. The series compensator of the UPQC is used to eliminate voltage power quality (PQ) and to maintain the sinusoidal, balanced, and constant amplitude voltages at load terminals irrespective of any variation in the system. Moreover, the current quality such as reactive power compensation, harmonics elimination, etc. are provided by the shunt compensator of the UPQC, simultaneously while improving voltage quality issues. In addition, the efficiency of the overall system is significantly improved by running the generator below its rated voltage and reduces the losses by operating at unity pf. The system frequency and the generated voltage magnitudes are maintained during any load fluctuation or imbalance loading. The model of the UPQC based hydro turbine driven PMSG system is developed in the Simulink-MATLAB environment, and its results are presented for analysis. The validation of the system is also done on the hardware prototype, and it performs effectively for the voltage and current PQ enhancement simultaneously. It significantly improves the PQs at the generator terminals and ensures to adhere the IEC-61727 and the IEEE-519 standards even with either balanced or unbalanced loads.

PENGARUH KETIDAKSEIMBANGAN BEBAN TERHADAP PROFIL JARINGAN TEGANGAN RENDAH

Load imbalance occurs due to unequal distribution of load in each phase, this can occur in low voltage network distribution lines, one of which occurs in the DS0588 transformer, Merdeka feeder, Denpasar. Based on the data obtained, the percentage of DS0588 transformer load unbalance is 14%. The DS0588 transformer is one of the transformers at the Merdeka Denpasar Feeder with a capacity of 160 kVA which is located on Jalan Badak Agung, Renon Denpasar. Load unbalance data obtained at PLN UP3 South Bali. The research was carried out by the method of redistribution of the load on each phase under unbalanced load conditions, so that the total load of the three phases is the same or close. The results obtained were that the percentage of unbalanced loads in unbalanced conditions was 14% and when balanced conditions decreased to 2.2%. The losses in the distribution network when the unbalanced condition is 25 kW and the balanced condition drops to 23.3 kW, this shows that the load imbalance has an effect on the low voltage network losses. The higher the load imbalance, the higher the losses incurred.

Power Quality Improvement using Dual Multilevel Converter for Micro Grid-Connected PV Energy Systems using ANFIS

This paper presents the implementation of dual voltage source inverter (DVSI) approach to improve the microgrid performance by enhancing the power quality. This paper also improves the power quality in photovoltaic (PV) generation interactive microgrids, respectively. The power generated from PV based distributive energy resources (DER) is perfectly applied to the microgrid through the two inverters, thus the nonlinear and unbalance load related problems are compensated. Thus, the power quality problems such as voltage sag, current drops, and power factor, active, and reactive powers are reduced by dual multilevel converter (DMLC). This converter also used for cooperative controlling to minimize the unbalances and voltage harmonics in microgrid by using adaptive neuro fuzzy interface system (ANFIS) based controller, which is applied in the shunt and series manner between the two VSIs. The total load current is mutually shared among the series and shunt VSI, if one VSI fails, then the other VSI continues its operation. Thus, the DMLC components failure rate is reduced, and the system lost energy is also reduced, which leads to improved reliability by maintain the reduction of down time price at environmental free conditions. The proposed control model is implemented in MATLAB/Simulink environment, and the obtained results shows that the superiority of total harmonic distortion (THD) reduction by the proposed ANFIS controller as compared to the conventional artificial neural network (ANN) and fuzzy logic controllers (FLC) by eliminating all the load current and grid voltage-based harmonics.

A Long-Term Dynamic Analysis of Heat Pumps Coupled to Ground Heated by Solar Collectors

In agreement with the decarbonization of the building sector to meet the 2050 climate neutrality targets, borehole thermal storage for solar energy represents a potential solution to increase the energy efficiency of renewable energy plants. As is well known, electricity is not the optimum solution to integrate large inflows of fluctuating renewable energy. In the present paper, we investigate the possibility to use the solar collector to give energy to the borehole field. In detail, a solar-assisted geothermal heat pump is applied to a school located in Milan, Italy. In winter, both the energy from the solar collector and the heat pump are collected into a storage tank connected to the emission terminals, whereas, in summer, as there is no energy demand, the hot water from the solar collector flows into the geothermal probes. By means of this seasonal thermal energy storage technology, the intermittent solar energy collected and stored during the summer months can be utilized during the winter months when the heating demand is high. A long-term dynamic analysis is performed by employing Trnsys. The results show that solar collectors coupled with ground-source heat pumps can give an important contribution to the soil temperature drift, and this also applies in cases of un-balanced loads during the heating season. Moreover, the employment of solar collectors increases the seasonal coefficient of performance of the heat pumps and may rise to reductions to the probes field.

A Novel Prairie Dog-Based Meta-Heuristic Optimization Algorithm for Improved Control, Better Transient Response, and Power Quality Enhancement of Hybrid Microgrids.

The growing demand for electricity driven by population growth and industrialization is met by integrating hybrid renewable energy sources (HRESs) into the grid. HRES integration improves reliability, reduces losses, and addresses power quality issues for safe and effective microgrid (MG) operation, requiring efficient controllers. In this regard, this article proposes a prairie dog optimization (PDO) algorithm for the photovoltaic (PV)-, fuel cell (FC)-, and battery-based HRESs designed in MATLAB/Simulink architecture. The proposed PDO method optimally tunes the proportional integral (PI) controller gain parameters to achieve effective compensation of load demand and mitigation of PQ problems. The MG system has been applied to various intentional PQ issues such as swell, unbalanced load, oscillatory transient, and notch conditions to study the response of the proposed PDO controller. For evaluating the efficacy of the proposed PDO algorithm, the simulation results obtained are compared with those of earlier popular methodologies utilized in the current literature such as bee colony optimization (BCO), thermal exchange optimization, and PI techniques. A detailed analysis of the results found emphasizes the efficiency, robustness, and potential of the suggested PDO controller in significantly improving the overall system operation by minimizing the THD, improving the control of active and reactive power, enhancing the power factor, lowering the voltage deviation, and keeping the terminal voltage, DC-link voltage, grid voltage, and grid current almost constant in the event of PQ fault occurrence. As a result, the proposed PDO method paves the way for real-time employment in the MG system.

A Device for Decreasing Loss in Electric Networks Containing Unbalanced Nonlinear Load

Matters concerned with controlling the operating modes of low-voltage electric networks are discussed. Thus, 0.4 kV electric networks are characterized by significant emission of additional current sequences generated by unbalanced nonlinear load. A versatile compensating device filtering additional power flows caused by unproductive fundamental and higher harmonic current components is proposed as a technical means minimizing the undesirable consequences of additional current load. A method and calculation software were developed, using which the operating mode of a 0.4 kV electric network section was studied with the possibility to incorporate a simulation model of the proposed device. The compensating device parameters are calculated proceeding from the unbalanced power consumption in the network section considered. By using the MATLAB software package, time diagrams visualizing the variation of the studied indicators have been obtained. The economic efficiency of the proposed versatile device for decreasing electric energy loss has been estimated.

Composite-disturbance-observer-based backstepping control for three-phase inverters with multiple disturbances

This paper deals with the output voltage tracking control problem of three-phase inverters with multiple disturbances (including parametric perturbations of filter, abrupt disturbances caused by load switching, and harmonic disturbances brought by unbalanced loads and nonlinear loads). Some novel composite disturbance observers are designed to estimate the above multiple disturbances. Based on the disturbance estimates and backstepping control technique, an innovative feedforward-feedback composite tracking control scheme is proposed. The new control scheme has a good disturbance rejection ability and ensures good tracking performances. In the meantime, rigorous stability proof is presented. Simulation and experimental results are illustrated to verify the feasibility and effectiveness of the proposed control scheme.

Effect of internal excitation induced by non-uniform contact of roller bearings on nonlinear vibration and stability of rotor system under combined loads

The misalignment of roller bearing rings will results in moment load, together with the unbalance and external loads, forming the combined dynamic loads. The complex combined load can cause non-uniform contact of rollers and rings, which reduces the bearing’s life and significantly affect the vibration of rotor systems. This paper mainly studies the roller bearing internal contact performances under combined loads and the influence of internal excitation on the nonlinear vibration of rotor systems. First, the “slices” method is used to establish the mechanical model of roller bearings, which considers the radial clearance and nonlinear Hertz contact. The obtained time-varying bearing nonlinear support reaction is introduced into the rotor concentrated mass model, and a roller bearing–rotor system dynamic model is proposed. Further, the system’s complex nonlinear vibrations, such as bifurcation and chaos, are analyzed by spectrum, orbits, bifurcation, and Poincare map. The roller bearing contact performances and stability under the influence of ring tilt angle, rotational speed, and unbalance, are analyzed by contact load statistical features. Finally, based on a rolling bearing–rotor test rig, the vibration experiment considering the combined load was performed, and the experiment results are compared with simulation results to verify the proposed model and conclusions.

Research on an Identification Method for Wheelset Coaxial Wheel Diameter Difference Based on Trackside Wheelset Lateral Movement Detection

The wheelset coaxial wheel diameter difference is one of the most common wheel faults of railway vehicles. The existence of the wheelset coaxial wheel diameter difference may lead to the off-load operation of vehicles, resulting in abnormal wheel tread wear, leading to the deterioration of the wheel–rail contact relationship, resulting in the deterioration of the vehicle’s operating stability and comfort, and even leading to an increase in the derailment coefficient, affecting the running safety. In order to monitor the freight car wheelset coaxial wheel diameter difference online, a vehicle–track coupling dynamics model based on a trackside detection method was established, and the response of rail lateral displacement under the condition of the wheelset coaxial wheel diameter difference was analyzed. The results show that the existence of the wheelset coaxial wheel diameter difference can lead to a deviation in the vehicle’s run, with an increase in the wheelset coaxial wheel diameter difference and an increase in the lateral offset of wheelset increases. The impact of vehicle unbalance loading on the lateral movement of the wheelset is much smaller than that of the wheelset coaxial wheel diameter difference. The existence of the wheelset coaxial wheel diameter difference can be better reflected by detecting the wheelset’s lateral displacement. On straight line, the variation of lateral displacement has no infection of vehicle speed, but shows a quadratic growth trend with the wheelset coaxial wheel diameter difference. Based on this, the mapping relationship between the wheelset coaxial wheel diameter difference and wheelset lateral displacement can be obtained. Through a mapping relationship, the size of the wheelset coaxial wheel diameter difference can be reversed precisely through the detection of a trackside lateral movement monitoring system. The reliability of the identification method was verified with a specific test on the trackside monitoring system.

Development of an H ∞ controller for a microgrid using LabVIEW

Abstract This paper focuses on designing a simple yet efficient H ∞ controller for regulating the voltage/frequency, output current, and active/reactive power-sharing in a microgrid (MG). The purpose of designing the robust H ∞ controller is to regulate the frequency and voltage in face of the uncertainties in the microgrid and load variation. The studied DC MG test bed includes an SMPS (switching-mode power supply) and DC-DC converter, necessary sensor and data acquisition systems. The proposed control scheme is simulated using MATLAB/Simulink and is then verified in real-time using LabVIEW. The control scheme is developed in the LabVIEW software’s block diagram panel of the virtual instrumentation interface. From both simulation and LabVIEW implementation, load sharing among the DGs, and voltage and frequency regulation at the nominal values are achieved by employing the proposed H ∞ controller. The robustness of the proposed controller is evaluated by comparing it with a robust observer-based controller (Zarei A, Mousavi Y, Mosalanezhad R, Atazadegan MH. Robust voltage control in inverter-interfaced microgrids under plug-and-play functionalities. IEEE Syst J 2020;14:2813–24) under balanced, unbalanced, and non-linear loads. The comparison results envisage that the proposed controller provides improved voltage/frequency regulation and power-sharing during disturbances including the addition of non-linear load to the MG system.

Bearing Non-Uniform Loading Condition Monitoring Based on Dual-Channel Fusion Improved DenseNet Network

Misalignment or unbalanced loading of machine tool spindle bearings often results in skewed bearing operation, which makes the spindle more susceptible to failure. In addition, due to the weak impact signal of the bearing in skewed operation, a single feature information cannot accurately characterize the operation status of the bearing. To address the above problems, this paper proposes a method to monitor the uneven running state of bearing load based on a dual-channel fusion improved dense connection (DenseNet) network. First, the original signal is pre-processed by overlapping sampling method, and the dual-channel experimental data are obtained by frequency-domain and time-frequency-domain algorithms; then the processed data are input into the improved 1D-DenseNet and 2D-DenseNet models respectively for feature extraction; then the frequency-domain and time-frequency-domain features are fused by concat splicing operation, and the output belongs to each category The probability distribution is used to characterize the operating state of the bearings. Finally, the validity of the algorithm model is verified by using the Case Western Reserve University public rolling bearing data set, and an experimental bench is designed and built for experimental verification of the uneven bearing load operation. The comparative analysis of the experimental results in this paper shows that the algorithm can extract the features of the input signal more comprehensively and finally achieve 100% recognition accuracy.

A novel design of 9 level cascade multi-level inverter for decoupled double synchronous reference frame in state delay controller

In this study, we investigate the performance and scheme of a Decoupled Dual Synchronous Reference Frame (DDSRF) system, which is investigated for compensation power generation via Shunt Active Filter (SAF)). Traditional direct power control theory and harmonic cancellation responsibilities are unreliable for unbalanced sources and loads. 9-level cascade multi-level inverter (NLC-MLI) ensures the establishment to generate sufficient compensation power. In this paper, instantaneous active power and reactive power (PQ) are represented by positive, negative, zero sequence and harmonic components. This is to counteract the unbalanced operation of the load, i.e. twice the frequency at which each reference signal is generated. Due to the delay properties of the signal generation control loop, the compensation time can deviate from the reference signal measurement point. A state delay controller (SDC) is proposed to reduce the intermediate delay between the inserted compensation power and the acquired reference signal. The efficiency of the proposed mathematical analysis method is performed using MATLAB/Simulink and verified by an experimental setup running under unbalanced conditions.

Optimisation of transmission towers under multiple load cases and constraint conditions with the KSM-GA method

Transmission towers operate in complex engineering environments, such as gravity, strong winds, ice and snow, wire breaking and unbalanced loads. Owing to complicated structural parameters, multiple load cases and multiple constraint conditions, the optimal design plan of the structure is difficult to acquire. Popular intelligent algorithms (Genetic Algorithm, GA; Particle Swarm Optimisation, PSO; and others) need to spend time in structural mechanical computation and search processes. To solve this problem, the commercial FE software ABAQUS was used to build the full parametric analytical and computational sub-procedures (general static, linear buckling and cost computation) for the transmission tower under multiple load cases and constraint conditions. Then, the main algorithm procedure, KSM-GA, was developed based on the GA optimiser and Kriging Surrogate Model (KSM). The KSM-GA could import the design variables (such as cross-section properties and structural dimensions) of the transmission tower into the FE computational sub-procedures and read the results (including stresses, displacements, buckling load and weight). The results show that the KSM-GA can reduce the search time more than 30% compared with the GA, PSO and BO-GP( Bayesian Optimisation with Gaussian Process) while the training precision of the KSM is above 99% accuracy of the FE results.

A Novel Unidirectional Three-Phase Multilevel Rectifier Composed of Star-Connected Three Single-Phase Topology Based on Five-Level Flying Capacitor DC–DC Converter

A novel unidirectional three-phase multilevel rectifier composed of star-connected three single-phase topology based on five-level flying capacitor DC-DC converter is proposed, which can be widely applied to many industrial applications, especially for the front-end of multilevel converters for AC adjustable motor drives with open-end winding connection. In addition to not requiring transformers (either line-frequency or high-frequency), compared to other high voltage rectifiers, this proposed topology features fewer active switches with lower voltage stress, a high voltage common DC bus, high input power factor and low input current harmonics. In this paper, a comprehensive analysis to the basic operating principles including the topology configuration, the steady-state modeling and phase-shifted SPWM modulation are presented. A hybrid control strategy is studied, including the input power factor control, the dc-link voltage balancing control and the flying capacitor voltage balancing control with balanced and unbalanced loads. Finally, the experimental results are presented to validate the feasibility and correctness of the proposed solution.

Dynamic Fog Federation Scheme for Internet of Vehicles

Federated fog computing is an answer for horizontally upscaling fog resources to improve the Quality of Service (QoS) of Internet of Things (IoT) applications. However, the dynamic nature of some IoT’s crucial components, such as the ones of Internet of Vehicles (IoV), may hinder the QoS improvement and result in its deterioration instead. Specifically, delays can occur due to the unoptimized distribution of services and unbalanced network traffic loads on the fog nodes. The current federated fog architectures ignore the mobility of users during the formation of fog federations. In this work, we present an adaptive and efficient fog federation formation scheme using game theory according to the service requirements. The problem formulation in terms of forming the federations and offloading requests among fog members is formulated as an integer program, then modeled as a Hedonic game. We adopt the Merge & Split as a formation technique, where the federations that are not satisfied in terms of QoS merge with other federations that would enhance the service performance. Our adaptive fog federation formation mechanism is designed to cope with the environmental changes in the IoV paradigm. Experimental evaluation shows that our framework can acquire better QoS and lower time to form the federations compared to the literature.

Gain Fault Detection Method for 3-phase AC Current Sensors

This paper proposes a novel method for detecting the gain fault of 3-phase AC current sensors in power electronics systems. In conventional methods, the sensor gain fault is detected by comparing the RMS values of the detection current of each phase. However, for an unbalanced three-phase load, a higher current will flow in the phase with the lower impedance, which causes misdiagnoses. In contrast, the proposed method utilizes the product of the detection current in each phase and sum of the detection current as part of the abnormality calculation (gain error calculation) of each current sensor, which can reduce calculation errors caused by an imbalance in the three-phase load. Simulation results show that the method can calculate the abnormality of the sensors with small error even if there is an imbalance in the three-phase load. Moreover, simulation results under conditions of varying current amplitude and frequency indicates that the method can detect sensor faults under transient conditions.

Performance Under Limited Service Capacity for Load Balancing EV Charging Network

The economic benefit and energy security brought by renewable energy have greatly promoted the development of microgrid (MG). However, the load demand varies from area to area, resulting in the unbalanced load distribution among MGs. With the perfection of charging facilities, electric vehicle (EV) has attracted more consumers in the automobile market. A large number of EVs connected to MGs without coordination may threaten the safe operation of the power grid. Moreover, considering the constraints of economic factors, the number of charging piles in the MG is limited, i.e., the service capacity of MG is limited. Based on this, the impact of service capacity on the load balancing and average user time is studied. The load balancing matching strategy (LBMS) is adopted to lead the EV charging behavior. We find that the larger service capacity means that the load distribution is more balanced and the average user time is shorter. Furthermore, we find the optimal service capacity of the power grid. When the service capacity is more than that, it will no longer improve the system performance and cause the waste of charging facilities.

Intelligent Prediction of Transformer Loss for Low Voltage Recovery in Distribution Network with Unbalanced Load

In order to solve the problem of low voltage caused by unbalanced load in the distribution network, a transformer loss intelligent prediction model under unbalanced load is proposed. Firstly, the mathematical model of a transformer with an unbalanced load is established. The zero-sequence impedance and neutral line current of the transformer are calculated by using the Chaos Game Optimization algorithm (CGO), and the correctness of the mathematical model is proved by using actual data. Then, the correlation among network input variables is eliminated by using Principal Component Analysis (PCA), so the number of network input variables is decreased. At the same time, Sparrow Search Algorithm (SSA) is used to optimize the initial weight and threshold of the BP network, and an accurate transformer loss prediction model based on the PCA-SSA-BP is established. Finally, compared with the transformer loss prediction model based on BP network, Genetic Algorithm optimized BP network (GA-BP), Particle Swarm optimized BP network (PSO-BP) and Sparrow Search Algorithm optimized BP network (SSA-BP), the transformer loss prediction model based on PCA-SSA-BP network has been proven to be accurate by using actual data and it is helpful for low-voltage recovery in the distribution network.

An individual sequencing control strategy for three-phase four-leg inverter under unbalanced loads

Under the influence of the unbalanced load, the negative and zero sequence components in the output voltage of the three-phase four-leg voltage source inverter(TPFL-VSI) will cause asymmetry voltage. This paper designs an individual sequencing control for the three-phase four-leg inverter to address this problem. The second-order generalized integrator is adopted to extract the current’s positive and negative sequence components. The virtual oscillator control(VOC) controls the positive sequence component, and the negative sequence component is suppressed by designing the virtual impedance and the multiple proportional resonance controller. The proportional resonance control is used to control the zero-sequence voltage of the fourth bridge arm. Considering that voltage deviation is caused by the access of negative sequence virtual impedance and load step, the secondary voltage compensation strategy is further added in the individual sequencing control to improve the droop relationship in the VOC and effectively solve the problem of system voltage instability. Ultimately, a TPFL-VSI model is built in Matlab/Simulink, and simulation results verify the feasibility and effectiveness of the proposed control strategy under different conditions.

Modified control structures for sharing of asymmetrical powers amongst inverter based distributed energy resources

Renewables interfaced through inverters in microgrids, may be controlled using centralized, decentralized or distributed approaches. The decentralized droop control involves mimicking the performance of a synchronous generator of the power system, so as to share load power proportionately amongst parallel connected sources. When the conventional droop control is used, only the fundamental real powers can be shared in proportion to the source ratings, which does not ensure satisfactory performances in the presence of unbalanced/ asymmetrical loads. Several schemes have been worked upon to achieve proportional load power-sharing with power quality aspects: in the presence of harmonic and unbalanced loads. This paper proposes five modifications for the popular virtual conductance vs. negative sequence power (G vs. Q-) approach, aimed at improving the sharing of the unbalanced currents amongst the sources to improve the power quality and microgrid system reliability. The eigenvalue analysis for determining the parameter range for assuring stability and comparisons with fixed virtual conductance values are discussed. The proposed modifications are discussed and demonstrated through simulations on a two inverter-based distributed generator (DG) system, a modified 13 bus system, and using experimental results on a lab-scale microgrid.