Search Results (31)

This paper presents an adaptive wireless droop control scheme that uses an adaptive virtual resistance to regulate the DC voltage and control the active power. The proposed methodology is implemented to address the power mismatch problem in a fixed-droop control for multi-terminal HVDC (MT-HVDC or MTDC) systems. Each inverter calculates available power and adjusts its output power accordingly while adapting the virtual resistance to mimic the behavior of a mesh system that is based on loading effects. The main objective of this methodology is to increase the reliability of the MTDC system by eliminating the need for fast communication links and ensuring proper power sharing between inverters. Additionally, this communication-free scheme includes a power management algorithm that controls power sharing during peak hours of the inverters among the rectifiers as per mutual agreements between the operators to mitigate the risk of a system overload and optimize the power sharing. A simulation of a five-terminal mesh MTDC system has been verified by using PSCAD/EMTDC to validate the performance and effectiveness of the proposed method. The results show the flexibility and feasibility of the proposed control method in three different modes. Full article

Background: Stroke is one of the most misdiagnosed conditions that causes serious medical disabilities. Its early and accurate diagnosis by the emergency team is crucial for the patient’s survival. This study aimed to determine the percentage of brain strokes incorrectly diagnosed by paramedic teams and to analyze the factors influencing incorrect diagnoses. Methods: The data of 103 patients, mean age of 68.4 ± 14.96 years, admitted in 2019 to hospital emergency departments of the two hospitals in Olsztyn, Poland, were analyzed retrospectively. All patient data were obtained from their information cards. The parameters of the patients misdiagnosed and accurately diagnosed by paramedics were analyzed with Odds Ratio (OR) calculations using IBM SPSS version 23 software. Results: Stroke and transient ischemic attack were recognized in 77 cases (74.8%). In 26 patients (25.2%), the diagnosis made in the ambulance differed from that made in the hospital ward. The analysis of the Odds Ratio (OR) has shown that typical stroke risk factors, if present in a patient, facilitate the correct diagnosis. The greatest source of misdiagnosis of stroke by the paramedic team was the lack of hemiplegia (OR = 6.0). Conclusions: The absence of typical stroke risk factors and neurological stroke symptoms, such as smoking, hemiplegia, aphasia, hypercholesterolemia, arrhythmia, diabetes or a drooping corner of the mouth, constitutes a high risk of misdiagnosing stroke by the paramedic team. Full article

In this article, a distributed control scheme to compensate for voltage harmonics in islanded microgrids is presented, where each distributed generation (DG) source has a primary control level and a secondary control level. In addition to the voltage and current control loops, the primary control level of DGs includes virtual impedance control loops in the main and harmonic components, which are responsible for dividing the power of the main component and the non-main component (harmonic) between the DGs of the microgrid, respectively. For coordinated operation between the inverters when facing the islanding phenomenon, it is very beneficial to use a droop controller structure. Here, the traditional droop controller is modified in such a way that the power is proportionally divided between the DGs, which causes accurate voltage regulation at the output of the DGs. By presenting a model for the inverter connected to the nonlinear load, a harmonic droop controller is designed. Through the droop controller related to each harmonic, the harmonic voltages are calculated and added to the reference voltage, which improves the quality of the output voltage. Then, the inverter voltage control loop is modified with resistive impedance in the presence of nonlinear loads in such a way that, when combined with the harmonic droop controller, the total harmonic distortion (THD) of the output voltage is significantly reduced. Lastly, the proposed method is implemented on the microgrid through MATLAB software, and the results show the ability of the proposed method to reduce voltage harmonics in the parallel operation of inverters. Full article

Wind and photovoltaic power generation connected to the independent power system can save fuel, reduce carbon emissions, and provide significant economic and environmental benefits. Influenced by the characteristics of light resources and wind resources, the wind and photovoltaic output active power is characterized by volatility and randomness, which affects the frequency stability of the independent power system. In order to evaluate the frequency stability, in this paper, the simulation model of an independent power system is established, and the simulation model of a diesel generator, wind and photovoltaic are connected. Through droop calculation and Simulink simulation, the frequency characteristics of an independent power system under different working conditions are analyzed, and the maximum absorption capacity of wind and photovoltaic is studied. In an independent power system, when the new energy output is 25% of the total output, all the new energy output is cut off, the frequency drops by 0.5 Hz, and the frequency fluctuation is within the specified range. Full article

Sag is an important indicator of the operational health of a transmission line, and its timely measurement is of great significance to maintain the stability and reliability of power systems. However, traditional contact measurements may be affected by the electromagnetic interference of conductors. In contrast, measurement methods without direct electrical contact with the subject provide greater portability and flexibility. This paper presents a study of a transmission line sag measurement and simulation based on non-contact electric field sensing. The finite element method was used to analyze the conductor distribution, establish the coupling relationships among the electric field, transmission line, and measurement point, propose a sag inverse calculation model, and assess the impact of the transmission line parameter on the curved drooping measurement. Simultaneously, sag measurement schemes for single-round and dual-circuit lines were designed for multi-conductive lines, and measurement array studies were conducted. The vertical component of the electric field in space measured by the array was obtained, which could be used to perform conductor sag measurement simply and efficiently. The proposed method will facilitate the monitoring of the overhead transmission line status, which is conducive to the effective operation of the entire system. Full article

The power calculation is an indispensable element in droop-controlled inverters because the bandwidth of the measured power has a direct impact on the controller performance. This paper proposes a fast and accurate power calculation algorithm based on the combined Second Order Generalized Integrator (SOGI) filters in stationary coordinates for a three-phase system, which takes into consideration the use of nonlinear loads. The power calculation scheme is formed by the two-stage SOGI filters that are employed for obtaining the active and reactive powers required to perform a droop-based inverter operation, respectively. From the two-stage structure, the first SOGI is used as a band-pass filter (BPF) for filtering harmonics and obtaining the fundamental current of the nonlinear load; The second SOGI is used as a low-pass filter (LPF) for extracting the DC-component, which corresponds with the average power. A small-signal model of a two droop-controlled inverters system is built to obtain the dynamical response and stability margin of the system. And compared it with the dynamical behaviour of a standard droop-control method. Next, the proposed power calculation system is designed in order to achieve the same ripple amplitude voltage as that obtained with the standard droop-control method by adjusting the bandwidth gains. Through simulation and hardware in the loop (HIL) validation, the proposed approach presents a faster and more accurate performance when sharing nonlinear loads, and also drives the inverters’ output voltage with lower distortion. Full article

Gas-fired reciprocating engine plants (GREPs) are widely used in power supply systems of industrial facilities, which allows for ensuring the operation of electrical loads in case of accidents in the power system. Operating experience attests to the fact that during islanded operations, GREPs are shut down by process protections or protective relays in the event of severe disturbances. This leads to complete load shedding, which is accompanied by losses and damage to industrial facilities. Severe disturbances include the following ones: large load surges on GREPs due to one of them being switched off, the group starting of electric motors, and load shedding (more than 50%) during short circuits or disconnection of process lines. Energy storage systems (ESS) have the ability to compensate for instantaneous power imbalances to prevent GREPs from switching off. The authors of this study have developed methods for intelligent control of the ESS that allow one to solve two problems: prevention of GREPs shutdowns under short-term frequency and voltage deviations as well as preservation of the calendar and cycling lifetime of battery storage (BS) of the GREP. The first method does not require performing the calculation of adjustments of control actions for active and reactive power on the ESS online but rather determines them by the value of frequency deviations and the voltage sag configuration, which greatly simplifies the system of automatic control of the ESS. The second method, which consists in dividing the steady-state power/frequency characteristic into sections with different droops that are chosen depending on the current load of the ESS and the battery state of charge, and offsetting it according to a specified pattern, allows for preventing the premature loss of power capacity of the ESS BS. Full article

Prostate cancer is a serious public health concern in the United States. The primary obstacle to effective long-term management for prostate cancer patients is the eventual development of treatment resistance. Due to the uniquely chaotic nature of the neoplastic genome, it is difficult to determine the evolution of tumor composition over the course of treatment. Hence, a drug is often applied continuously past the point of effectiveness, thereby losing any potential treatment combination with that drug permanently to resistance. If a clinician is aware of the timing of resistance to a particular drug, then they may have a crucial opportunity to adjust the treatment to retain the drug’s usefulness in a potential treatment combination or strategy. In this study, we investigate new methods of predicting treatment failure due to treatment resistance using a novel mechanistic model built on an evolutionary interpretation of Droop cell quota theory. We analyze our proposed methods using patient PSA and androgen data from a clinical trial of intermittent treatment with androgen deprivation therapy. Our results produce two indicators of treatment failure. The first indicator, proposed from the evolutionary nature of the cancer population, is calculated using our mathematical model with a predictive accuracy of 87.3% (sensitivity: 96.1%, specificity: 65%). The second indicator, conjectured from the implication of the first indicator, is calculated directly from serum androgen and PSA data with a predictive accuracy of 88.7% (sensitivity: 90.2%, specificity: 85%). Our results demonstrate the potential and feasibility of using an evolutionary tumor dynamics model in combination with the appropriate data to aid in the adaptive management of prostate cancer. Full article

The contribution current of an inverter-interfaced distributed generator unit during a fault is one of the significant challenges for two modes: grid-connected and isolated AC microgrid. For this challenge, this article is aimed to study two methods of fault current calculation for two modes: grid-connected and isolated microgrids. These methods include a virtual equivalent impedance and a proposed method. The proposed method is a new technique for calculating the fault current contribution depending on the droop control of inverter-interfaced DG. The proposed method can control the contribution short-circuit current of DG within its limit (2 p.u.) where it is dependent on the voltage value of the DG bus to calculate the short circuit current of DG by using the control criterion. Static security risk and load shedding are calculated after fault clearance using an operation scenario in which the distribution system will be divided into small subsystems and is then grid-connected and isolated due to the removal of the faulted bus by protection devices. The proposed technique is applied to a standard IEEE 33-bus distribution network with five DGs. The results show that the contribution current of inverter-interfaced DG during the fault has more effects than the fault current of the nearest faulted bus to the DG bus. The proposed technique improves the calculated fault current value by about 30% for the grid-connected microgrid and by about 50% for the isolated microgrid from its value of the virtual impedance method. The static security risk is improved after load shedding. The static security risk improved by about 0.025%. Full article

This paper presents a stability analysis for droop-based islanded AC microgrids via an autonomous shooting method based on bifurcation theory. Shooting methods have been used for the periodic steady-state analysis of electrical systems with harmonic or unbalanced components with a fixed fundamental frequency; however, these methods cannot be directly used for the analysis of microgrids because, due to the their nature, the microgrids frequency has small variations depending on their operative point. In this way, a new system transformation is introduced in this work to change the droop-controlled microgrid mathematical model from an non-autonomous system into an autonomous system. By removing the explicit time dependency, the steady-state solution can be obtained with a shooting methods and the stability of the system calculated. Three case studies are presented, where unbalances and nonlinearities are included, for stability analysis based on bifurcation analysis; the bifurcations indicate qualitative changes in the dynamics of the system, thus delimiting the operating zones of nonlinear systems, which is important for practical designs. The model transformation is validated through time-domain simulation comparisons, and it is demonstrated through the bifurcation analysis that the instability of the microgrid is caused by supercritical Neimark–Sacker bifurcations, and the dynamical system phase portraits are presented. Full article

The high penetration of wind power decreases the system inertia and primary frequency reserve while replacing the conventional synchronous generators (SGs). Therefore, if the system operator does not take appropriate action on the remaining generation units (GUs) operation, high penetration of wind power will aggravate the frequency stability. To solve this problem, wind power plants (WPPs) may provide the inertial response and primary frequency response (PFR) to support the frequency stability. However, due to the variability of renewable energy, WPPs may not provide adequate frequency response whenever it is required. This paper proposes an algorithm to determine the operation of GUs to provide appropriate PFR for a power system with high penetration of wind power. Through the proposed algorithm, it calculates the required PFR to restore the decreased frequency stability caused by the high penetration of wind power. Then, while considering the available PFR from WPPs, it redetermines the droop coefficient of SGs governor to provide the sufficient PFR to recover the frequency stability. Finally, the effectiveness of the proposed algorithm is verified on the practical Korean electric power system. Full article

An aerodynamic optimization for a Droop-Nose Leading-Edge (DNLE) morphing of a well-known UAV, the UAS-S45, is proposed, using a novel Black Widow Optimization (BWO) algorithm. This approach integrates the optimization algorithm with a modified Class-Shape Transformation (CST) parameterization method to enhance aerodynamic performance by minimizing drag and maximizing aerodynamic endurance at the cruise flight condition. The CST parameterization technique is used to parameterize the reference airfoil by introducing local shape changes and provide skin flexibility to obtain various optimized morphing airfoil configurations. The optimization framework uses an in-house MATLAB algorithm, while the aerodynamic calculations use the XFoil solver with flow transition estimation criteria. These results are validated with a CFD solver utilizing the Transition $\left(\gamma -R{e}_{\theta }\right)$ Shear Stress Transport (SST) turbulence model. Numerical studies verified the effectiveness of the optimization strategy, and the optimized airfoils have shown a significant improvement in overall aerodynamic performance by up to 12.18% drag reduction compared to the reference airfoil, and an increase in aerodynamic endurance of up to 10% for the UAS-S45 optimized airfoil configurations over its reference airfoil. These results indicate the importance of leading-edge morphing in enhancing the aerodynamic efficiency of the UAS-S45 airfoil. Full article

Modern distribution networks face an increasing number of challenges in maintaining balanced grid voltages because of the rapid increase in single-phase distributed generators. Because of the proliferation of inverter-based resources, such as photovoltaic (PV) resources, in distribution networks, a novel method is proposed for mitigating voltage unbalance at the point of common coupling by tuning the volt–var curve of each PV inverter through a day-ahead deep reinforcement learning training platform with forecast data in a digital twin grid. The proposed strategy uses proximal policy optimization, which can effectively search for a global optimal solution. Deep reinforcement learning has a major advantage in that the calculation time required to derive an optimal action in the smart inverter can be significantly reduced. In the proposed framework, multiple agents with multiple inverters require information on the load consumption and active power output of each PV inverter. The results demonstrate the effectiveness of the proposed control strategy on the modified IEEE 13 standard bus systems with time-varying load and PV profiles. A comparison of the effect on voltage unbalance mitigation shows that the proposed inverter can address voltage unbalance issues more efficiently than a fixed droop inverter. Full article

In a DC microgrid, droop control is the most common and widely used strategy for managing the power flow from sources to loads. Conventional droop control has some limitations such as poor voltage regulation and improper load sharing between converters during unequal source voltages, different cable resistances, and load variations. This paper addressed the limitations of conventional droop control by proposing a simple adaptive droop control technique. The proposed adaptive droop control method was designed based on mathematical calculations, adjusting the droop parameters accordingly. The primary objective of the proposed adaptive droop controller was to improve the performance of the low-voltage DC microgrid by maintaining proper load sharing, reduced circulating current, and better voltage regulation. The effectiveness of the proposed methodology was verified by conducting simulation and experimental studies. Full article

The high penetration of photovoltaic (PV) systems and fast communications networks increase the potential for PV inverters to support the stability and performance of microgrids. PV inverters in the distribution network can work cooperatively and follow centralized and decentralized control commands to optimize energy production while meeting grid code requirements. However, there are older autonomous inverters that have already been installed and will operate in the same network as smart controllable ones. This paper proposes a decentralized optimal control (DOC) that performs multi-objective optimization for a group of PV inverters in a network of existing residential loads and autonomous inverters. The interaction of independent DOC groups in the same network is considered. The limit of PV inverter power factor is included in the control. The DOC is done by the power flow calculation and an autoregression prediction model for estimating maximum power point and loads. Overvoltage caused by prediction errors resulting in non-optimal commands from the DOC is avoided by switching to autonomous droop control (ADC). The DOC and ADC operate at different time scales to take account of communication delays between PV inverters and decentralized controller. The simulation of different scenarios of network control has proved the effectiveness of the control strategies. Full article