Search

DC microgrids (DCMGs) are evolving into cyber-physical systems with advanced communication networks and computational methodologies, making them sensitive to cyber-attacks. These attacks can threaten the safe operation of a system. In this article, a virtual sensor-based framework is proposed for continuously monitoring and detecting malicious activities at the hardware level of a DCMG system. An adaptive state observer with a low computational burden is designed to estimate the voltage and current of a dc–dc converter. The proposed method considers the effects of cyber-attacks by injecting false data (FD) at targeted nodes in an attempt to affect the voltage regulation and current sharing by modifying the onboard voltage and current sensors. In the presented strategy, first, a DCMG is operated and controlled without any false data injecting attacks with different load conditions. Next, the DCMG is exposed to various cyber-attacks, and the output voltages and currents of dc–dc converters are estimated. Based on the error between the estimated and actual sensed signals, the cyber-attack is detected and corrected with the proposed framework. The proposed scheme is simple in design, efficient in operation, and easily implemented in a distributed control system. The effectiveness and robustness of the proposed method are illustrated by implementing it in real-time hardware using the LabView test bench by considering four dc systems (including a solar photovoltaic system) connected in a ringlike manner communicated via an ethernet-based local area network. [ABSTRACT FROM AUTHOR]

The increase in the numbers of electric vehicles (EVs) is seen as an upgrading of the existing vehicles for various reasons. This calls for an in‐depth analysis of the heart of these vehicles—the motor. A motor in an electric vehicle propulsion system is a crucial component that has the ability to affect the efficiency, weight, cost, reliability, power output and performance. Hence a detailed comparative study, that compares the existing types and topologies of various motors, is the need of the hour. The various motors that can be used in electric traction, namely DC, induction, switched reluctance, permanent magnet brushless AC motors and permanent magnet brushless DC motors, are reviewed in view of their capabilities with respect to EV propulsion. A detailed review is presented of existing motors and the application of power electronic techniques to EVs, and recommendations for some new designs of brushless DC motors. These include permanent magnet hybrid motors, permanent magnet spoke motors and permanent magnet inset motors. [ABSTRACT FROM AUTHOR]

This article proposes a computationally simple strategy by using a three-sample-based technique for a grid-connected inverter in a single-phase active distribution system. The proposed control is to improve the performance during varying grid conditions such as voltage sag, swell, and frequency swing. A comparative analysis between the proposed controller and the conventional second-order generalized integrator phase-locked loop (PLL) based controller for dynamic grid conditions in weak-grid scenario has been presented. Additionally, a frequency domain analysis via describing function method is used to model the dynamics of nonlinear hysteresis current controller to analyze the closed-loop stability of the system. Further validation of the proposed control algorithm is simulated in MATLAB/SIMULINK environment for various scenarios. To establish the effectiveness of the proposed approach in real time, the proposed control strategy is tested in a 1 kVA based experimental setup. [ABSTRACT FROM AUTHOR]

The autonomous microgrid (MG) with multiple voltage source inverters (VSI) is operated in droop mode to share the load proportionally. These VSI controllers require higher droop constants if the feeder lines connecting the VSI to microgrid has a low X/R ratio. The higher droop gains and large loading conditions in the microgrid may exhibit instability with the low frequency power modes (LFPM). This paper details a systematic multivariable plant model of the MG using dynamic phasor modeling of power flow transfer functions to analyze the LFPM. Further, a robust supplementary multivariable controller is developed to stabilize the developed plant model, damp LFPM and improve transient power sharing performance of VSIs without affecting their steady-state power sharing. This stabilizer is developed based on Glover-McFarlane H∞ loop shaping robust stabilization technique with an additional pole placement constraints formulated in linear matrix inequality framework. A laboratory scale experimental validation is presented to evaluate the performance of proposed stabilizer under various operating conditions and uncertainties in the autonomous MG. Moreover, the transient power sharing performance of DGs with proposed controller was compared with that of widely used derivative droop controller. [ABSTRACT FROM AUTHOR]

A new multiple parallel input and parallel output architecture-based models are developed for forecasting electric load power consumption. Attention was paid toward the improvement of the accuracy of forecasting using this new architecture built-in by us, as compared to others in the latest literature. The models have an ability to forecast daily load profiles with a lead time of one to seven days. Both multivariate linear regression and feed-forward neural network techniques have been chosen for comparative performance study and analysis. The real-time data used for this research work were collected from Tata Power Delhi Distribution Limited, Delhi, India. Based on the performance criteria provided in the literature, each model is analyzed and the results are presented for two different lead times, i.e., day-ahead and week-ahead only. [ABSTRACT FROM AUTHOR]

This paper presents an adaptive droop based cooperative energy management scheme for a photovoltaic (PV) battery based autonomous dc microgrid. To overcome the basic challenges in managing multiple batteries in a distributed dc network, a cooperative cyber network is employed to formulate an enhanced adaptive droop control philosophy. With PV panels operating as a constant power source at maximum power point tracking (MPPT), battery energy storage systems cooperate among themselves to balance state-of-charge (SoC) between them and undergo constant voltage (CV) charging mode when the condition arises, which is handled using the proposed adaptive droop concept. Further emphasis is given on optimal voltage regulation to induce robustness against time-delay as compared to the conventional voltage observers, which cause high observing error. Moreover, the design criteria of the proposed strategy is provided to ensure system stability under normal and time-delayed conditions. The proposed control strategy is simulated in MATLAB/SIMULINK environment to demonstrate SoC balancing, CV charging albeit various communication issues such as delay and multiple link failure. The proposed strategy is further tested on an field-programmable gate array (FPGA)-based experimental prototype to validate the effectiveness of the proposed strategy. [ABSTRACT FROM AUTHOR]

In realistic scenarios, the dynamic performance of a microgrid cluster is largely affected by the intermittent power of renewable energy sources and frequent load changes. To address this issue, a distributed fixed-time based dual layer secondary controller is designed to improve inter-microgrid and intra-microgrid dynamic performance within a fixed settling time. The proposed controller is independent of initial operating values as opposed to the finite time control law. Each global agent in a microgrid operates to mitigate loading mismatch between other global agents, whereas each local agent in a microgrid operates to achieve proportionate load current sharing and average voltage regulation between them in fixed time. However, as loading mismatch mitigation during light load conditions affects the system efficiency due to significant line losses, the cluster operation switches to a distributed loss minimization approach, which operates using online measurements from the neighboring microgrids. To characterize the mode of operation in the global cyber layer, a critical point of loading threshold for the cluster is thus determined. The performance of the cluster employing the proposed strategy is simulated in MATLAB/SIMULINK environment for various scenarios to demonstrate its reliability and efficiency. [ABSTRACT FROM AUTHOR]

The grid-connected photovoltaic (PV) system with battery energy storage (BESS) has been in use for many demand-related issues. This article discusses the use of grid-connected PV with BESS in case of open-phase condition in the distribution system. An open-phase condition at medium voltage (11 kV) will result in continuous voltage sag at low voltage (LV) voltage level (400 V), which may be detrimental to various kind of loads, especially for constant power loads. This article presents an approach to mitigate such a scenario by using a control strategy for voltage source converter of grid-connected PV connected to the distribution transformer terminal. The utility of the proposed configuration is demonstrated as the voltage is restored in all phases at the LV level during an open-phase fault at the MV level, and results obtained for selected possible loading conditions have been presented. For further validating the proposed control strategy in real-time conditions, experimental verification is also done on an NI-based PXI hardware setup along with an Opal-RT based hardware in the loop system, and results for the same have been presented. [ABSTRACT FROM AUTHOR]

This study presents the application of non‐linear disturbance observer (NDO) for automatic generation control of interconnected thermal area power systems considering generation rate constraints. In this work, any change in electrical power arising in the system due to either load change or change in power output of intermittent renewable energy sources is called a disturbance. This disturbance is estimated using an NDO and the same is rejected by giving an equivalent command to the governor of thermal power units to maintain a power balance in the system; thereby maintaining frequency and tie‐line power flows in each area of an interconnected power system. The analysis is presented on a two‐area power system and it is shown that the proposed control scheme effectively mitigates any active power imbalance in the system not only for normal operations but also when there is large communication delay in the system. The key advantages of the proposed scheme not only include faster frequency and tie‐line power control but also reduced control efforts as compared to other established control schemes. Furthermore, the proposed scheme requires the optimisation of only one control parameter in each area. Therefore, the scheme gives away the requirement of complex optimisation algorithms. [ABSTRACT FROM AUTHOR]

This paper proposes a cooperative mechanism for detecting potentially deceptive cyber attacks that attempt to disregard average voltage regulation and current sharing in cyber-physical dc microgrids. Considering a set of conventional cyber attacks, the detection becomes fairly easy for distributed observer based techniques. However, a well-planned set of balanced attacks, termed as the stealth attack, can bypass the conventional observer based detection theory as the control objectives are met without any physical error involved. In this paper, we discuss the formulation and associated scope of instability from stealth attacks to deceive distributed observers realizing the necessary and sufficient conditions to model such attacks. To address this issue, a novel cooperative vulnerability factor (CVF) framework for each agent is introduced, which accurately identifies the attacked agent(s) under various scenarios. To facilitate detection under worst cases, the CVFs from the secondary voltage control sublayer is strategically cross coupled to the current sublayer, which ultimately disorients the control objectives in the presence of stealth attacks and provides a clear norm for triggering defense mechanisms. Finally, the performance of the proposed detection strategy is simulated in MATLAB/SIMULINK environment and experimentally validated for false data injection and stealth attacks on sensors and communication links. [ABSTRACT FROM AUTHOR]

The focus of this work is to analyse the performance of automatic generation control (AGC) of two area four units interconnected deregulated power system for implementing modified sine cosine algorithm (MSCA) to design the conventional PID and fuzzy‐PID (FPID) controllers. Each area consists of thermal generating unit with reheat turbine and a gas generating unit. Thermal generating units of both areas are employed with appropriate generation rate constraint. At first, sine cosine algorithm (SCA) is modified to implement MSCA technique and superiority of MSCA is proved over SCA using four benchmark functions. Then the work is extended to design the conventional PID and FPID controllers using both the algorithms. Three different situations of deregulated markets are considered. For the design of optimal controller gains integral time absolute error is taken as the objective function. To analyse the dynamic behaviour of the deregulated power system undershoot, overshoot and settling time are considered as transient parameters. After the analysis, it is found that MSCA‐based FPID controller exhibits a better transient response in terms of less undershoot, overshoot and settling time. Robustness analysis is performed by varying some of the important parameters of the power system to show the proposed FPID controller is less sensitive to parametric variations. [ABSTRACT FROM AUTHOR]

The paper proposes a centralized protection scheme with a localized backup for a MVDC microgrid. The centralized scheme is implemented using the percentage differential current approach backed up with a localized scheme employing running autoregressive smoothing average. An adaptive mathematical analysis of the parameters employed is performed for a justified assent. The proposed scheme is ratified to be accurate and immune to the system configuration, voltage fluctuations, and high-resistance faults with its security, dependability, and selectivity validated for different transients and fault contingencies employing minimum solid state circuit breakers in the microgrid. [ABSTRACT FROM AUTHOR]

Development of microgrids and wide spread deployment of renewable generation and energy storage systems have highlighted the need for distributed control schemes to achieve maximum utilization and coordination among all the connected resources. In DC microgrids, the key goals of system-wide control are droop-based current sharing and network dc-voltage regulation. These may be achieved using a consensus algorithm secondary control that a) averages all the node voltages dynamically and maintains them at a nominal value and b) based on information from neighboring source currents to converge to a consensus in current sharing. Achieving the dynamic consensus may impose significant communication burden when implemented using conventional periodic communication methods. In this paper, an event-triggered communication based dynamic consensus algorithm is proposed that helps achieve both the stated goals of proportional current sharing along with average DC voltage regulation in a DC microgrid. The convergence and stability of the modified dynamic consensus algorithm and event triggering condition is proven using Lyapunov's stability criterion. The proposed control is applied to a DC microgrid system for secondary control of voltage and current regulation, and the performance of the proposed technique is validated under various operating conditions and disturbance in the communication system in both simulation and hardware environment. [ABSTRACT FROM AUTHOR]

This paper presents a step in microlevel photovoltaic (PV) summation technology for combining unsymmetrical PV modules with differences in specification and age, relocation on nonfertile land, or multilocation mounting by designing an add-on modular hardware interface to a multi-input single-output (MISO) dc bus, using an MISO controller employing a suitable maximum power point (MPP) tracker under partial shading/long distance/mismatching PV module conditions along with a sensor-less PV vector control inverter (PV–VCI) driving a three-phase asynchronous squirrel cage induction motor dedicated to irrigation, with the facility of autoconfiguration/autotuning at the beginning. A PV source gets automatically added/removed in a ramp profile in proportion to the load in steps, thus keeping on only when required, enabling high efficiency, minimum heating, and prolonged life as that of a PV module. The contribution includes a reduced PV energy cost per watt by 24.10%, improved return on investment by 27.48%, improved water discharge yield by 11.06%, and improved MPP tracker impact by 14.59% with 90.88% MISO system efficiency compared to a normal scheme. [ABSTRACT FROM AUTHOR]

Modern power system involves growing use of open channel communication in secondary frequency regulation which introduces time delay in the automatic generation control loop which may lead to system instability. This study proposes a novel power system frequency stabiliser (PSFS) which is a modified secondary controller in order to improve the system stability in the presence of large communication delays. An auxiliary signal is added to the secondary controller to provide additional damping. The gain of the controller is obtained by meta‐heuristic methods. The proposed controller is first developed on a single area hydropower system and the same is then applied on the Western System Coordinating Council 3‐machine, 9‐bus power system. Furthermore, to show the effectiveness of the proposed PSFS in a large practical multi‐area system; it is also applied to the IEEE 39‐bus system. Results show that the proposed controller significantly improves the stability of a power system operating with large communication delay which is first considered as constant and then the stability improvement with the proposed PSFS in the presence of random communication delays is also shown. The PSFS performance is tested by the results obtained with MATLAB/Simulink simulations and further verified on a real‐time simulator. [ABSTRACT FROM AUTHOR]

A robust controller design for the voltage control of an autonomous three-phase voltage source converter (VSC) is proposed. As compared with the conventional proportional plus integral (PI) controllers, fractional order controllers make the VSC system robust due to their fractional characteristics. The fractional PI $\lambda$ controller has an additional degree of freedom $\lambda$ along with $k_p$ and $k_i$ gains of the conventional PI controller. Detailed modeling of a VSC is used in the controller design process so as it include inner current control and filter dynamics. The outer fractional voltage controller is designed such that the VSC system satisfies a required phase margin, with improved robustness in the system and capability to attenuate the noise. The overall system stability is analyzed using both bode plot and step response, and these responses are compared with a conventional PI controller. Further, the dynamic performance of the fractional controller is evaluated by simulating the nonlinear system. A hardware prototype is also developed to demonstrate the practical realization of the controller. [ABSTRACT FROM AUTHOR]

In this paper, a dynamic power management scheme (PMS) is proposed for a standalone hybrid ac/dc microgrid, which constitutes a photovoltaic (PV)-based renewable energy source, a proton exchange membrane fuel cell (FC) as a secondary power source, and a battery and a supercapacitor as hybrid energy storage. The power management algorithm accounts for seamless operation of the microgrid under various modes and state-of-charge limit conditions of hybrid energy storage when all the sources, storages, and loads are connected directly at the dc link. The PMS generates current references for dc converter current controllers of the FC, the battery, and the supercapacitor. The average and fluctuating power components are separated using a moving average filter. The dc-link voltage regulation under dynamic changes in load and source power variation is proposed. Also, PV power curtailment through control is formulated. The proposed power management is modified and extended to multiple PV generation systems and batteries, with all the sources and storages geographically distributed and operating under multitime-scale adaptive-droop-based control with supervisory control for mode transition. The proposed PMS is validated using simulation results. Also, field programmable gate array/Labview-based laboratory-scale experimental results are presented to validate the PMS under various critical conditions. [ABSTRACT FROM AUTHOR]

The dissolved gas-in-oil analysis is a prevailing methodology being extensively utilized to diagnose incipient faults in oil-immersed power transformers. However distinct approaches have been implemented to find out dissolved gas analysis (DGA) results, they may sometimes fail to diagnose precisely. The incipient fault identification accuracy of various artificial intelligence (AI)-based methodology is assorted with change of input parameters. Thus, selection of input variable to an AI model is major research area. In this paper, principle component analysis algorithm using RapidMiner is applied to 360 experimental datasets, imitated in lab to identify most pertinent input variables for incipient fault classification. Thereafter, multi-class Extreme Learning Machine (ELM) technique is implemented to classify the incipient faults of power transformer and its performance is compared with artificial neural network, gene expression programming, fuzzy-logic, and support vector machine. The compared result shows that ELM provides better diagnosis results up to 100% accuracy at proposed input variable in short of time period which is helpful in on-line condition monitoring. [ABSTRACT FROM AUTHOR]

Low voltage (LV) distribution systems are typically unbalanced in nature due to unbalanced loading and unsymmetrical line configuration. This situation is further aggravated by single-phase power injections. A coordinated control scheme is proposed for singlephase sources, to reduce voltage unbalance. A consensus-based coordination is achieved using a multi-agent system, where each agent estimates the averaged global voltage and current magnitudes of individual phases in the LV network. These estimated values are used to modify the reference power of individual single-phase sources, to ensure system-wide balanced voltages and proper power sharing among sources connected to the same phase. Further, the high X/R ratio of the filter, used in the inverter of the single-phase source, enables control of reactive power, to minimize voltage unbalance locally. The proposed scheme is validated by simulating a LV distribution network with multiple single-phase sources subjected to various perturbations. [ABSTRACT FROM AUTHOR]

In this paper, an online empirical mode decomposition (EMD) based algorithm is proposed for the control of a shunt active filter (AF). Standard EMD algorithm has worked on the principle of time-scale difference between the upper maximum values and lower minimum values of a signal, and for a long time it has been considered good for offline analysis of signals. This paper deals with the real-time application of EMD for the control of AF under balanced and unbalanced loads. Linear interpolators are employed for construction of upper and lower envelopes to avoid computation complexity. Moreover, customized iterative computations for extraction of intrinsic mode functions maintain the efficiency of algorithm. The algorithm extracts the fundamental component of load current and helps in estimating reference currents. Simulations are performed on MATLAB/Simulink platforms. Simulation results are verified with experimental results of a developed prototype of shunt AF. [ABSTRACT FROM PUBLISHER]

Accurate diagnosis of incipient faults in oil-filled power transformers is important in preventive maintenance of transformers. Dissolved gas analysis (DGA) is an effective tool to diagnose incipient transformer faults. The majority of the methods reported in literature to analyze DGA results lay more emphasis on user experience rather than mathematical formulation/justification. Furthermore, sometimes DGA results for a certain fault do not belong to any of the IEC/IEEE standard and cannot be categorized/diagnosed. To address these issues, we propose a new approach for DGA interpretation using gene expression programming (GEP). The proposed approach is employed for analysis of 552 DGA samples collected from transformers of Himachal Pradesh State Electricity Board, India, in conjunction with samples extracted from reliable literature. We use the aforementioned dataset to test and validate our proposed GEP model. We also compare the performance of our approach against other artificial intelligence-based techniques such as artificial neural network, fuzzy-logic, and support vector machine. Results and comparison against other soft computing approaches show relative superiority of GEP-based DGA interpretation in terms of classification accuracy. [ABSTRACT FROM AUTHOR]

The diesel‐photovoltaic (PV) based hybrid AC microgrid systems with conventional control philosophies deliver very good performance in the grid connected mode. However, once the microgrid is isolated from the main grid the same philosophies which control the PV at its maximum power can make the microgrid unstable. In this connection, this study proposes a novel neuro‐fuzzy controller to ensure the smooth transition of microgrid from grid connected mode to isolated mode, to retain the system stability even in isolated mode and to deliver the superior performance in grid connected mode as well. The considered artificial neural networks is trained with PMPP–Temp against VMPP characteristic, first of its kind. The fuzzy part of the controller derives the reference voltages subjected to the limits provided by the ANN. This study describes how well the data analytics can be utilised to retain the power system stability in emergencies. The proposed controller has been evaluated under different operating conditions and is exhibiting superior performance in achieving the desired control objectives. Results from the numerical simulations are confirmed from the experiments in real‐time environment. [ABSTRACT FROM AUTHOR]

The diagnosis of incipient fault is important for power transformer condition monitoring. Incipient faults are monitored by conventional and artificial intelligence based models. Key gases, percentage value of gases, and ratio of the Doernenburg, Roger, IEC methods are input variables to artificial intelligence models, which affects the accuracy of incipient fault diagnosis, so selection of the most influencing relevant input variable is an important research area. With this main objective, Waikato Environment for Knowledge Analysis software is applied to 360 simulated samples having different operating lives to find the most influencing input parameters for incipient fault diagnosis in the gene expression programming model. The Waikato Environment for Knowledge Analysis identifies%C2H2,%C2H4,%CH4, C2H6/C2H2, C2H2/C2H4, CH4/H2, C2H4/C2H6, and C2H2/CH4as the most relevant input variables in incipient fault diagnosis, and it is used for fault diagnosis using different artificial intelligence methods,i.e., artificial neural networks, fuzzy logic, support vector machines, and gene expression programming. The compared results shows that gene expression programming gives better results than the artificial neural network, fuzzy logic, and support vector machine with accuracy variation from 98.15 to 100%, proving the gene expression programming method can be used in transformer fault diagnosis research. [ABSTRACT FROM AUTHOR]

This study presents a novel approach to localise, detect and classify non‐stationary power signal disturbances using a modified frequency slice wavelet transform (MFSWT). MFSWT is an extension of frequency slice wavelet transform (FSWT), which provides frequency‐dependant resolution with additional window parameters for better localisation of the spectral characteristics. An advantage of the MFSWT is attributed to the fact that the modulating sinusoids are fixed with respect to the time axis, whereas a localising scalable modified Gaussian window dilates and translates. Several practical power signals are considered for visual analysis using MFSWT, and the disturbance patterns are appropriately localised with unique signature corresponding to each type. This work also evaluates the detection capability of the proposed methodology and a comparison with earlier FSWT and Hilbert transform to show the superiority of proposed technique in detecting the power quality disturbances. A probabilistic neural network (PNN) based classifier is used for identifying the various disturbance classes. The spread parameter of the Gaussian activation function in PNN is tuned and its effect on the classification at different strengths of noise is studied. [ABSTRACT FROM AUTHOR]

This article presents a multiobjective control scheme for a bidirectional interlinking converter (ILC) of renewable energy based ac–dc hybrid microgrid. The prime focus of the power management algorithm is to feed the ac loads, and dc loads from ac source, and photovoltaic battery energy storage (BES), respectively. The second objective is to utilize the solar power to maximum capacity, by feeding it to dc load, BES, and ac load, in the given order of priority. The ac and dc subgrids operate independently, while supporting each other in case of overloading/underloading, thus reducing the amount of power reserve required in each, and eliminating the need of dump loads. The ANFIS-MN-based power quality control is integrated in order to ensure the total harmonics distortion of ac source current remains below 5% as per IEEE 519 standard, irrespective of the nature of load connected. In addition, the ILC control prevents any negative sequence currents from entering the ac source, even if there is any open circuit fault leading to unbalanced loading on the three phases. The performance of ANFIS-MN-based ILC control is demonstrated to be superior when compared with the conventional and contemporary techniques under different scenarios. [ABSTRACT FROM AUTHOR]

Abstract: This paper deals with automatic generation control (AGC) of a three unequal area hydrothermal system. Reheat turbines in thermal areas and electric governor in hydro area are considered. Appropriate generation rate constraints are considered in the areas. Bacterial foraging (BF) technique is used to simultaneously optimize the integral gains (KIi ) and speed regulation parameter (Ri ) keeping frequency bias fixed at frequency response characteristics. The integral controller in this case is termed as BFIC. The performance of a multilayer perception neural network (MLPNN) controller using reinforcement learning is evaluated for the system. In this reinforcement learning, the weights are dynamically adjusted online using backpropagation algorithm with error being the area control error (ACE). The performance of the MLPNN controller is compared with that of BFIC. Also, the performance of MLPNN controller over a wide range of system loading conditions and step load perturbations is compared with BFIC. Investigations clearly reveal the superior performance of MLPNN controller over BFIC. Sensitivity analysis subject to wide changes in system loading, inertia constant (H) and size and location of step load perturbation is carried out to investigate the robustness of the controller with the optimum KIi and Ri obtained at nominal condition. [Copyright &y& Elsevier]

This paper uses the recently proposed H∞-learning method, for updating the parameter of the radial basis function neural network (RBFNN) used as a control scheme for the unified power flow controller (UPFC) to improve the transient stability performance of a multimachine power system. The RBFNN uses a single neuron architecture whose input is proportional to the difference in error and the updating of its parameters is carried via a proportional value of the error. Also, the coefficients of the difference of error, error, and auxiliary signal used for improving damping performance are depicted by a genetic algorithm. The performance of the newly designed controller is evaluated in a four-machine power system subjected to different types of disturbances. The newly designed single-neuron RBFNN-based UPFC exhibits better damping performance compared to the conventional PID as well as the extended Kalman filter (EKF) updating-based RBFNN scheme, making the unstable cases stable. Its simple architecture reduces the computational burden, thereby making it attractive for real-time implementation. Also, all the machines are being equipped with the conventional power system stabilizer (PSS) to study the coordinated effect of UPFC and PSS in the system. [ABSTRACT FROM AUTHOR]

In this article, multiple parallel photovoltaic (PV) inverters based microgrid is developed to enhance the reliability and accessibility of electricity in remote areas. A self-adaptive control strategy is presented for a microgrid to ensure a seamless transition between the islanded mode (IAM) and grid-connected mode (GCM) of operation with a proportional power sharing. This microgrid consists of two solar PV inverters based on local distributed generation (DG) units. Each PV-inverter unit feeds an active power to support local loads and the power demand of each local load is shared between respective DG units and microgrid. The PV-battery-interfaced main unit with a self-adaptive control strategy in parallel with a PV array supported unit-2 is considered to operate in the IAM and GCM of operation. The control strategy achieves transient free operation during load disturbances, power variation at the PV array side, and off-grid operation. Moreover, the microgrid ensures high-quality performance at the point of common coupling and provides the seamless transition between GCM and IAM to guarantee a continuous power to critical loads. The microgrid simulation and experimental results are presented under various operating conditions, such as load variation, intermittent power generation, and automated mode transition between GCM and IAM. [ABSTRACT FROM AUTHOR]

RNA interference (RNAi) is a primitive evolutionary mechanism developed to escape incorporation of foreign genetic material. siRNA has been instrumental in achieving the therapeutic potential of RNAi by theoretically silencing any gene of interest in a reversible and sequence‐specific manner. Extrinsically administered siRNA generally needs a delivery vehicle to span across different physiological barriers and load into the RISC complex in the cytoplasm in its functional form to show its efficacy. This review discusses the designing principles and examples of different classes of delivery vehicles that have proved to be efficient in RNAi therapeutics. We also briefly discuss the role of RNAi therapeutics in genetic and rare diseases, epigenetic modifications, immunomodulation and combination modality to inch closer in creating a personalized therapy for metastatic cancer. At the end, we present, strategies and look into the opportunities to develop efficient delivery vehicles for RNAi which can be translated into clinics. [ABSTRACT FROM AUTHOR]

Nanotherapy has emerged as an improved anticancer therapeutic strategy to circumvent the harmful side effects of chemotherapy. It has been proven to be beneficial to offer multiple advantages, including their capacity to carry different therapeutic agents, longer circulation time and increased therapeutic index with reduced toxicity. Over time, nanotherapy evolved in terms of their designing strategies like geometry, size, composition or chemistry to circumvent the biological barriers. Multifunctional nanoscale materials are widely used as molecular transporter for delivering therapeutics and imaging agents. Nanomedicine involving multi-component chemotherapeutic drug-based combination therapy has been found to be an improved promising approach to increase the efficacy of cancer treatment. Next-generation nanomedicine has also utilized and combined immunotherapy to increase its therapeutic efficacy. It helps in targeting tumor immune response sparing the healthy systemic immune function. In this review, we have summarized the progress of nanotechnology in terms of nanoparticle designing and targeting cancer. We have also discussed its further applications in combination therapy and cancer immunotherapy. Integrating patient-specific proteomics and biomarker based information and harnessing clinically safe nanotechnology, the development of precision nanomedicine could revolutionize the effective cancer therapy. [ABSTRACT FROM AUTHOR]

This article presents an enhanced power quality solar photovoltaic (PV) inverter enabling common-mode leakage current elimination. A three-phase transformerless solar energy conversion system is considered here, which, along with peak active-power production from PV array, ensures different power quality improvement capabilities such as grid current harmonics mitigation, grid currents balancing while also offering the grid reactive power support. Unlike conventional power quality inverters, this strategy is robust with respect to abnormalities in grid voltages at far radial ends, and does not compromise with the leakage currents caused by parasitic capacitance of PV array with ground. Common practice in the PV inverter power quality control is to neglect the PV leakage currents; however, they considerably affect the system performance by deteriorating the power quality and causing the safety issues of operating personnel. The standards VDE-00126 and NB/T-32004, therefore, compel the transformerless PV systems to operate with leakage current under 300 mA range. Various simulation and test results show the satisfactory performance of the presented strategy, even under various grid-side abnormalities. The comparative analysis with the state-of-the-art techniques shows the effectiveness of the strategy. Under all test conditions, the harmonics in grid currents are observed within limits as per the IEEE-519 and IEC-61727 standards, whereas the PV leakage currents are maintained well within the range recommended by VDE-00126 standard. [ABSTRACT FROM AUTHOR]

This article aims to develop a solar- battery energy storage (BES) based system, which ensures an uninterruptable supply to loads irrespective of availability of the grid. This system comprises of a solar photovoltaic (PV) array, a BES, the grid and local residential loads. A new control is implemented such that the active power demand of residential loads, is fed from the PV array, a BES unit and the utility grid. In this system, the power control operates in different power modes, which delivers the benefits to the end users with an integration of BES and an excess of PV array power, which is sold back to the grid. For this, an effective control logic is developed for the grid tied voltage source converter. Moreover, this system deals with the issue of an integrating power quality enhancement along with the power generation from the solar PV source. The cascaded delayed signal cancellation based phase locked loop is implemented for grid synchronization during the grid voltage distortion. The developed control is easily implemented in a real time controller (dSPACE-1202). Test results validate the performance of the implemented control in different operating conditions such as varying solar power generation, load variations and unavailability of the grid. [ABSTRACT FROM AUTHOR]

The dual active bridge (DAB) converters have the capability of handling high power in compact form and it is one of the key elements for interconnecting different dc microgrid clusters. A DAB also offers bidirectional power transfer with galvanic isolation between two power buses of similar or different voltage levels, i.e., low voltage and high voltage buses. In microgrid applications, bus voltage regulation is necessary for an uninterrupted power flow and reliable operation of dc microgrids. Due to the galvanic isolation and modularity nature of a DAB, the output can be easily interconnected for efficient and reliable power sharing. In this article, taking the advantage of modularity property of the DAB, an efficient and improved power sharing scheme is developed to stabilize the bus voltage in microgrid applications. A robust bidirectional power sharing control strategy is developed between DABs from different high voltage buses to low voltage buses that improves the voltage stability. An advanced supervisory controller is designed by considering the nonlinearity and uncertainty that ensures stable dc bus voltage and reliable power sharing among DABs under different operating conditions. The controller is validated theoretically and a small-scale laboratory prototype is developed. The concept is verified experimentally at different possible scenarios. From theoretical and experimental results, it is found that the proposed DAB control provides excellent performance in terms of power sharing, dc-bus voltage regulation and power quality. [ABSTRACT FROM AUTHOR]

A reduced-order model of a converter-dominated microgrid system may not resemble its full-order system associated with uncertainties. This paper aims to provide a singular perturbation-based contraction framework for model order reduction in converter-dominated uncertain microgrid systems. For this purpose, the concerned microgrid system is modeled as a generalized multi-timescale system, and certain sufficient conditions are derived such that convergence between the trajectories of the uncertain full-order and the corresponding reduced-order model can be guaranteed. The contraction theory-based strategy also provides explicit parameter-dependent expressions for quantifying discrepancies. The derived results are utilized to analyze the inverter-based microgrid system’s convergence behavior and obtain uncertainty bounds on its parameters. Further, the effects of modeling uncertainties and different loading conditions on the reduced-order model’s validity are also discussed. It is observed that for any uncertainty associated with the microgrid parameters that are within the bounds of checkable conditions, the states of the reduced-order microgrid model converge to that of the uncertain full-order system. Further, it is also shown that the obtained discrepancy expressions are more precise than state of the art. [ABSTRACT FROM AUTHOR]

In this paper we propose a one-dimensional convolutional neural network (CNN)-based state of charge estimation algorithm for electric vehicles. The CNN is trained using two publicly available battery datasets. The influence of different types of noises on the estimation capabilities of the CNN model has been studied. Moreover, a transfer learning mechanism is proposed in order to make the developed algorithm generalize better and estimate with an acceptable accuracy when a battery with different chemical characteristics than the one used for training the model, is used. It has been observed that using transfer learning, the model can learn sufficiently well with significantly less amount of battery data. The proposed method fares well in terms of estimation accuracy, learning speed and generalization capability. [ABSTRACT FROM AUTHOR]

The article presents a corrective control philosophy of a grid tied inverter for adapting the instability incurred at the Point of Common Coupling (PCC) due to uncertainty in the utility grid. It has been observed that the converter impedance which is dependant on the control system loop have a considerable impact on the stability. Therefore, the proposed philosophy explores the participation of the control parameters in shaping the return ratio trajectory which consequently modifies the stability margins of the system. A sensitivity function has been formulated which gives the gradient of each point in the return ratio trajectory to changes in the control parameters. The formulated function has an additional advantage of being grid parameter independent, thus increasing robustness and reducing complexity. An adaptive multi-variable, multi-degree of freedom feedback philosophy using the sensitivity gradients has been proposed to dynamically reach the optimum value of the control parameters in case of grid impedance change. The result shows that the proposed philosophy successfully brings stability to the system in the presence of a weak grid. As well as it preserves the dynamic performance requirements of the converter control. [ABSTRACT FROM AUTHOR]

This study proposes a new modelling approach for studying low‐frequency oscillations (LFOs) in a droop controlled islanded microgrid. Due to the absence of inertia, these sources are more vulnerable to power and frequency oscillations. Their quick response can introduce faster electrical dynamics in the system which should be monitored from time to time. To ease the analysis process, this study proposes a simplified method for finding LFO in the microgrid. Inspired from the small‐signal automatic generation control model of the conventional grid, a transfer function based closed‐loop small‐signal model of inverter‐based islanded microgrid is presented in this study to study power‐sharing among the various inverters. The proposed model uses the concept of dynamic power flow through the network to find the power output of each source following load perturbations in a system. Time domain simulation results and eigenvalue analysis is provided to verify the effectiveness of the proposed small‐signal model. By comparing the results obtained with actual system simulation in MATLAB/Simulink, it is found that the proposed simplified model is able to predict the stability margin and the LFO of the system without using actual detailed state‐space modelling procedure. [ABSTRACT FROM AUTHOR]

In this work, a multifunctional control is implemented for a solar photovoltaic (PV) integrated battery energy storage (BES) system (PVBES), which operates both in the grid-connected mode (GCM) and a standalone mode (SAM). This system addresses the major issues of integrating power quality enhancement along with the solar PV generation. Thus, a multifunctional control of voltage source converter (VSC) is implemented to provide the load compensation, harmonics mitigation, unity power factor, and an automated transition between GCM and SAM in PVBES. A single VSC is used to control the active power and to maintain the power quality in this PVBES. Furthermore, due to an automated transition in the system, the local loads have continuous power irrespective of the grid accessibility. The main challenges addressed are the operation of an automated transition between GCM and SAM with the least disturbance to the nonlinear loads. The integration of a BES enables the SAM operation and improves the reliability of the PVBES. The charging and discharging of BES are controlled by using a dc–dc bidirectional converter. The performance of the implemented controls is tested using a real-time processor (dSPACE-1202) and validated through test results for steady state and dynamic conditions. In all operating conditions, the harmonics content of the grid current is maintained less than 5%, which follows the IEEE standard 519-2014. [ABSTRACT FROM AUTHOR]

For microgrids (MGs) owned by different utilities, it is always desirable that the steady state impact of load or generation changes in one MG, does not affect the generation cost in another MG. To ensure this, the power flow through the tie-line is typically regulated at a pre-scheduled value thereby enforcing the individual MGs to manage their respective load at steady state. To this end, this article presents a distributed control scheme to regulate tie-line power flow between two autonomous dc MG clusters. In this article, a unifying hierarchical control scheme based on distributed communication is proposed where the tie-line power flow control based on a pinning control strategy is unified with the distributed optimization and average voltage regulation control loops. The distributed optimization utilizes economic dispatch to minimize the operating costs of the DG, while the average voltage control regulates the MGs average voltage at its nominal value. With the application of this approach, the responsibility of tie-line regulation is distributed in an economic manner without degrading the voltage quality in the system. Time-domain simulations, real-time simulation using Ethernet-based transmission control protocol/internet protocol (TCP/IP) communication, and experimental results are presented to validate the performance of proposed distributed control under normal and faulty system conditions. [ABSTRACT FROM AUTHOR]

It is well-known that distributed control can improve the resiliency of dc microgrids against multiple link failures as compared to centralized control. However, the control layer is still vulnerable to cyber attacks. Unlike widely studied false data injection attacks, which involve adding false signals on top of the existing ones in the controller or communication links, hijacking attacks completely replace the existing signals. As a result, the compromised agent(s) diverge from steady state owing to imbalance in the iterative rule of consensus algorithm. To detect hijacking attacks, a novel distributed screening (DS) methodology is proposed. In addition to that, a fault detection (FD) metric is provided to assist the proposed attack detection strategy in differentiating between hijacking attacks and sensor faults. This reduces the complexity of decision making in the attack mitigation approach. Furthermore, interoperability of the proposed detection metrics allows simultaneous detection of sensor faults and hijacking attacks. The performance of the proposed detection metrics is evaluated under simulation and experimental conditions to conclude that it successfully detects the attacked agent(s) as well as sensor fault(s). [ABSTRACT FROM AUTHOR]

This paper proposes an extended Kalman filter (EKF) based control strategy for fault ride-through operation in two-stage grid-connected photovoltaic (GPV) system. Unlike the conventional controllers for ride-through operation, the proposed strategy does not compromise with power quality improvement features in the system while enabling ride-through operation. The controller accounts for nonlinear loads in the system, grid harmonic-currents elimination, and grid-currents balancing even during the harmonic/distorted grid voltages. The IEEE Standard-1547.4 compels the distributed resource to ride-through during voltage disturbances caused by faults. For the ride-through operation, a limit is imposed on PV active power injection to prevent inverter overcurrents and dc-link energy aggregation, which reduces the lifetime of dc-link capacitor. The reactive power is fed to the grid, as per the depth in voltage-sag. The derated PV array power is supplied in cases where the inverter cannot handle the utmost PV-power. The power quality improvement is ensured using EKF state estimator, which precisely estimates the fundamental load currents. In distribution network with modern nonlinear loads, especially at far radial ends, the grid voltages are prone to huge diversions and the proposed controller provides a possible solution to maintain active/reactive power support and maintain power quality in the network. The effectiveness of the strategy is demonstrated through simulations and experiments. Under all disturbances, the harmonic content in grid currents is observed within limits, in accordance with the IEEE Standard-519. [ABSTRACT FROM AUTHOR]

This paper presents optimal power flow management in real time for grid connected photovoltaic (PV)–battery system. The objective is the real time, dynamic and optimal scheduling of battery storage which reduces grid power consumption and achieves the peak load shaving. For this purpose, two strategies are developed; one is rule-based and other is optimization algorithm based. Two strategies are compared, pros and cons of those strategies are established. Though rule-based technique is simple & easy to implement, the optimization technique provides more optimal regulation of battery which provides the lesser electricity cost. Forecasted PV/load powers are used to get optimal value of battery power. In order to handle uncertainties due to forecasted data, fuzzy-based corrective strategy is developed to modify the reference battery power as per the present values of PV/load powers. The proposed analysis is carried out for over one exemplary day. The simulations are presented using typical load/PV data of India and Finland as a part of research collaboration. Experimental results are also carried out using proposed scheme. [ABSTRACT FROM AUTHOR]

Oscillatory instability in modern power system has increased due to increasing complexity and integration of dynamic loads. Stability analysis of such interconnected power system is very prominent in the presence of uncertain load/generation. In this paper, a power system stabilizer (PSS) design approach, which aims at enhancing the oscillatory stability of the multi-machine power system over the specified uncertainty range in forecasted load/generation, is presented. With non-statistical uncertainty, problem of selecting design parameters of the PSS is formulated as an optimization problem with minimization of eigenvalues and damping ratios based multi-objective function. In order to account the non-statistical uncertainties, a boundary active power loss (BAPL) based objective function is proposed. This non-linear BAPL objective function is minimized for determining the optimal setting of the generators voltage and taps of the online tap changing transformers (OLTC) under various power system constraints. In this paper, both the objective functions are solved by a new metaheuristic technique known as gray wolf optimization (GWO). Boundary value-based approach is used to minimize the repeated load flows under uncertain load/generation scenarios. Improved small-signal stability (SSS) is achieved with optimal active power loss of uncertain power system. Eigenvalue and time domain analysis for New England system are carried out under wide range of disturbances to demonstrate the potential of the proposed approach. [ABSTRACT FROM AUTHOR]

DC distribution networks and micro grids are gaining importance enabling the integration of hybrid distributed generation, energy storage units, modern loads including electric vehicles and different micro grid topologies, thus permitting the consequent development of DC Distribution Systems (DCDS). For maximum utilization of distribution network without compromising the security and reliability of the supply system, determination of critical loading is crucial. With this objective, this paper proposes a modified DC continuation power flow based approach for determining the loadability limit of the active DCDS. DC-DC converters play an important role in bus voltage regulation and system loadability. Impact of these converters must be accounted in any analysis and planning of active DCDS. In this paper, two different mathematical models of lossless DC-DC converters are developed to account them in power flow model of the system. The proposed approach can be applied to both radial and meshed DCDS. Impacts of integration of converters in the system are illustrated by results of two realistic DCDS and results are compared with the corresponding AC Distribution Systems (ACDS). [ABSTRACT FROM AUTHOR]

The active power distribution network operation with the integration of various renewable distributed generations (DGs), storage units, and dynamic loads are attracting a lot of interest due to substantial benefits in maximizing the penetration of available renewable energy resources (RES). However, the risk of voltage violation in the active distribution system (ADS) is exacerbated due to increasing penetration of DGs. It has become a bottleneck to maximize the DG penetration into the system. This bottleneck can be handled by effective voltage regulation and reactive power support into ADS. Nowadays, power electronic devices are frequently used for voltage and reactive power support over the conventional approaches. In this paper, an approach to maximize the penetration of RES, such as solar, wind, etc., into ADS by maximum utilization of existing solar photovoltaic inverters (SPVI) in the system is presented. Optimal utilization of SPVI may enhance the voltage stability of the ADS and wind power penetration into the system. The proposed SPVI control approaches are depended on active power generation of solar photovoltaic (SPVG), rating and capability of SPVI, and required reactive power in the ADS. In this paper, the problem of maximum penetration of RES is formulated as an optimal power flow embedded nonlinear optimization problem subject to the physical limitations of the SPVI. The results of the analysis performed on an IEEE 33 bus system show that the proposed SPVI control strategies can improve the voltage profile of the ADS with minimization of curtailment of wind power generation. [ABSTRACT FROM AUTHOR]

Highlights • Distributed secondary energy management of DC microgrids is developed. • Stable performance during communication delay and link failure is ensured. • Reverse droop methodology is used to enhance the controller’s dynamic performance. • Maximum allowable transmission delay is determined to observe system’s stability. Abstract As link failure in a centralized network results into unstable behavior, the distributed control mechanism is often employed since the reliability and stability is enhanced by communicating with the neighbors thereby reducing the infrastructural cost required for communication. However, such compromised spanning loosely connected networks may sometimes lead to slow convergence or may even go unstable. Under such circumstances, it is essential to incorporate fast convergence speed using limited information for each controller to enhance operational reliability. Hence, this paper proposes a distributed secondary controller for each unit comprising of PV & batteries to achieve average regulation within predefined bounds and proportionate current sharing between units in finite time for DC microgrids for uniform energy management in each unit. To conform to the containment control philosophy, the followers converge to the leaders’ command in finite-time. To alleviate the dynamic performance in a significantly resistive network, a reverse droop methodology is adopted concurrently to the proposed distributed secondary controller thereby eliminating the issue of cascaded control loops. A Lyapunov based analysis is carried out to analyze its stability for varying control parameters alongwith a bode plot analysis to determine its stability margins. In addition to this, a time-delay analysis is carried out to calculate the maximum transmission delay that the controllers can withstand to maintain stability. To test the robustness of the designed controller, it is simulated for disturbances such as load change, communication delay, converter failure, link failure between leader-follower & two followers. Moreover, the real-time simulation using software-in-loop of the modeled system is also done to test the efficacy of the proposed strategy. [ABSTRACT FROM AUTHOR]

This paper proposes a repetitive learning-based phase locked loop (RLPLL) to improve power quality of the grid-connected dc microgrids under distorted grid voltage in a weak grid. The harmonic component present in grid current in a high impedance network amplifies the distortion in voltage, which often leads to instability. Since the behavior of the conventional synchronous reference frame PLL (SRF-PLL) varies, owing to the proportional-integral gains constrained to harmonic rejection bandwidth ultimately leading to a sluggish response. However, RLPLL accommodates this limitation with a comparable dynamic performance and enhanced harmonic attenuation properties. This has been achieved by using a Lyapunov-based approach for harmonic estimation, which facilitates the periodicity and boundedness of the harmonic component to obtain an adaptive learning-based update. To deal with the computational burden, this paper also provides a low-computing alternative model of the proposed strategy. The dynamic response of RLPLL along with a comparative analysis with SRF-PLL is governed by many events directly affecting the dc voltage, which is critical for the operation of dc microgrids. Its performance is validated under different scenarios in a 1-kVA field programmable gate array-based experimental setup. [ABSTRACT FROM AUTHOR]

Eigenvalue analysis is a very essential technique for power system small‐signal stability (SSS) determination. Uncertainties in load/generation forecast are very common in power systems due to its geographical spread, size and complexity. These uncertainties can be divided into two types: (a) statistical (b) non‐statistical. It is observed from the literature that the effects of non‐statistical uncertainties in eigenvalue analysis are discussed comparatively less. In this study, a boundary eigenvalue analysis is developed based on boundary power flow to handle the non‐statistical uncertainties in loads and solar photovoltaic generation (SPVG) forecasts. First, mathematical model for evaluation of boundary of the critical eigenvalues for SSS analysis of dynamic power system (DPS) is developed. Then, the upper/lower boundary of a particular eigenvalue for a given range of uncertainties in load/SPVG at various buses is investigated. The boundary eigenvalue analysis predicts the worst‐case scenario for a given range of uncertainty in forecasted data which may help for secure operation of DPS. Second, Hopf bifurcations which may lead in highly stressed DPS is evaluated with increasing load/generation in the system in the presence of non‐statistical uncertainties. Results for two standard test systems are taken to demonstrate the potential of the proposed approach. [ABSTRACT FROM AUTHOR]

This article presents an adaptive control algorithm for power quality enhancement of a synchronous reluctance generator based stand-alone generator system with a battery energy storage system by employing the compensation capabilities of a voltage source converter. The proposed synchronous reluctance generator system is implemented using a 3.75-kW synchronous reluctance generator, a voltage source converter with a battery support, and a digital signal processor. The control algorithm is used for estimation of reference currents keeping in view the limited rating of the voltage source converter. A modified leaky least mean square algorithm using a variable-step–variable-weight factor is proposed for the control. The variable-step–variable-weight least mean square algorithm decomposes the load currents, extracts its real positive-sequence component to track the unit vectors by varying the rate of convergence of the algorithm, and accordingly tunes the weights, thus enabling selective compensation. The proposed control algorithm offers satisfactory harmonics mitigation, compensation of reactive power demand, and load balancing of a stand-alone synchronous reluctance generator system under linear/non-linear and dynamic loads. [ABSTRACT FROM AUTHOR]

Developing a robust and reliable high-voltage (HV) pulse power system (PPS) is essential for the characterization and testing of microwave tubes and industrial applications. This paper presents the design, simulation, and implementation of a modular and versatile high-voltage pulse power supply used in microwave device characterization and testing. A microcontroller-based digitally controlled pulse generation unit is also developed to generate the trigger pulses for high-voltage switching modules to control the turn-ON and turn-OFF of the switching devices. The digitally controlled pulse generation unit provides better resolution of pulse width, pulse repetition frequency, and system protection over the entire range of operations. The pulse generation and control circuit controls the pulse repetition frequency (PRF) and pulse wide (PW). The PRF and PW can be varied from 100 to 1000 Hz and 10 to 100 µs, respectively. The experimental prototype with ten series-connected high-voltage modules is connected to achieve a 25 kV pulsed output voltage. The experimental results of HV-PPS on a resistive dummy load and 5 GHz klystron tube are presented in this work. [ABSTRACT FROM AUTHOR]