Showing papers by "Sanjeevikumar Padmanaban published in 2021"
TL;DR: The proposed SCMLI topology consists of nine power semiconductor switches with one dc voltage source and two capacitors, capable of generating a nine-level output voltage waveform with twice voltage gain and a selective harmonic elimination pulsewidth modulation technique is applied.
Abstract: Multilevel inverter (MLI) topologies play a crucial role in the dc–ac power conversion due to their high-quality performance and efficiency. This article aims to propose a new switched-capacitor-based boost multilevel inverter topology (SCMLI). The proposed topology consists of nine power semiconductor switches with one dc voltage source and two capacitors, capable of generating a nine-level output voltage waveform with twice voltage gain. With the addition of two switches, the proposed topology can be used for higher voltage-gain applications. Other features of the proposed topology include the self-voltage balancing of the capacitors, parallel operation of the capacitors, lower voltage stress across the switches, along with the inherent polarity changing capability. To obtain the high-quality output waveform, a selective harmonic elimination pulsewidth modulation technique is applied. In this technique, the detrimental low-order harmonics can easily be regulated and eliminated from the output voltage of MLI. The proposed topology is compared with the recently introduced SCMLI topologies considering various parameters to set the benchmark of the proposed topology. The performance of the proposed MLI is investigated through various experimental results using a laboratory prototype setup.
97 citations
TL;DR: In this paper, the authors proposed a hybrid Cascaded H-bridge multilevel inverter with reduced components topology, which is a blend of a single-phase T-Type inverter and an H-Bridge module made of sub switches.
Abstract: The multilevel inverters (MLI) are resourceful in producing a voltage waveform with superior-quality staircase counterfeit sinusoidal and depressed harmonic distortion (THD). Several conventional topologies are proposed to realize the MLI however, the limitations of these topologies may involve more DC sources and power-switching devices, and less THD, which in turn, increases the cost and size of the inverter. These drawbacks can be eliminated with the proposed hybrid Cascaded H-Bridge Multilevel Inverter with reduced components topology. As compared with the established MLI topologies the recommended topology having a reduced number of DC sources, power-switching devices, component count level factor, lesser TSV, more efficient, lesser THD, and cost-effective. The proposed MLI is a blend of a single-phase T-Type inverter and an H-Bridge module made of sub switches. This article incorporates the design and simulation of the multilevel inverter with staircase PWM technique. Further, the 9-level and 17-level MLI is examined with different combinational loads. The proposed inverter is stable during nonlinear loads, and it is well suited for FACTS and renewable energy grid-connected applications. An operational guideline has been explained with correct figures and tables. The Output voltage wave is realized in numerical simulation. Finally, the experimental demonstrations were performed by implementing a hardware prototype setup for both linear and nonlinear loads using the dSPACE controller laboratory.
72 citations
TL;DR: The result proves that the proposed P&O MPPT technique can track the MPP accurately under various operating conditions and is enhanced by including the change in current, in addition to the changes in output voltage and output power of the PV module.
Abstract: The primary concerns in the practical photovoltaic (PV) system are the power reduction due to the change in operating conditions, such as the temperature or irradiance, the high computation burden due to the modern maximum power point tracking (MPPT) mechanisms, and to maximize the PV array output during the rapid change in weather conditions. The conventional perturb and observation (P&O) technique is preferred in most of the PV systems. Nevertheless, it undergoes false tracking of maximum power point (MPP) during the rapid change in solar insolation due to the wrong decision in the duty cycle. To avoid the computational burden and drift effect, this article presents a simple and enhanced P&O MPPT technique. The proposed technique is enhanced by including the change in current ( dI ), in addition to the changes in output voltage and output power of the PV module. The effect of including the dI profile with the traditional method is explained with the fixed and variable step-size methods. The mathematical expression for the drift-free condition is derived. The traditional boost converter is considered for validating the effectiveness of the proposed methods by employing the direct duty cycle technique. The proposed algorithm is simulated using MATLAB/Simulink and validated under various scenarios with the developed laboratory prototype in terms of drift-free characteristics and tracking efficiency. The result proves that the proposed technique can track the MPP accurately under various operating conditions.
72 citations
TL;DR: In this paper, a recurrent neural network-based Long Short-Term Memory (LSTM) approach was proposed to detect high impedance fault (HIF) in solar photovoltaic (PV) integrated power system.
Abstract: This paper presents the detection of High Impedance Fault (HIF) in solar Photovoltaic (PV) integrated power system using recurrent neural network-based Long Short-Term Memory (LSTM) approach. For study this, an IEEE 13-bus system was modeled in MATLAB/Simulink environment to integrate 300 kW solar PV systems for analysis. Initially, the three-phase current signal during non-faulty (regular operation, capacitor switching, load switching, transformer inrush current) and faulty (HIF, symmetrical and unsymmetrical fault) conditions were used for extraction of features. The signal processing technique of Discrete Wavelet Transform with db4 mother wavelet was applied to extract each phase’s energy value features for training and testing the classifiers. The proposed LSTM classifier gives the overall classification accuracy of 91.21% with a success rate of 92.42 % in identifying HIF in PV integrated power network. The prediction results obtained from the proffered method are compared with other well-known classifiers of K-Nearest neighbor’s network, Support vector machine, J48 based decision tree, and Naive Bayes approach. Further, the classifier’s robustness is validated by evaluating the performance indices (PI) of kappa statistic, precision, recall, and F-measure. The results obtained reveal that the proposed LSTM network significantly outperforms all PI compared to other techniques.
65 citations
TL;DR: Inverters in microgrids face significant challenges during their parallel operations, such as accurate power sharing, deviations in system voltage magnitude and frequency, and imbalance between generation and load demand, so centralized and distributed control techniques at the secondary control layer are needed.
Abstract: Inverters in microgrids (MGs) face significant challenges during their parallel operations, such as accurate power sharing, deviations in system voltage magnitude and frequency, and imbalance between generation and load demand. To solve these technoeconomic challenges, hierarchical control structures are implemented in MGs. The structure consists of three layers as primary, secondary, and tertiary controls. The control approach can be either communication-based or communication-less at the various layers. The use of communication at primary and secondary layers faces problems, such as communication latency, data drop-up, and expense issues. On the other hand, improved decentralized control techniques being communication-less can avoid the disadvantages of using communication. This article presents an insight into the limitations with the communication-based approach by briefing about the centralized and distributed control techniques at the secondary control layer. Subsequently, the communication-less control techniques and algorithms to achieve accurate power sharing along with the restoration of MG voltage and frequency are described. A comparison among different decentralized droop-based power sharing methods in the primary control layer is done based on review and simulations. In addition, improved communication-less secondary restoration techniques are explained. Finally, future research directions in these areas are listed, aiming to improve the reviewed techniques.
37 citations
TL;DR: In this paper, a taxonomy of authentication schemes in VANETs has been presented, and the authentication schemes have been compared with security, privacy and scalability requirement with the use of recent technologies such as 5G, 5G-SDN, and Blockchain.
Abstract: Vehicular ad-hoc network (VANET) has been gaining importance due to the fast growing technology as well as its requirements in intelligent transportation systems (ITS) and vehicular social network (VSN). VANET facilitates vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) communication and improves the ride quality with value added services. The number of connected vehicles is expected to grow to a huge number with enormous exchange of safety and non-safety messages which are susceptible to security and privacy threat. To ensure secured communication, VANET must implement an authentication protocol to resist the attack and preserve the privacy. In this paper, a detailed discussion on the taxonomy for authentication schemes in VANET has been presented. The authentication schemes have been compared with security, privacy and scalability requirement. The use of recent technologies such as 5G, 5G-SDN, and Blockchain to design authentication schemes with low cost, and low communication, computational overhead has been discussed. Finally, the paper concludes with open challenges in VANET authentication. This paper is expected to open new avenues for researchers working in the domain of VANETs.
37 citations
TL;DR: In this article, a novel asymmetric 21-level multilevel inverter topology for solar PV application is presented, where the PV voltage is boosted over the DC link voltage using a three-level DC-DC boost converter interfaced in between the solar panels and the inverter.
Abstract: This article presents a novel asymmetrical 21-level multilevel inverter topology for solar PV application. The proposed topology achieves 21-level output voltage without H-bridge using asymmetric DC sources. This reduces the devices, cost and size. The PV standalone system needs a constant DC voltage magnitude from the solar panels, maximum power point tracking (MPPT) technique used for getting a stable output by using perturb and observe (P&O) algorithm. The PV voltage is boosted over the DC link voltage using a three-level DC-DC boost converter interfaced in between the solar panels and the inverter. The inverter is tested experimentally with various combinational loads and under dynamic load variations with sudden load disturbances. Total standing voltage with a cost function for the proposed MLI is calculated and compared with multiple topologies published recently and found to be cost-effective. A detailed comparison is made in terms of switches count, and sources count, gate driver boards, the number of diodes and capacitor count and component count level factor with the same and other levels of multilevel inverter and found to be the proposed topology is helpful in terms of its less TSV value, devices count, efficient and cost-effective. In both simulation and experimental results, total harmonic distortion (THD) is observed to be the same and is lower than 5% which is under IEEE standards. A hardware prototype is implemented in the laboratory and verified experimentally under dynamic load variations, whereas the simulations are done in MATLAB/Simulink.
32 citations
TL;DR: In this article, a new mechanism to detect injection of any false data in AC-SE based on signal processing technique is proposed, which is based on analyzing temporally consecutive system states via wavelet singular entropy (WSE).
Abstract: Since Smart-Islands (SIs) with advanced cyber-infrastructure are incredibly vulnerable to cyber-attacks, increasing attention needs to be applied to their cyber-security. False data injection attacks (FDIAs) by manipulating measurements may cause wrong state estimation (SE) solutions or interfere with the central control system performance. There is a possibility that conventional attack detection methods do not detect many cyber-attacks; hence, system operation can interfere. Research works are more focused on detecting cyber-attacks that target DC-SE; however, due to more widely uses of AC SIs, investigation on cyber-attack detection in AC systems is more crucial. In these regards, a new mechanism to detect injection of any false data in AC-SE based on signal processing technique is proposed in this paper. Malicious data injection in the state vectors may cause deviation of their temporal and spatial data correlations from their ordinary operation. The suggested detection method is based on analyzing temporally consecutive system states via wavelet singular entropy (WSE). In this method, to adjust singular value matrices and wavelet transforms’ detailed coefficients, switching surface based on sliding mode controller are decomposed; then, by applying the stochastic process, expected entropy values are calculated. Indices are characterized based on the WSE in switching level of current and voltage for cyber-attack detection. The proposed detection method is applied to different case studies to detect cyber-attacks with various types of false data injection, such as amplitude, and vector deviation signals. The simulation results confirm the high-performance capability of the proposed FDIA detection method. This detection method’s significant characteristic is its ability in fast detection (10 ms from the attack initiation); besides, this technique can achieve an accuracy rate of over 96.5%.
31 citations
TL;DR: In this article, the authors presented a novel topology for the single-phase 31-level asymmetrical multilevel inverter accomplished with reduced components count, which can be used for renewable energy applications.
Abstract: This paper presents a novel topology for the single-phase 31-level asymmetrical multilevel inverter accomplished with reduced components count. The proposed topology generates maximum 31-level output voltage with asymmetric DC sources with an H-bridge. The fundamental 13-level multilevel inverter (MLI) topology is realized, and further, the topology is developed for 31-level can be used for renewable energy applications. This reduces the overall components count, cost and size of the system. Rather than the many advantages of MLIs, reliability issues play a significant role due to higher components count to reduce THD. This is a vital challenge for the researchers to increase the reliability with less THD. Several parameters are analyzed for both fundamental 13-level and developed 31-level MLIs such as total standing voltage (TSV), cost function (CF) and power loss. The inverter is tested experimentally with various combinational loads and under dynamic load variations with sudden load disturbances. Total standing voltage with the cost function for the proposed MLI is compared with various topologies published recently and is cost-effective. A detailed comparison of several parameters with graphical representation is made. Less TSV and components requirement is observed for the proposed MLI. The obtained total harmonic distortion (THD) is under IEEE standards. The topology is simulated in MATLAB/Simulink and verified experimentally with a hardware prototype under various conditions.
30 citations
TL;DR: In this article, a new solar PV fed Dynamic Voltage Restorer (DVR) based on Trans-Z-source Inverter (TransZSI) is proposed to improve the power quality of on-grid photovoltaic (PV) systems.
Abstract: In this article, a new solar PV fed Dynamic Voltage Restorer (DVR) based on Trans-Z-source Inverter (TransZSI) is proposed to improve the power quality of on-grid Photovoltaic (PV) systems. DVR is a power electronic compensator using for injecting the desired voltage to the Point of Common Coupling (PCC) as per the voltage disturbance. In the proposed DVR, in place of traditional VSI, TransZSI with outstanding merits of buck/boost, a broader range of voltage boost gain, fewer passive components, and lower voltage stress, is put forth. For efficient detection, accurate voltage disturbances mitigation, and also lessening the injected voltage harmonics, a hybrid Unit Vector Template with Maximum Constant Boost Control (UVT-MCBC) method is proposed for TransZSI-DVR. The performance of the proposed TransZSI-DVR with UVT-MCBC has been analyzed under severe sag, slight sag with harmonics, swell, and interruption. The comparative studies and simulation results have shown the effectiveness of the proposed TransZSI-DVR, as opposed to traditional ZSI-DVR and VSI-DVR. The TransZSI-DVR in the PV system has mitigated voltage sag/swell/interruption. It has also improved the power quality of both the injected voltage to the PCC and PV system’s output voltage.
28 citations
TL;DR: In this paper, the authors proposed an optimal solution for simultaneously allocating the feeder routing issue and substation facilities and finding the models of installed conductors and economic hardening of power lines due to unexpected physical attacks on vital urban operational infrastructure.
Abstract: Unexpected natural disasters or physical attacks can have various consequences, including extensive and prolonged blackouts on power systems. Energy systems should be resistant to unwanted events, and their performance is not easily affected by such conditions. The power system should also have sufficient flexibility to adapt to severe disturbances without losing its full version; it should restore itself immediately after resolving the disturbance. This critical feature of the behavior of infrastructure systems in power grids is called resilience. In this paper, the concepts related to resilience in the power system against severe disturbance are explained. The resilience and evaluation process components are introduced; then, an optimal design of resilient substations in the Noorabad city distribution grid against physical attack is presented. This research proposes an optimal solution for simultaneously allocating the feeder routing issue and substation facilities and finding the models of installed conductors and economic hardening of power lines due to unexpected physical attacks on vital urban operational infrastructure. The values of distribution networks are calculated using the grey wolf optimization (GWO) algorithm to solve the problem of designing an optimal distribution network scheme (ODNS) and optimal resilient distribution network scheme (ORDNS). Obtained results confirm the effectiveness of the proposed resiliency-cost-based optimization approach.
TL;DR: In this paper, a hybrid Artificial Neural Network - Newton Raphson (ANN-NR) is introduced to mitigate the undesired lower-order harmonic content in the cascaded H-bridge multilevel inverter for solar photovoltaic (PV).
Abstract: In this article, a hybrid Artificial Neural Network - Newton Raphson (ANN-NR) is introduced to mitigate the undesired lower-order harmonic content in the cascaded H-Bridge multilevel inverter for solar photovoltaic (PV). Harmonics are extracted by the excellent choice of opting switching angles by exploiting the Selective Harmonic Elimination (SHE) PWM technique accompanying a unified algorithm in order to optimize and reduce the Total Harmonic Distortion (THD). ANN is trained with optimum switching angles, and the estimates generated by the ANN are the initial guess for NR. In this study, the CHB-MLI is combined with a traditional boost converter, it boosts the PV voltage to a superior dc-link voltage Perturb and Observe (P&O) based Maximum Power Point Tracking (MPPT) algorithm is used for getting a stable output and efficient operation of solar PV. The proposed system is proved over an eleven-level H-bridge inverter, the work is carried out in MATLAB/Simulink environment, and the respective results are confirmed that the proposed technique is efficient, and offers an actual firing angles with a few iterations results in a better capability of confronting local optima values. The suggested algorithm is justified by the experimental development of eleven-level cascaded H-bridge inverter.
TL;DR: The proposed algorithm proved to be successful for detecting different PQ disturbances under all the investigated operating conditions and will help to enhance the SE integration level into the utility grid.
Abstract: Enhancement in solar energy (SE) injection into the power system network creates power quality (PQ) issues in the supply. This article presents an approach supported by Stockwell transform ( $S$ -transform) for assessment of PQ issues related with the grid interfaced solar photovoltaic (SPV) system under various operating conditions. This will help to enhance the SE integration level into the utility grid. The set up, to perform assessment of the PQ issues includes an emulated SPV system interfaced with the utility at the point of common coupling (PCC). Measurements of voltage and current signals are performed by utilizing power network analyzer. The captured voltage signals are analyzed using $S$ -transform for the detection of a variety of PQ problems associated with the grid interfacing and outage of the SPV system. Effects on PQ due to presence of the various types of loads at PCC have also been investigated under the same operating conditions. Effect of partial shading of SPV plates on the PQ is also investigated. Harmonic analysis is performed for all the investigated events. The proposed algorithm proved to be successful for detecting different PQ disturbances under all the investigated operating conditions.
TL;DR: Comparative analysis with state-of-the-art MLIs in terms of the number of components, voltage stress, and cost factor demonstrate the merit of the proposed extendable SC MLIs.
Abstract: Multilevel inverters (MLIs) with self-balanced switched-capacitors (SC) have received wide recognition for increasing the reliability and efficiency of renewable energy and high-frequency power distribution systems. This article presents a new SC MLI structure using a reduced number of components. The proposed dual-source SC MLI can be extended in various ways to increase the voltage levels at the output. The SCs are self-balanced by using a suitable charging–discharging pattern, and thereby, voltage boosting is achieved. The operational analysis and features of the proposed 25-level MLI are delineated in detail. Comparative analysis with state-of-the-art MLIs in terms of the number of components, voltage stress, and cost factor demonstrate the merit of the proposed extendable SC MLIs. Extensive simulation of the proposed MLI structure is performed on the MATLAB/Simulink environment using both the low and high switching frequency control schemes. Furthermore, simulation results are validated experimentally by developing a prototype of the proposed MLI under load variations, frequency change condition, and variation in the modulation index.
TL;DR: In this article, a Wavelet-Alienation-Neural (WAN) technique was developed for the fault analysis of Unified Power Flow Controller (UPFC) compensated transmission network, where the detection and classification of various outages are accomplished by alienation of wavelet based approximate coefficients computed from current signals.
Abstract: Fault analysis (detection, classification and location) of transmission network is of great importance in power system. A Wavelet-Alienation-Neural (WAN) technique has been developed for the fault analysis of Unified Power Flow Controller (UPFC) compensated transmission network. The detection and classification of various outages are accomplished by alienation of wavelet based approximate coefficients computed from current signals. The precise location of faults is carried out by an Artificial Neural Network fed from estimated approximate coefficients computed from voltage and current signals of the same quarter cycle. The robustness of the algorithm is proved with the case studies of varying fault locations, sampling frequency, system parameters, effects of noise, fault incipient angle, different control strategies and fault path impedances.
TL;DR: A comprehensive review of research published for solving the short-term hydrothermal scheduling problem in the last four decades is presented in this paper, where a number of research articles have been published addressing STHTS using different techniques.
Abstract: Short term hydrothermal scheduling (STHTS) is a non-linear, multi-modal and very complex constrained optimization problem which has been solved using several conventional and modern metaheuristic optimization algorithms A number of research articles have been published addressing STHTS using different techniques This article presents a comprehensive review of research published for solving the STHTS problem in the last four decades
TL;DR: In this paper, a new single-phase 15-level inverter with a reduced number of components for the solar PV application is proposed, which can improve efficiency and reduce losses, cost, and complexity of the overall system.
Abstract: A new single-phase 15-level inverter with a reduced number of components for the Solar PV application is proposed in this paper. It is incorporate the proposed inverter with a boost converter to extract energy from the solar PV modules, the proposed inverter aids to generate fifteen stepped output voltage levels with lower THD. The proposed inverter can improve efficiency and reduce losses, cost, and complexity of the overall system. The conventional boost converter will boost the output voltage to a maximum voltage from Solar PV with MPPT(P&O). The proposed inverter is tested experimentally using the dSPACE RTI 1104 controller along with MATLAB/Simulink. A detailed comparison with existing MLIs with the proposed inverter. The work presents experimental results not only to show its efficiency but also to the effectiveness under different circumstances of linear and non-linear loads. The inverter is stable during the non-linear loads and well suits for grid-connected systems.
TL;DR: In this article, the authors proposed a 53-Level multilevel inverter topology based on a switched capacitor (SC) approach, where the SC cells are cascaded for implementing 17 and 33 levels of the output voltage.
Abstract: The efficient and compact design of multilevel inverters (MLI) motivates in various applications such as solar PV and electric vehicles (EV). This paper proposes a 53-Level multilevel inverter topology based on a switched capacitor (SC) approach. The number of levels of MLI is designed based on the cascade connection of the number of SC cells. The SC cells are cascaded for implementing 17 and 33 levels of the output voltage. The proposed structure is straightforward and easy to implement for the higher levels. As the number of active switches is less, the driver circuits are reduced. This reduces the device count, cost, and size of the MLI. The solar panels, along with a perturb and observe (P&O) algorithm, provide a stable DC voltage and is boosted over the DC link voltage using a single input and multi-output converter (SIMO). The proposed inverters are tested experimentally under dynamic load variations with sudden load disturbances. This represents an electric vehicle moving on various road conditions. A detailed comparison is made in terms of switches count, gate driver boards, sources count, the number of diodes and capacitor count, and component count factor. For the 17-level, 33-level, and 53-level MLI, simulation results are verified with experimental results, and total harmonic distortion (THD) is observed to be the same and is lower than 5% which is under IEEE standards. A hardware prototype is implemented in the laboratory and verified experimentally under dynamic load variations, whereas the simulations are done in MATLAB/Simulink.
TL;DR: In this paper, the authors proposed multi-update position criteria to enhance the exploration properties of the conventional firefly technique while including the effect of the global best solution on the movement of the fireflies in the search space of the objective function.
Abstract: The absence of the global best component in the update equation of the conventional firefly algorithm degrades its exploration properties. This research proposes multi-update position criteria to enhance the exploration properties of the conventional firefly technique while including the effect of the global best solution on the movement of the fireflies in the search space of the objective function. Moreover, the dynamic search space squeezing is applied to constrict the movement of the fireflies within the certain limits to avoid their oscillatory movement as the solution approaches towards the global best by determining the optimal trajectory for each firefly. The robustness of the suggested firefly algorithm is tested on a hybrid energy system consisting of thermal, hydroelectric, and Photovoltaic (PV) energy source. The intermittent nature of the PV energy source is explained using fractional integral polynomial model and Auto Regressive Integrated Moving Average (ARIMA) model. The main dispatch problem is successfully computed using both the modified firefly and the simple firefly algorithm by determining the optimal power share of each energy source for different scheduling intervals. The suggested operational strategy reduces the overall generation cost of the system while preserving the various system constraints. Due to the stochastic nature of the meta-heuristic techniques, the two suggested algorithms are compared statistically for different test cases using the independent t-test results. The statistical comparison suggests that the performance of the modified firefly is superior to its conventional counterpart as the evaluation parameters of the modified firefly converge to relatively lower value as compared to the parameters of the simple firefly algorithm.
DOI•
29 Nov 2021
TL;DR: In this paper, the role of power electronics converters in an electric vehicle is elaborated and the existing bidirectional DC-DC converter topologies are discussed with a comprehensive review, comparison and application.
Abstract: Today, the Internal Combustion Engine (ICE) is gradually being replaced by electric motors which result in higher efficiency and low emission of greenhouse gases. The electric vehicle either works wholly or partially on electrical energy like battery and ultra-capacitor. The battery or ultra-capacitor is either charged from the AC supply connected to a grid line in a plug-in electric vehicle or from ICE in the hybrid electric vehicle. Alternatively, the battery charges from traction motor by regenerative braking. In the reverse direction, the energy from battery or ultra-capacitor is injected into the AC grid line in the plug-in electric vehicle. Power electronic converters play a vital role in the conversion process from grid line to traction motor and in the reverse direction. In this paper, the role of power electronics converters in an electric vehicle is elaborated. The bidirectional DC-DC converter plays a vital role in the power conversion process of electric vehicles. The existing bidirectional DC-DC converter topologies are discussed with a comprehensive review, comparison and application. Additionally, the advancement in power electronics converters to improve the efficiency and reliability of the vehicular system is elaborated.
14 Jan 2021
TL;DR: In this article, a custom power device known as dynamic voltage restorer (DVR) has been investigated to operate a distribution system at its desired performance, which has been controlled using optimized proportional and integral (PI) gains integrated with gradient adaptive variable learning rate least mean square control algorithm.
Abstract: A custom power device known as dynamic voltage restorer (DVR) has been investigated to operate a distribution system at its desired performance. The distribution system with voltage-related power quality issues in the supply side has been addressed through this article using DVR. Four different grid disturbances, such as voltage sag, swell, unbalances, and distortions, have been taken into account while testing the DVR capability. DVR has been controlled using optimized proportional and integral (PI) gains integrated with gradient adaptive variable learning rate least mean square control algorithm. Adaptiveness of variable step-size in LMS makes the control robust in case of dynamics in the system, which assures better performance. Also, the other major contribution of this article is the implementation of optimization-based self-tuning PI gains in the proposed control. The evaluation of optimizer in estimating the PI gains is presented in terms of the response of dc-link voltage DVR. The simulation work of proposed control algorithms on DVR has been done and satisfactory results are found. For the experimental validation, d-SPACE made Micro Lab Box is used as control processor, and both dynamic and steady-state results are discussed for its effectiveness.
TL;DR: The modeling results in terms of uncertainties in the system indicate that the use of load management along with PVCS design and flexible electric vehicle charge control strategies improves power quality parameters and optimizes system cost over a period of 10 years.
Abstract: Photovoltaic charging stations (PVCSs) are one of the most important pieces of charging equipment for electric vehicles (EVs). Recently, the process of designing solar charging stations as flexible sources has been growing and developing. This paper presents a relatively complete design of a solar charging station as a flexible economic resource in a 10-year planning horizon based on a genetic algorithm in two scenarios. PVCSs are not considered in the first scenario. This scenario is only to confirm the results, and the proposed method is proposed. However, in the second scenario, the effects of PVCSs and the demand response strategy (DR) on this development are considered. Copula probability distribution functions are used to create appropriate scenarios for vehicles during different planning years. The proposed energy management system shows a stable performance in terms of the annual load growth index and electricity price of each level of demand over the time horizon along with minimizing power losses and costs required, which makes PVCS efficiency higher and gives them a suitable structure and stability. The modeling results in terms of uncertainties in the system indicate that the use of load management along with PVCS design and flexible electric vehicle charge control strategies improves power quality parameters and optimizes system cost over a period of 10 years. Compared to the obtained results with the traditional case, it is observed that long-term planning in terms of DR and PVCSs and the technical specifications of the network have been improved. As a result of this proposed long-term planning, PVCSs are more flexible.
TL;DR: In this paper, an improved version of particle swarm optimization (PSO) algorithm, known as Accelerated Particle Swarm Optimization (APSO), was proposed for solving short-term hydrothermal scheduling (STHTS) problems.
Abstract: Short-term hydrothermal scheduling (STHTS) is a highly non-linear, multi-model, non-convex, and multi-dimensional optimization problem that has been worked upon for about 5 decades. Many research articles have been published in solving different test cases of STHTS problem, while establishing the superiority of one type of optimization algorithm over the type, in finding the near global best solution of these complex problems. This paper presents the implementation of an improved version of a variant of the Particle Swarm Optimization algorithm (PSO), known as Accelerated Particle Swarm Optimization (APSO) on three benchmark test cases of STHTS problems. The adaptive and variable nature of the local and global search coefficients for the proposed APSO significantly improve its performance in obtaining the optimal solution for the STHTS test cases. Two of these cases are non-cascaded cases of STHTS problem (NCSTHTS) and one case is cascaded case of STHTS problem (CSTHTS). The results are compared with the results of the previous implementations of the other algorithms as presented in the literature. Due to the stochastic nature of the meta-heuristic algorithms, the parametric and non-parametric statistical tests have been implemented to establish the superiority of results of one type of algorithm over the results of the other type of algorithms.
TL;DR: In this paper, a genetic optimization algorithm (GOA) approach which integrated the Steepest Descend Technique (SDT) is proposed and enhanced based on the features of the mentioned issue to sketch the optimal location and control of automatic and manual cross-section switches and protection relay systems in distribution power systems.
Abstract: Automation in power distribution systems and supervisory control and data acquisition (SCADA), which perform network switching automatically and remotely, allows distribution companies to flexibly control distribution power grids. Cross-section switches also has a significant role in the automation in distribution systems, in that the operational optimization of these switches is able to enhance the supply power quality and reliability indicators, and can be a prosperous solution to increase the reliability, efficiency and overall service quality in services to customers. In this regard, in this work, the genetic optimization algorithm (GOA) approach which integrated the Steepest Descend Technique (SDT) is proposed and enhanced based on the features of the mentioned issue to sketch the optimal location and control of automatic and manual cross-section switches and protection relay systems in distribution power systems. The GOA is able to search globally that can prevent the result from locally convergence, also, GOA gives superior primary solutions for the SDT. Thus, the SDT can search locally with higher performance which increase the solutions’ accuracy. Therefore, an optimization formulation is proposed to improve the value-based reliability of the suggested layout considering the cost of customer downtime and the costs related to segmentation of switches and relay protection devices. Also, a distributed generation (DG) system in distribution networks is considered based on the islanded state of generation units. The effectiveness of the optimal suggested procedure is evaluated and represented via performing a practical test system in the distribution network of Ahvaz city in Iran. The results show that using proposed method and by optimally allocating switches maneuver, energy losses without switches are reduced from 310.17 (MWh) to 254.2 (MWh), and also by using DG, losses are reduced from 554.01 to 533.61 which confirms the ability and higher accuracy of the proposed method to improve reliability indices.
TL;DR: In this paper, two hybrid meta-heuristic algorithms were proposed to improve the maximum power point tracking technique of partially shaded photovoltaic systems, which is based on the Whale Optimization Algorithm and Differential Evolution algorithms.
TL;DR: In this paper, a GA-based optimization method is used to select a specific system-on-chip (SoC) architecture for heterogeneous IoT applications, which is implemented in MATLAB to identify the optimized SoC architecture concerning device parameters such as a clock, cache, RAM space, external storage, network support, etc.
Abstract: The Internet of Things (IoT) refers to a network of physical devices, which collects data and processes into a system without human intervention In the commercialized market, IoT architectures are upgrading day by day to reduce data transmission costs, latency, and bandwidth usage for various application requirements The extensively available IoT architectures and their specification resist the researchers to select a system-on-chip (SoC) for heterogeneous IoT applications This paper seeks to comprehend the various IoT device specifications and their characteristics to support multiple applications Moreover, microprocessor architectures and their components are detailed to facilitate developer knowledge in advanced methodology and technology The various instructions set architectures (ISA) are implemented in a Zynq-7000 (xc7Zz20clg484-1) FPGA device to examine the feasibility of design space requirements for real-time hardware execution To select specific system-on-chip (SoC) architecture for heterogeneous IoT applications, a genetic algorithm (GA) based optimization method is implemented in MATLAB The proposed algorithm identifies the optimized SoC architecture concerning device parameters such as a clock, cache, RAM space, external storage, network support, etc Further, the confusion matrix method evaluates the proposed algorithm’s accuracy, which yields 8462% accuracy The outcome of SoCs attained through the GA are tested by analyzing their execution time and performance using various evaluation benchmarks This article helps the researchers and field engineers to comprehend the microarchitecture device configurations and to identify the superior SoC for next-generation IoT practices