Search

In this article, islanding detection, control, grid synchronization, and power share techniques have been considered for the seamless operation of ac microgrid in grid-connected mode, islanded mode, and during the transition between both modes. A master–slave organization coordinates the power distribution among microgrid sources. The control scheme of each source is designed with a nested loop robust linear quadratic regulator and mixed $H_{2}/H_{\infty }$ optimal controller. The islanding detection algorithm is developed with synchro-extraction transform and optimal support vector machine (OSVM). An optimal linear Kalman filter-based synchronous reference frame phase locked loop (OLKF-SRFPLL) method is considered for the reconnecting of the microgrid to the utility grid. For optimal parameter tuning in the OSVM and LKF-SRFPLL methods, a particle swarm optimization technique is used. The seamless operation of the proposed ac microgrid system is verified in MATLAB/SIMULINK, and the practical feasibility is verified with an experimental photo-type setup and dSPACE 1202 control kit. Simulation and experimental results are presented to illustrate the seamless operation of the proposed ac microgrid system. [ABSTRACT FROM AUTHOR]

Highlights: [•] Neuro-fuzzy scheme to investigate the winding insulation paper (WIP) deterioration. [•] To investigate the deterioration condition of the WIP in oil-immerged power transformer. [•] New technique also diagnoses those samples which are out of IEEE and IEC standard range. [•] Testing results are better as compare to IEEE and IEC methods. [ABSTRACT FROM AUTHOR]

State-estimation plays a vital role to monitor, observe and understand the combined heat and electric network. In this paper, a hybrid framework is presented to accurately estimate the system states of electric distribution network and heat network, using the limited non-redundant measurements obtained from supervisory control and data acquisition and advanced metering infrastructure systems. The presented hybrid framework involves two steps, namely, the state-forecasting and the state-estimation. The state-forecasting uses a deep neural network to forecast the system states at every fifteen minutes interval, while these forecasted states are further used by the hybrid estimator, which uses a robust extended Kalman filter to estimate the system states with help of both datasets corresponding to supervisory control and data acquisition and advanced metering infrastructure systems, at hourly interval. The proposed framework does not completely rely on the system model at different instants. The effectiveness of the method is validated through thorough comparisons with simulation studies carried out using the Barry Island test system, United Kingdom. Satisfactory performance is observed even with the presence of bad data in the measurements. • A framework to estimate states of electric and heat networks with SCADA and AMI data • A method of forecasting the CHEN states using only a limited SCADA dataset • A robust Kalman filter for accurate estimation under gross errors in data. • Test results that validate the method on Barry Island CHEN system. • Comparative results over the state-of-art WLS and ANN based estimators. [ABSTRACT FROM AUTHOR]

This article presents a grid-connected single-stage photovoltaic (PV) system using an adaptive normalized notch filter (ANNF). An unknown time-varying fundamental frequency is precisely estimated from a normalized notch filter and consequently, the fundamental load component is extracted using this algorithm. The convergence of the algorithm is independent of both amplitude and the frequency of the fundamental component, and therefore, this algorithm is robust to these changes in the load current. The adaptive estimation of fundamental load current with perturbations on load/grid side system is well analyzed. The ANNF based control strategy is not only efficient in fundamental extraction, however, it also achieves the objectives of supplying real power to the grid, grid currents balancing, and power factor correction. Moreover, this algorithm is robust to harmonic/ distorted/ unbalanced grid voltages caused at far radial ends in the weak distribution network. Elaborated simulation results are presented to show the effectiveness of the strategy. A prototype is developed to validate this control strategy at various perturbations. Under all operating conditions, test results are found satisfactory. [ABSTRACT FROM AUTHOR]

Grid-edge distributed energy resources (DERs) present both operational challenges and opportunities to distribution system operators (DSO). This paper presents a day-ahead scheduling strategy for DER-rich active distribution networks to leverage operational flexibilities of various DERs for effective network management. The scheduling strategy is realized based on a DSO-centric day-ahead market model that incorporates a multi-period and two-stage optimal power flow (OPF) model to determine scheduling and pricing for network and non-network DERs. The uncertainties in day-ahead operation stemming from local generation, load consumption, and market prices are robustly considered for hedging the intermittency and forecasting uncertainties. A novel bid price function is proposed for local distributed solar PV generation aiming at maximizing participation in network service. A new reactive power management and pricing scheme is also presented for optimal scheduling of voltage support devices within distribution network. The proposed framework is implemented on IEEE-33 bus balanced test system and operational planning strategy is analyzed for overall cost-benefits of the system at various uncertainty levels. A 7-10 percent saving in cost of procurement for DSO can be accrued at various uncertainty levels, and a 10 percent increase in revenue for the PV generation can be observed. • An optimal and sustainable operational planning for the DSO is proposed. • The proposed framework uses day-ahead model for operational planning of DERs. • The uncertainties in market prices, load, and PV generation are considered. • A new reactive power management strategy for fair pricing is proposed. • The proposed framework incentivizes older PV technologies with higher marginal prices. [ABSTRACT FROM AUTHOR]

This article proposes a standalone single stage photovoltaic (PV) fed reduced switch inverter (RSI) based permanent magnet synchronous motor (PMSM) drive for water pumping application. The proposed system aims at reducing the switching losses and overall cost by using reduced switch inverter. The proposed system comprises a PMSM drive, fed by PV source through an inverter employing reduced number of switches. The inverter uses only four switches whereas the conventional voltage source inverter utilizes six switches. Field oriented control scheme is employed to control the PMSM drive. Perturb and observe maximum power point tracking technique is used to generate a speed reference to PMSM drive. The proposed system is simulated using MATLAB/Simulink platform, and it is also experimentally verified with field programmable gate array (FPGA) controller based 400 W laboratory prototype PMSM drive. The simulation and experimental results demonstrate the efficacy of the proposed system. [ABSTRACT FROM AUTHOR]

Though recent advancements in dc microgrids are largely based on distributed control strategies to enhance reliability and scalability, the absence of a centralized controller to check the global information makes these schemes highly susceptible to cyber attacks. Since false data injection attacks (FDIAs) are considered as a prominent attack methodology in dc microgrids, prior emphasis is usually laid on compromised sensors and controllers only related to dc voltages. Hence, this article first segregates the FDIAs on the output currents into destablization and deception attacks, based on the modeling of attack elements with respect to the consensus theory. Second, a discordant element based detection approach is designed to detect the attacked nodes accurately, using an extended analysis of the cooperative control network. A risk assessment framework for dc microgrids against cyber attacks is provided alongside all the case studies. An evaluation theory is also presented to assist the proposed detection scheme to differentiate between cyber attacks and faults. Further, the proposed detection approach is theoretically verified and validated using simulation and experimental conditions. [ABSTRACT FROM AUTHOR]

This work deals with an implementation of a unique control approach for the power quality enhancement in solar photovoltaic (PV) based grid interfaced system. In this work, a robust control technique with strong filtering capabilities is implemented. A single‐phase two‐stage grid interacted solar PV topology is considered with a second‐order sequence filter as a test system for the validation of the power quality enhancement features. The system constitutes a PV array, a boost converter, a DC link capacitance, a voltage source converter (VSC), an interfacing inductor and a ripple filter. A boost converter is used at a primary stage of proposed topology, which supports the extraction of maximum power from the solar PV array. In addition, the VSC feeds the solar PV power into the grid. It also provides harmonics elimination and power factor correction. A new maximum power point tracking technique avoiding a drift feature is adopted for the fast dynamic performance. The implementation of the solar PV system is performed and the harmonic profile of grid current is observed in compliance to the IEEE‐519 standard. [ABSTRACT FROM AUTHOR]

Partial shading is one of the certain conditions in photovoltaic (PV) power plants. Often the panels get partially shaded due to soiling, clouds, and trees. The effect of shading is of high concern and importance especially in applications such as water pumps due to agricultural environments in which they are employed in. However, the research focus on PV fed pumps till date has been restricted to only uniform shading conditions. Unlike uniform shading conditions during maximum power tracking, where the panel voltage remains almost constant for an entire range of irradiance, partial shading offer conditions such as highly variable panel voltage and transitions of intermediate DC–DC power converter from continuous conduction mode to discontinuous conduction mode. These effects severely affect the performance of the power converter and, therefore, the power output of the pump. This paper presents a study on the effects caused by partial shading conditions on pumps through simulations and verified by experimentations. The simulation and experimental results are found to be in good agreement with each other. This research thus helps in understanding the detrimental effects caused by partial shading conditions and thus serves as a reference tool for practitioners who wish to study PV fed pumps. [ABSTRACT FROM AUTHOR]

Characteristics of photovoltaic arrays exhibit multiple peaks under mismatching conditions. In order to harness maximum energy, it is imperative to track the global maximum power point. A novel global peak tracking algorithm is proposed using current control in this paper. The proposed method operates in the backward phase and forward phase to track the global peak. The objective of the proposed algorithm is to track the global maximum accurately with minimum tracking time. The enhanced performance of the proposed algorithm is verified using simulations by comparing it with an existing method. Experimental validation is done using a solar array simulator, boost converter, resistive load, and dSPACE controller. Experimental results are in close agreement with simulation. The proposed algorithm is intended to track the global peak of a PV string that contains a group of modules. [ABSTRACT FROM AUTHOR]

For the effective operation of a dynamic voltage restorer (DVR), a control strategy plays a significant role. This paper presents an enhanced control strategy for DVR using dual role cascaded delay signal cancellation (CDSC)-based dual vector control (DVC) under unbalanced and distorted grid conditions. Based on the numerical analysis, it is found that the CDSC prefilter is a promising solution when grid voltage is distorted by symmetric, asymmetric harmonics, and unbalanced sag. Mainly, the CDSC prefilter extracts instantaneous symmetrical components of the grid voltage required for voltage sags detection and generation of fundamental component of reference voltage for the DVR. A CDSC-based DVC algorithm with inductor current and capacitor voltage feedback is implemented in a synchronous reference frame, which tracks the fundamental DVR reference voltages. An extractor based on the modified CDSC strategy is designed to extract harmonics from load voltage during distorted grid conditions. These extracted harmonic components (nonfundamental) are added in phase opposition with fundamental component and fed to pulse width modulation block to generate reference voltages. Experimental studies are conducted on scaled down (100 V, 0.5 kVA) laboratory prototype DVR to verify the effectiveness of the proposed control algorithm under unbalanced and distorted grid conditions. [ABSTRACT FROM AUTHOR]

As the penetration of intermittent, low carbon generation increases, system inertia will decrease dramatically and pose a major threat to system stability. The majority of research in this area investigates the methods of providing inertia from the supply side, but this paper develops a novel method that will evaluate the demand side contributions to system inertia based on historical data of frequency outage events in the GB power system. This is achieved by isolating the generation contribution from the total system inertia and considering the power/frequency ratio as an indicator of the additional inertia contribution from spinning reserve. The results show that the demand side could contribute an average of 1.75-s inertia constant in the system load base, representing 20% of the total system inertia in the GB power system. Finally, the system inertia distribution, the rate of change of frequency and the minimum primary frequency response requirements are investigated at a variety of demand levels. [ABSTRACT FROM AUTHOR]

This study presents the fuzzy logic integrator gain-tuned improved second-order generalized integrator (GI) for a double-stage grid-interfaced photovoltaic (PV) system. The proposed system includes the functionalities of feeding active power to the grid, power factor correction, grid currents balancing and system isolation under grid side faults. Moreover, the smooth system operation is ensured under weak distribution grids where grid voltage is subject to huge diversions. Furthermore, automatic protection scheme for the system under grid-side faults is also established with the proposed algorithm for increased reliability. The fuzzy-tuned GI provides advantages of efficient and effective extraction of load current fundamental component under steady-state and dynamic grid conditions. The non-linear frequency error variation is compensated here using fuzzy logic-based self-tuning integrator gain of the controller. The controller is improved to mitigate the possible DC component in the load current. The neutral current in the loads is nullified by using a four wire system. The adaptive DC bus voltage helps to minimize the switching losses and prevents unexpected tripping of the PV inverter. The system is experimentally verified using a prototype built in the laboratory. [ABSTRACT FROM AUTHOR]

This study presents the fuzzy logic integrator gain‐tuned improved second‐order generalized integrator (GI) for a double‐stage grid‐interfaced photovoltaic (PV) system. The proposed system includes the functionalities of feeding active power to the grid, power factor correction, grid currents balancing and system isolation under grid side faults. Moreover, the smooth system operation is ensured under weak distribution grids where grid voltage is subject to huge diversions. Furthermore, automatic protection scheme for the system under grid‐side faults is also established with the proposed algorithm for increased reliability. The fuzzy‐tuned GI provides advantages of efficient and effective extraction of load current fundamental component under steady‐state and dynamic grid conditions. The non‐linear frequency error variation is compensated here using fuzzy logic‐based self‐tuning integrator gain of the controller. The controller is improved to mitigate the possible DC component in the load current. The neutral current in the loads is nullified by using a four wire system. The adaptive DC bus voltage helps to minimize the switching losses and prevents unexpected tripping of the PV inverter. The system is experimentally verified using a prototype built in the laboratory. [ABSTRACT FROM AUTHOR]

This paper presents a multipurpose three-phase double-stage grid interfaced photovoltaic (GPV) system using an adaptive nonlinear control strategy. Along with a peak power extraction from a photovoltaic array, the proposed system is capable of harmonics currents elimination, reactive power compensation, grid currents balancing, and adaptive dc-link voltage control. The fundamental and harmonics information from the polluted load current are precisely estimated using an adaptive observer. A strictly positive real Lyapunov function is used to derive update laws for an adaptive observer. The DC-link voltage is adaptively adjusted in proportion to the point of common coupling voltage to minimize switching losses in voltage source converter and to avoid its tripping in sensitive distribution grids. A feed-forward loop for PV contribution is included to improve system response under dynamic conditions. Simulated and test results depict the performance of the GPV system with aforementioned functionalities. Improved steady-state and dynamic performances are observed with the proposed nonlinear adaptive estimation based control approach. The total harmonic distortions in grid currents are found well within the limits prescribed by an IEEE-519 standard. [ABSTRACT FROM PUBLISHER]

This study deals with a control scheme for single‐stage solar photovoltaic (SPV) grid‐interfaced system. The voltage‐source inverter (VSI) is a power electronic interface between SPV array and the grid. The VSI provides power quality features, i.e. harmonics mitigation, power factor correction and perturb and observe maximum power point tracking for single‐stage SPV grid‐interfaced system. The SPV array supplies active power to the non‐linear load and grid through VSI, during daytime only or when SPV generation is more than the load power. To increase the utilisation of VSI, it is used as an active power filter at night, to mitigate harmonics and to provide active power to the load from the utility grid. The proposed adaptive linear combiner filter has the capability to extract harmonics and enhances the power quality in SPV grid‐interfaced system. It has also satisfied an IEEE‐519 standard of harmonics by improving the quality of power of SPV grid‐integrated system. Simulation results of the SPV system are presented, which are simulated using MATLAB and response of system under non‐linear load and varying environmental condition are also studied experimentally on a developed prototype in the laboratory. [ABSTRACT FROM AUTHOR]

A control algorithm for a standalone solar photovoltaic (PV)-diesel-battery hybrid system is implemented in this paper. The proposed system deals with the intermittent nature of the energy generated by the PV array and it also provides power quality improvement. The PV array is integrated through a dc–dc boost converter and is controlled using a maximum power point tracking algorithm to obtain the maximum power under varying operating conditions. The battery energy storage system (BESS) is integrated into the diesel engine generator set for the coordinated load management and power flow within the system. The admittance-based control algorithm is used for load balancing, harmonics elimination, and reactive power compensation under three-phase four-wire linear and nonlinear loads. A four-leg voltage-source converter with BESS also provides neutral current compensation. The performance of the proposed standalone hybrid system is studied under different loading conditions experimentally on a developed prototype of the system. [ABSTRACT FROM PUBLISHER]

Summary: This paper deals with a sixth‐order generalized integrator for single phase grid interlinked solar photovoltaic generation system (PVGS). The objective of the proposed algorithm is to control the power transfer between the photovoltaic (PV) and grid and the load at unity power factor and load current harmonics compensation. The proposed PVGS works in 3 modes: (1) PV‐voltage source converter (VSC), (2) VSC as an active power filter (ie, solar power is zero), and (3) PV‐VSC without the load. The VSC is to inject the available active power from PV array to load and the grid, with auxiliary services such as harmonics compensation with high utilization factor. The sixth‐order generalized integrator structure provides fast response than a single second‐order generalized integrator with same harmonics attenuation. The effectiveness of the control algorithm of PVGS under different modes and environmental conditions is validated by using the simulation and experimental results. [ABSTRACT FROM AUTHOR]

In the recent past, Internet of Things (IoT) plays a significant role in different applications such as health care, industrial sector, defense and research etc.… It provides effective framework in maintaining the security, privacy and reliability of the information in internet environment. Among various applications as mentioned health care place a major role, because security, privacy and reliability of the medical information is maintained in an effective way. Even though, IoT provides the effective protocols for maintaining the information, several intermediate attacks and intruders trying to access the health information which in turn reduce the privacy, security and reliability of the entire health care system in internet environment. As a result and to solve the issues, in this research Learning based Deep-Q-Networks has been introduced for reducing the malware attacks while managing the health information. This method examines the medical information in different layers according to the Q-learning concept which helps to minimize the intermediate attacks with less complexity. The efficiency of the system has been evaluated with the help of experimental results and discussions. [ABSTRACT FROM AUTHOR]