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A novel distributed real-time energy management strategy for inverter-based microgrids based on dynamic algorithms with a low computational burden and without the requirement of offline forecast or a central optimizer is presented in this paper. A dynamic economic dispatch problem is solved while a stability performance is guaranteed. The algorithm is able to dynamically adjust the power references under sudden load changes, generator disconnection, and communication failures. In steady-state, the proposed real-time energy management strategy guarantees optimality conditions and frequency regulation. Finally, the effectiveness of the proposed strategy and its compatibility with the conventional proportional-resonant inner controllers and primary droop controllers are validated in experiments.

The main focus of this paper is to present the current prospects, potentials, research activities, future concerns, and applications of solar photovoltaic (PV) systems in Bangladesh. Despite the existence of several articles in the literature on solar energy prospects in Bangladesh, the diffusion of several solar PV applications throughout the country, their rapid progress analysis, and existing feasibility study outcome analysis are still unrevealed. Therefore, an endeavour has been made for the first time to condense the government and non‐government contributions to disseminating solar energy throughout the country. Twenty‐one feasibility studies at different locations of Bangladesh are reviewed and analysed, in terms of financial viability, sensitivity analysis, and greenhouse gas emissions, to foresee the prospects of solar energy in Bangladesh. Sensitivity analyses are performed, with six sensitivity variables, which reveal that the total net present cost of the solar project implementation may be increased by 20% (maximum) in the lowest solar potential area than the highest one with an average payback period of 13 years. This paper also identifies the policy gaps, classifies the barriers into eight categories, and discusses the conceivable approaches to defeat those barriers, followed by recommendations in six different aspects.

Some systems, in spite of having multiple outputs, have only one control input, which makes their control a challenge. Two novel controllers are proposed that utilise an adaptive finite‐time sliding mode control (AFSMC) scheme for a class of single‐input multiple‐output (SIMO) nonlinear systems in the presence of unknown mismatched uncertainties. To alleviate the inherent chattering phenomenon of sliding mode control, new forms of the two designed controllers are suggested by using new sliding surfaces. Not only can the proposed AFSMC scheme stabilise the system in a finite time, but also it can provide estimated data of the uncertainty upper bound in the controller. Lyapunov stability theory is used to obtain finite‐time stability analysis of the closed‐loop system. Finally, simulation results are carried out in Simulink/MATLAB for a four‐dimensional autonomous hyper‐chaotic system with mismatched uncertainties as an example of SIMO uncertain nonlinear systems to reveal the effectiveness of the proposed controllers.

Nowadays, transformer‐less Photovoltaic‐based grid‐connected inverters are more popular in renewable energy application due to their reduced size, cost, and high efficiency. However, the absence of galvanic isolation leads to the flow of leakage current in such system hindering personal safety, and deteriorating power quality. Therefore, this paper presents a five‐level transformer‐less inverter topology for PV applications with less component count and reduced complexity. The proposed inverter topology completely eliminates the common mode leakage current. Besides, the proposed topology has an inherent capability to boost the voltage without using any magnetic component or boosting circuit, and is based on the principle of switched/auxiliary capacitor. The proposed topology do not have any limitation of modulation index since the auxiliary capacitors are naturally balanced, hence less complex or no dedicated control scheme is required for balancing/regulating the auxiliary capacitor voltages. In order to verify the performance of the proposed inverter topology, a laboratory prototype is developed which confirms the operation, and feasibility of the proposed inverter. Results depicting the output voltage, load current, and voltage across the auxiliary capacitor are presented for various operating conditions. Further, simulation results depicting the leakage current in the proposed, H5, and H6 topologies are included. Finally, a quantitative comparison study is done, highlighting the benefits of the proposed inverter topology regarding boosted voltage, elimination of leakage current, and reduced component count.

This paper presents a mixed-sensitivity-based robust H∞ loop-shaping partial feedback linearized control scheme to enhance the transient stability of a battery energy storage-associated standalone solar photovoltaic system. The proposed control scheme has been provided independent operating points for a generalized nonlinear dynamical model of DC microgrids connected standalone hybrid solar photovoltaic and battery energy storage system. A parametric uncertainty model is developed for the generalized dynamical model, and the noise disengaging merit of the proposed control technique has been investigated. The designed controller’s performance has been demonstrated under four different scenarios, and it is compared with the conventional PI controller for partial feedback linearized control law.

Although energy management of a microgrid is generally performed using a day-ahead scheduling method, its effectiveness has been questioned by the research community due to the existence of high uncertainty in renewable power generation, power demand and electricity market. As a result, real-time energy management schemes are recently developed to minimise the operating cost of a microgrid while high uncertainty presents in the network. This paper develops modified particle swarm optimisation (MPSO) algorithms to solve optimisation problems of energy management schemes for a community microgrid and proposes a scheduling approach after taking into consideration high uncertainty to effectively minimise the operational cost of the microgrid. The optimisation problems are formulated for real-time and scheduling approaches, and solution methods are developed to solve the problems. It is observed that the scheduling program demonstrates superior performance in all the cases, including uncertainty in prediction, as compared to the other energy management approaches, although solutions have significant deviations due to prediction errors.

A distribution network is one of the main parts of a power system that distributes power to customers. While there are various types of power distribution networks, a recently introduced novel structure of an aromatic network could begin a new era in the distribution levels of power systems and designs of microgrids or smart grids. In order to minimize blackout periods during natural disasters and provide sustainable energy, improve energy efficiency and maintain stability of a distribution network, it is essential to configure/reconfigure the network topology based on its geographical location and power demand, and also important to realize its self-healing function. In this paper, a strategy for reconfiguring aromatic networks based on structures of natural aromatic molecules is explained. Various network structures are designed, and simulations have been conducted to justify the performance of each configuration. It is found that an aromatic network does not need to be fixed in a specific configuration (i.e., a DDT structure), which provides flexibility in designing networks and demonstrates that the successful use of such structures will be a perfect solution for both distribution networks and microgrid systems in providing sustainable energy to the end users.

The integration of renewable energy sources together with an energy storage system into a distribution network has become essential not only to maintain continuous electricity supply but also to minimise electricity costs. The operational costs of this paradigm depend highly upon the optimal use of battery energy. This paper proposes day-ahead scheduling of the battery energy while considering its degradation costs due to charging-discharging cycles. The degradation costs with respect to the depth of charge are modelled and added to the objective function to determine the actual operational costs of the system. A framework to solve the function is developed in which particle swarm optimisation, the Rainflow algorithm and scenario techniques are integrated. Uncertainties of parameters, modelled by scenario generation and reduced by scenario reduction techniques, are discussed. Simulation results demonstrate that the proposed method can reduce the operational costs by around 40% compared to the baseline method. They also reveal that uncertainty in power generation and power demand has no influence on the energy schedule of the battery, but variation in electricity prices has an impact on the outcome. Several pragmatic tests verify the effectiveness of the proposed method.

The typical layout of power systems is experiencing significant change, due to the high penetration of renewable energy sources (RESs). The ongoing evaluation of power systems is expecting more detailed and accurate mathematical modeling approaches for RESs which are dominated by power electronics. Although modeling techniques based on state&ndash, space averaging (SSA) have traditionally been used to mathematically represent the dynamics of power systems, the performance of such a model-based system degrades under high switching frequency. The multi-frequency averaging (MFA)-based higher-index dynamic phasor modeling tool is proposed in this paper, which is entirely new and can provide better estimations of dynamics. Dynamic stability analysis is presented in this paper for the MFA-based higher-index dynamical model of single-stage single-phase (SSSP) grid-connected photovoltaic (PV) systems under different switching frequencies.

The corrosion of steel reinforcement in concrete often leads to huge unbudgeted expenses for maintaining, monitoring and renovating an infrastructure. This is mainly due to the presence of salts or chemical chlorides that pose a danger to the concrete structures. The determination of the existence of these corrosive salts is vital for defining the service life of concrete. This research looked at developing an electromagnetic induction (EMI) sensor for the detection of corrosive salts. The first design adopted a single-loop coil (SLC) concept, and the second was based on a multiple-loop coil (MLC) one using copper wire. Tests were conducted on these two techniques, and with the results obtained, the latter seemed more promising, thus, a prototype sensor was developed using the MLC concept. As this new prototype sensor was able to detect the manifestation of chemical contents in a concrete structure, it could be used as a non-destructive evaluation (NDE) technique for the detection of corrosive chemicals in concrete and has the further possibility of detecting corrosion in concrete.

In this paper, super-short-term prediction of solar power generation for applications in dynamic control of energy system has been investigated. In order to follow and satisfy the dynamics of the controller, the deployed prediction method should have a fast response time. To this end, this paper proposes fast prediction methods to provide the control system with one step ahead of solar power generation. The proposed methods are based on univariate time series prediction. That is, instead of using external data such as the weather forecast as the input of prediction algorithms, they solely rely on past values of solar power data, hence lowering the volume and acquisition time of input data. In addition, the selected algorithms are able to generate the forecast output in less than a second. The proposed methods in this paper are grounded on four well-known prediction algorithms including Autoregressive Integrated Moving Average (ARIMA), K-Nearest Neighbors (kNN), Support Vector Regression (SVR), and Random Forest (RF). The speed and accuracy of the proposed algorithms have been compared based on two different error measures, Mean Absolute Error (MAE) and Symmetric Mean Absolute Percentage Error (SMAPE). Real world data collected from the PV installation at the University of California, Riverside (UCR) are used for prediction purposes. The results show that kNN and RF have better predicting performance with respect to SMAPE and MAE criteria.

The Microgrids (MGs) are an effective way to deal with the smart grid challenges, including service continuity in the event of a grid interruption, and renewable energy integration. The MGs are compounded by multiple distributed generators (DGs), and the main control goals are load demand sharing and voltage and frequency stability. Important research has been reported to cope with the implementation challenges of the MGs including the power sharing control problem, where the use of cybernetic components such as virtual components, and communication systems is a common characteristic. The use of these cybernetic components to control complex physical systems generates new modeling challenges in order to achieve an adequate balance between complexity and accuracy in the MG model. The standardization problem of the cyber-physical MG models is addressed in this work, using a cyber-physical energy systems (CPES) modeling methodology to build integrated modules, and define the communication architectures that each power sharing control strategy requires in an AC-MG. Based on these modules, the control designer can identify the signals and components that eventually require a time delay analysis, communication requirements evaluation, and cyber-attacks&rsquo, prevention strategies. Similarly, the modules of each strategy allow for analyzing the potential advantages and drawbacks of each power sharing control technique from a cyber physical perspective.

There has been a considerable importance for the islanding detection due to the growing integration of distributed generations (DGs) in the modern power grids. This paper proposes a novel active islanding detection scheme for synchronous DGs, considering two additional compensators and a positive feedback for each of active and reactive power control loops. The added blocks are designed using the small gain theorem and stability margins definition considering characteristics of open loop transfer functions of synchronous DG control loops. Islanding can be detected using the proposed method even where there is an exact match between generation and local load without sacrificing power quality. In addition, the performance of the proposed method can be retained even with high penetration of motor loads. The proposed scheme improves the stability and power quality of the grid, when the synchronous DG is subjected to the grid-connected disturbances. Furthermore, this method augments the stability margins of the system in the grid-connected conditions to enhance the disturbances ride-through capability of the system and reduce the negative impact of the active methods on the power quality. Simultaneous advantages of the proposed scheme are demonstrated by modeling a test system in MATLAB software and time-domain simulation achieved by PSCAD.

Over the last two decades, increasing the scanning speed of an atomic force microscopy (AFM) has been attempted either by applying novel controllers, using alternative scanning methods, or by modifying the hardware setup. This paper demonstrates, the first two approaches to achieve high-speed AFM image scanning. A robust minimax linear quadratic Gaussian (LQG) controller is designed and spiral scanning is considered as an alternative scanning method rather than conventional raster scanning. The minimax LQG controller is designed based on an uncertain system model which is constructed by measuring the plant variations due to variations in sample mass and also modeling error between the measured and model frequency responses. This controller is also robust against uncertainties introduced as a result of variations of sample mass, spillover dynamics of the scanner at frequencies higher than the first resonance frequency of the scanner, and variation in plant transfer functions due to temperature and humidity. The designed controller is experimentally implemented on an AFM using a dSPACE ds-1103 real-time prototyping system and open-loop and closed-loop spiral imaging performances are evaluated. The proposed controller provides sufficient damping at the resonant modes to accurately track the sinusoidal reference signal and generate vibration free images. Also, creep, hysteresis, and cross-coupling effects are significantly reduced. The experimental results show that the proposed scheme outperforms the open-loop case and some other existing approaches. Refereed/Peer-reviewed

An optimal controller for high-precision spiral positioning of a piezoelectric tube scanner used in an atomic force microscope (AFM) is proposed in this paper. In the proposed control scheme, a second-order vibration compensator is incorporated with the piezoelectric tube scanner (PTS) to suppress the vibration of the PTS at the resonant frequency. An internal model of a reference sinusoidal signal is included with the augmented plant model and an integrator is introduced with a linear quadratic Gaussian controller which reduces the phase error between the input and output sinusoids. The proposed method allows a commercial AFM to scan at high scanning speeds as an alternative to the raster scanning approach. The performance of this controller is assessed with closed-loop frequency response, tracking accuracy, and a set of spiral scanned images. The raster scanned images obtained using the standard AFM PI controller is also presented for comparison with the spiral images. Experimental results prove the effectiveness of the proposed method. Refereed/Peer-reviewed

This paper presents the impact of large penetration of wind power on the transient stability through a dynamic evaluation of the critical clearing times (CCTs) by using intelligent agent-based approach. A decentralised multi-agent-based framework is developed, where agents represent a number of physical device models to form a complex infrastructure for computation and communication. They enable the dynamic flow of information and energy for the interaction between the physical processes and their activities. These agents dynamically adapt online measurements and use the CCT information for relay coordination to improve the transient stability of power systems. Simulations are carried out on a smart microgrid system for faults at increasing wind power penetration levels and the improvement in transient stability using the proposed agent-based framework is demonstrated.

The design of a phase-locked loop (PLL)-based proportional integral (PI) controller for compensating the phase error between motions from the lateral axes of a piezoelectric tube scanner (PTS) during spiral scanning for an atomic force microscope (AFM) is proposed in this paper. Spiral motion of the PTS for scanning of material surfaces or biological samples using an AFM is achieved by applying two sinusoidal signals with a 90 degree phase-shift and of varying amplitudes to the X and Y-axes of the scanner. The phase error between the X and Y-axes positions and scanner's vibration due to its mechanical properties increase with increasing scanning speeds which reduce the imaging performance of the AFM at high frequencies. In the proposed control scheme, a vibration compensator is used with the X and Y-PTS to damp the vibration of the PTS at its resonant frequency and the phase error between the displacements of the two lateral axes of the scanner is measured by a phase detector and a PI controller is used to reduce the error. Comparisons of experimental results for reference tracking and imaging performance with the AFM PI controller demonstrate the efficiency of the proposed control method. Refereed/Peer-reviewed

In most nanotechnology applications, speed and precision are important requirements for obtaining good topographical maps of material surfaces using atomic force microscopes (AFMs), many of which use piezoelectric tube scanners (PTSs) for scanning and positioning at nanometric resolutions. However, PTS suffers from various intrinsic problems that degrade its positioning performance, such as: (i) lightly damped low-frequency resonant modes due to its mechanical structure; (ii) nonlinear behavior due to hysteresis and creep; and (iii) the cross-coupling effect between its axes (in 3D positioning systems such as AFMs). This paper presents a survey of the literature on the PTS, an overview of a few emerging innovative solutions for its nanopositioning and future research directions. Refereed/Peer-reviewed

This paper presents an approach for designing a robust vibration control system for a piezoelectric tube scanner (PTS) used in an atomic force microscope (AFM). In this control design, an uncertainty system model is constructed by measuring modeling error between the measured and model frequency response data. Then a minimax linear quadratic Gaussian (LQG) control technique is used to design a controller which minimizes scanner vibration at its resonant mode. This controller is robust against uncertainties introduced as a result of truncating higher order modes of the scanner, variation of plant transfer function due to temperature and humidity and measurement noise from the position sensors. The experimental results show that the proposed controller is able to reduce the vibration at its resonant mode and track the reference signal. Refereed/Peer-reviewed

This paper presents the design of an internal reference model-based optimal linear quadratic Gaussian (LQG) controller for the lateral positioning of a piezoelectric tube actuator (PTA) used in an atomic force microscope (AFM). In this control design, internal modeling of the reference signal and system error are considered. As a result, the steady-state tracking error is minimized. In addition to the LQG controller, a vibration compensator is incorporated with the plant to suppress the vibration of the PTA at the resonance frequency. It achieves a high closed-loop bandwidth and significant damping of the resonant mode of the PTA, which enables a reference triangular signal to be tracked. Comparison of performance of the optimal LQG controller augmented with a vibration compensator and a PI controller demonstrates that the proposed controller shows significant improvements over the existing AFM PI controller. Refereed/Peer-reviewed

This paper considers a high-speed spiral scanning method using an atomic force microscope (AFM). In it, spirals are generated by applying single-frequency cosine and sine waves of slowly varying amplitudes in the X and Y-axes, respectively, of the AFM's piezoelectric tube (PZT) scanner. Due to these single-frequency sinusoidal input signals, the scanning process can be faster than that of conventional raster scanning. A linear quadratic Gaussian (LQG) controller is designed to track the reference sinusoidal signal. An internal model of the reference sinusoidal signal is included in the plant model and an integrator for the system error is introduced in the proposed control scheme. As a result, the phase error between the input and output sinusoid from the X and Y-PZTs is reduced. The spirals produced have particularly narrow-band frequency measures which change slowly over time, thereby making it possible for the scanner to achieve improved tracking and continuous high-speed scanning rather than being restricted to the back and forth motion of raster scanning. Also, a fifth-order Butterworth filter is used to filter noises in the signals emanating from the position sensors. A comparison of images scanned using the proposed controller (spiral) and the AFM proportional integral (PI) controller (raster) provide evidence of the efficacy of the proposed method. Refereed/Peer-reviewed

In this article the design and experimental implementation of an observer based model predictive control (OMPC) scheme for active damping of the first two resonant modes of a smart structure is presented. The design of this controller is based on an identified model of the plant. A Kalman filter is used to obtain full state information. The experimental results verify the efficacy of the proposed controller Refereed/Peer-reviewed

This article presents the design and experimental implementation of an observer-based model predictive control (OMPC) scheme with a notch filter which aims to compensate for the effects of creep, hysteresis, cross-coupling, and vibration in piezoactuators in order to improve the nanopositioning of an atomic force microscope (AFM). The controller design is based on an identified model of the piezoelectric tube scanner (PTS) for which the control scheme achieves significant compensation of its creep, hysteresis, cross-coupling, and vibration effects and ensures better tracking of the reference signal. A Kalman filter is used to obtain full-state information of the plant. The experimental results exemplify the use of this proposed control scheme. Refereed/Peer-reviewed

In this paper we describe the cross-coupling effect between X-Y axes of piezoelectric tube (PZT) scanner used in an atomic force microscope (AFM). During raster scanning X-Y axes induced cross-coupling effect in the lateral positioning of the scanner stage of the AFM and as a result, it produces blurred or distorted images. To address this effect, an LQG controller is designed and implemented on AFM which minimizes the cross-coupling effect between the axes mainly at the resonance frequency of the scanner tube. The proposed controller has an integral action with the error signal which makes it possible to track the reference signal and a significant damping of the resonant modes of the PZT in the X and Y axes. This controller compensates the cross-coupling between X-Y axes dynamics of the AFM system, reducing the artifacts instigating by the system dynamic behavior at high scan rates. The closed-loop frequency responses for both the axes have achieved high bandwidth. Consequently, scanned results are evaluated as a better one than the open-loop of the AFM. Refereed/Peer-reviewed

An atomic force microscope (AFM) is an extremely versatile investigative tool in the field of nanotechnology, the performance of which is significantly influenced by its conventional zig-zag raster pattern scanning method. In this paper, we consider the use of a spiral scanning method with an improved model predictive control (MPC) scheme for its faster scanning. The proposed MPC controller reduces the phase error between the input and output sinusoids and provides better tracking of the reference signal. Also, a notch filter is designed and included in the feedback loop with the plant to suppress vibrations of the piezoelectric tube scanner (PTS) at the resonant frequency. Consequently, the proposed controller achieves a higher closed-loop bandwidth and significant damping of the resonant mode of the AFM's PTS. Experimental results show that, by using the proposed method, the AFM's scanning speed is significantly increased to up to 180 Hz and produces improved image quality. Refereed/Peer-reviewed