Hydrogen is acknowledged as a potential and appealing energy carrier for decarbonizing the sectors that contribute to global warming, such as power generation, industries, and transportation. Many people are interested in employing low-carbon sources of energy to produce hydrogen by using water electrolysis. Additionally, the intermittency of renewable energy supplies, such as wind and solar, makes electricity generation less predictable, potentially leading to power network incompatibilities. Hence, hydrogen generation and storage can offer a solution by enhancing system flexibility. Hydrogen saved as compressed gas could be turned back into energy or utilized as a feedstock for manufacturing, building heating, and automobile fuel. This work identified many hydrogen production strategies, storage methods, and energy management strategies in the hybrid microgrid (HMG). This paper discusses a case study of a HMG system that uses hydrogen as one of the main energy sources together with a... [more]

This article proposes a formal method of designing robotic systems focusing on communication between components, as well as standardization of the messages between those components. The objective is to design a robotic system controller in a systematic way, focusing on communication at an abstract agent level. Communication, thus organized, and its properly defined specification facilitate the system’s further development. The method uses a standard message structure, based on IEEE FIPA standards, for communication within robotic systems composed of agents. Communication-focused top-down design of robotic systems based on binary decomposition is proposed, and used to design a companion robot working in the kitchen environment. The implemented robotic system is verified based on whether or not the specification conforms to the specified requirements. The characteristics of the designed communication are evaluated. The obtained results prove that the proposed method of designing robotic... [more]

A novel bare-bones particle swarm optimization (BBPSO) algorithm is proposed to realize intelligent mine ventilation decision-making and overcome the problems of low precision, low speed, and difficulty in converging on an optimal global solution. The proposed method determines the decision objective function based on the minimal power consumption and maximal air demand. Three penalty terms, namely, dynamic ventilation condition, the supplied air volume at the location where the air is required, and roadway wind speed, are established. The particle construction method of “wind resistance” instead of “wind resistance & air volume” is proposed to reduce the calculation dimension effectively. Three optimization strategies, namely the contraction factor, optimal initial value, and elastic mirror image, are proposed to avoid premature convergence of the algorithm. The application flow of intelligent decision-making in the field and the parallel computing architecture are also discussed. Fiv... [more]

Fault detection is a necessary component to perform ongoing monitoring of photovoltaic plants and helps in their safety, maintainability, and productivity with the desired performance. In this study, an innovative technique is introduced by amalgamating Latent Variable Regression (LVR) methods, namely Principal Component Regression (PCR) and Partial Least Square (PLS), and the Triple Exponentially Weighted Moving Average (TEWMA) statistical monitoring scheme. The TEWMA scheme is known for its sensitivity to uncovering changes of small magnitude. Nevertheless, TEWMA can only be utilized for monitoring single variables and ignoring the correlation among monitored variables. To alleviate this difficulty, the LVR methods (i.e., PCR and PLS) are used as residual generators. Then, the TEWMA is applied to the obtained residuals for fault detection purposes, where the detection threshold is computed via kernel density estimation to improve its performance and widen its applicability in practic... [more]

Reliability of the multilevel inverters (MLIs) is one of the most important concerns in industrial applications, mainly due to the semiconductor devices. Whenever a fault occurs in one of the switches of the inverter, it leads to abnormal conditions and can also cause serious damage to the equipment connected to the multilevel inverter. In this paper, a recently proposed nine-level Packed-E-Cell (PEC) multilevel inverter topology is investigated for its fault-tolerant capability and improved reliability. The analysis is carried out for a reduced device multilevel inverter topology that, due to a lack of redundant states, cannot tolerate switch failures. The fault-tolerant (FT) topology provides additional redundant states in the switching sequence of the existing topology. The work in this paper presents Packed-E-Cell MLI modified for fault tolerance against single-switch open-circuit faults. The modified FT topology inherently achieves self-voltage balance in the DC-link capacitors. N... [more]

This paper presents an improvement of the tuning process of the holistic control published by the authors in previous research to achieve a seamless transition among three operation mode changes and load transients. The proposed tuning approach reveals an improvement in the energy consumption of the Battery Energy Storage System (BESS) during all operation mode transients compared to the holistic control. For this aim, the system addressed is a BESS with the capability to ride through three operation modes of interest: the grid-connected mode as an inverter, the grid-connected mode as a rectifier, and the islanded operation mode. The LCL filter design by using the Butterworth polynomial approach is presented in more detail, and its smooth inherent transient response is preserved when the tuning of the controller gains is carried out by using the same polynomial approach but now including the integral action within the Butterworth polynomial. To reveal the reduction in energy consumptio... [more]

The capacity of photovoltaic solar power installations has been boosted last years by reaching a new record with 175 GWdc of newly installed solar power in 2021. To guarantee reliable performances of photovoltaic (PV) plants and maintain target requirements, faults have to be reliably detected and diagnosed. A method for an effective and reliable fault diagnosis of PV plants based on the behavioral model and performance analysis under the LabVIEW environment is presented in this paper. Specifically, the first phase of this study consists of the behavioral modeling of the PV array and the inverter in order to estimate the electricity production and analyze the performance of the 9.54 kWp Grid Connected PV System (GCPVS). Here, the results obtained from the empirical models were validated and calibrated by experimental data. Furthermore, a user interface for modeling and analyzing the performance of a PV system under LabVIEW has been designed. The second phase of this work is dedicated t... [more]

The gradual displacement of conventional generation from the energy mix to give way to renewable energy sources represents a paradigm shift in the operation of future power systems: on the one hand, renewable technologies are, in general, volatile and difficult to predict; and on the other hand, they are usually connected to the grid through electronic power converters. This decoupling due to power converters means that renewable generators lack the natural response that conventional generation has to the imbalances between demand and generation that occur during the regular operation of power systems. Renewable generators must, therefore, provide a series of complementary services for the correct operation of power systems in addition to producing the necessary amount of energy. This paper presents an overview of existing methods in the literature that allow photovoltaic generators to participate in the provision of ancillary services, focusing on solutions based on power curtailment... [more]

This paper aims to address a finite-horizon model predictive control (MPC) for non-linear drum-type boiler-turbine system using a system-identification method. Considering that the strong state coupling of a non-linear mechanism model, the subspace identification method is first utilized to obtain a linear state-space model, and transformed into an input−output model. By taking the inputs and outputs of the input−output model as system states, an augmented non-minimal state-space (NMSS) model of state measurable is constructed. In order to reduce the computation burden, the augmented NMSS model is further transformed into a canonical formulation by adopting a Kalman decomposition. Based on the minimal realization state-space model, the MPC controller is parameterized as a finite-horizon optimization problem. Finally, simulations are performed and evaluated the performance of the proposed method, and the simulation results show that: the linear model approximate the non-linear system ac... [more]

The effects of varying modulation indices on the current and voltage harmonics of an induction motor (IM) powered by a three-phase space vector pulse-width modulation (SVM) inverter are presented in this research. The effects were examined using simulation and an experimental setup. IMs can be governed by an SVM inverter drive or a phase-angle control drive for applications that require varying speeds. The analysis of THD content in this study used the modulation index (MI), whose modification affects the harmonic content, and voltage-oriented control (VOC) with SVM in three-phase pulse-width modulation (PWM) inverters with fixed switching frequencies. The control technique relies on two cascaded feedback loops, one controlling the grid current and the other regulating the dc-link voltage to maintain the required level of dc-bus voltage. The control strategy was developed to transform between stationary (α−β) and synchronously rotating (d−q) coordinate systems. To test the viability of... [more]

DC microgrids have shown to be a good approach for better accommodating stochastic renewable energy sources (RES) and for the charging of electric vehicles (EVs) at the distribution level. For this, fast-acting energy storage units (ESSs) are essential. This requires that both the bi-directional power converter topology and the control scheme present the right set of features. The ESS discussed in this paper consists of a new DC-DC converter based on a tapped inductor (TI) for a higher voltage gain at moderate duty cycles. The direction of the current in its intermediate inductor does not need to be reversed for power flow reversal, leading to a faster action. Moreover, it can employ a multi-state and multi-variable modulation scheme that eliminates the right half-plane (RHP) zero, common in boost-type converters. In order to achieve good dynamic performance across a wide range of operating points, a control scheme based on feedback linearization is developed. This paper presents the m... [more]

The intermittence and fluctuation of renewable energy aggravate the power fluctuation of the power grid and pose a severe challenge to the frequency stability of the power system. Thermostatically controlled loads can participate in the frequency regulation of the power grid due to their flexibility. Aiming to solve the problem of the traditional control methods, which have limited adjustment ability, and to have a positive influence on customers, a deep reinforcement learning control strategy based on the framework of soft actor−critic is proposed, considering customer satisfaction. Firstly, the energy storage index and the discomfort index of different users are defined. Secondly, the fuzzy comprehensive evaluation method is applied to evaluate customer satisfaction. Then, the multi-agent models of thermostatically controlled loads are established based on the soft actor−critic algorithm. The models are trained by using the local information of thermostatically controlled loads, and... [more]

This paper presents a DC/AC converter consisting of two two-level inverters. The complex converter is built using two standard three-phase inverters: the main inverter (MI) and the auxiliary one (AI). The MI is controlled in a simple way to generate the stepped output voltage and the AI works as an active filter limiting the higher harmonics in the MI output voltage. The filtering process is based on the orthogonal space vector theory. A development and modification of the basic solution are presented here. The output voltage of the MI takes the shape of a stepped voltage comparable to the voltage generated by multilevel inverters. The AI operates as a very effective active power filter (APF) of the MI output voltage. The AI power is significantly lower in comparison to the MI power.

Microgrids deal with challenges presented by intermittent distributed generation, electrical faults and mode transition. To address these issues, to understand their static and dynamic behavior, and to develop control systems, it is necessary to reproduce their stable operation and transient response through mathematical models. This paper presents a data-driven low-order model identification methodology applied to voltage characterization in a photovoltaic system of a real campus microgrid for secondary voltage regulation. First, a literature review is presented focusing on secondary voltage modeling strategies and control. Then, experimental data is used to estimate and validate a low-order MIMO (multiple input−multiple output) model of the microgrid, considering reactive power, solar irradiance, and power demand inputs and the voltage output of the grid node. The obtained model reproduced the real system response with an accuracy of 88.4%. This model is used for dynamical analysis o... [more]

DC-DC power converters play an important role in the performance and control methods of solar power systems. Solar power converters are prone to high power losses due to intermittent irradiation and shading effects on solar photovoltaic (PV) modules. The device topology and control algorithm of a solar power converter are key factors to increase the total amount of harvested energy. In this paper, a solar power converter is proposed with a two−phase interleaved boost converter (IBC) topology and a novel maximum power point tracking (MPPT) method. The proposed MPPT controller is based on extended Kalman filtering (EKF) and it improves the tracking efficiency in both steady irradiation and partial shading conditions. The algorithm is improved with the prediction and estimation capabilities of the EKF algorithm. The proposed EKF MPPT is validated with simulations and experimentally validated by using the implemented two−phase IBC that is comprised of SiC MOSFETs. The proposed converter pr... [more]

Although brushless direct current motor (BLDCM) drives are becoming more popular in industrial and commercial applications, there are still significant difficulties and unresolved research issues that must be addressed. In BLDCM drives, commutation current ripple (CCR) and diode freewheeling during non-commutation zone (NCZ) are the major challenges. To overcome these limitations, this paper proposes a novel PWM-Model Antiseptic Control (PWM-MAC) technique to alleviate the freewheeling of the diode. The proposed PWM technique is used to alleviate the diode freewheeling in the NCZ, whereas the DCLV circuit is utilized to obtain variable DC-link voltage to address the CCR in the CZ. The MATLAB/Simulink results are included along with experimental results obtained from a laboratory prototype of 325 W. The proposed module reduces the current ripple by 31.7% and corresponding torque ripples are suppressed by approximately 32.5%. This evidences the performance of the proposed control techniq... [more]

Being the primary cause of inter-area oscillations and due to the fact that they limit the generation’s output, Low-Frequency Electromechanical Oscillations (LFEOs) represent a real threat to power system networks. Mitigating their effects is therefore crucial as it may lead to system collapse if not properly damped. As rotor angle instability is the primary cause of LFEOs, this paper presents a novel Model-Reference Adaptive Control (MRAC) scheme that enhances its stability. The proposed scheme is tested using the Single-Machine Infinite Bus (SMIB) network. The results obtained validate the proposed decentralized control architecture. The robustness of this oscillation damping controller is verified through simulations in MATLAB/SIMULINK. With Gaussian noise added to the structure of the generator to emulate small load variations responsible for the rotor angle instability, the results of the simulations show that the rotor angle remains stable. Furthermore, when subjected to faults,... [more]

Improving the stability of power systems using FACT devices is an important and effective method. This paper uses a static synchronous series compensator (SSSC) installed in a power system to smooth out inter-area oscillations. A meta-heuristic optimization method is proposed to design the supplementary damping controller and its installation control channel within the SSSC. In this method, two control channels, phase and magnitude have been investigated for installing a damping controller to improve maximum stability and resistance in different operating conditions. An effective control channel has been selected. The objective function considered in this optimization method is multi-objective, using the sum of weighted coefficients method. The first function aims to minimize the control gain of the damping controller to the reduction of control cost, and the second objective function moves the critical modes to improve stability. It is defined as the minimum phase within the design co... [more]

This paper proposes a dynamic characteristic improvement of an integrated on-board charger (OBC) using a model predictive control (MPC) method. The integrated OBC performs both battery charging and starter generator (SG) driving for engine starting in plug-in hybrid electric vehicles (PHEVs). If it performs battery charging, battery-side voltage and battery-side current are control objects which are usually controlled by using a proportional-integral (PI) controller. However, it has the disadvantage of undesirable dynamic characteristics, and gain tuning of the PI controller is necessary to properly control the voltage and current. Therefore, this paper proposes the MPC method for the dynamic characteristic improvement of integrated OBC. It can achieve not only dynamic characteristic improvement, but also robustness from the abrupt change of load impedance. By using the proposed MPC method for integrated OBC, the settling time to control the output voltage is decreased by 50% in the tr... [more]

This study proposes a broken rotor bar (BRB) fault diagnosis method for an induction motor using the sum of the weighted Fourier series coefficients squares of a complex current as a diagnosis signal. First, the sum of the squares of the Fourier series coefficients confirms the very narrow band-pass filter characteristics to derive a specific frequency component. This assists us in obtaining a BRB fault diagnosis signal that exists in a limited frequency range. Second, the magnitude of the Fourier series coefficients of the BRB fault signal is proportional to the slip frequency and load condition. A weighting factor is proposed to render the BRB fault signal irrelevant to the slip frequency and load condition. Consequently, the proposed fault diagnosis can be conducted without the slip frequency information or searching for the maximum coefficient component. Finally, the proposed fault diagnosis method is validated through experiments using a 55 kW induction motor with and without a BR... [more]

Different types of deep-hole blasting techniques are needed to solve gas drainage problems in complex and variable cases. Blasting parameters suitable for mines are selected based on the relationship between blast stress field changes and gas flow combined with field application and numerical simulation. The Datong Mine was a background to study the blast crush zone and drainage influence range following deep-hole blasting with holes laid in coal seams, which resulted in a 24% increase in gas flow in the drainage hole 6 m from the blast hole. In response to the difficulty of forming blast holes in the soft coal seam of the Yuyang Mine, drilling and blasting in the floor rock stratum adjacent to the coal seam increased the gas flow in the drainage holes by 125%. When applying the deep-hole technique with holes crossing multi-seams for gas drainage in Shiping Mine, the volume of gas drainage increases significantly with increased effective stress in the drainage hole. For example, when t... [more]

The work delineated in this paper deals with the reduced sensor-based operation of PV-DSTATCOM (Photovoltaic distribution static compensator) focusing on the voltage source inverter (VSI) switch current limiting control. In this study, the soft computing technique of PV-DSTATCOM control based on the variable leaky least mean square (VLLMS) algorithm is modified to incorporate both reduced sensor and switch current limiting schemes. DSTATCOM is predominantly introduced to improve current related power quality issues by providing non-real power (i.e., the reactive and harmonic component) of the load demand. However, during uncertain increase in the non-real power requirement at the load end due to sudden change in the load demand or any other transient conditions, the non-real current injected by the DSTATCOM may increase to a level which is beyond the current handling capacity of the DSTATCOM switches. As a consequence, the switches may become permanently damaged and, subsequently, the... [more]

The long-distance traditional belt conveyor driven by a single high-power motor has the problems of excessive tension increments and sharp fluctuations in speed and tension. This paper designs a distributed permanent magnet direct drive belt conveyor system. The dynamic model of the conveyor belt unit and the permanent magnet motor is analyzed. The multi-motor ring coupling control strategy and the double sliding film direct torque control strategy of the belt conveyor system are formulated. The mechanical-electrical coupling dynamic model of the belt conveyor system is built. Using MATLAB/Simulink modeling and simulation, the vector control strategy and electromechanical coupling dynamic behavior of the traditional belt conveyor system and the distributed permanent magnet direct drive belt conveyor system under light load start-up and local variable load operation conditions are studied. The results show that: the distributed permanent magnet direct drive belt conveyor system signific... [more]

Digital hydraulic drives are known for their superior efficiency, power density, and robustness. Such advantages make them an attractive alternative (to electric drives) for actuation of exoskeleton devices. This work presents development of a prototype for such a digital hydraulically driven knee exoskeleton and its experimental testing. The device uses two miniature hydraulic cylinders and a novel mechanism to translate the linear motion to rotary motion. The device is controlled via a passive control method in the stance phase and a simplified model predictive control method in the swing phase. In this work, the design of the exoskeleton device is optimized with respect to compactness and weight. Next, the features of the design are further refined to ensure that the device is able to support the operational loads. This design is then realized into a prototype with a mixture of inhouse manufactured parts and procured components. Finally, via experimental tests, the performance of th... [more]

Solar energy is one of the most important renewable energy sources. Photovoltaic (PV) systems, as the most crucial conversion medium for solar energy, have been widely used in recent decades. For PV systems, faults that occur during operation need to be diagnosed and dealt with in a timely manner to ensure the reliability and efficiency of energy conversion. Therefore, an effective fault diagnosis method is essential. Artificial neural networks, a pivotal technique of artificial intelligence, have been developed and applied in many fields including the fault diagnosis of PV systems, due to their strong self-learning ability, good generalization performance, and high fault tolerance. This study reviews the recent research progress of ANN in PV system fault diagnosis. Different widely used ANN models, including MLP, PNN, RBF, CNN, and SAE, are discussed. Moreover, the input attributes of ANN models, the types of faults, and the diagnostic performance of ANN models are surveyed. Finally,... [more]