The uncertainty brought about by the high proportion of distributed generations poses great challenges to the operational safety of novel distribution systems. Therefore, this paper proposes an online reactive power and voltage control method that integrates source−load uncertainty and a mechanism−data hybrid drive (MDHD) model. Based on the concept of a mechanism and data hybrid drive, the mechanism-driven deterministic reactive power optimization strategy and the stochastic reactive power optimization strategy are used as training data. By training the data-driven CNN−GRU network model offline, the influence of source−load uncertainty on reactive power optimization can be effectively assessed. On this basis, according to the online source and load predicted data, the proposed hybrid-driven model can be applied to quickly obtain the reactive power optimization strategy to enable fast control of voltage. As observed in the case studies, compared with the traditional deterministic and s... [more]

Industrial robots have a key role in the concept of Industry 4.0. On the one hand, these systems improve quality and productivity, but on the other hand, they require a huge amount of energy. Energy saving solutions have to be developed and applied to provide sustainable production. The purpose of this research is to develop the optimal control strategy for industrial robots in order to minimize energy consumption. Therefore, a case study was conducted for the development of two control strategies to be applied to the RV-2AJ Mitsubishi robot arm with 5 DOF, where the system is a nonlinear one. The first examined controller is the classical linear proportional integral derivative (PID) controller, while the second one is the linear model predictive control (MPC) controller. In our study, the performances of both the classical PID model and the linear MPC controller were compared. As a result, it was found that the MPC controller in the execution of the three defined reference trajectori... [more]

The article is devoted to solving the problem of managing the mode parameters of an urban electrical network in case of a discrepancy between the actual electrical load and the specific load. Such an issue leads to a deviation of the parameters, in particular, voltage asymmetry in phases due to current asymmetry. To optimize the mode parameters, it is required that the effective value of the electrical load corresponds as much as possible to the values of the specific electrical load. This depends on the following: actual power consumption, external (climatic and meteorological) factors, internal factors (structural design of residential buildings, uneven load when distributed over the phases of three-phase lines and inputs, different number of electrical receivers for consumers), and the provision of consumers with other sources of energy (both gas and heat supply, and hot water supply). To establish the influencing factors on the actual power consumption, it is proposed to generalize... [more]

At present, most of the winding fault detections of transformers use offline methods, which require the entire line to be powered off or after the transformer has been shut down due to a serious fault, and they cannot detect the running status of the windings in real time and online. Since the transformer will be impacted by VFTO during operation, the VFTO is used as the excitation, and the basic principle of the frequency response method is used to propose an online detection method of transformer winding deformation based on VFTO characteristics. The finite element software is used to calculate the equivalent circuit parameters of normal and deformed windings, and the equivalent circuit model of the transformer windings before and after deformation is established. Due to the uncertainty of the VFTO waveform, combined with the frequency response method, the VFTO waveform is injected into the transformer winding health, and the frequency response curve is obtained from the deformed equ... [more]

Bearingless switched reluctance motor (BSRM) adopts a doubly salient structure without windings on the rotor. BSRMs have the advantages of high rate of fault tolerance and simple structure, high power, super high speed and strong adaptability. They have broad application prospects in aerospace, flywheel energy storage, new energy and biomedical fields. Firstly, the suspension operation mechanism of a conventional double winding BSRM is described in this paper. The coupling between torque and suspension force is analyzed with a finite element method. On this basis, from the perspective of magnetic circuit optimization of the torque system and suspension system, the magnetic circuit design, decoupling mechanism and performance characteristics of self-decoupled BSRMs with different topological structures are described centering on the self-decoupled topology form of the BSRM. Finally, the study and development of BSRMs in the future are prospected based on the research status.

A review of the control laws (models) of alternating current arc steelmaking furnaces’ (ASF) electric modes (EM) is carried out. A phase-symmetric three-component additive fuzzy model of electrode movement control signal formation is proposed. A synthesis of fuzzy inference systems based on the Sugeno model for the implementation of the proposed additive three-component fuzzy law of arc length control is performed. A structural computer Simulink model of the EM control system in a high-power arc steelmaking furnace of the DSP-200 type with an ARDM-T-12 arcs power regulator is created. Computer research into control dynamics indicators under the influence of deterministic perturbations and also integral indicators of energy efficiency when handling stationary random arc lengths fluctuations (corresponding to various technological stages of melting) are carried out. A comparative analysis of dynamics indicators, energy efficiency, and electromagnetic compatibility of the proposed fuzzy a... [more]

One major cost of improving the automotive fuel economy while simultaneously reducing tailpipe emissions is increased powertrain complexity. This complexity has consequently increased the resources (both time and money) needed to develop such powertrains. Powertrain performance is heavily influenced by the quality of the controller/calibration. Since traditional control development processes are becoming resource-intensive, better alternate methods are worth pursuing. Recently, reinforcement learning (RL), a machine learning technique, has proven capable of creating optimal controllers for complex systems. The model-free nature of RL has the potential to streamline the control development process, possibly reducing the time and money required. This article reviews the impact of choices in two areas on the performance of RL-based powertrain controllers to provide a better awareness of their benefits and consequences. First, we examine how RL algorithm action continuities and control−act... [more]

The automation strategies currently used in HVAC systems do not control the system temperature variables (supplied air, chilled, and condensation water temperatures) in an optimized way. Normally, these temperatures are fixed in design conditions, or vary according to the weather conditions. However, studies demonstrate that adequate control of these three temperatures can provide significant reductions in the energy consumption of the air conditioner system. Therefore, this work analyzes the benefits of individualized and integrated automation of these three variable temperatures in different tropical and subtropical weather conditions through computer simulation for a typical commercial building. The results of integrated automation show savings in consumption between 5.03% and 19.68% compared to a fixed control, and between 3.22% and 8.21% compared to a weather-based control alone, showing that the integrated strategies are better than both models adopted as market benchmarks.

Collective heating systems have multiple end-users with time-varying, often different temperature demands. There are several concepts catering to this, e.g., multi-pipe networks and 2-pipe networks with or without decentralised booster systems. In this study, we focus on 2-pipe networks with a changing supply temperature by smart use of decentralised storage. By grouping high-temperature demands, the average supply temperature can be lowered during large parts of the day, which is beneficial for system efficiency. The actual energy-saving potential, however, can be case-specific and is expected to depend on design choices and implemented control strategies. In this paper, these dependencies are assessed and identified by implementing two optimised rule-based control strategies, providing in such a way a bench-mark for other control strategies. The results show that grouping yields energy savings of up to 36% at similar peak demand as with conventional control strategies. The energy-sav... [more]

The structure of large biomass circulating fluidized bed (BCFB) boilers is complex, and control schemes for coal-fired boilers cannot be simply applied to biomass boilers. Multivariable coupling and operational disturbances are also common issues. In this study, a state space model of a 130 t/h BCFB boiler was established under different operating conditions. Using the 100% operating point as an example, a model predictive controller was designed and tested under output disturbance and input disturbance conditions. The results show that the predictive control system designed in this study has a fast response speed and good stability.

Compared to conventional façades, adaptive façades (AFs) can adjust their properties in response to environmental changes and user requirements. Often performed through the integration of actuators, sensors, and control units, this provides benefits such as reduced energy consumption in buildings but also increases the complexity of the façade design. To efficiently deal with the higher complexity, this article aims to provide suitable decision support for the early design phase, identify suitable design goals, and compare these to previously implemented Afs (make-or-buy decision). There is particular focus on the AF-specific characteristics, as these are new compared to well-known conventional façades. To systematically develop decision support, requirements are identified in expert interviews and the literature, and the current state of the art is evaluated against these. Research gaps found in current methods are addressed in this article, and continuous decision support is develope... [more]

The evaluation of pore structure is critical in understanding reservoir characteristics. This study aims to analyze the microscopic pore structure characteristics of tight reservoirs from various provenances through physical property analysis, casting thin sections, scanning electron microscopy (SEM), and constant−rate mercury injection. The pore throat parameters of the Chang 7 reservoir were analyzed and compared to those of the Xin’anbian and the Heshui areas. The results show that intergranular pores dominate the pore type of the Chang 7 reservoir in the Xin’anbian area, followed by feldspathic dissolution pores, with high-necked and tubular throat content caused by weak compaction and dissolution, respectively. On the other hand, feldspar dissolution pores dominate the pore type of the Chang 7 reservoir in the Heshui area, followed by intergranular pores, with a high content of tube−bundle throats caused by dissolution and flake−bent flake throats caused by compaction. The differe... [more]

Energy in microgrids (MGs) can now be generated from a variety of renewable sources, but their effective and sustainable use is dependent on electrical energy storage (EES) systems. Consequently, the expansion of MGs is greatly reliant on EES systems. The high infiltration of electric vehicles (EVs) causes some problems for the smooth functioning of the electric power system. However, EVs are also able to offer ancillary services, such as energy storage, to power systems. The research presented in this paper aims to develop a novel frequency regulation (FR) approach for biogas diesel engines (wind), the organic Rankine cycle (ORC), and solar-based two-area islanded microgrids with EVs in both areas. This article discusses the introduction of a fuzzy logic controller (FLC) for FR with scaled factors configured as proportional integral (PI) and proportional derivative with filter (PDF), i.e., a FLC-SF-PI-PDF controller. A recently created modified dragonfly algorithm is used to determine... [more]

This research work aims to develop a fault detection and performance monitoring system for a photovoltaic (PV) system that can detect and communicate errors to the user. The proposed system uses real-time data from various sensors to identify performance problems and faults in the PV system, particularly for encapsulation failure and module corrosion. The system incorporates a user interface that operates on a micro-computer utilizing Python software to show the detected errors from the PV miniature scale system. Fault detection is achieved by comparing the One-diode model with a controlled state retrieved through field testing. A database is generated by the system based on acceptable training data and it serves as a reference point for detecting faults. The user is notified of any deviations based on the threshold value from the training data as an indication of an error by the system. The system offers real-time monitoring, easy-to-understand error messages, and remote access capabi... [more]

Hydrogen is attracting attention as a good energy-storage medium for renewable energy. Among hydrogen production technologies using renewable energy, water electrolysis is drawing attention as a key technology for green hydrogen production using renewable energy. In particular, polymeric electrolyte membrane water electrolysis systems have several advantages compared to other types of water electrolysis technologies, such as small size and mass, high efficiency, low operating temperature, and low power consumption. However, until now, proton-exchange membrane (PEM) water electrolysis systems have not been reliable. In this study, system failure diagnosis techniques were presented among the various methods for improving reliability. We developed PEM water electrolysis stack models and system models to predict the performance of the system and analyze the dynamic properties using MATLAB/Simulink® 2018a, which have been validated under various conditions. The developed dynamic characteris... [more]

Over the past few decades, the electric power industry evolved in response to growing concerns about climate change and the rising price of fossil fuels. The usage of renewable energy sources (RES) rose as a remedy for these problems. The increased penetration of RES in the existing generation system increased the need for an intelligent energy management system (EMS) so that the system can operate in any possible circumstances. Many sectors of society, including the education sector, are working to realize the importance of this sustainable energy system. This paper reviews the process of selecting an efficient control technique for continuous power flow from different RES to meet the load demand requirement using an enhanced model predictive control (MPC)-based EMS framework. This EMS is a software platform to provide fundamental support services and applications to deliver the functionality needed for the effective operation of electrical generation and transmission facilities to en... [more]

Classic algorithms show high performance in tracking the maximum power point (MPP) of photovoltaic (PV) panels under uniform irradiance and temperature conditions. However, when partial or complex partial shading conditions occur, they fail in capturing the global maximum power point (GMPP) and are trapped in one of the local maximum power points (LMPPs) leading to a loss in power. On the other hand, intelligent algorithms inspired by nature show successful performance in GMPP tracking. In this study, an MPPT system was set up in MATLAB/Simulink software consisting of six groups of serially connected PV panels, a DC-DC boost converter, and load. Using this system, the cuckoo search (CS) algorithm, the modified incremental conductivity (MIC) algorithm, the particle swarm optimization (PSO) algorithm, and the grey wolf optimization (GWO) algorithm were compared in terms of productivity, convergence speed, efficiency, and oscillation under complex shading conditions. The results showed th... [more]

In this study, the load frequency control of a two-area thermal generation system based on renewable energy sources is considered. When solar generation is used in one of the control areas, the system becomes nonlinear and complicated. Zero deviations in the frequencies and the flow of power through the tie lines are achieved by considering load disturbances. A novel grey wolf optimizer, which is a metaheuristic algorithm motivated by grey wolves is utilized for tuning the controller gains. The proportional, integral, and derivative gains values are optimized for the two-area Solar integrated Thermal Plant (STP). As the load connected to the system varies continuously with time, random load variation is also applied to observe the effectiveness of the proposed optimization method. Sensitivity analyses have also been adopted with the deviation in the time constants of different systems. Inertia constant variations of both areas are considered from −25% to +25%, with or without STP. The... [more]

In Wireless Network Control System (WNCS), a study approach is relevant for the development and analysis of control strategies that provide the operation of dynamic systems. Among the real characteristics of the communication channels, a packet loss is one of the main deficiencies present in the transmission of data in a wireless network. For a dynamic system in the presence of losses, a filtering technique makes it possible to estimate system states using process output measurements and to mitigate a performance drop. It is important to study packet losses in Wireless Network Control Systems because packet loss can severely degrade the network performance. Wireless networks are particularly vulnerable to packet loss due to factors such as interference, fading and signal attenuation. The present work analyzed the behavior of a real WNCS plant at different levels of packet loss using the IEEE 802.15.4 protocol. Also, we propose a compensation model for packet loss using the Kalman filte... [more]

The marine energy (ME) industry historically lacked a standardized data processing toolkit for common tasks such as data ingestion, quality control, and visualization. The marine and hydrokinetic toolkit (MHKiT) solved this issue by providing a public software deployment (open-source and free) toolkit for the ME industry to store and maintain commonly used functionality for wave, tidal, and river energy. This paper demonstrates an initial model verification study in MHKiT. Using Delft3D, a numerical model of the Tanana River Test Site (TRTS) at Nenana, Alaska was created. Field data from the site was collected using an Acoustic Doppler Current Profiler (ADCP) at the proposed Current Energy Converter (CEC) locations. MHKiT is used to process model simulations from Delft3D and compare them to the transect data from the ADCP measurements at TRTS. The ability to use a single tool to process simulation and field data demonstrates the ease at which the ME industry can obtain results and coll... [more]

This paper presents a comprehensive study of model-based fault diagnosis (FD) and a fault-tolerant control (FTC) scheme for sensor and actuator faults of turbojet engines. For actuator FD, an unbiased estimation scheme with a modified Kalman filter (KF) was developed. For sensor FD, two approaches, the generalized likelihood ratio with robust KF and the pseudo actuator model with modified KF, were investigated in a comparative study. For fault detection and isolation, test statistics are commonly employed to detect fault behavior. For FTC, integral-type sliding mode control using control reconfiguration and the reconstruction of the sensor signal was adopted with the FD schemes. The effectiveness of the employed methods was demonstrated in this study and discussed with numerical simulations.

A typical feature of shale gas reservoirs is that they contain a significant amount of adsorbed gas. The evaluation and prediction of adsorbed gas play important roles in shale gas exploration and development. However, the presence of water in shale reservoirs makes this work more difficult. In recent years, research related to the occurrence and distribution of water in shales and its effect on methane adsorption have become a prominent issue. In this paper, the factors controlling water in shale nanopores and its influence on methane adsorption were systematically reviewed. It is revealed that the connate water content in shales and their water absorption capacity vary widely, and both are mainly related to the organic matter contents and properties and mineral compositions. The water absorption capacity of organic matter in shales is mainly affected by its nanopore content, structure and surface chemical properties (such as the type and amount of oxygen-containing functional groups)... [more]

Commercial buildings consume approximately 1.9 EJ of energy in the United States, 50% of which is for heating, cooling, and lighting applications. It is estimated that windows contribute up to 34% of the energy used for heating and cooling. However, window retrofits are not often undertaken to increase energy efficiency because of the high cost and disruptive nature of window installation. Highly efficient window technologies would also need shading devices for glare prevention and visual comfort. An automated window shading system with an appropriate control strategy is a technology that can reduce energy demand, maintain occupant comfort, and enhance the aesthetics and privacy of the built environment. However, the benefits of the automated shades currently used by the shading industry are not well studied. The topic merits an analysis that will help building owners, designers and engineers, and utilities make informed decisions using knowledge of the impact of this technology on ene... [more]

This paper presents an alternative approach to the flow control of an oxidizer in a proton exchange membrane (PEM) fuel cell system in which pure oxygen is the gas supplied to the cathode channel of the stack. The proposed oxygen flow control is implemented based on information about the current drawn from the fuel cell stack and the voltage variation in the stack. This information and a fuzzy-logic-based control algorithm are used to increase oxygen utilization in a PEM fuel cell system without a recirculation system in relation to the control, in which the oxygen flow rate is determined only in proportion to the current drawn from the stack. To verify the validity of the adopted assumptions, simulation tests of the proposed fuzzy control algorithm were conducted, for which parameters were adopted arbitrarily and determined with help of genetic algorithms. For simulation research, the proposed empirical mathematical model was used, which describes the mathematical relationship between... [more]

Load switches in power systems may cause oscillations in active and reactive power flow. Such oscillations can be damped by synthetic inertia provided by smart inverters providing power from DC sources such as photovoltaic or battery storage. However, AC current provided by inverters is inherently non-sinusoidal, making measurements of active and reactive power subject to harmonic distortion. As a result, transient effects due to load switching can be obscured by harmonic distortion. An RLC circuit serves as a reference load. The oscillation caused by switching in the load presents as a dual-sideband suppressed-carrier signal. The carrier frequency is available via voltage data but the phase is not. Given a group of candidate signals formed from phase voltages, an algorithm based on Costas Loop that can quickly quantify the phase difference between each candidate and carrier (thus identifying the best signal for demodulation) is presented. Algorithm functionality is demonstrated in the... [more]