An active magnetic bearing (AMB) is a kind of high-performance bearing that uses controllable electromagnetic force to levitate the rotor. Its control performance directly affects the operation characteristics of high-speed motors and other electromechanical products. The magnetic bearing control model is nonlinear and difficult to control. Sliding mode control algorithm can be used in the magnetic bearing control system, but the traditional sliding mode control has the problem of high-frequency chattering, which affects the operation stability of magnetic bearings. Based on the second-order sliding mode control algorithm, a new second-order sliding mode controller for active magnetic bearing control was designed, and the stability of the designed sliding mode control law was proven by Lyapunov criterion. On the basis of the established active magnetic bearing control model, the numerical analysis of the designed controller was carried out, and the control effect was compared with that... [more]

In past decades, many manufacturing enterprises have followed the business model of productivity maximization, in which achieving maximum profit using limited resources is the business goal. Although this industrial strategy may make profit, it can be detrimental to the long-term social welfare. Industrial regulations require that enterprise should be responsible for the natural environment and the health of their employees while achieving their business goals. This presents a complex problem involving the trade-off between ecology and economy so that an efficient strategic decision support method is needed. Since the value-added process of a manufacturing company encompasses both desirable and undesirable outputs, in this study we use a data envelopment analysis-based model to measure performance sustainability. In it, energy, water, and manpower are considered as input resources, meanwhile CO2 emissions, wasted water, chemical compounds, and laborers’ injuries are considered as bad o... [more]

Failures of the gas turbine hot components often cause catastrophic consequences. Early fault detection can detect the sign of fault occurrence at an early stage, improve availability and prevent serious incidents of the plant. Monitoring the variation of exhaust gas temperature (EGT) is an effective early fault detection method. Thus, a new gas turbine hot components early fault detection method is developed in this paper. By introducing a priori knowledge and quantum particle swarm optimization (QPSO), the exhaust gas temperature profile continuous distribution model is established with finite EGT measuring data. The method eliminates influences of operating and ambient condition changes and especially the gas swirl effect. The experiment reveals the presented method has higher fault detection sensitivity.

PV hosting capacity (PVHC) analysis on a distribution system is an attractive technique that emerged in recent years for dealing with the planning tasks on high-penetration PV integration. PVHC uses various system performance indices as judgements to find an available amount of PV installation capacity that can be accommodated on existing distribution system infrastructure without causing any violation. Generally, approaches for PVHC assessments are implemented by iterative power flow calculations with stochastic PV deployments so as to observe the operation impacts for PV installation on distribution systems. Determination of the stochastic PV deployments in most of traditional PVHC analysis methods is automatically carried out by the program that is using random selection. However, a repetitive problem that exists in these traditional methods on the selection of the same PV deployment for a calculation was not previously investigated or discussed; further, underestimation of PVHC res... [more]

We apply deep reinforcement learning to active closed-loop control of a two-dimensional flow over a cylinder oscillating around its axis with a time-dependent angular velocity representing the only control parameter. Experimenting with the angular velocity, the neural network is able to devise a control strategy based on low frequency harmonic oscillations with some additional modulations to stabilize the Kármán vortex street at a low Reynolds number Re=100. We examine the convergence issue for two reward functions showing that later epoch number does not always guarantee a better result. The performance of the controller provide the drag reduction of 14% or 16% depending on the employed reward function. The additional efforts are very low as the maximum amplitude of the angular velocity is equal to 8% of the incoming flow in the first case while the latter reward function returns an impressive 0.8% rotation amplitude which is comparable with the state-of-the-art adjoint optimization r... [more]

Recent research has enabled the integration of traditional Volt-VAr Control (VVC) resources, such as capacitor banks and transformer tap changers, with Distributed Energy Resources (DERs), such as photo-voltaic sources and energy storage, in order to achieve various Volt-VAr Optimization (VVO) targets, such as Conservation Voltage Reduction (CVR), minimizing VAr flow at the transformer, minimizing grid losses, minimizing asset operations and more. When more than one target function can be optimized, the question of multi-objective optimization is raised. In this work, a general formulation of the multi-objective Volt-VAr Optimization problem is proposed. The applicability of various multi-optimization techniques is considered and the operational interpretation of these solutions is discussed. The methods are demonstrated using a simulation on a test feeder.

The applicability of organic Rankine cycle (ORC) technology to waste heat recovery (WHR) is currently experiencing growing interest and accelerated technological development. The utilization of low-to-medium grade thermal energy sources, especially in the presence of heat source intermittency in applications where the thermal source is characterized by highly variable thermodynamic conditions, requires a control strategy for off-design operation to achieve optimal ORC power-unit performance. This paper presents a validated comprehensive model for off-design analysis of an ORC power-unit, with R236fa as the working fluid, a gear pump, and a 1.5 kW sliding vane rotary expander (SVRE) for WHR from the exhaust gases of a light-duty internal combustion engine. Model validation is performed using data from an extensive experimental campaign on both the rotary equipment (pump, expander) and the remainder components of the plant, namely the heat recovery vapor generator (HRVH), condenser, rese... [more]

Power electronic converters, together with their loads, sources, and controls, form a coupled system that includes many nonlinear interactions, for instance due to pulse-width modulation (PWM) and feedback control. In this paper we develop a complete, nonlinear modeling approach for voltage-source inverters in the frequency domain, taking into account the harmonic components introduced into the system from the inputs and from the nonlinear digital PWM. The most important contribution is a method for analyzing how these harmonics propagate through the nonlinear system in steady state. To enable this, an analytic model of PWM with arbitrary, multiple-frequency input is necessary. A revised model of Asymmetrical regularly-sampled double-edge PWM (AD-PWM) is proposed and its incorporation into the system model regarding sampling effects is discussed. The resulting nonlinear equation system is numerically and simultaneously solved, yielding the spectra of all relevant signals in the convert... [more]

Recently, many wastewater treatment plants (WWTPs) have had to deal with serious problems related to the restrictive requirements regarding the effluent quality, as well as significant energy consumption associated with it. In this situation, mainstream deammonification and/or shortened nitrification-denitrification via nitrite (so-called “nitrite shunt”) is a new promising strategy. This study shows the mechanisms and operating conditions (e.g., dissolved oxygen (DO) concentration, temp.), leading to the complete domination of ammonium oxidizing bacteria (AOB) over nitrite oxidizing bacteria (NOB) under aerobic conditions. Its successful application as shortcut nitrification in the sequencing batch reactor (SBR) technology will represent a paradigm shift for the wastewater industry, offering the opportunity for efficient wastewater treatment, energy-neutral or even energy-positive facilities, and substantial reductions in treatment costs. In this study, under low and moderate temperat... [more]

With the increasing penetration of distributed photovoltaics (PVs) in active distribution networks (ADNs), the risk of voltage violations caused by PV uncertainties is significantly exacerbated. Since the conventional voltage regulation strategy is limited by its discrete devices and delay, ADN operators allow PVs to participate in voltage optimization by controlling their power outputs and cooperating with traditional regulation devices. This paper proposes a decoupling rolling multi-period reactive power and voltage optimization strategy considering the strong time coupling between different devices. The mixed-integer voltage optimization model is first decomposed into a long-period master problem for on-load tap changer (OLTC) and multiple short-period subproblems for PV power by Benders decomposition algorithm. Then, based on the high-precision PV and load forecasts, the model predictive control (MPC) method is utilized to modify the independent subproblems into a series of subprob... [more]

In this study, we propose a higher order mining approach that can be used for the analysis of real-world datasets. The approach can be used to monitor and identify the deviating operational behaviour of the studied phenomenon in the absence of prior knowledge about the data. The proposed approach consists of several different data analysis techniques, such as sequential pattern mining, clustering analysis, consensus clustering and the minimum spanning tree (MST). Initially, a clustering analysis is performed on the extracted patterns to model the behavioural modes of the studied phenomenon for a given time interval. The generated clustering models, which correspond to every two consecutive time intervals, can further be assessed to determine changes in the monitored behaviour. In cases in which significant differences are observed, further analysis is performed by integrating the generated models into a consensus clustering and applying an MST to identify deviating behaviours. The vali... [more]

An integrated electrical and thermal residential renewable energy system consisting of solar thermal collectors, gas boiler, fuel cell combined heat and power, a photovoltaic system with battery, inverter, and thermal storage for a single-family house of Sonnenhaus standard is investigated with a model predictive controller (MPC). The main focus of this article is to define a multi-objective mathematical function, develop a coupled simulation framework for the nonlinear time-varying deterministic discrete-time problem of the energy system using TRNSYS and MATLAB. With the developed methodology, a sensitivity analysis of maximum optimization time, swarm (or population or mesh) size of a typical spring day and a typical summer day assuming a 100% accurate weather and load forecast with three different algorithms: particle swarm optimization (PSO), genetic algorithm (GA) and global pattern search (GPS) are analyzed. Finally, the obtained results are compared with a status quo controller.... [more]

The interconnection of dynamic subsystems that share limited resources are found in many applications, and the control of such systems of subsystems has fueled significant attention from scientists and engineers. For the operation of such systems, model predictive control (MPC) has become a popular technique, arguably for its ability to deal with complex dynamics and system constraints. The MPC algorithms found in the literature are mostly centralized, with a single controller receiving the signals and performing the computations of output signals. However, the distributed structure of such interconnected subsystems is not necessarily explored by standard MPC. To this end, this work proposes hierarchical decomposition to split the computations between a master problem (centralized component) and a set of decoupled subproblems (distributed components) with activation constraints, which brings about organizational flexibility and distributed computation. Two general methods are considere... [more]

To solve the contradiction between dynamic performance and steady-state performance of the robot system, a smooth-switching control strategy is proposed. By combining robot and motor model, the complete model of the robot driving system is established. The single-loop Feedback Linearization (FL) controller and Port-Controlled Hamiltonian (PCH) controller based on the complete model are derived to ensure the rapidity and stability of the system respectively. A smooth-switching function based on position error is designed. It can ensure the smooth-switching between two controllers and avoid the instability caused by switch-switching. The proposed algorithm can make the robot system have good dynamic and steady performance. Simulation and experiment results demonstrate the effectiveness of the smooth-switch control strategy.

This article presents a remote management architecture of an unmanned aerial vehicles (UAVs) fleet to aid in the management of solar power plants and object tracking. The proposed system is a competitive advantage for sola r energy production plants, due to the reduction in costs for maintenance, surveillance, and security tasks, especially in large solar farms. This new approach consists of creating a hardware and software architecture that allows for performing different tasks automatically, as well as remotely using fleets of UAVs. The entire system, composed of the aircraft, the servers, communication networks, and the processing center, as well as the interfaces for accessing the services via the web, has been designed for this specific purpose. Image processing and automated remote control of the UAV allow generating autonomous missions for the inspection of defects in solar panels, saving costs compared to traditional manual inspection. Another application of this architecture r... [more]

This paper presents the power factor control of a permanent magnet synchronous wind generator (PMSG) wind turbine using a phase voltage-oriented control (PVOC) scheme, which is different from the conventional rotor flux-oriented control (RFOC) method and without using a rotor position sensor or sensorless estimator. The proposed control system is operated in two separately synchronously rotating d-q frames. One is for a phase-locked loop (PLL) and the other is for the PVOC current control loop. A PI controller functioned as a low-pass filter in the PLL loop is designed for extracting the phase voltage angle for the coordinate transformation between the stationary α-β frame and the synchronously rotating d-q frame in the PVOC control loop. The d-q modeling of the PMSG with the three-phase voltage vector aligned on the d-axis is then derived and based on which an another PI controller followed by decoupling control is designed, so that the three-phase currents are in phase with the three... [more]

This paper presents a methodology for enhancing community resilience through optimal renewable resource allocation and load scheduling in order to minimize unserved load and thermal discomfort. The proposed control architecture distributes the computational effort and is easier to be scaled up than traditional centralized control. The decentralized control architecture consists of two layers: The community operator layer (COL) allocates the limited amount of renewable energy resource according to the power flexibility of each building. The building agent layer (BAL) addresses the optimal load scheduling problem for each building with the allowable load determined by the COL. Both layers are formulated as a model predictive control (MPC) based optimization. Simulation scenarios are designed to compare different combinations of building weighting methods and objective functions to provide guidance for real-world deployment by community and microgrid operators. The results indicate that t... [more]

Literature about the importance of renewable energy resources, including wind and solar energy, is becoming increasingly important; however, these energy sources are unstable and volatile in nature, and are usually integrated with conventional energy sources, such as hydropower, forming hybrid power generation systems that maintain a stable grid. Short-term changes in wind speed or solar radiation intensity have a great impact on the stability of hybrid systems, and have been reported in the literature. However, reliable models to manage such systems are lacking, and previous studies have regarded the hour scale as the minimum baseline for systematic change. In this article, hybrid power systems are proposed that are controlled on very short time intervals. The results of a feasibility analysis of the proposed model indicate the viability of complementary hybrid systems in controlling and maintaining the stability, which are subjected to short durations of fluctuations in wind or solar... [more]

With the continuous development of new energy, there is more and more research on step-up inverters in photovoltaic and wind power generation systems. The Z-source inverter has become a research hotspot because of its small output THD (Total Harmonic Distortion) and high reliability. However, the traditional Z-source inverters cannot meet the higher boost requirements of new energy power generation. The quasi-z-source inverter with stronger boosting ability came into being. The high step-up Z-source inverters presented in existing literature is only focused on one or several topologies and lacks a comparative analysis on different topologies. Based on the quasi-Z-source inverter, this paper proposes a family of quasi-z-source inverters with a coupled inductor. The required voltage gain can be obtained by changing the turns ratio of the coupled inductor, which provides a new control variable for the system and makes the design of the system becomes more flexible. Through the analysis an... [more]

In this paper, the impact of transformer turns ratio on the performance of the quasi-Z-source galvanically isolated DC-DC converters is studied. Embedded buck−boost functionality enables these converters to regulate the input voltage and load in a wide range, which makes them suitable for such demanding application as photovoltaic microconverters. The isolation transformer here plays a central role as its turns ratio defines the point of transition between the boost and buck modes and overall capability of the converter to regulate the input voltage in a wide range at high efficiency. The studied quasi-Z-source galvanically isolated DC-DC converter is benchmarked in terms of power loss of components and weighted power conversion efficiency for three different turns ratios of isolation transformer to achieve the best and optimized turns ratio lead to the efficient operation. Operation in a wide range of input voltage at high efficiency is the main criterion for assessing the effect of t... [more]

Between 60% and 70% of the total energy load of a house or office occurs through the exteriors of the building, and in the case of offices, heat loss from windows and doors can approach 40%. A need for glass that can artificially control the transmittance of visible light has therefore emerged. Smart windows with suspended particle device (SPD) film can reduce energy consumption by responding to environmental conditions. To measure the effect of SPD windows on the energy requirements for cooling and heating in Korea, we installed a testbed with SPD windows. With TRNSYS18, the comparison between measurements and simulation has been made in order to validate the simulation model with respect to the modeling of an SPD window. Furthermore, the energy requirements of conventional and SPD-applied windows were compared and analyzed for a standard building that represented an actual office building. When weather for the city of Anseong and a two-speed heat pump were used to verify the simulati... [more]

The paper deals with the main prospects and challenges of radical transformations of electric power systems (EPSs) with changes in their structure and properties conditioned by wide use of innovative energy-related technologies and digitalization and intellectualization of system operation and control. Structural trends of EPS development are the focus of the analysis. Consideration is given to changes in EPS properties driven by the use of new technologies, to the problems of system flexibility and to its enhancement. EPS “resiliency” and “survivability” notions are subjected to comparison. The main factors favoring the formation of future EPSs to cyber-physical systems are discussed. Objective trends of EPS control and protection system development are under consideration.

Control of AC/DC pulse-width modulation (PWM) power electronic converter, referred to as “AC/DC PWM converter”, is vital to the efficient regulation of power flow between AC and DC parts of a hybrid microgrid. Given the importance of such converters in AC/DC microgrids, this paper investigates the design of fault-tolerant control for AC/DC PWM converters in the presence of microgrid faults. In particular, two novel fault-tolerant schemes based on fuzzy logic and model predictive control are proposed and implemented in an advanced hybrid microgrid benchmark in MATLAB/Simulink environment. The considered hybrid microgrid consists of dynamic loads and distributed energy resources including solar photovoltaic arrays, wind turbines, and battery energy storage systems. The proposed schemes especially target the fault effects due to common power-loss malfunctions in solar photovoltaic arrays in the presence of microgrid uncertainties and disturbances. The effectiveness of proposed fault-toler... [more]

The paper presents a controller design for grid-connected inverters (GCI) with very small dc-link capacitance that are coupled to the grid via an LCL filter. The usual controller designs would fail and result in instability. The proposed controller has a cascaded structure with a current controller as inner control loop and an outer dc-link voltage controller. The controller design is performed in discrete time and it is based on a detailed stability analysis of the dc-link voltage controller to determine the controller parameters which guarantee stability for all operating points. The inner loop is a state-feedback current controller that is designed based on the discrete linear-quadratic regulator (DLQR) theory. An additional integral error feedback assures steady-state accuracy of the current control loop. The simulation and experimental results validate performance and stability of proposed controller design.

In concentrated solar power technology, the precise shape of the reflective surfaces is crucial for efficiency. Considering the geometry and size of a parabolic trough collector, measuring the actual shape is not trivial and some techniques can only be adopted during the assembly operations, evaluating only the manufacturing and alignment processes. The method proposed and tested in this work exploits a laser scanner-based three-dimensional digitization technique that can be used without any marker or other tools, and is attached to the structure. This technique is particularly suitable for assessing the behavior and the optical efficiency of the collectors under load and for validating a finite element model of the structure. The method defines the shape of the parabolic surface by collecting a 3D point cloud of the parabolic surface using a laser scanner. The measured form can then be compared with the ideal shape obtained from a finite element analysis of the structure subject to th... [more]