In this paper, a Fractional Order Power System controller (FOPSS) is designed, and its performance and robustness are experimentally evaluated by tests in a 10 kVA laboratory scale power system. The FOPSS design methodology is based on the tuning of an additional design variable, namely the fractional order of the controller transfer function. This design variable is tuned aiming to obtain a tradeoff between satisfactory damping of dominant oscillating mode and improved closed-loop system robustness. For controller synthesis, transfer function models were estimated from data collected at selected operating points and subsequently applied for the controller design and for obtaining upper bounds estimates on the operating-point depends on plant uncertainties. The experimental results show that the FOPPS was able to obtain a robust performance for the considered set of the power system operating conditions.

Finite-control-set model predictive current control (FCS-MPCC) has been widely investigated in the field of motor control. When the discrete motor prediction model is not obtained accurately, prediction error often occurs, which can result in improper determinations of optimal voltage vectors and can further affect the control performance of motor systems. However, papers evaluating the motor control performance employing FCS-MPCC rarely consider prediction error and its utilization to weaken the influence of inaccurate prediction model. This paper investigates in depth the prediction error caused by three influencing factors from the perspective of model accuracy—discretization method, prediction stepsize, and parameter mismatch. Firstly, the evaluation index, prediction error, is defined and its formulas considering the above three factors are derived based on interior permanent magnet synchronous motor (IPMSM). Then, the theoretical analysis of prediction error is provided. Finally,... [more]

A prospect of increasing penetration of uncoordinated electric vehicles (EVs) together with intermittent renewable energy generation in microgrid systems has motivated us to explore an effective strategy for safe and economic operation of such distributed generation systems. This paper presents a robust economic dispatch strategy for grid-connected microgrids. Uncertainty from wind power and EV charging loads is modeled as an uncertain set of interval predictions. Considering the worst case scenario, the proposed strategy can help to regulate the EV charging behaviors, and distributed generation in order to reduce operation cost under practical constraints. To address the issue of over-conservatism of robust optimization, a dispatch interval coefficient is introduced to adjust the level of robustness with probabilistic bounds on constraints, which gradually improves the system's economic efficiency. In addition, in order to facilitate the decision-making strategies from an economic per... [more]

The Switched Reluctance Generator (SRG) is suitable for wind power generation due to its good reliability and robustness. However, The SRG system adopting the conventional control algorithm with Pulse Width Modulation (PWM) method has a drawback, low response speed. The pulse train (PT) control has been widely used in dc/dc power converters operating in the discontinuous conduction mode due to its advantages of simple implementation and fast response. In this paper, for the first time, the PT control method is modified and adopted for controlling the output voltage of SRG system in order to achieve fast response. The capacitor current on the output side is sampled and combined with the output voltage to select the pulse trains and the low frequency oscillation cased by PT can be suppressed by tuning the feedback coefficient of the capacitor current. Also, good performance can be guaranteed with a wide range of voltage regulations, fast response, and no overshoot. The experimental platf... [more]

Recent attention to industrial peak shaving applications sparked an increased interest in battery energy storage. Batteries provide a fast and high power capability, making them an ideal solution for this task. This work proposes a general framework for sizing of battery energy storage system (BESS) in peak shaving applications. A cost-optimal sizing of the battery and power electronics is derived using linear programming based on local demand and billing scheme. A case study conducted with real-world industrial profiles shows the applicability of the approach as well as the return on investment dependence on the load profile. At the same time, the power flow optimization reveals the best storage operation patterns considering a trade-off between energy purchase, peak-power tariff, and battery aging. This underlines the need for a general mathematical optimization approach to efficiently tackle the challenge of peak shaving using an energy storage system. The case study also compares t... [more]

The demands of remarkable reliability and high power density of traction systems are becoming more and more rigorous. The conflicting requirements imposed on the control strategy are higher accuracy and higher efficiency over the whole speed range. However, parameter variations caused by the cross coupling and magnetic saturation effect (omitted from the cross saturation effects in the following) are usually neglected in conventional control strategies, which could reduce the control precision. In order to fully consider the influence of parameter changes on the motor control and derive an approach that could realize the maximum efficiency during the whole speed range, this paper proposes a dynamic DC-link voltage adjustment strategy considering the cross coupling and magnetic saturation effects. The strategy can be categorized into three parts. Firstly, the torque request is transformed to the optimal current reference signal. Secondly, the differences between the setpoint and the rea... [more]

This paper addresses the issues related to the rapid production of hydrogen from methane steam reforming by means of process intensification. Methane steam reforming coupled with catalytic combustion in thermally integrated microchannel reactors for the production of hydrogen was investigated numerically. The effect of the catalyst, flow arrangement, and reactor dimension was assessed to optimize the design of the system. The thermal interaction between reforming and combustion was investigated for the purpose of the rapid production of hydrogen. The importance of thermal management was discussed in detail, and a theoretical analysis was made on the transport phenomena during each of the reforming and combustion processes. The results indicated that the design of a thermally integrated system operated at millisecond contact times is feasible. The design benefits from the miniaturization of the reactors, but the improvement in catalyst performance is also required to ensure the rapid pr... [more]

In this paper, the modeling and the experimental verification of the “bidirectional DC/DC boost converter⁻DC motor„ system are presented. By using circuit theory along with the model of a DC motor, the mathematical model of the system is derived. This model was experimentally tested under time-varying duty cycles obtained via the system differential flatness property. The experimental verification was carried out using Matlab-Simulink and a DS1104 board in a built prototype of the system.

Fischer-Tropsch diesel fuel synthesized from coal (CFT) is an alternative fuel that gives excellent emission performance in compression ignition (CI) engines. In order to study the vibration characteristics, which are important for determining the applicability of the fuel, CFT-diesel blends were tested on a CI engine to acquire vibration signals from the engine head and block. Based on the FFT and continuous wavelet transformation (CWT) analysis, the influence of CFT on the vibration was studied. The results showed that the root mean square (RMS) values of the vibration signal decrease as the proportion of CFT in the blends increases. The CWT results indicated that the vibration energy areas motivated by the pressure shock of transient combustion were weak with increasing CFT proportion for the different frequency bands. The blend of 90% pure petro-diesel and 10% CFT registered the largest RMS value for piston side thrust response, and the RMS of high-frequency pressure oscillation re... [more]

A transient 3D thermal model based on the thermal quadrupole method, coupled to ray tracing analysis, is presented. This methodology can predict transient temperature maps under any time-fluctuating irradiance flux—either synthetic or experimental—providing a useful tool for the design and parametric optimization of concentration photovoltaics systems. Analytic simulations of a concentration photovoltaics system thermal response and assessment of in-plane thermal gradients induced by fast tracking point perturbations, like those induced by wind, are provided and discussed for the first time. Computation times for time-resolved temperature maps can be as short as 9 s for a full month of system operation, with stimuli inspired by real data. Such information could pave the way for more accurate studies of cell reliability under any set of worldwide irradiance conditions.

Expansion of photovoltaic (PV) generation is increasing the challenge for network operators to keep voltages within operational limits. Voltage rise occurs in low voltage (LV) networks when distributed generators export, particularly at times of low demand. However, there is little work quantifying the scale of voltage issues and subsequently potential solutions across large numbers of real networks. In this paper, a method is presented to analyse a large quantity of geographically and topographically varying distribution networks. The impact of PV on voltages in 9163 real LV distribution networks is then quantified. One potential mitigation measure is increased network demand to reduce voltages. In this work, location algorithms are used to identify where increased demand, through energy storage, has the greatest effect on overvoltage. The study explores the impact on overvoltage of two modes of storage installation reflecting differing routes to adoption: purchase of storage by homeo... [more]

Captured CO₂ is in a subcritical state, whereas CO₂ deep underground is in a supercritical state because of the high geothermal heat and pressure. The properties of CO₂ can change rapidly at the critical point and in the near-critical region during the transportation and injection process. This study aims to identify the instabilities in the CO₂ flow in these regions, along with the causes and effects, during the transportation and injection process, and propose relevant design specifications. Thus, the critical points and near-critical region of CO₂ flow were numerically analyzed. The unstable region is presented in terms of temperature and pressure ranges, and the changes in the CO₂ properties in this region were analyzed. In the unstable region, the sudden change in density was similar to the density wave oscillation of a two-phase flow. The CO₂ stability map we obtained and the stability map of supercritical water show similar trends. Flow instability was also found to occur in sta... [more]

Recent electricity price forecasting (EPF) studies suggest that the least absolute shrinkage and selection operator (LASSO) leads to well performing models that are generally better than those obtained from other variable selection schemes. By conducting an empirical study involving datasets from two major power markets (Nord Pool and PJM Interconnection), three expert models, two multi-parameter regression (called baseline) models and four variance stabilizing transformations combined with the seasonal component approach, we discuss the optimal way of implementing the LASSO. We show that using a complex baseline model with nearly 400 explanatory variables, a well chosen variance stabilizing transformation (asinh or N-PIT), and a procedure that recalibrates the LASSO regularization parameter once or twice a day indeed leads to significant accuracy gains compared to the typically considered EPF models. Moreover, by analyzing the structures of the best LASSO-estimated models, we identify... [more]

Load forecasting models are of great importance in Electricity Markets and a wide range of techniques have been developed according to the objective being pursued. The increase of smart meters in different sectors (residential, commercial, universities, etc.) allows accessing the electricity consumption nearly in real time and provides those customers with large datasets that contain valuable information. In this context, supervised machine learning methods play an essential role. The purpose of the present study is to evaluate the effectiveness of using ensemble methods based on regression trees in short-term load forecasting. To illustrate this task, four methods (bagging, random forest, conditional forest, and boosting) are applied to historical load data of a campus university in Cartagena (Spain). In addition to temperature, calendar variables as well as different types of special days are considered as predictors to improve the predictions. Finally, a real application to the Span... [more]

This paper examines the data collected from the power industry over the last six years of actual reported emissions of sulphur hexafluoride (SF₆) and the potential impact. The SF₆ emissions have been collated from the 14 different regions in England, Scotland, and Wales (Great Britain) from the six distribution network operators. The emissions of SF₆ due to the transmission network of Great Britain have also been collated from the three different transmission network operators. By collecting this SF₆ emissions data from the power industry, in both the distribution and transmission networks, an overall view of the scale of SF₆ emissions in Great Britain can be evaluated. Data from the power industry also shows the inventory of SF₆ power equipment in use over the last six years in Great Britain and shows the calculated percentage leakage rate of all of this equipment. In this paper, these figures, as reported by the electrical power industry to the UK government, have been used to estima... [more]

Wave energy converter (WEC) arrays deployed in coastal regions may create physical disturbances, potentially resulting in environmental stresses. Presently, limited information is available on the nature of these physical disturbance or the resultant effects. A quantitative Spatial Environmental Assessment Tool (SEAT) for evaluating the potential effects of wave energy converter (WEC) arrays on nearshore hydrodynamics and sediment transport is presented for the central Oregon coast (USA) through coupled numerical model simulations of an array of WECs. Derived climatological wave conditions were used as inputs to the model to allow for the calculation of risk metrics associated with various hydrodynamic and sediment transport variables such as maximum shear stress, bottom velocity, and change in bed elevation. The risk maps provided simple, quantitative, and spatially-resolved means of evaluating physical changes in the vicinity of a hypothetical WEC array in response to varying wave co... [more]

Flow-induced motion (FIM) performs well in energy conversion but has been barely investigated, particularly for prisms with sharp sections. Previous studies have proven that T-section prisms that undergo galloping branches with high amplitude are beneficial to energy conversions. The FIM experimental setup designed by Tianjin University (TJU) was improved to conduct a series of FIM responses and energy conversion tests on a T-section prism. Experimental results are presented and discussed, to reveal the complete FIM responses and power generation characteristics of the T-section prism under different load resistances and section aspect ratios. The main findings are summarized as follows. (1) Hard galloping (HG), soft galloping (SG), and critical galloping (CG) can be observed by varying load resistances. When the load resistances are low, HG occurs; otherwise, SG occurs. (2) In the galloping branch, the highest amplitude and the most stable oscillation cause high-quality electrical ene... [more]

This paper presents a comprehensive approach to analyze and design the voltage and current loops of switching DC-DC converters by using sliding-mode control theory. The approach is interchangeably applied to switching converters under current-programmed control with both fixed and variable frequency modulation. An ideal sliding-mode dynamics model is then obtained together with its circuit schematic representation that can be used for designing the output voltage compensator, as well as to predict the large signal behavior such as during start-up and under large disturbances. Simulations and experimental measurements illustrate the theoretical approach for two different examples of switching converters.

This paper presents a stator winding temperature detection method for permanent magnet synchronous motors (PMSMs) using a motor parameter estimation method. PMSM performance is highly dependent on the motor parameters. However, the motor parameters vary with temperature. It is difficult to measure motor parameters using a voltage equation without additional sensors. Herein, a stator winding temperature estimation method based on a d-axis current injection method is proposed. The proposed estimation method can be used to obtain stator temperatures and to achieve reliable operation. The validity of the proposed method is verified through simulations and experimental results.

Uncertainty commonly exists in the wireless power transfer (WPT) systems for moving objects. To enhance the robustness of the WPT system to uncertain parameter variations, a modified WPT system structure and an interval-based uncertain optimization method are proposed in this paper. The modified WPT system, which includes two Q-type impedance matching networks, can switch between two different operating modes. The interval-based uncertain optimization method is used to improve the robustness of the modified WPT system: First, two interval-based objective functions (mean function and variance function) are defined to evaluate the average performance and the robustness of the system. A double-objective uncertain optimization model for the modified WPT system is built. Second, a bi-level nested optimization algorithm is proposed to find the Pareto optimal solutions of the proposed optimization model. The Pareto fronts are provided to illustrate the tradeoff between the two objectives, and... [more]

This study proposes a framework for green remodeling for the elderly that emphasizes the role of designers and the notion of aging in place. Energy efficiency is critical for older persons because many of them spend more time at home and are less likely to heat and cool their homes appropriately. Improving the energy performance of the elderly’s housing by green remodeling could promote energy efficiency and healthy living for the elderly. Based on remodeling components derived from related work, key factors to be considered regarding the remodeling for the elderly were investigated. A framework for green remodeling enabling energy efficiency was developed for home upgrades for the elderly. Identifying the area of application and critical components for energy efficiency helps improve the energy performance for the elderly. This study is significant because it considers the elderly’s characteristics and experiences in the development of a sustainable remodeling process rather than new-... [more]

Urban agriculture has become a favored activity in many cities around the world. This study explores how urban agriculture’s potential can be maximized in Seoul, South Korea, a city characterized by high-density residential complexes. It selects six existing residential complexes with representative site typologies and diverse density levels. The study’s aim is to assess the impact of various typology and density settings on percentages of ground-level surface with direct sunlight above certain thresholds during warmer seasons when crops can grow. DIVA-for-Rhino is used for simulation. The findings suggest that parallel typologies and lower density levels offer the best performance, while other combinations show mixed results. This study could benefit citizens and policymakers to facilitate urban agriculture practices around the world by suggesting feasible solutions for high-density residential developments.

Massive Multiple Input Multiple Output MIMO technology is a promising candidate for the next generation of communication applications, which essentially group hundreds of transmitting antennas together at the base station and provides the higher energy and spectral efficiency. In this article, the transmitting antennas are assumed to be closely spaced at the base station, which in turn results into a mutual coupling effect between the antenna terminals. The optimal system parameters and the energy efficiency are computed by considering the mutual coupling effect between the antenna terminals. Mutual coupling effect is deeply investigated on the energy efficiency and the other optimal parameters. We propose the domain splitter algorithm for the optimization of energy efficiency and the computation of different optimal system parameters in this article. The computational complexity of the proposed domain splitter algorithm is not dependent on the number of transceiver chains, and the det... [more]

Concentration polarization is one of the main challenges of membrane-based processes such as power generation by reverse electrodialysis. Spacers in the compartments can enhance mass transfer by reducing concentration polarization. Active spacers increase the available membrane surface area, thus avoiding the shadow effect introduced by inactive spacers. Optimizing the spacer-filled channels is crucial for improving mass transfer while maintaining reasonable pressure losses. The main objective of this work was to develop a numerical model based upon the Navier⁻Stokes and Nernst⁻Planck equations in OpenFOAM, for detailed investigation of mass transfer efficiency and pressure drop. The model is utilized in different spacer-filled geometries for varying Reynolds numbers, spacer conductivity and fluid temperature. Triangular corrugations are found to be the optimum geometry, particularly at low flow velocities. Cylindrical corrugations are better at high flow velocities due to lower pressu... [more]

This paper presents a stability analysis and dynamic characteristics investigation of deadbeat-direct torque and flux control (DB-DTFC) of interior permanent magnet synchronous motor (IPMSM) drives with respect to machine parameter variations. Since a DB-DTFC algorithm is developed based on a machine model and parameters, stability with respect to machine parameter variations should be evaluated. Among stability evaluation methods, an eigenvalue (EV) migration is used in this paper because both the stability and dynamic characteristics of a system can be investigated through EV migration. Since an IPMSM drive system is nonlinear, EV migration cannot be directly applied. Therefore, operating point models of DB-DTFC and CVC (current vector control) IPMSM drives are derived to obtain linearized models and to implement EV migration in this paper. Along with DB-DTFC, current vector control (CVC), one of the widely used control algorithms for motor drives, is applied and evaluated at the sam... [more]