In this paper, we present an energy optimization technique to schedule three types of household appliances (user dependent, interactive schedulable and unschedulable) in response to the dynamic behaviours of customers, electricity prices and weather conditions. Our optimization technique schedules household appliances in real time to optimally control their energy consumption, such that the electricity bills of end users are reduced while not compromising on user comfort. More specifically, we use the binary multiple knapsack problem formulation technique to design an objective function, which is solved via the constraint optimization technique. Simulation results show that average aggregated energy savings with and without considering the human presence control system are 11.77% and 5.91%, respectively.

In this paper, the environmental and economic impacts of the life cycle of an advanced lithium based energy storage system (ESS) for a battery electric vehicle are assessed. The methodology followed to perform the study is a Multiregional Input⁻Output (MRIO) analysis, with a world IO table that combines detailed information on national production activities and international trade data for 40 countries and a region called Rest of the World. The life cycle stages considered in the study are manufacturing, use and recycling. The functional unit is one ESS with a 150,000 km lifetime. The results of the MRIO analysis show the stimulation that the life cycle of the EES has in the economy, in terms of production of goods and services. The manufacturing is the life cycle stage with the highest environmental load for all the impact categories assessed. The geographical resolution of the results show the relevance that some countries may have in the environmental performance of the assessed pro... [more]

A fractional derivative system identification approach for modeling battery dynamics is presented in this paper, where fractional derivatives are applied to approximate non-linear dynamic behavior of a battery system. The least squares-based state-variable filter (LSSVF) method commonly used in the identification of continuous-time models is extended to allow the estimation of fractional derivative coefficents and parameters of the battery models by monitoring a charge/discharge demand signal and a power storage/delivery signal. In particular, the model is combined by individual fractional differential models (FDMs), where the parameters can be estimated by a least-squares algorithm. Based on experimental data, it is illustrated how the fractional derivative model can be utilized to predict the dynamics of the energy storage and delivery of a lithium iron phosphate battery (LiFePO 4 ) in real-time. The results indicate that a FDM can accurately capture the dynamics of the energy... [more]

Passive cooling techniques have been used mostly in countries with hot and arid climates such as Iran, Egypt, and India. However, the use of this important technology has not been seriously considered until a time of energy crisis, and consequently, environmental crisis scenarios, emerge. Scholars have renewed their interest in investigating passive cooling technology, particularly the aspects of new materials, thermal comfort, energy efficiency, new designs, climate, and environmental considerations. This review paper highlights the opportunities to use green materials, such as geopolymers, as evaporative cooling materials with different types of industrial and agricultural waste products as components. Novel ideas for passive cooling design using ancient and nature-inspired concepts are also presented to promote green technology for future applications.

The axial magnetic-field-modulated brushless double-rotor machine (MFM-BDRM) is a novel possible alternative power-split device for hybrid electric vehicles (HEVs). This paper proposes a two-dimensional (2-D) analytical method to predict the performance of the axial MFM-BDRM to reduce computing time. The computation is based on the solution of Laplace’s or Poisson’s equation with boundary conditions for each elementary rectangular region. By taking account of the existence of modulating ring and the stator slotting effect, the proposed model is able to calculate magnetic-field distribution with high accuracy. In order to assess the proposed method, the 2-D analytical and three-dimensional (3-D) finite element analysis (FEA) results have been compared, and good agreements have been achieved. As the analytical computation is much faster and more flexible, the proposed method can be used in the preliminary design process of the axial MFM-BDRM.

This paper contributes to the political and scientific debate surrounding the economic costs entailed by the regular power cuts in Lebanon. Examining the data on electricity consumption that was produced by onshore and offshore power plants, this paper estimates the economical costs of power interruptions in Lebanon over the period 2009⁻2014. Based on 700 USD/MWh, representing the average value of lost load (VOLL) in that period, results indicate that electricity shortages continue to render significant transfers of wealth to the detriment of economy and society as a whole. Over the period 2009⁻2014, the total losses for the Lebanese economy reached 23.23 billion USD. Just as importantly, some evidence suggests a sharp decline in the economical costs of power interruptions with the inception of the two floating power plants in 2013. The results are crucial for the decision makers to identify the economic efficiency of alternative measures to enhance the security of the Lebanese electri... [more]

In alternating current (AC) power systems the power generated by power plants has to match the power drawn by consumers plus the system losses at any time. In the case of an imbalance between generation and consumption the frequency in the system deviates from its rated value. In order to avoid an unsuitable frequency, control power plants have to step in to level out this imbalance. Control power plants need time to adjust their power, which is why the inertial behaviour of today’s AC systems is crucial for frequency control. In this paper it is discussed that the inertia in the European Continental Synchronous Area decreases due to the transition to renewable energy sources. This will become a problem for frequency control, which is why the provision of non-inherent inertia is proposed. This system consists of fast-responding energy storage. Its dimensions in terms of power and energy are determined. Since such non-inherent inertia requires investments a cost-efficient solution has t... [more]

Recently, Vernier permanent magnet (VPM) machines, one special case of magnetic flux-modulated (MFM) machines, benefiting from their compact, simple construction and low-speed/ high-torque characteristics, have been receiving increasing interest. In this paper, the Vernier structure is integrated with an axial-flux PM machine to obtain the magnetic gear effect and produce an improved torque density for direct-drive wind power generation application. Another advantage of the proposed machine is that the stator flux rotating speed can be relatively high when the shaft speed is low. With this benefit, sensorless control strategy can be easily implemented in a wide speed range. In this paper, an improved sliding mode observer (SMO) is proposed to estimate the rotor position and the speed of the proposed machine. With the estimated shaft speeds, the maximum power point tracking (MPPT) control strategy is applied to maximize the wind power extraction. The machine design and the sensorless MP... [more]

As safety and reliability critical components, lithium-ion batteries always require real-time diagnosis and prognosis. This often involves a large amount of computation, which makes diagnosis and prognosis difficult to implement, especially in embedded or mobile applications. To address this issue, this paper proposes a run-time Reconfigurable Computing (RC) system on Field Programmable Gate Array (FPGA) for Relevance Vector Machine (RVM) to realize real-time Remaining Useful Life (RUL) estimation. The system leverages state-of-the-art run-time dynamic partial reconfiguration technology and customized computing circuits to balance the hardware occupation and computing efficiency. Optimal hardware resource consumption is achieved by partitioning the RVM algorithm according to a multi-objective optimization. Moreover, pipelined and parallel computation circuits for kernel function and matrix inverse are proposed on FPGA to further accelerate the computation. Experimental results with two... [more]

Interior permanent magnet (IPM) motors are widely used in electric vehicles (EVs), benefiting from the excellent advantages of a more rational use of energy. For further improvement of energy utilization, this paper presents an analytical method of d- and q-axis inductance calculation for IPM motors with V-shaped rotor in no-load condition. A lumped parameter magnetic circuit model (LPMCM) is adopted to investigate the saturation and nonlinearity of the bridge. Taking into account the influence of magnetic field distribution on inductance, the winding function theory (WFT) is employed to accurately calculate the armature reaction airgap magnetic field and d- and q-axis inductances. The validity of the analytical technique is verified by the finite element method (FEM).

Attributing to the advantages of high efficiency, low electromagnetic interference (EMI) noise and closest to the pulse-width-modulation (PWM) converter counterpart, zero-voltage-transition (ZVT) PWM soft-switching inverters are very suitable for high-performance applications. However, the conventional control algorithms intended for high efficiency generally results in voltage distortion. Thus, this paper, for the first time, proposes a high-precision control method to eliminate the dead-time effect through controlling the auxiliary current in the auxiliary resonant snubber inverter (ARSI), which is a typical ZVT PWM inverter. The dead-time effect of ARSI is analyzed, which is distinguished from hard-switching inverters. The proposed high-precision control is introduced based on the investigation of dead-time effect. A prototype was developed to verify the effectiveness of the proposed control. The experimental results shows that the total harmonic distortion (THD) of the output curre... [more]

To determine the fuel economy and emissions of a vehicle using a chassis dynamometer, the load to which the vehicle is subjected when it actually runs on a road, or the road load specifications, must be simulated when the dynamometer is applied. The most commonly used method to measure road load specifications is coastdown testing. Currently, road load is measured and provided by the manufacturer of the vehicle. Verification of the accuracy of the manufacturer’s reported road load specifications by a third party may reveal that the specifications are inaccurate, possibly because of different testing locations, test drivers or test equipment. This study aims at identifying key factors that can affect a vehicle’s road load correlation by using experimental design and deriving criteria for determining the correlation based on the energy difference.

A building integrated holographic concentrating photovoltaic-thermal system has been optically and energetically simulated. The system has been designed to be superimposed into a solar shading louvre; in this way the concentrating unit takes profit of the solar altitude tracking, which the shading blinds already have, to increase system performance. A dynamic energy simulation has been conducted in two different locations—Sde Boker (Israel) and Avignon (France)—both with adequate annual irradiances for solar applications, but with different weather and energy demand characteristics. The simulation engine utilized has been TRNSYS, coupled with MATLAB (where the ray-tracing algorithm to simulate the holographic optical performance has been implemented). The concentrator achieves annual mean optical efficiencies of 30.3% for Sde Boker and 43.0% for the case of Avignon. Regarding the energy production, in both locations the thermal energy produced meets almost 100% of the domestic hot wate... [more]

The choice of materials for the future nuclear fusion reactors is a crucial issue. In the fusion reactors, the combination of very high temperatures, high radiation levels, intense production of transmuting elements and high thermomechanical loads requires very high-performance materials. Erosion of PFCs (Plasma Facing Components) determines their lifetime and generates a source of impurities (i.e., in-vessel tritium and dust inventories), which cool down and dilute the plasma. The resuspension of dust could be a consequences of LOss of Coolant Accidents (LOCA) and LOss of Vacuum Accidents (LOVA) and it can be dangerous because of dust radioactivity, toxicity, and capable of causing an explosion. These characteristics can jeopardize the plant safety and pose a serious threat to the operators. The purpose of this work is to determine the experimental and numerical steeps to develop a numerical model to predict the dust resuspension consequences in case of accidents through a comparison... [more]

In order to investigate how artificial neural networks (ANNs) have been applied for partial discharge (PD) pattern recognition, this paper reviews recent progress made on ANN development for PD classification by a literature survey. Contributions from several authors have been presented and discussed. High recognition rate has been recorded for several PD faults, but there are still many factors that hinder correct recognition of PD by the ANN, such as high-amplitude noise or wide spectral content typical from industrial environments, trial and error approaches in determining an optimum ANN, multiple PD sources acting simultaneously, lack of comprehensive and up to date databank of PD faults, and the appropriate selection of the characteristics that allow a correct recognition of the type of source which are currently being addressed by researchers. Several suggestions for improvement are proposed by the authors include: (1) determining the optimum weights in training the ANN; (2) usin... [more]

Trigeneration plants can use different types of chillers in the same plant, typically single effect and double effect absorption chillers, vapour compression chillers and also cooling storage systems. The highly variable cooling demand of the buildings connected to a district heating and cooling (DHC) network has to be distributed among these chillers to achieve lower operating costs and higher energy efficiencies. This problem is difficult to solve due to the different partial load behaviour of each chiller and the different chiller combinations that can cover a certain cooling demand using an appropriate sizing of the cooling storage. The objective of this paper is to optimize the daily plant operation of an existing trigeneration plant based on cogeneration engines and to study the optimal cooling load sharing between different types of absorption chillers using a mixed integer linear programming (MILP) model. Real data from a trigeneration plant connected to a DHC close to Barcelon... [more]

Wireless power transfer (WPT) is greatly affected when the transmission channel is surrounded by non-ferromagnetic metallic objects and the alternating magnetic field interacts with the metal conductor, which is more of an issue in wirelessly charged electric vehicle (EV) applications. This paper analyses the performances of a WPT system in an environment with a non-ferromagnetic metal plate. The impedance model of the WPT system in the metal environment is established. Moreover the variation law of a coil’s equivalent inductance and resistance is deduced when the coil is surrounded by the non-ferromagnetic metal plate. Meanwhile, simulations, theory and experiments all confirm that the model is correct. Finally, since the system performance of a wireless charging system is influenced by non-ferromagnetic metals, this paper puts forward a method to improve the performance, that is, to place ferrite cores between the receiving coil and a metal plate. Experiments are carried out to verif... [more]

The authors wish to make the following changes to the published paper [1].[...]

The objective of this paper is to numerically investigate the effects of the atmospheric boundary layer on the aerodynamic performance and loads of a novel dual-rotor wind turbine (DRWT). Large eddy simulations are carried out with the turbines operating in the atmospheric boundary layer (ABL) and in a uniform inflow. Two stability conditions corresponding to neutral and slightly stable atmospheres are investigated. The turbines are modeled using the actuator line method where the rotor blades are modeled as body forces. Comparisons are drawn between the DRWT and a comparable conventional single-rotor wind turbine (SRWT) to assess changes in aerodynamic efficiency and loads, as well as wake mixing and momentum and kinetic energy entrainment into the turbine wake layer. The results show that the DRWT improves isolated turbine aerodynamic performance by about 5%⁻6%. The DRWT also enhances turbulent axial momentum entrainment by about 3.3 %. The highest entrainment is observed in t... [more]

In cognitive radio (CR), the spectrum sensing of the primary user (PU) may consume some electrical power from the battery capacity of the secondary user (SU), resulting in a decrease in the transmission power of the SU. In this paper, a multislot simultaneous spectrum sensing and energy harvesting model is proposed, which uses the harvested radio frequency (RF) energy of the PU signal to supply the spectrum sensing. In the proposed model, the sensing duration is divided into multiple sensing slots consisting of one local-sensing subslot and one energy-harvesting subslot. If the PU is detected to be present in the local-sensing subslot, the SU will harvest RF energy of the PU signal in the energy-harvesting slot, otherwise, the SU will continue spectrum sensing. The global decision on the presence of the PU is obtained through combining local sensing results from all the sensing slots by adopting “Or-logic Rule”. A joint optimization problem of sensing time and time splitter factor is p... [more]

Advanced metering infrastructure (AMI) subsystems monitor and control energy distribution through exchange of information between smart meters and utility networks. A key challenge is how to select a cost-effective communication system without compromising the performance of the applications. Current communication technologies were developed for conventional data networks with different requirements. It is therefore necessary to investigate how much of existing communication technologies can be retrofitted into the new energy infrastructure to cost-effectively deliver acceptable level of service. This paper investigates broadband power line communications (BPLC) as a backhaul solution in AMI. By applying the disparate traffic characteristics of selected AMI applications, the network performance is evaluated. This study also examines the communication network response to changes in application configurations in terms of packet sizes. In each case, the network is stress-tested and perfor... [more]

This paper presents an application and extension of multiple-criteria decision-making (MCDM) methods to account for stochastic input variables. More in particular, a comparative study is carried out among well-known and widely-applied methods in MCDM, when applied to the reference problem of the selection of wind turbine support structures for a given deployment location. Along with data from industrial experts, six deterministic MCDM methods are studied, so as to determine the best alternative among the available options, assessed against selected criteria with a view toward assigning confidence levels to each option. Following an overview of the literature around MCDM problems, the best practice implementation of each method is presented aiming to assist stakeholders and decision-makers to support decisions in real-world applications, where many and often conflicting criteria are present within uncertain environments. The outcomes of this research highlight that more sophisticated me... [more]

This paper presents a review of over a decade of research on Vertical Axis Wind Turbines (VAWTs) conducted at Uppsala University. The paper presents, among others, an overview of the 200 kW VAWT located in Falkenberg, Sweden, as well as a description of the work done on the 12 kW prototype VAWT in Marsta, Sweden. Several key aspects have been tested and successfully demonstrated at our two experimental research sites. The effort of the VAWT research has been aimed at developing a robust large scale VAWT technology based on an electrical control system with a direct driven energy converter. This approach allows for a simplification where most or all of the control of the turbines can be managed by the electrical converter system, reducing investment cost and need for maintenance. The concept features an H-rotor that is omnidirectional in regards to wind direction, meaning that it can extract energy from all wind directions without the need for a yaw system. The turbine is connected to a... [more]

This paper presents the development of a WebGIS application aimed at providing safe and reliable data needed for reclamation of abandoned mines in national parks and other protected areas in Vojvodina in compliance with existing legal regulations. The geodatabase model for this application has been developed using UML and the CASE tool Microsoft Visio featuring an interface with ArcGIS. The WebGIS application was developed using GeoServer, an open source tool in the Java programming language, with integrated PostgreSQL DB and the possibility of generating and publishing WMS, WFS and KML services. The WebGIS application is publicly available, based on an appropriate central database, which for the first time encompasses all available data on abandoned mines in Vojvodina, and as such may serve as a model for similar databases on the territory of the Republic of Serbia.

In electric power systems, there are always power quality disturbances (PQDs). Usually, noise contamination interferes with their detection and classification. Common methods perform frequency or time-frequency analyses on the power distribution signal for detecting and classifying a limited number of PQDs with some difficulties at low signal-to-noise ratio (SNR). In this regard, recently proposed methodologies for PQD detection estimate several parameters and apply distinct signal processing techniques to improve the detection of PQD. In this work, a novel methodology that merges empirical mode decomposition (EMD), the moments of a random variable, and an artificial neural network (ANN) is proposed for detecting and classifying different PQD. The proposed method estimates skewness, kurtosis, and Shannon entropy from the EMD of one-phase voltage/current signal. Then, an ANN is in charge of classifying the input signal into one of nine different classes for PQD, receiving these paramete... [more]