Optimization methods are increasingly used for the design process of electrical machines. The quality of the optimization result and the necessary simulation effort depend on the optimization methods, machine models and optimization parameters used. This paper presents a multi-stage optimization environment for the design optimization of induction machines. It uses the strategies of simulated annealing, evolution strategy and pattern search. Artificial neural networks are used to reduce the solution effort of the optimization. The selection of the electromagnetic machine model is made in each optimization stage using a methodical model selection approach. The selection of the optimization parameters is realized by a methodical parameter selection approach. The optimization environment is applied on the basis of an optimization for the design of an electric traction machine using the example of an induction machine and its suitability for the design of a machine is verified by a compari... [more]

This paper presents an investigation factors that need to be considered in the design and selection of components for the conversion of a fleet of plug-in electric golf carts at Princess Nourah Bint Abdelrahman University, (PNU), Riyadh, Kingdom of Saudi Arabia (KSA), into solar power energy. Currently, the plug-in electric golf carts are powered by a set of deep-cycle lead-acid battery packs consisting of six units. Solar energy systems (photovoltaics and solar thermal) provide significant environmental benefits and opportunities over the traditional and conventional sources. Therefore, they can contribute positively to many aspects of the built environment and societies. There are many factors that affect the energy generated from the solar panel system. These include type and dimension of the solar panels, weight, speed, acceleration, and other characteristics of the used golf carts, and the energy efficiency of the solar energy system, as main factors that affect the green energy g... [more]

This study presents a novel switching scheme for three-level neutral point clamped (NPC) inverters. The proposed switching method independently drives the upper- and lower-arm elements of the inverter based on the polarity information of the reference current. The proposed switching scheme does not require the inclusion of dead-time for each switching, except when the current polarity changes. Therefore, unlike the conventional inverter switching method, dead-time compensation is not needed, and the possibility of an arm-short accident is prevented. In this study, a switching procedure is detailed, and the operation mode analysis of the proposed switching scheme is presented. The effectiveness of the proposed switching method is verified experimentally by application to a grid-connected inverter that requires inverter current control.

A quantitative assessment of the material flux emerging from a pilot plant for the treatment of end-of-life photovoltaic panel waste was reported. The process included the manual dismantling of aluminum frames, mechanical treatment for size reduction, and the physical treatment of the milled materials for the release of coarse glass from the encapsulant polymer. Demonstration activities were performed using 1 ton of Si-, 1 ton of CdTe-, and 1 ton of CIGS-based photovoltaic panels (investigated separately), confirming the ability of the process to treat different photovoltaic technologies. The characterization of the input materials was performed and compared with previous literature data. The major bottleneck in the definition of an effective process option for the treatment of different panel technologies was emphasized by the high heterogeneity reported. Mass balances for the proposed process were derived by the recovered material flow. It was highlighted that in processes based on m... [more]

Despite the extensive use of ejectors in the process industry, it is complex to predict suction and motive fluids mixture characteristics, especially with multiphase flows, even if, in most cases, mixture pressure control is necessary to satisfy process requirements or to avoid performance problems. The realization of an ejector model can allow the operators to overcome these difficulties to have real-time control of the system performance. In this context, this work proposes a framework for developing a Digital Twin of an ejector installed in an experimental plant able to predict the future state of an item and the impact of negative scenarios and faults diagnosis. ANNs have been identified as the most used tool for simulating the multiphase flow ejector. Nevertheless, the complexity in defining their structure and the computational effort to train and use them are not suitable for realizing standalone applications onboard the ejector. The proposed paper shows how Swarm Intelligence a... [more]

This paper investigates the degradation mechanism of pressure-sintered silver (s-Ag) film for silicon carbide (SiC) chip assembly with a 2-millimeter-thick copper substrate by means of thermal shock test (TST). Two different types of silver paste, nano-sized silver paste (NP) and nano-micron-sized paste (NMP), were used to sinter the silver film at 300 °C under a pressure of 60 MPa. The mean porosity (p) of the NP and MNP s-Ag films was 2.4% and 8%, respectively. The pore shape of the NP s-Ag was almost spherical, whereas the NMP s-Ag had an irregular shape resembling a peanut shell. After performing the TST at temperatures ranging from −40 to 150 °C, the scanning acoustic tomography (SAT) results suggested that delamination occurs from the edge of the assembly, and the delamination of the NMP s-Ag assembly was faster than that of the NM s-Ag assembly. The NMP s-Ag assembly showed a random delamination, indicating that the delamination speed varies from place to place. The difference i... [more]

The aerospace industry develops prognosis and health management algorithms to ensure better safety on board, particularly for in-flight controls where jamming is dreaded. For that, vibration signals are monitored to predict future defect occurrences. However, time series are not labeled according to severity level, and the user can only assess the system health from the data mining procedure. To that extent, a clustering algorithm using a deep neural network core is developed. Time series are encoded into pictures to be fed into an artificially trained neural network: U-NET. From the segmented output, one-dimensional information on cluster frontiers is extracted and filtered without any parameter selection. Then, a kernel density estimation finally transforms the signal into an empirical density. Ultimately, a Gaussian mixture model extracts the latter independent components. The method empowered us to reveal different degrees of severity faults in the studied data, with their respecti... [more]

Dye-sensitized solar cells (DSSCs) were fabricated using a photoelectrode covered by a porous layer of titanium dioxide, platinum counter electrode, iodide/triiodide electrolyte and three different dyes: phenylfluorone (PF), pyrocatechol violet (PCV) and alizarin (AL). After the adsorption of the dyes on the mesoporous TiO2 layer, the measurement of absorption spectra of all the tested dyes revealed a significant broadening of the absorption range. The positions of highest occupied molecular orbital (HOMO) and lowest occupied molecular orbital (LUMO) levels of dye molecules were determined, indicating that all three dyes are good candidates for light harvesters in DSSCs. The cells were tested under simulated solar light, and their working parameters were determined. The results showed that the implementation of the back reflector layer made of BaSO4 provided an improvement in the cell efficiency of up to 17.9% for phenylfluorone, 60% for pyrocatechol violet and 21.4% for alizarin dye.

Given the large amount of energy required in the building sector, an interesting opportunity to reach future sustainable energy systems is the path towards low energy buildings. This work proposes an approach for optimally integrating building-scale energy technologies (both traditional and renewable) to enhance the transformation of the existing buildings (often energetically inefficient) in low-carbon systems. The approach promotes a transition sustainable from both the economic and environmental perspectives. Both operation and design optimization are considered with the aim of suggesting the best set of capacity of the technologies to be installed taking into account the expected operations. The building-scale technologies are integrated with proper storage units: Li-ion batteries and thermal storage (latent heat, that requires low installation space). As a dispatchable renewable technology, a biogas small-scale combined heat and power unit is included in the system. Once the key r... [more]

This paper proposes a compensation method for interpolation error of the maximum power control of a PMSM control system that generates current commands through a look-up table. A torque control system using a look-up table created through experiments has superior characteristics, such as control stability and torque accuracy, compared to a system that executes torque control via a linear controller based on modeling. However, it is impossible to generate information on all the currents for the output torque in the table. Therefore, because the data stored in the look-up table have a discrete characteristic, they are linearly interpolated to generate a current command for the torque command. However, the PMSM current trajectory is generally elliptical, which causes an error owing to linear interpolation, reducing the maximum output power. In particular, when the table data are insufficient, such as in the high-speed operation range, the reduced maximum output cannot be ignored. This pap... [more]

The method of analyzing the results of dust concentration measurements in mine workings that was conducted within the ROCD (Reducing risks from Occupational exposure to Coal Dust) European project using the developed dust prediction algorithm is presented. The analysis was based on the measurements of average dust concentration with the use of the CIP-10R gravimetric dust meters, for the respirable PM4 dust concentration, and IPSQ analyzer for instantaneous concentration measurements (including PM2.5 dust) and with the use of Pł-2 optical dust meters for instantaneous concentration measurements of PM10 dust. Based on the analyses of the measurement results, the characteristics of the distribution of PM10, PM4, and PM2.5 dust particles were developed for the tested dust sources. Then, functional models based on power functions were developed. The determined models (functions) allow predicting the dust distribution in such conditions (and places) for which we do not have empirical data.... [more]

The 2018 revision of the European Performance Building Directive (EPBD) requires that from the year 2020 onwards, all new buildings will have to be “nearly zero energy buildings”. It also further promotes smart building technologies, raising awareness amongst building owners and occupants of the value behind building automation. The European Commission also identified, in 2011, Key Enabling Technologies (KETs), which provide the basis for innovation in the EU. In the frame of the SUDOKET project, the Solar XXI building was used as a pilot case, as innovative integrated solutions and technologies are monitored and controlled. The objective of this paper is to validate a simulation of the laboratorial test room in EnergyPlus with data obtained experimentally and determine the impact of the control systems on energy needs and on thermal comfort. Two systems, in particular, were studied: the Building-Integrated Photovoltaic (BIPV) and the earth tubes. Once validated, the simulation of the... [more]

The integrated electricity and heating system (IEHS) can satisfy the diversified energy demand and improve energy efficiency through electro-thermal synergy and complementarity, which is beneficial for energy transformation and global climate governance. To reduce the operation cost, renewable energy source (RES) abandonment, and purchased electricity of IEHS, an optimal dispatching method of IEHS with multiple functional areas considering the flow regulation of the heat network is proposed. Firstly, the functional area of IEHS is classified and the functional area’s load characteristics are analyzed. Secondly, a heat network model considering refined resistance and dynamic characteristics is constructed and the operation regulation modes of the heat network are analyzed. Thirdly, an optimal dispatching model of IEHS with multiple functional areas considering heat network flow regulation is established to minimize the operation cost of IEHS with multiple functional areas while consider... [more]

In light of the global effort to limit the temperature rise, many cities have undertaken initiatives to become climate-neutral, making decentralized urban energy production more relevant. This paper addresses the potential of urban wind energy production with small wind turbines, using Berlin as an example. A complete framework from data selection to economic feasibility is constructed to enable the empirical assessment of wind energy for individual buildings and Berlin as a whole. Based on a detailed dataset of all buildings and hourly wind speed on a 1 km2 grid, the results show that multiple turbines on suitable buildings can significantly contribute to households’ energy consumption but fall short of covering the full demand. For individual households, our economic evaluation strongly recommends the self-consumption of the produced electricity. The findings suggest that while the use of small wind turbines should be continuously encouraged, exploring other renewable resources or co... [more]

With continued urbanization in China, the construction of urban gas pipelines is increasing, and the safety of gas pipelines are also increasingly affected by urban development and the increased scope of buildings and roads. Pipes with defects are more likely to fail under the surface loads. In this study, uniaxial tensile tests of high-density polyethylene (HDPE) pipes were carried out to obtain the real material parameters of pipe. A pipeline-soil interaction finite element model of HDPE pipeline with defects under surface load was established. The failure mechanism of the urban gas pipeline was studied and the influence of parameters such as internal pressure, defect position, defect depth on the mechanical behavior, and failure of pipelines were analyzed. A failure criterion for HDPE pipes with defects under surface load was proposed based on the limit-state curves obtained under different working conditions. Furthermore, an accurate and efficient fitness-for-service assessment pro... [more]

The mowing of sports fields generates a significant amount of waste biomass which requires appropriate management. On the largest scale, this problem affects golf courses with a grass surface area of up to 100 ha. Currently, the main directions for grass clippings management include composting, grass cycling, and waste. A certain alternative may be the energetic utilization of grass clippings, which not only solves the problem of organic waste management, but also brings measurable economic profits in the form of generated electricity and heat. This paper presents a techno-economic analysis of the application of a micro biogas plant, fed with grass clippings from a golf course project in Tuscany, with a grass surface of 111.21 ha. It has been shown that the annual biomass potential is 526.65 tDM∙year−1 (±45.64 tDM∙year−1), which makes it possible to build a micro biogas plant with an electric power of ca. 46 kW. The potential amount of electricity produced during the year is able to co... [more]

A centralised smart supervisor (CSS) controller with enhanced electrical energy management (E2-EM) capability has been developed for an Iron Bird Electrical Power Generation and Distribution System (EPGDS) within the Clean Sky 2 ENhanced electrical energy MAnagement (ENIGMA) project. The E2-EM strategy considers the potential for eliminating the 5 min overload capability of the generators to achieve a substantial reduction in the mass of the EPGDS. It ensures optimal power and energy sharing within the EPGDS by interfacing the CSS with the smart grid network (SGN), the energy storage and regeneration system (ESRS), and the programmable load bank 1 secondary distribution board (PLB1 SDU) during power overloads and failure conditions. The CSS has been developed by formalizing E2-EM logic as an algorithm operating in real time and by following safety and reliability rules. The CSS undergoes initial verification using model-in-the-loop (MIL) testing. This paper describes the EPGDS simulate... [more]

Compared with the marine shale from North America, Chinese lacustrine basins have more complex geological and reservoir conditions, which makes the selection of sweet spot intervals in the shale oil reservoir particularly difficult. It is thus crucial to accurately predict the shale oil sweet spots for effective exploration and development of shale oil in a lacustrine basin. In this paper, we propose an innovative evaluation method of shale oil sweet spots, which considers five primary parameters (i.e., total oil content, movable oil ratio, reservoir pressure coefficient, permeability, and rock brittleness index) to construct a comprehensive weighting factor, which is used to quantitatively identify a favorable shale oil reservoir. This method firstly constructs an evaluation function for each of the parameters, and then calculates a comprehensive weighting factor to determine the shale oil sweet spot. Statistical results show that the oil production of formation testing intervals have... [more]

Unmanned Ground Vehicles (UGV) are devices capable of performing basic working movements without the operator being in their immediate working environment. Their capabilities include but are not limited to the perception of the environment with the use of sensors, determining the platform’s position, and planning and executing its movement. Ultra Wideband (UWB) is one of the wireless communication technologies which is increasingly used in location systems. This article presents the use of UWB technology in developing a guide localization system for a UGV (one of the stages of implementing a follow-me system). The article describes tests carried out on the developed testbed. Their aim was to determine the hardware configuration of the anchor arrangement characterized by the minimum number of lost data packets during operation. In order to determine the influence of the analysed variables on the output values, the method of global sensitivity analysis for neural networks was used.

This essay considers the rural-to-urban transition and correlates it with urban energy demands. Three distinct themes are inspected and interrelated to develop awareness for an urbanizing world: internal urban design and innovation, technical transition, and geopolitical change. Data were collected on the use of energy in cities and, by extension, nation states over the last 30 years. The urban population boom continues to pressure the energy dimension with heavily weighted impacts on less developed regions. Sustainable urban energy will need to reduce resource inputs and environmental impacts and decouple economic growth from energy consumption. Fossil fuels continue to be the preferred method of energy for cities; however, an increased understanding is emerging that sustainable energy forms can be implemented as alternatives. Key to this transition will be the will to invest in renewables (i.e., solar, wind, hydro, tidal, geothermal, and biomass), efficient infrastructure, and smart... [more]

Inefficiencies in energy trading systems of microgrids are mainly caused by uncertainty in non-stationary operating environments. The problem of uncertainty can be mitigated by analyzing patterns of primary operation parameters and their corresponding actions. In this paper, a novel energy trading system based on a double deep Q-networks (DDQN) algorithm and a double Kelly strategy is proposed for improving profits while reducing dependence on the main grid in the microgrid systems. The DDQN algorithm is proposed in order to select optimized action for improving energy transactions. Additionally, the double Kelly strategy is employed to control the microgrid’s energy trading quantity for producing long-term profits. From the simulation results, it is confirmed that the proposed strategies can achieve a significant improvement in the total profits and independence from the main grid via optimized energy transactions.

Significant reduction in fuel consumption and NOx emissions can be achieved just by changing the driving along the road. In this paper, dynamic programming is employed to find two different driving profiles optimized for fuel consumption and NOx creation minimization in a diesel vehicle. Results, show that the fuel reduction driving cycle leads to fuel savings of 4% compared with the average consumption with arbitrary driving. The NOx reduction driving profile improves the emissions of arbitrary driving by a 34.5%. NOx oriented driving profile improves the emissions of the fuel-oriented cycle by a 38% at the expense of a fuel consumption penalty of 10%. This result points out the difficulty of a simultaneous NOx and fuel consumption reduction, stressing the efforts to be done in this field during the following years. Strategies followed and conclusions drawn from this paper are relevant concerning vehicle autonomy integration.

This article presents a variable-order derivative (VOD) time fractional model for describing heat transfer in the rotor or stator in non-contacting mechanical face seals. Most theoretical studies so far have been based on the classical equation of heat transfer. Recently, constant-order derivative (COD) time fractional models have also been used. The VOD time fractional model considered here is able to provide adequate information on the heat transfer phenomena occurring in non-contacting face seals, especially during the startup. The model was solved analytically, but the characteristic features of the model were determined through numerical simulations. The equation of heat transfer in this model was analyzed as a function of time. The phenomena observed in the seal include the conduction of heat from the fluid film in the gap to the rotor and the stator, followed by convection to the fluid surrounding them. In the calculations, it is assumed that the working medium is water. The maj... [more]

Power system planning in numerous electric utilities merely relies on the conventional statistical methodologies, such as ARIMA for short-term electrical load forecasting, which is incapable of determining the non-linearities induced by the non-linear seasonal data, which affect the electrical load. This research work presents a comprehensive overview of modern linear and non-linear parametric modeling techniques for short-term electrical load forecasting to ensure stable and reliable power system operations by mitigating non-linearities in electrical load data. Based on the findings of exploratory data analysis, the temporal and climatic factors are identified as the potential input features in these modeling techniques. The real-time electrical load and meteorological data of the city of Lahore in Pakistan are considered to analyze the reliability of different state-of-the-art linear and non-linear parametric methodologies. Based on performance indices, such as Root Mean Square Error... [more]

The production of a single gas well is influenced by many geological and completion factors. The aim of this paper is to build a production prediction model based on machine learning technique and identify the most important factor for production. Firstly, around 159 horizontal wells were collected, targeting the Duvernay Formation with detailed geological and completion records. Secondly, the key factors were selected using grey relation analysis and Pearson correlation. Then, three statistical models were built through multiple linear regression (MLR), support vector regression (SVR), gaussian process regression (GPR). The model inputs include fluid volume, proppant amount, cluster counts, stage counts, total horizontal lateral length, gas saturation, total organic carbon content, condensate-gas ratio. The model performance was assessed by root mean squared errors (RMSE) and R-squared value. Finally, sensitivity analysis was applied based on best performance model. The analysis shows... [more]