One of the bottlenecks of autonomous systems is to identify and/or design models and tools that are not too resource demanding. This paper presents the concept and design process of a moving platform structure−electric vehicle. The objective is to use artificial intelligence methods to control the model’s operation in a resource scarce computation environment. Neural approaches are used for data analysis, path planning, speed control and implementation of the vision system for road sign recognition. For this purpose, multilayer perceptron neural networks and deep learning models are used. In addition to the neural algorithms and several applications, the hardware implementation is described. Simulation results of systems are gathered, data gathered from real platform tests are analyzed. Experimental results show that low-cost hardware may be used to develop an effective working platform capable of autonomous operation in defined conditions.

This study aims to develop a predictive and reliable data-driven model for forecasting the fluid production (oil, gas, and water) of existing wells and future infill wells for CO2-enhanced oil recovery (EOR) and CO2 storage projects. Several models were investigated, such as auto-regressive (AR), multilayer perceptron (MLP), and long short-term memory (LSTM) networks. The models were trained based on static and dynamic parameters and daily fluid production while considering the inverse distance of neighboring wells. The developed models were evaluated using walk-forward validation and compared based on the quality metrics, span, and variation in the forecasting horizon. The AR model demonstrates a convincing generalization performance across various time series datasets with a long but varied forecasting horizon across eight wells. The LSTM model has a shorter forecasting horizon but strong generalizability and robustness in forecasting horizon consistency. MLP has the shortest and mos... [more]

A new SOC (State-Of-Charge)−VOC (Voltage-of-Open-Circuit) mathematical model was proposed in this paper, which is particularly useful in parallel lithium battery modeling. When the battery strings are charged in parallel connection, the batteries can be deemed as capacitors with different capacitances, and the one with larger capacitance always obtains the higher current. According to this mathematical model, the parallel battery charging with different peak capacitances can result in different voltage slew rates on different battery strings during the constant current control. Different parallel battery strings are charged with different currents, of which the battery string under higher current can induce higher power loss and higher temperature. The conventional solution can use this model to switch the constant current charging into the constant voltage charging with the correct timing to avoid overcurrent charging. Other battery pack protection methods including current sense resi... [more]

As a new energy source, gas hydrates have attracted worldwide attention, but their exploration and development face enormous challenges. Thus, it has become increasingly crucial to identify hydrate distribution accurately. Electrical resistivity tomography (ERT) can be used to detect the distribution of hydrate deposits. An ERT inversion network (ERTInvNet) based on a deep neural network (DNN) is proposed, with strong learning and memory capabilities to solve the ERT nonlinear inversion problem. 160,000 samples about hydrate distribution are generated by numerical simulation, of which 10% are used for testing. The impact of different deep learning parameters (such as loss function, activation function, and optimizer) on the performance of ERT inversion is investigated to obtain a more accurate hydrate distribution. When the Logcosh loss function is enabled in ERTInvNet, the average correlation coefficient (CC) and relative error (RE) of all samples in the test sets are 0.9511 and 0.109... [more]

In the European energy market, the community energy sector is earmarked to make a significant contribution to the transition from fossil fuels to sustainable sources. Based on the diffusion of innovation model, large-scale development of community energy requires that the concept and the success of existing energy communities be widely communicated to potential participants and that user confidence be developed over time. In this paper, we present the architecture, design, prototyping, and testing of a digital support platform, co-designed with EU-wide energy communities, to support this process. The platform has been designed to engage early-stage or ongoing groups to progress projects and to connect and share experiences with other communities. This “community of communities” creates the necessary communication channel defined in the Diffusion of Innovation model. A transactional architecture for such a platform is outlined with clear links to all community energy actors. Based on th... [more]

For low permeability coal seam permeability is weak, low degree of gas migration, prone to gas accidents and other issues. In this paper, a numerical model is established to simulate the process of hydraulic fracturing under monotonic loading and cyclic loading, and a method of increasing permeability of coal seam by cyclic loading hydraulic fracturing technology is proposed. Combined with similar experiments, the influence of cyclic load and cyclic load applied parameters on the fracturing effect of coal and rock mass was analyzed by applying a cyclic load with a pulse pump. The effect of cyclic load pressure technology on coal seam drainage was analyzed by application in 20915 gas control roadways of a coal mine in Guizhou. The results show that after fracturing, the fracture extends along the weak plane of the prefabricated fracture, the pore pressure in the fracture is high pressure, and the pore pressure around the fracture decreases step by step. Due to the compression of the cra... [more]

For assessment of the insulation performance of high-voltage (HV) equipment installed in extra-high-voltage (EHV) systems, switching impulse voltage tests are performed in an HV testing laboratory. The waveform parameters of the switching impulse voltages are defined by peak voltage (Up), time to crest (Tp), and time to half (T2) according to IEC 60060-1. In this paper, a new, simplified, and accurate approach used for determination of the waveform parameters of the switching impulse voltages is presented. The formula used in the evaluation of Tp was derived from analytically simulated two-exponential waveforms, where Tp and T2 are in the ranges of 20 μs to 300 μs and 1000 μs to 4000 μs, respectively. The accuracy of the proposed approach was validated by the waveforms collected from the test waveform data generator (TDG) provided by IEC 61083-2, simulations, and experiments. It is found that the accuracy of the proposed approach is relatively higher than the expressions provided by IE... [more]

The climate emergency has intensified the search for the generation of electricity from renewable energies in order to turn cities into sustainable cities. Small-scale wind power offers new opportunities for decentralized electricity production, avoiding dependence on the grid and transmission losses. Among viable locations within the urban environment, high-rise buildings are especially promising due to the elevated height and less turbulent wind conditions. They can also be integrated into the architecture of the building or as independent units in the urban environment. In this area, this work presents a methodology for determining the annual energy production of urban wind projects. The proposal is divided into four stages: location, wind and urban indicators, turbine selection and annual production estimation, and economic/environmental analysis. The evaluation of the solution is carried out for a Spanish case study. According to the results, more than 68,000 kWh/year can be gener... [more]

The hydraulic accumulator has the advantages of high power density, fast response, stable operation and high cost performance. However, compared with the electric energy storage method, the hydraulic accumulator has low energy density and large pressure fluctuation while absorbing and discharging energy, which severely limits its application in hydraulic excavators. To improve the potential energy loss of the boom during the lowering process, an electro-hydraulic drive and energy recovery system for excavator booms (EHDR-EEB) based on a battery and accumulator is proposed. As a result, a simulation model of the electro-hydraulic drive and energy management strategy of a 1.6 t pure electric hydraulic excavator is built to investigate the energy regeneration and utilization. The simulation outcomes show that the potential energy recovery rate is as high as 92%. This research on EHDR-EEB makes a significant contribution to the economic improvement of electric hydraulic excavators.

A turbulent jet ignition engine enables operation with lean mixtures, decreasing nitrogen oxide (NOX) emissions up to 92%, while the engine efficiency can be increased compared to conventional spark-ignition engines. The geometry of the pre-chamber and engine operating parameters play the most important role in the performance of turbulent jet ignition engines and, therefore, must be optimized. The initial experimental and 3D CFD results of a single-cylinder engine fueled by gasoline were used for the calibration of a 0D/1D simulation model. The 0D/1D simulation model was upgraded to capture the effects of multiple flame propagations, and the evolution of the turbulence level was described by the new K-k-ε turbulence model, which considers the strong turbulent jets occurring in the main chamber. The optimization of the pre-chamber volume, the orifice diameter, the injected fuel mass in the pre-chamber and the spark timing was made over 9 different operating points covering the variatio... [more]

The paper presents and solves the problems of modeling and designing the required EV charging service capacity for systems with a slow dynamic component. This includes possible bursts within a peak hour interval. A simulation tool with a newly implemented capacity planning method has been developed and implemented for these needs. The method can be used for different system simulations and simultaneously for systems with high, medium, and low service dynamics. The proposed method is based on a normal distribution, a primary mechanism that describes events within a daily interval (24 h) or a peak hour interval (rush hour). The goal of the presented approach, including the proposed method, is to increase the level and quality of the EV charging service system. The near-optimal solution with the presented method can be found manually by changing the service capacity parameter concerning the criterion function. Manual settings limit the number of rejected events, the time spent in the queu... [more]

The function of vehicle powertrains (including hybrid powertrains) is to transmit power from the power source (engine or electric machine) to driving wheels. The planetary gear train (PGT) is a core structure of mechanisms of powertrains. The detection of topological symmetry is helpful for improving the efficiency of mechanism design. In this paper, we present a fully automatic and reliable method for detecting symmetry of plane kinematic chains and extend this method to symmetry detection and the topological design of mechanisms of powertrains. First, the topological model and adjacency matrix are introduced to represent various kinds of plane kinematic chains. Then, the moment matrix of the kinematic chain is established to obtain link groups, based on which we propose an algorithm to generate the unique numerical code of each link and precisely detect the symmetry. Our method is applied to synthesize different kinds of plane kinematic chains and mechanisms, which can improve the de... [more]

With the large amounts of small capacity and heterogeneous distributed electricity units connected to the distribution power network, there exist increasingly complex management challenges. In this paper, a new management scheme that can classify and divide the distributed units according to their adjustable characteristics is proposed, which consequently forms an effective collection of fragmented adjustable ability and promotes the utilization of micropower resources. Inspired by the social division of labor in the biological community, the approach is based on a logical aggregation with the division of labor. A feature extraction method was acquired on the basis of the daily output curve, which reduces the data dimension and, subsequently, clusters the output feature points by the K-means algorithm. The simulation is performed by taking the measured output curve of low voltage distributed units on the low voltage side. The experimental results analyze the characteristics of seven cl... [more]

This paper aims at presenting a novel effective approach to probabilistic analysis of distribution power grid with high penetration of PV sources. The novel method adopts a Gaussian Mixture Model for reproducing the uncertainty of correlated PV sources along with a piece-wise-linear approximation of the voltage-power relationship established by load flow problem. The method allows the handling of scenarios with a large number of uncertain PV sources in an efficient yet accurate way. A distinctive feature of the proposed probabilistic analysis is that of directly providing, in closed-form, the joint probability distribution of the set of observable variables of interest. From such a comprehensive statistical representation, remarkable information about grid uncertainty can be deduced. This includes the probability of violating the safe operation conditions as a function of PV penetration.

Efforts to decarbonize the world have shown a quick increase in electric vehicles (EVs), limiting increasing pollution. During this electric transportation revolution, lithium-ion batteries (LIBs) play a vital role in storing energy. To determine the range of an electric vehicle (EV), the state of charge and the state of health (SOH) of the battery pack is essential. Access to high-quality data on battery parameters is a crucial challenge for researchers working in the energy storage domain due primarily to confidentiality constraints on manufacturers of batteries and EVs. This paper proposes a hybrid framework for predicting the state of a lithium-ion battery for electric vehicles (EV). Electric vehicles are growing worldwide because of their environmental and sustainability advantages. Batteries are replacing fossil fuels in electric vehicles. In order to prevent failure, Li-ion batteries in electric vehicles should be operated and controlled in a controlled and progressive manner to... [more]

This paper proposes a novel network anomaly detection framework based on data balance and feature selection. Different from the previous binary classification of network intrusion, the network anomaly detection strategy proposed in this paper solves the problem of multiple classification of network intrusion. Regarding the common data imbalance of a network intrusion detection set, a resampling strategy generated by random sampling and Borderline SMOTE data is developed for data balance. According to the features of the intrusion detection dataset, feature selection is carried out based on information gain rate. Experiments are carried out on three basic machine learning algorithms (K-nearest neighbor algorithm (KNN), decision tree (DT), random forest (RF)), and the optimal feature selection scheme is obtained.

In modern Electric Power Systems, emphasis is placed on the increasing share of electricity from renewable energy sources (PV, wind, hydro, etc.), at the expense of energy generated with the use of fossil fuels. This will lead to changes in energy supply. When there is excessive generation from RESs, there will be too much energy in the system, otherwise, there will be a shortage of energy. Therefore, smart devices should be introduced into the system, the operation of which can be initiated by the conditions of the power grid. This will allow the load profiles of the power grid to be changed and the electricity supply to be used more rationally. The article proposes an elastic energy management algorithm (EEM) in a hierarchical control system with distributed control devices for controlling domestic smart appliances (SA). In the simulation part, scenarios of the algorithm’s operation were carried out for 1000 households with the use of the distribution of activities of individual SAs.... [more]

The shift toward electric mobility in Germany is a major component of the German climate protection program. In this context, public charging is growing in importance, especially in high-density urban areas, which causes an additional load on the distribution grid. In order to evaluate this impact and prevent possible overloads, realistic models are required. Methods for implementing such models and their application in the context of grid load are research topics that are only minorly addressed in the literature. This paper aims to demonstrate the entire process chain from the selection of a modelling method to the implementation and application of the model within a case study. Applying a stochastic approach, charging points are modelled via probabilities to determine the start of charging, plug-in duration, and charged energy. Subsequently, load profiles are calculated, integrated into an energy system model and applied in order to analyze the effects of a high density of public cha... [more]

Variable renewable energy (VRE) generation changes the shape of residual demand curves, contributing to the high operating costs of conventional generators. Moreover, the variable characteristics of VRE cause a mismatch between electricity demand and power generation, resulting in a greater expected energy not supplied (EENS) value. EENS involves an expected outage cost, which is one of the important components of power-generation costs. A utility-scale battery energy storage system (BESS) is popularly used to provide ancillary services to mitigate the VRE impact. The general BESS ancillary-service applications are as a spinning reserve, for regulation, and for ramping. A method to determine optimal sizing and the optimal daily-operation schedule of a grid-scale BESS (to compensate for the negative impacts of VRE in terms of operating costs, power-generation-reliability constraints, avoided expected-outage costs, and the installation cost of the BESS) is proposed in this paper. Moreove... [more]

Building renovation was declared a key point for sustainable development, however, the renovation rate of residential buildings in the European Union is insufficient to meet the climate and energy targets set. This paper analyses the main circular economy models used in the construction sector, as well as the situation of the building renovation market, to set a framework for circular economy models in building renovation. Of all the existing strategies in this sector, design, material recovery, building renovation and end-of-life actions would be the best, respectively. It also includes a market analysis consisting of a literature review covering PEST perspectives (political, economic, social and technical) and a SWOT analysis (strengths, weaknesses, opportunities and threats), concluding with a market gap analysis. The results of these analyses allow the development of a series of suggestions and strategies to be followed in order to solve the main barriers that hinder the implementa... [more]

In recent years, experimental tests related to building components through laboratory facilities have relatively matured. The techniques are based on one-dimensional heat transfer by creating a permanent temperature difference over a specimen to control heat fluxes. The three main methods are the Guarded Hot Box (GHB) method, the Calibrated Hot Box (CHB) method, and the Heat-Flow Meter method (HFM). The HFM method is the most widely applied technique for measuring on-site U-values of building components and several scientific works stressed the need for high temperature differences between the environments, suggesting 10 °C or 15 °C. However, temperature stability and high temperature gradients are difficult to obtain, especially for Mediterranean climatic conditions. Starting from this, an experimental study was conducted through a GHB apparatus, setting temperature differences from 2 °C to 20 °C between the hot and cold chambers. Heat flow measurements were performed to compute the t... [more]

Hydrogen is a carbon-free fuel that can be produced in many ways starting from different sources. Its use as a fuel in internal combustion engines could be a method of significantly reducing their environmental impact. In spark-ignition (SI) engines, lean hydrogen−air mixtures can be burnt. When a gaseous fuel like hydrogen is port-injected in an SI engine, working with lean mixtures, supercharging becomes very useful in order not to excessively penalize the engine performance. In this work, the performance of a turbocharged PFI spark-ignition engine fueled by hydrogen has been investigated by means of 1-D numerical simulations. The analysis focused on the engine behavior both at full and partial load considering low and medium engine speeds (1500 and 3000 rpm). Equivalence ratios higher than 0.35 have been considered in order to ensure acceptable cycle-to-cycle variations. The constraints that ensure the safety of engine components have also been respected. The results of the analysis... [more]

With the development of power plant units of higher capacity and with improved parameters, the proportion of high-capacity units for generating power has increased; this requires large capacity units to take responsibility for power-grid peak shaving. When the boiler operates at low loads, the working fluid in the boiler water wall tubes is subjected to high heat flux in the furnace, which can cause heat transfer deterioration, tube overheating or even leakage. Therefore, it is particularly important to study the reliability of the boiler hydrodynamic cycle during peak shaving (low load operation). This study takes a 1000 MW ultra-supercritical single-reheat Π type boiler with single furnace and double tangential firing as the research object. A furnace Computational Fluid Dynamics (CFD) and hydrodynamic coupling analysis model is established and verified according to the actual operating conditions on site. The calculation results show that the simulated value is in good agreement wit... [more]

This paper presents a technical overview for Switched Reluctance Generators (SRG) in Wind Energy Conversion System (WECS) applications. Several topics are discussed, such as the main structures and topologies for SRG converters in WECS, and the optimization control methods to improve the operational efficiency of SRGs in wind power generation systems. A comprehensive overview including the main characteristics of each SRG converter topology and control techniques were discussed. The analysis presented can also serve as a foundation for more advanced versions of SRG control techniques, providing a necessary basis to spur more and, above all, motivate the younger researchers to study magnetless electric machines, and pave the way for higher growth of wind generators based on SRGs.

A general rise in environmental and anthropogenically induced greenhouse gas emissions has resulted from worldwide population growth and a growing appetite for clean energy, industrial outputs, and consumer utilization. Furthermore, well-established, advanced, and emerging countries are seeking fossil fuel and petroleum resources to support their aviation, electric utilities, industrial sectors, and consumer processing essentials. There is an increasing tendency to overcome these challenging concerns and achieve the Paris Agreement’s priorities as emerging technological advances in clean energy technologies progress. Hydrogen is expected to be implemented in various production applications as a fundamental fuel in future energy carrier materials development and manufacturing processes. This paper summarizes recent developments and hydrogen technologies in fuel refining, hydrocarbon processing, materials manufacturing, pharmaceuticals, aircraft construction, electronics, and other hydro... [more]