Climate change motivated by human activities constitutes one of the main challenges of this century. To cut carbon emissions in order to mitigate carbon’s dangerous effects, the current energy generation mix should be shifted to renewable sources. The main drawback of these technologies is their intermittency, which will require energy storage systems to be fully integrated into the generation mix, allowing them to be more controllable. In recent years, great progress to develop an effective and economically feasible energy storage systems, particularly motivated by the recent rise of demand for electric transportation, has been made. Lithium-ion (Li-ion) battery prices have fallen near 90% over the past decade, making possible the affordability of electric vehicles and transforming the economics of renewable energy. In this work, a study on storage capacity demand previously presented as conference paper is expanded, including a deep analysis of the Spanish generation mix, the evaluat... [more]

Based on the ventilation characteristics of the gob-side entry retaining face, a mathematical model of spontaneous combustion in the gob-side entry retaining face is established. From the overburden caving of the goaf along the goaf retaining roadway, the development characteristics of rock strata and residual coal fissures in the goaf are summarized and analyzed. In addition, by using numerical simulation software, the effects of normal mining period, goaf retaining roadway as return air roadway, air leakage prevention, and nitrogen injection measures in goaf on spontaneous combustion in goaf are studied, and the distribution characteristics of flow field, oxygen concentration field and temperature field in goaf are obtained. The results show that the mining of the Geng 20 working face has a significant impact on the Geng 19 coal seam. The Geng 19 coal seam is in the range of fracture zone, and the fracture is well developed. Furthermore, the permeability coefficient of the Geng 19 co... [more]

Solar photovoltaic (PV) power generation is prone to drastic changes due to cloud cover. The power is easily affected within a very short period of time. Thus, the accuracy of grasping cloud distribution is important for PV power forecasting. This study proposes a novel sky image method to obtain the cloud coverage rate used for short-term PV power forecasting. The authors developed an image analysis algorithm from the sky images obtained by an on-site whole sky imager (WSI). To verify the effectiveness of cloud coverage rate as the parameter for PV power forecast, four different combinations of weather features were used to compare the accuracy of short-term PV power forecasting. In addition to the artificial neural network (ANN) model, long short-term memory (LSTM) and the gated recurrent unit (GRU) were also introduced to compare their applicability conditions. After a comprehensive analysis, the coverage rate is the key weather feature, which can improve the accuracy by about 2% co... [more]

Wireless sensor networks (WSNs) and the Internet of Things (IoT) are increasingly making an impact in a wide range of domain-specific applications. In IoT-integrated WSNs, nodes generally function with limited battery units and, hence, energy efficiency is considered as the main design challenge. For homogeneous WSNs, several routing techniques based on clusters are available, but only a few of them are focused on energy-efficient heterogeneous WSNs (HWSNs). However, security provisioning in end-to-end communication is the main design challenge in HWSNs. This research work presents an energy optimizing secure routing scheme for IoT application in heterogeneous WSNs. In our proposed scheme, secure routing is established for confidential data of the IoT through sensor nodes with heterogeneous energy using the multipath link routing protocol (MLRP). After establishing the secure routing, the energy and network lifetime is improved using the hybrid-based TEEN (H-TEEN) protocol, which also... [more]

In this research, a Concentrated Solar Power (CSP) as a Parabolic Trough Collector (PTC), using Peltier cooling modules for power generation was analyzed by the Cross-Entropy method. When comparing conventional solar electric generators with this system, we have the advantage that it is compact and lightweight and can be easily assembled and used as low-cost power generation equipment. For this system, we perform I(V) measurements and use fit models to accurately extract the model parameters. This is all in a standalone, robust, and simultaneous fit of three equations, through the global optimization method called Cross-Entropy. This is a robust method that had never been applied to extract parameters in a thermoelectric generation.

Charcoal is produced in large quantities in the Portuguese region of Alentejo mainly using traditional brick kilns. Information about this type of carbonization technology is scarce, which makes it urgent to characterize the process as a starting point for performance improvements. In this context, this study aims to characterize the operation of a cylindrical brick kiln (≈80 m3) during regular wood carbonization cycles. Relevant process parameters were monitored along with the yields and/or composition of the main products (carbonization gas, charcoal, and charcoal fines) to evaluate the mass balance of the process. The results show that the bulk of the kiln operates at temperatures below 300 °C, which greatly limits the quality of the charcoal. For instance, the fixed carbon content of charcoal can easily be as low as 60 wt.%. The yield of charcoal is also low, with values below 25 wt.% of dry wood feed. This means that significant quantities of by-products are generated in the proce... [more]

The hydraulic turbine governing system (HTGS) is a complex nonlinear system that regulates the rotational speed and power of a hydro-generator set. In this work, an incremental form of an HTGS nonlinear model was established and the Takagi−Sugeno (T-S) fuzzy linearization and mixed H2/H∞ robust control theory was applied to the design of an HTGS controller. A T-S fuzzy H2/H∞ controller for an HTGS based on modified hybrid particle swarm optimization and gravitational search algorithm integrated with chaotic maps (CPSOGSA) is proposed in this paper. The T-S fuzzy model of an HTGS that integrates multiple-state space equations was established by linearizing numerous equilibrium points. The linear matrix inequality (LMI) toolbox in MATLAB was used to solve the mixed H2/H∞ feedback coefficients using the CPSOGSA intelligent algorithm to optimize the weighting matrix in the process so that each mixed H2/H∞ feedback coefficients in the fuzzy control were optimized under the constraints to im... [more]

The quality of electricity is a very important indicator. The durability and reliable operation of all connected devices depend on the quality of the network voltage. Rapid changes in loads, changes in network connections and the presence of uncontrolled energy sources require the development of new voltage regulation systems. This requires voltage regulation systems capable of responding quickly to sudden voltage changes. In substations with control transformers, it is possible thanks to the use of semiconductor tap changers. Moreover, voltage regulation and reactive power compensation systems should be built as one system. This is due to the close dependence of voltage and reactive power in the network node. Therefore, it was proposed to use artificial intelligence methods to build a new voltage regulation and reactive power compensation system using all measurement voltages of network nodes. In the first stage of the research, active and reactive powers, as well as the voltage of th... [more]

In view of the flow instability problem caused by the strong shock wave and secondary flow in the channel of the high-load counter-rotating compressor, this paper adopts the design method of coupling aerodynamic optimization technology and CFD and establishes a three-dimensional aerodynamic optimization design platform for the blade channel based on an artificial neural network and genetic algorithm. The aerodynamic optimization design and internal flow-field diagnosis of a high-load counter-rotating compressor with a 1/2 + 1 aerodynamic configuration are carried out. The research indicates that the optimized blade channel can drive and adjust the flow better, and the expected supercharging purpose and efficient energy conversion process are achieved by controlling the intensity of the shock wave and secondary flow in the channel. The total pressure ratio at the design point of the compressor exceeds 2.9, the adiabatic efficiency reaches 87%, and the aerodynamic performance is excellen... [more]

The aims of this study were to determine the concentrations and elemental composition of PM10 in the village of Kotórz Mały (Poland), to analyse their seasonal variability, to determine the sources of pollutant emissions and to compare the consistency of the results obtained using different methods. Sampling and weather condition measurements were carried out in the winter (January−February) and spring (April) of 2019. Two combinations of different techniques were used to examine PM10 concentrations and their chemical composition: gravimetric method + atomic absorption spectrometry (GM+AAS) and continuous particle monitor + energy dispersive X-ray fluorescence (CPM+EDXRF). In winter, the average concentrations of PM10 measured by the GM and CPM were similar (GM 44.3 µg/m3; CPM 34.0 µg/m3), while in spring they were clearly different (GM 49.5 µg/m3; CPM 29.8 µg/m3). Both AAS and EDXRF proved that in both seasons, Ca, K and Fe had the highest shares in the PM10 mass. In the case of the l... [more]

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]