The chemical looping gasification of residual biomasses—operated in fluidized beds composed of oxygen-carriers—may allow the production of biofuels from syngas. This biomass-to-fuel chain can contribute to mitigate climate change, avoiding the accumulation of greenhouse gases in our atmosphere. The ongoing European research project Horizon2020 CLARA (G.A. 817841) investigates wheat-straw-pellets (WSP) and raw-pine-forest-residue (RPR) pellets as feedstocks for chemical looping gasification. This work presents experimental results from devolatilizations of WSP and RPR, in bubbling beds made of three different oxygen-carriers or sand (inert reference), at 700, 800, 900 °C. Devolatilization is a key step of gasification, influencing syngas quality and quantity. Tests were performed at laboratory-scale, by a quartz reactor (fluidizing agent: N2). For each pellet, collected data allowed the quantification of released gases (H2, CO, CO2, CH4, hydrocarbons) and mass balances, to obtain gas yi... [more]

Frequency control is essential to ensure reliability and quality of power systems. North American Electric Reliability Corporation’s (NERC) Control Performance Standard 1 (CPS1) is widely adopted by many operating authorities to examine the quality of the frequency control. The operating authority would have a strong interest in knowing how the frequency-sensitive features affect the CPS1 score and finding out more effective unit-dispatch schedules for reaching the CPS1 goal. As frequency-sensitive features usually possess multi-variable and high-correlated characteristics, this paper employed an ensemble learning technique (the Gradient Boosting Decision Tree algorithm, GBDT) to construct Frequency Response Model (FRM) of the Taipower system in Taiwan to evaluate by CPS1 score. The proposed CPS1 model was then integrated with Unit Commitment (UC) program to determine the unit-dispatch that achieves the targeted CPS1 score. The feasibility and effectiveness of the proposed CPS1-UC plat... [more]

Due to the rapidly increasing energy demand and the more serious environmental pollution problems, lithium-ion battery is more and more widely used as high-efficiency clean energy. State of Charge (SOC) representing the physical quantity of battery remaining energy is the most critical factor to ensure the stability and safety of lithium-ion battery. The novelty SOC estimation model, which is two recurrent neural networks with gated recurrent units combined with Coulomb counting method is proposed in this paper. The estimation model not only takes voltage, current, and temperature as input feature but also takes into account the influence of battery degradation process, including charging and discharging times, as well as the last discharge charge. The SOC of the battery is estimated by the network under three different working conditions, and the results show that the average error of the proposed neural network is less than 3%. Compared with other neural network structures, the propo... [more]

This study aimed to determine the flow structures and heat transfer for flow past a tandem cylinder array and the effect of a slit on the enhancement of heat transfer. Different distances between cylinders and inclination angles of the slit were simulated to determine the effects on the flow pattern and heat transfer. Overall, the Nusselt number of the array is increased by 6−15% with applying a slit on a cylinder. However, in some special conditions, the slit induces two kinds of flow pattern transforms which are Suppression and Revival. The suppression mode inhibits the vortex shedding and reduces the heat transfer. In contrast, the revival mode triggers the vortex shedding and increases heat transfer.

In this work, the main research question is how a high penetration of energy communities (ECs) affects the national electricity demand in the residential sector. Thus, the existing building stock of three European regions/countries, namely, the Iberian Peninsula, Norway, and Austria, is analyzed and represented by four different model energy communities based on characteristic settlement patterns. A tailor-made, open-source model optimizes the utilization of the local energy technology portfolio, especially small-scale batteries and photovoltaic systems within the ECs. Finally, the results on the national level are achieved by upscaling from the neighborhood level. The findings of different 2030 scenarios (building upon narrative storylines), which consider various socio-economic and techno-economic determinants of possible future energy system development, identify a variety of modification potentials of the electricity demand as a result of EC penetration. The insights achieved in th... [more]

A fault propagates along physical paths until it reaches the boundary of the equipment or system, which shows as a functional failure. Hence, inferring the fault propagation helps to ensure the normal operation of the industrial system. To infer the fault propagation in the steam turbine system, a graph model is developed. Firstly, a process graph topology is constructed according to the system mechanism, whose nodes and edges represent the equipment and mutual relationships. Meanwhile, a fault graph topology is built, in which nodes indicate potential faults and edges are inferred propagation paths. Then, the representations of fault nodes are realized through a graph neural network. Lastly, link prediction methods based on nodes’ representations are conducted, along with the paths inference results. Consequently, the accuracy of fault propagation inference for the steam turbine system is over 86%.

Since most of our industries use induction motors, it is essential to develop condition monitoring systems. Nowadays, industries have power quality issues such as sag, swell, harmonics, and transients. Thus, a condition monitoring system should have the ability to detect various faults, even in the presence of power quality issues. Most of the fault diagnosis and condition monitoring methods proposed earlier misidentified the faults and caused the condition monitoring system to fail because of misclassification due to power quality. The proposed method uses power quality data along with starting current data to identify the broken rotor bar and bearing fault in induction motors. The discrete wavelet transform (DWT) is used to decompose the current waveform, and then different features such as mean, standard deviation, entropy, and norm are calculated. The neural network (NN) classifier is used for classifying the faults and for analyzing the classification accuracy for various cases. T... [more]

With the increasing penetration of renewable resources into the low-voltage distribution grid, the demand for alternatives to grid reinforcement measures has risen. One possible solution is the use of battery systems to balance the power flow at crucial locations in the grid. Hereby, the optimal location and size of the system have to be determined in regard to investment and its effect on grid stability. In this paper, the optimal placement and sizing of battery storage systems for grid stabilization in a small low-voltage distribution grid in southern Germany with high PV penetration are investigated and compared to a grid heuristic reinforcement strategy.

For apartment complexes receiving medium-voltage electrical energies, the apartments can choose an electricity charging method between the single and general contracts in the Republic of Korea. In the single contract, a residential high-voltage rate is applied to the total electrical energy consumptions of households and common areas. On the other hand, in the general contract, different rate plans are applied to the electrical energy consumptions of households and their common areas, where a generic high-voltage rate plan is applied to the common consumption. Hence, depending on the amounts and composition of the consumptions, both contracts have their own strengths and weaknesses in terms of the total electricity charge. The management office of an apartment complex can select its preferred contract considering the amount and composition of the power consumptions on an annual basis. In this paper, we first formulate a model for the contracts and analyze their properties based on Mont... [more]

This article introduces a new non-pillar coal mining technology (i.e., Gob-side Entry Retaining by Roof Cutting (GERRC)) under the condition of thick and hard roofs. First, we theoretically analyzed the solution to the large suspension span of the thick and hard roof in coal mining. Three-Zone pre-split blasting design in non-pillar coal mining for thick and hard roofs was proposed, based on the principles of rock mechanics. After field experiments, the technology was successfully applied to the non-pillar coal mining of a huge thick conglomerate roof. This research supplements the non-pillar mining technology system. The proposed technologies and methods have strong applicability and have certain guiding significance for the safe and efficient mining of related coal mines.

In this study, a performance evaluation of a photovoltaic thermal (PVT) system using nanofluids was carried out through an efficiency comparison study using water, CuO-water, and Al2O3-water nanofluids as the heat medium of the PVT system. In addition, a model for computational fluid dynamics (CFD) analysis was established, and the validity of the model was verified by comparing it with the experimental results of the PVT system. Through this, it was confirmed that the outlet temperature of the PVT system using nanofluids can be predicted by applying various conditions. Based on the results, the use of nanofluid as heating medium for the PVT system is proposed to improve the efficiency sufficiently compared to the conventional heating media.

The new standards on energy saving for new and existing buildings have animated both researchers and technicians in recent years, aiming at reducing the dependence on fossil fuels, improving indoor comfort, and systems efficiency. In this scenario, special attention must be paid to historical buildings that need to preserve their key testimonial heritage within the society. This paper describes the design and realization stages of a pilot system based on a ground-coupled heat pump, operating both in heating and cooling modes, installed in the monumental site of Saints Marcellino and Festo (SM&F), in Naples, Southern Italy. This study aims to demonstrate that low-enthalpy geothermal systems can be employed as energy retrofit applications in buildings of historical, artistic, and cultural interest and, at the same time, to prove that the use of this technology allows achieving the objectives, set at global level by the current regulations, and requiring a reduction of carbon dioxide emis... [more]

A new robust scheduling method for pumping water in a water distribution system under the uncertainty of activating regulation reserves is proposed in this paper. During the operation of power systems, utilizing the energy equipment of the customer to enhance supply-demand control is attracting attention. Because water pumps have been already installed, they can be regarded as a relatively inexpensive, operational, and flexible resource. Changes in the operation of the water pump can contribute to the power supply and demand control. The proposed method helps generate a robust daily schedule for pumping water and provides regulation reserves under the uncertainty of activating regulation reserves. It is based on electric energy prices and regulation reserves, hourly water demand profiles, and the properties of water flow quantity and the electricity consumption of water pumps. This method comprises an optimization model formulated using mixed integer linear programming, validated throu... [more]

A slightly and two severely biodegraded crude oils with the same origin were analysed using negative-ion electrospray ionization Orbitrap mass spectrometry (ESI Orbitrap MS), gas chromatography-nitrogen chemiluminescence detector (GC-NCD), and GC-sulfur chemiluminescence detector (GC-SCD) to investigate the composition of heteroatomic compounds and their fate during severe biodegradation and to provide insights into biodegradation pathway of hopanes, nitrogen- and sulfur-containing compounds. Twelve heteroatomic compound classes, including O1−O5, N1, N2, N1O1−N1O3, N1S1 and O3S1, were detected and assigned unambiguous molecular formulae. The O1 species are likely phenols with additional naphthenic and/or aromatic rings. Carboxylic acids (O2 species) are originated from oxidation of hydrocarbons, and the tricyclic naphthenic acids are the most resistant, followed by bicyclics. Hopanes could be biodegraded by demethylation or by unstable hopanoic acids as intermediates to yield 25-norhop... [more]

The thirst of the Earth for energy is lurching towards catastrophe in an era of increasing water shortage where most of the power plants are hydroelectric. The hydro-based power systems are facing challenges in determining day-ahead generation schedules of cascaded hydropower plants. The objective of the current study is to find a speedy and practical method for predicting and classifying the future schedules of hydropower plants in order to increase the overall efficiency of energy by utilizing the water of cascaded hydropower plants. This study is significant for water resource planners in the planning and management of reservoirs for generating energy. The proposed method consists of data mining techniques and approaches. The energy production relationship is first determined for upstream and downstream hydropower plants by using multiple linear regression. Then, a cluster analysis is used to find typical generation curves with the help of historical data. The decision tree algorith... [more]

The gravel packing completion method for horizontal wells has the advantages of maintaining high oil production for a long time, maintaining wellbore stability, and preventing sand production, so it has become the preferred completion method for horizontal wells. At present, this technology still faces the problems of high sand bed height and poor gravel migration. In order to improve the efficiency of gravel packing in horizontal wells, pulsed gravel packing technology for horizontal wells is proposed for the first time. Based on the mechanism of hydraulic pulse, the Eulerian−Eulerian model, k-ε model based on the renormalization group theory (RNG k-ε model), and Fluent are used to simulate the solid-liquid two-phase flow. By optimizing the parameters such as frequency and amplitude of pulse waveform, the optimal pulse waveform of pulsed gravel packing in horizontal wells is determined. The effects of parameters such as sand-carrying fluid displacement, sand-carrying fluid viscosity,... [more]

In this study, coconut oils have been transesterified with ethanol using microwave technology. The product obtained (biodiesel and FAEE) was then fractional distillated under vacuum to collect bio-kerosene or bio-jet fuel, which is a renewable fuel to operate a gas turbine engine. This process was modeled using RSM and ANN for optimization purposes. The developed models were proved to be reliable and accurate through different statistical tests and the results showed that ANN modeling was better than RSM. Based on the study, the optimum bio-jet fuel production yield of 74.45 wt% could be achieved with an ethanol−oil molar ratio of 9.25:1 under microwave irradiation with a power of 163.69 W for 12.66 min. This predicted value was obtained from the ANN model that has been optimized with ACO. Besides that, the sensitivity analysis indicated that microwave power offers a dominant impact on the results, followed by the reaction time and lastly ethanol−oil molar ratio. The properties of the... [more]

Interior and exterior wind turbine blade inspections are necessary to extend the lifetime of wind turbine generators. The use of unmanned vehicles is an alternative to exterior wind turbine blade inspections performed by technicians that require the use of cranes and ropes. Interior wind turbine blade inspections are even more challenging due to the confined spaces, lack of illumination, and the presence of potentially harmful internal structural components. Additionally, the cost of manned interior wind turbine blade inspections is a major limiting factor. This paper analyses all aspects of the viability of using manually controlled or autonomous aerial vehicles for interior wind turbine blade inspections. We discuss why the size, weight, and flight time of a vehicle, in addition to the structure of the wind turbine blade, are the main limiting factors in performing internal blade inspections. We also describe the design issues that must be considered to provide autonomy to unmanned v... [more]

A wellbore surface is an irregular surface structure. The distribution of points on the wellbore surface measured based on the drilling diameter is not uniform. Thus, the conventional modeling method based on a point cloud cannot satisfy the needs of real-time measurement updating and wellbore display. This study proposes a spiral profile method for drilling shaft surface reconstruction. Scattered data along the drilling diameter are measured, and an inverse distance weighting cylindrical space surface algorithm with iterative interpolation is used to obtain the spiral angle and pitch of a relatively homogeneous helical contour line along the surface of the shaft. Using sets of four adjacent points in the spiral, quadrilaterals are formed, and then all obtained quadrilaterals are used to form the wellbore inner surface structure. This method can further construct the outer surface spiral contour line to advance the quadrilateral surface to the spatial hexahedron structure. The caliper... [more]

Nowadays we can observe a growing demand for installations of new gas pipelines in Europe. A large number of them are installed using trenchless Horizontal Directional Drilling (HDD) technology. The aim of this work was to develop and compare new machine learning models dedicated for risk assessment in HDD projects. The data from 133 HDD projects from eight countries of the world were gathered, profiled, and preprocessed. Three machine learning models, logistic regression, random forests, and Artificial Neural Network (ANN), were developed to predict the overall HDD project outcome (failure free installation or installation likely to fail), and the occurrence of identified unwanted events. The best performance in terms of recall and accuracy was achieved for the developed ANN model, which proved to be efficient, fast and robust in predicting risks in HDD projects. Machine learning applications in the proposed models enabled eliminating the involvement of a group of experts in the risk... [more]

Electric arcing is a common problem in DC power systems. To overcome this problem, the electric arc detection algorithm has been developed as a faster alternative to existing algorithms. The following issues are addressed in this paper: The calculation of the proposed algorithm of incremental decomposition of the signal over time; the computational complexity of Fast Fourier Transform (FFT) and the incremental decomposition; the test bench used to measure electric arcs at given parameters; the analysis of measurements using FFT; and the analysis of measurements using incremental decomposition. The parameters are the DC voltage, electric load, and width of the gap between electrodes. The results showed that the proposed algorithm allows for a faster calculation—about seven times faster than FFT—and cheaper implementation in electric arc detection devices than FFT.

Demand side response is becoming an increasingly significant issue for reliable power systems’ operation. Therefore, it is desirable to ensure high effectiveness of such programs, including electricity tariffs. The purpose of the study is developing a method for analysing electricity tariff’s effectiveness in terms of demand side response purposes based on statistical data concerning tariffs’ use by the consumers and price elasticity of their electricity demand. A case-study analysis is presented for residential electricity consumers, shifting the settlement and consequently the profile of electricity use from a flat to a time-of-use tariff, based on the comparison of the considered tariff groups. Additionally, a correlation analysis is suggested to verify tariffs’ influence of the power system’s peak load based on residential electricity tariffs in Poland. The presented analysis proves that large residential consumers aggregated by tariff incentives may have a significant impact on th... [more]

For hydrothermal liquefaction of dry biomass to produce liquid fuels, water needs to be added or the aqueous phase products can be recycled. This paper focuses on understanding the relationship between hydrothermal degradation of the dry biomass and oil formation under the condition of accumulative recycling of the aqueous phase. Completely dried corn stalk and deionized water were used for the hydrothermal liquefaction (HTL) experiment. The aqueous products for subsequent recycling were not diluted. It was demonstrated that the recycling of the aqueous can promote the enrichment of organic acids and the conversion of ketones and phenols in the aqueous, improving the yield and quality of Bio-crude oil. After recycling, the yield of Bio-crude oil increased from 20.42% to 24.31% continuously, and the oxygen content decreased from 13.34% to 9.90%. Although the process was accompanied by solid deposition and had a negative impact on the hydrothermal degradation efficiency, the formation of... [more]

This paper presents an algorithm to remove the DC drift from the B-H curve of an additively manufactured soft ferromagnetic material. The removal of DC drift from the magnetization curve is crucial for the accurate estimation of iron losses. The algorithm is based on the sliding mean value subtraction from each cycle of calculated magnetic flux density (B) signal. The sliding mean values (SMVs) are calculated using the convolution theorem, where a DC kernel with a length equal to the size of one cycle is convolved with B to recover the drifting signal. The results are based on the toroid measurements made by selective laser melting (SLM)-based 3D printing mechanism. The measurements taken at different flux density values show the effectiveness of the method.

Additive manufacturing has many advantages over traditional manufacturing methods and has been increasingly used in medical, aerospace, and automotive applications. The flexibility of additive manufacturing technologies to fabricate complex geometries from copper, polymer, and ferrous materials presents unique opportunities for new design concepts and improved machine power density without significantly increasing production and prototyping cost. Topology optimization investigates the optimal distribution of single or multiple materials within a defined design space, and can lead to unique geometries not realizable with conventional optimization techniques. As an enabling technology, additive manufacturing provides an opportunity for machine designers to overcome the current manufacturing limitation that inhibit adoption of topology optimization. Successful integration of additive manufacturing and topology optimization for fabricating magnetic components for electrical machines can en... [more]