The study concerns the preparation of post-consumer food packaging for selective collection that takes place in households. The previously reported results suggested that the economic cost of washing the packaging exceeded the value of recyclable materials. A shortage of up-to-date papers on the economic balance of packaging washing, taking into account current trends in the increase of prices of materials and energy carriers, has been identified. The main objective of this study was to determine the effect of the application of particular heat sources on the total cost of preparing the glass and plastic packaging for selective collection, as well as to compare the cost with the economic value of recyclables. Over the last ten years, a drop in the purchase price of glass cullet and post-consumer plastic, as well as an increase in the cost of cold and hot water, have been reported. Accordingly, the profit of packaging cleaning, defined as the difference between the value of recyclable m... [more]

Recent studies have shown that relative permeability can be modeled as a state function which is independent of flow direction and dependent upon phase saturation (S), phase connectivity (X), and fluid−fluid interfacial area (A). This study evaluates the impact of each of the three state parameters (S, X, and A) in the estimation of relative permeability. The relative importance of the three state parameters in four separate quadrants of S-X-A space was evaluated using a machine learning algorithm (out-of-bag predictor importance method). The results show that relative permeability is sensitive to all the three parameters, S, X, and A, with varying magnitudes in each of the four quadrants at a constant value of wettability. We observe that the wetting-phase relative permeability is most sensitive to saturation, while the non-wetting phase is most sensitive to phase connectivity. Although the least important, fluid−fluid interfacial area is still important to make the relative permeabil... [more]

Energy is at the center of human society and drives the technologies and overall human well-being. Today, artificial intelligence (AI) technologies are widely used for system modeling, prediction, control, and optimization in the energy sector. The internet of things (IoT) is the core of the third wave of the information industry revolution and AI. In the energy sector, tens of billions of IoT appliances are linked to the Internet, and these appliances generate massive amounts of data every day. Extracting useful information from the massive amount of data will be a very meaningful thing. Complex event processing (CEP) is a stream-based technique that can extract beneficial information from real-time data through pre-establishing pattern rules. The formulation of pattern rules requires strong domain expertise. Therefore, at present, the pattern rules of CEP still need to be manually formulated by domain experts. However, in the face of complex, massive amounts of IoT data, manually set... [more]

There is increasing growth in load demands and financial strain to upgrade the present power distribution system. It faces challenges such as power losses, voltage deviations, lack of reliability and voltage instability. There is also a sense of responsibility in the wake of environmental and energy crises to adopt distributed renewable resources for power generation. These challenges can be resolved by optimally allocating distributed generators (DGs) at different suitable locations in the radial power distribution system. Optimal allocation is a non-linear problem which is solved by powerful metaheuristic optimization algorithms. In this work, an objective function is introduced to optimally size four different types of DGs by utilizing honey badger algorithm (HBA), and comparison is drawn with grey wolf optimization (GWO) and whale optimization algorithm (WOA). The objective is to boost the voltage profile and minimize the power losses of the standard IEEE 33bus and 69-bus radial po... [more]

The significant proliferation of renewable resources, primarily inverter interfaced distributed generation (IIDG) in the utility grid, leads to a dearth of overall inertia. Subsequently, the system illustrates more frequency nadir and a steeper frequency response. This may degrade the dynamic frequency stability of the overall system. Further, virtual inertia has been synthetically developed in IIDG, which is known as a virtual synchronous generator (VSG). In this work, a novel STO-STC-based controller has been developed, which offers flexible inertia following system disturbance. The controller is based on the super-twisting algorithm (STA), which is a further advancement in the conventional sliding mode control (SMC), and has been incorporated in the control loop of the VSG. In this scheme, two steps have been implemented, where the first one is to categorize all states of the system using a super-twisting observer (STO) and further, it is required to converge essential states very q... [more]

The increasing popularity of electric vehicles (EVs) has been attributed to their low-carbon and environmentally friendly attributes. Extensive research has been undertaken in view of the depletion of fossil fuels, changes in climatic conditions due to air pollution, and the goal of developing EVs capable of matching or exceeding the performance of today’s internal combustion engines (ICEs). The transition from ICE vehicles to EVs can reduce greenhouse gases significantly over a vehicle’s lifetime. Across the different types of EVs, the widespread usage of batteries is due to their high power density and steady output voltage, making them an excellent energy storage device (ESD). The current downsides of battery-powered electric vehicles include long recharge times, the impact of additional strain on the grid, poor societal acceptance due to high initial costs, and a lack of adequate charging infrastructure. Even more problematic is their short driving range when compared to standard I... [more]

The current work presents the electro-oxidation of olive mill and biodiesel wastewaters in an alkaline medium with the aim of hydrogen production and simultaneous reduction in the organic pollution content. The process is performed, at laboratory scale, in an own-design single cavity electrolyzer with graphite electrodes and no membrane. The system and the procedures to generate hydrogen under ambient conditions are described. The gas flow generated is analyzed through gas chromatography. The wastewater balance in the liquid electrolyte shows a reduction in the chemical oxygen demand (COD) pointing to a decrease in the organic content. The experimental results confirm the production of hydrogen with different purity levels and the simultaneous reduction in organic contaminants. This wastewater treatment appears as a feasible process to obtain hydrogen at ambient conditions powered with renewable energy sources, resulting in a more competitive hydrogen cost.

The increasing penetration of renewable energy sources creates a challenge for the stability of current power systems due to their intermittent and stochastic nature. This paper presents the field results of an efficient demand response solution for controlling and adjusting the electric demand of buildings in an energy district through the activation of their thermal mass while respecting the occupants’ thermal comfort constraints. This multilevel control approach aims to support grid flexibility during peak times by constraining the energy exchange with the grid and increasing the self-consumption of the district. The results show a great potential for increasing the self-consumption up to 37% for offices, as well as improving the indoor environment, based on real data collected from a case study in Greece.

Climate change is a growing global concern, threatening the worldwide environment, health, and economy [...]

Among all the energy production technologies based on renewables, the photovoltaic panels are the ones with the highest rate of development and applications worldwide. In this context, significant efforts are put into research on innovative materials in order to improve the performance of photovoltaic cells. Nevertheless, possibilities available to enhance the energy yield of existing technologies also exist and are explored, such as the cooling of photovoltaic modules. This approach can decrease the mean operation temperature of photovoltaic cells, leading to an increase in efficiency and energy produced. In the present paper, this method is investigated by developing and testing a dedicated water cooling system for photovoltaic panels. In order to investigate the performance of the cooling system, two market-available monocrystalline photovoltaic panels with a power of 50 and 310 Wp were tested under laboratory and real operation conditions, respectively. Based on the results obtaine... [more]

Production of syngas from the gasification of a biomass is attracting attention with an eye to the concepts of circularity, sustainability, and recent needs, triggered by socio-political events, to increase the level of self-sufficiency of energy sources for a given community. This manuscript reports on the gasification of spruce wood chips in a demonstration fluidised bed gasifier (1.5 MWth, height of 5.40 m, internal diameter of 1.2 m), with 0.2−0.4 mm olivine inventory (1000 kg). Gasification was carried out in air, at four different values of equivalence ratio (from 27% to 36%). The bed was fluidised at about 0.6 m/s, and the bed temperature resulted in the range of about 960−1030 °C as a function of the different tests. A mass flow rate of biomass in the range of about 360−480 kg/h (as a function of the different tests) was fed to the fluidised bed gasifier. Syngas lower heating value, specific mass and energetic yield, and chemical composition, were reported along with data on th... [more]

Pinewood biomass in Portugal can be considered a major source of biochar for soil physical, chemical, and biological edaphic amendment. This work intended to evaluate the aptitude of lab produced biochar for upgrading soil moisture dynamics’ relationships considering mixtures of biochar with silica-based sand. The methodology used focused on the carbonization of pine biomass with inert atmosphere at 300 °C, 400 °C, 500 °C and 600 °C, followed by a chemical proximate and thermogravimetric analysis, scanning electron microscopy, Fourier Transform Infrared analysis, numerical modeling, and characterization of biochar porosity by gas adsorption (Brunauer−Emmett−Teller) and mercury porosimetry. The results showed the increased amounts of soil water retention and plant available water, evaluated through pF curves, due to biochar application. The thermogravimetric analysis mass loss patterns and FTIR transmittance, reflected major structural modifications in carbonized products by comparison... [more]

Pipeline transportation of crude oil has great advantages over traditional oil transmission methods, in terms of economic and environmental protection. The main costs in the oilfield surface system are the fuel costs for heating the crude oil during transportation and the electricity costs for the pumping units. In the northeast of China, where winter temperatures are extremely low and the oil has a high freezing point and high viscosity, higher temperatures, and pressures are required to transport crude oil. With machine learning widely used in many industries and achieving better results, the digital management of oil pipelines has stored a large amount of production and operation data, which has laid the foundation for the research of oil pipeline process calculation using machine learning methods. In this paper, a crude oil pressure drop calculation of an oil pipeline in Northeast China is carried out based on a neural network. For pipeline pressure drop calculation, the back propa... [more]

The current stage of development of autonomous energy systems is characterized by a rapid increase in renewable energy sources’ installed capacity. Such growth is observed both in centralized and isolated energy systems. Renewable energy sources show high efficiency in the electrification of rural remote settlements around the world. The power of such power complexes varies from several kilowatts to tens of megawatts. When solving the problems of rural remote settlements electrification, the main issues of optimizing the composition of equipment and the structure of the energy systems play an extremely important role. Moreover, depending on the specifications of the problem being solved, criteria for evaluating efficiency are used, which are different. For example, the following are used as objective functions: minimization of the levelized cost of energy and fossil fuel consumption; maximizing the standard of people living and reliability indicators; the payback period of the project... [more]

The aim of this study is to identify non-technological critical success factors (CSFs) that influence the different phases of the project life cycle for the deployment of centralized biogas projects; as there is a knowledge gap in this area. This was performed by applying a longitudinal process analysis approach and an analytical framework based on findings from previous studies. Data were collected through extensive document collection and analysis, combined with in-depth semi-structured interviews. The study resulted in the identification of a total of 30 non-technological critical success factors in the case of Solrød Biogas. These were subsequently linked to one of the different phases of the project lifecycle (conceptualization phase, planning phase, execution phase) or categorized as general CSFs. We hope that the findings in this study can help ensure better management of biogas projects and enhance the capabilities of governmental bodies in supporting projects in the future, so... [more]

With the rapid development of machine learning, deep reinforcement learning (DRL) algorithms have recently been widely used for energy management in hybrid electric urban buses (HEUBs). However, the current DRL-based strategies suffer from insufficient constraint capability, slow learning speed, and unstable convergence. In this study, a state-of-the-art continuous control DRL algorithm, softmax deep double deterministic policy gradients (SD3), is used to develop the energy management system of a power-split HEUB. In particular, an action masking (AM) technique that does not alter the SD3′s underlying principles is proposed to prevent the SD3-based strategy from outputting invalid actions that violate the system’s physical constraints. Additionally, the transfer learning (TL) method of the SD3-based strategy is explored to avoid repetitive training of neural networks in different driving cycles. The results demonstrate that the learning performance and learning stability of SD3 are una... [more]

Current research assesses the impact of industrialization and the renewable energy sector on greenhouse gas emissions, proxied by CO2 emissions in Europe and Central Asia. We rely on a two-step system GMM estimator on a sample of 48 countries over the period 2000−2018. Empirical results show that industrialization has a positive effect on CO2 emissions: a 10% increase in industry value added as % of GDP leads to an increase of 2.6% in CO2 emissions. In contrast, renewable energy mitigates CO2 emissions. Ten percentage points increase in renewable energy consumption reduces CO2 emissions per capita by 2.2%. The interaction term between renewable energy and industry value added is negative, suggesting that renewable energy consumption compensates for the negative effect of industrialization on environmental quality. Our main results also confirm the U-shaped inverted relationship between GDP per capita and CO2 emissions. Our study has a number of policy implications and avenues for futur... [more]

Biogas and anaerobic digestion has begun to be considered an important renewable and sustainable energy source. The sustainable development of the anaerobic digestion process depends largely on the ability to manage large amounts of by-products generated during the biogas production process. We hypothesized that the use of digestate increases the accumulation of C in stable forms. We supposed that the effect of digestate on soil depends on the land-use system, leading to different stratifications of C. The main task of our research was to ascertain changes in the amount of stabile organic carbon (SOCstabile) in digestate-treated soils. Two field experiments were performed using the same design in 2019−2020. We studied the fertilization effects of digestate on Fluvisol. Fertilization: control; separated liquid digestate 85 kg ha−1 N and 170 kg ha−1 170 N; separated solid digestate 85 kg ha−1 N and 170 kg ha−1 N. A randomized experimental design with three field replicates was used. In t... [more]

To improve the prediction accuracy of short-term load series, this paper proposes a hybrid model based on a multi-trait-driven methodology and secondary decomposition. In detail, four steps were performed sequentially, i.e., data decomposition, secondary decomposition, individual prediction, and ensemble output, all of which were designed based on a multi-trait-driven methodology. In particular, the multi-period identification method and the judgment basis of secondary decomposition were designed to assist the construction of the hybrid model. In the numerical experiment, the short-term load data with 15 min intervals was collected as the research object. By analyzing the results of multi-step-ahead forecasting and the Diebold−Mariano (DM) test, the proposed hybrid model was proven to outperform all benchmark models, which can be regarded as an effective solution for short-term load forecasting.

Accurate simulation of the VAPEX process relies heavily on precise modeling of the solvent chamber propagation. In the previously developed models, the solvent chamber possesses either a linear, circular, or parabolic shape. In this study, an exponential solvent chamber model was considered to represent the propagation of the chamber throughout the spreading and falling stages of the VAPEX process. The tuning parameters of the proposed model include the exponential function coefficient and the transition region thickness. These parameters are altered by employing a MATLAB-based Genetic Algorithm (GA) to minimize the error between determined and measured cumulative produced oil in four experimental case studies presented in the literature. According to the outcomes, the proposed method can accurately adjust the cumulative produced oil to the measured values in both spreading and falling stages. Additionally, the thickness of the transition region obtained by this model is in reasonable... [more]

Most of the charcoal in the world comes from small and medium-sized producers, using rudimentary carbonization kilns that require significant time or energy during the heating and cooling stages of the process. Despite advances in improving the performance, the influence of materials used in the sidewalls of these kilns has been scarcely studied. Therefore, based on numerical simulations, the present study analyses the thermal performance of cylindrical sidewalls composed of combinations of metallic materials, ceramic materials, and insulating blankets grouped in three configurations: configuration I (sidewall with just one material), configuration II (sidewall with two materials assembled in series), and configuration III (pivoting sidewall). Results were encouraging, especially when comparing kiln configuration I with the novel configuration III. Simulations suggested that the proposed configuration III could reduce the heating time by 62%, the cooling time by 91%, the heat supplied... [more]

The energy economy is continually evolving in response to socio-political factors in the nature of primary energy sources, their conversions to useful forms, such as electricity and heat, and their utilization in different sectors. Nuclear energy has a crucial role to play in the evolution of energy economy due to its clean and non-carbon-emitting characteristics. A techno-economic analysis was undertaken to establish the viability of selling heat along with electricity for an advanced 100 MWth small modular reactor (SMR) and four nuclear hybrid energy system (NHES) configurations featuring the SMR paired with chemical heat pump (ChHP) systems providing a thermal output ranging from 1 to 50 MWth. Net present value, payback period, discounted cash flow rate of return, and levelized cost of energy were evaluated for these systems for different regions of U.S. reflecting a range of electricity and thermal energy costs. The analysis indicated that selling heat to high temperature industria... [more]

A plasma jet-triggered gas switch (PJT-GS) has been developed as an important piece of equipment to operate in an ±800 kV ultra-high voltage direct current transmission system (UHV DC) to achieve grid system protection and control. The crucial factors that would affect its operational performance, such as the current level the PJT-GS could withstand and the gas gap distance between the two rotating electrodes, are comparatively studied in the present work by analysing the arc dynamic characteristics. The rotating electrode used in the PJT-GS is designed with a helical-slotted structure, and the arc can be rotated circularly driven by the produced transverse magnetic field (TMF) along the electrode edge. The objective of such research is to provide a thorough study of the arc dynamic behaviour during the current flowing process of the PJT-GS and also to characterise the physical mechanism that affects the arc rotation and the PJT-GS operation performance. The magnetohydrodynamic-based (... [more]

The desorption of heavy oil is one of the important indicators affecting the development efficiency of the remaining oil in nanopores. However, the study of the adsorption and diffusion mechanisms of heavy oil molecules in nanopores remains scarce. In this work, the influences of temperature on the adsorption and diffusion properties of the heavy oil four-fractions in quartz nanopore have been investigated via molecular dynamics simulations. Our results show that the heavy oil molecules will form a denser multilayer adsorption oil layer on the nanopore surface, and high temperature can alter the adsorption behaviors of the heavy oil four-fractions. As the temperature increases, the saturate molecules are desorbed from the nanopore surfaces, but the aromatic, resin, and asphaltene molecules maintain a tendency to aggregate towards the nanopore surface. In particular, the agglomeration behaviors of most saturate, aromatic and asphaltene molecules in nanopore can be suppressed by the conf... [more]

Supervisory control and data acquisition (SCADA) systems are critical for wind power grid integration and wind farm operation and maintenance. However, wind turbines are affected by regulation, severe weather factors, and mechanical failures, resulting in abnormal SCADA data that seriously affect the usage of SCADA systems. Thus, strict and effective data quality control of the SCADA data are crucial. The traditional anomaly detection methods based on either “power curve” or statistical evaluation cannot comprehensively detect abnormal data. In this study, a multi-approach based abnormal data detection method for SCADA wind speed data quality control is developed. It is mainly composed of the EEMD (Ensemble Empirical Mode Decomposition)-BiLSTM network model, wind speed correlation between adjacent wind turbines, and the deviation detection model based on dynamic power curve fitting. The proposed abnormal data detection method is tested on SCADA data from a real wind farm, and statistic... [more]