In the past few decades, the machine learning (or data-driven) approach has been broadly adopted as an alternative to scientific discovery, resulting in many opportunities and challenges. In the oil and gas sector, subsurface reservoirs are heterogeneous porous media involving a large number of complex phenomena, making their characterization and dynamic prediction a real challenge. This study provides a comprehensive overview of recent research that has employed machine learning in three key areas: reservoir characterization, production forecasting, and well test interpretation. The results show that machine learning can automate and accelerate many reservoirs engineering tasks with acceptable level of accuracy, resulting in more efficient and cost-effective decisions. Although machine learning presents promising results at this stage, there are still several crucial challenges that need to be addressed, such as data quality and data scarcity, the lack of physics nature of machine lea... [more]

Energy security affects the functioning of countries politically, economically, and socially. Energy is an important factor in sustainable development efforts. Hence, countries are assessing their energy systems for compatibility with sustainable development goals by creating new concepts for energy development. Combining the concepts of energy security and sustainable energy consumption, an analysis of the differentiation of EU countries in terms of selected indicators indicated in Goal 7 of Agenda 2030 was carried out in dynamic terms. Two groups of indicators were distinguished. One group of indicators was selected to represent the changes in energy demand reported by final consumers, taking into account the use of energy obtained from renewable sources. The second group of indicators represents those relating to the security of supply of raw materials, i.e., energy dependency indicators broken down by major energy commodities and an energy productivity indicator. The analysis uses... [more]

Firewood stoves are widespread and popular for renewable heat supply in Europe. Several new technological measures have been developed recently that aim at improving the appliance performance in terms of emissions and efficiency. In order to support the trend towards “(nearly) zero-emissions technologies”, the objective of this study was to provide a profound overview of the most relevant technical primary and secondary measures for emission reduction and to analyze their functionality, the relevant framework conditions for their application and their costs. Since user behavior is essential for emission and efficiency performance, the state of knowledge about user behavior is summarized and the latest measures for its optimization are evaluated as non-technical primary measures. Primary and secondary measures were analyzed separately, but also potentially promising combinations of primary and secondary optimization were evaluated using SWOT analysis. The results showed that complementa... [more]

The (Cu,Mn,Co)3O4 (CMC) spinel layer is useful in inhibiting Cr vaporization that deteriorates the solid oxide fuel cell performance. The effectiveness of the spinel layer in suppressing volatile Cr species from the metallic interconnects is strongly dependent on layer density, which is influenced by particle size distributions and agglomerations of the spinel powders. Considering that the material properties were influenced by the synthesizing conditions, this study elucidated the influences of citric acid (fuel) on the structure, morphology, and electrical properties of sol−gel derived CMC spinel powders. Dual-phase CMC spinel powders, consisting of cubic CuMnCoO and tetragonal Mn2CoO4, were successfully synthesized at citrate-to-nitrate (CA/MN) ratios of 0.8, 1.0, and 1.2. An undesired CuCo2O4 phase was observed in spinel powders synthesized at a low CA/MN ratio of 0.5. The CA/MN ratio has influenced not only the phase formation of CMC spinel, but also the particle size distribution... [more]

In January 2019, the Canadian province of Alberta enacted limits on crude oil and bitumen production. These production controls, a policy referred to as curtailment, represent a shift for a government that historically avoided market intervention. The policy was designed to shrink a growing and prolonged price differential between the Western Canadian Select price of oil, the key benchmark for Alberta’s heavy oil production, and the West Texas Intermediate benchmark. The curtailment created artificial scarcity, shrinking the price differential from more than $40 USD per barrel in November 2018 to less than $15 USD per barrel in February 2019. In the process, this policy transferred market surplus from refiners, mainly those in the US Midwest, to producers in Alberta. We review this large-scale market intervention and calculate the magnitude of the economic transfer. We find the curtailment increased producer surplus by $659M CAD per month and reduced consumer surplus by $763M per month... [more]

This study addresses the issue of energy optimization by investigating solutions for the reduction of energy consumption in the diagnostics and monitoring of technological processes. The implementation of advanced process control is identified as a key approach for achieving energy savings and improving product quality, process efficiency, and production flexibility. The goal of this research is to develop a cost-effective system with a minimal number of ultrasound sensors, thus reducing the energy consumption of the overall system. To accomplish this, a novel method for obtaining high-resolution reconstruction in transmission ultrasound tomography (t-UST) is proposed. The method involves utilizing a convolutional neural network to take low-resolution measurements as input and output high-resolution sinograms that are used for tomography image reconstruction. This approach allows for the construction of a super-resolution sinogram by utilizing information hidden in the low-resolution m... [more]

The IEEE 1459 standard states that: “There is a need to quantify correctly the distortions caused by the nonlinear and parametric loads …” The paper undertakes this problem. The article includes an analysis of selected steady-state properties of a single-phase AC circuit containing a series connection of a resistance, an inductance, and a nonlinear element described by a signum function. The circuit is supplied from a sinusoidal voltage source. The mathematical model of this circuit is described using dimensionless variables. Based on the harmonic balance, a description of the circuit for the fundamental harmonic and the circuit for the remaining harmonics was separated. On the basis of the relationship between the current and voltage waveforms, the solution for all harmonics, the harmonic content coefficients, and the elements of the equivalent scheme of the nonlinear load, were estimated symbolically. Based on the circuit equations, a circuit model and measurement systems were develo... [more]

The Mobile Ad-hoc Network is a self-configuring decentralized network, where the network topology is dynamically modifiable. The IoT (Internet of Things) based Wireless Sensor Network contains more sensors and shares information over the Internet to a cloud server. However, the IoT-based wireless sensor network channel has moderate security is poor compared to MANET and packet loss is increased due to attackers. In IoT, all the sensors forward the detected data frequently to the internet gateway, so the energy saving in the network is low compared to MANET. In this work, the smart environment of IoT, Wireless Sensor Networks (WSN) and MANET make a great heterogeneous network in IT Technology; the combination of this heterogeneous network has new challenging issues. In this heterogeneous network, MANET provides a trusted route between the sensor to gateway nodes into the IoT environment using Energy Saving Optimization Techniques [MANET-ESO in IoT]. It saves energy for each node and red... [more]

An intermediate fluid vaporizer (IFV) is a typical vaporizer of liquefied natural gas (LNG), which is used in a large number of LNG terminals. Since it requires a large supply of seawater during its operation, it generates a lot of energy consumption. In this study, to reduce the seawater consumption in the regasification system, the heat transfer process was first numerically calculated, and the heat transfer coefficient of the IFV was determined for different seawater inlet temperatures, seawater flow rates, and LNG flow rates. The calculation results of the heat transfer coefficient were integrated into the numerical model in HYSYS, and the minimum seawater flow of the IFV under different working conditions was obtained. For receiving terminals using multiple IFVs, this study programmed calculations based on optimization software. The operating configuration of the IFVs under different operating conditions was optimized to reduce the consumption of seawater in the regasification sys... [more]

With a view to reducing harmonic content in electrical power systems, and, consequently, improving power quality level, filters and other harmonic compensation devices are widely used. In the category of filters, they can be distinguished into two classes that are related to the operating mode, active or passive, both widely known and applied in electrical power grids and in the most diverse industry sectors. In this sense, taking into account the use of compensating devices in four-wire electrical systems feeding single-phase, non-linear loads, this paper presents a new hybrid arrangement of harmonic compensation that incorporates both active and passive filtering, which performs all functions concerning the harmonic compensation of a four-leg shunt active power filter. In this hybrid arrangement, the harmonic filtering of positive and negative sequence components is performed by a three-leg shunt active power filter, while the filtering of zero-sequence harmonics is attributed to the... [more]

The effective exploitation of renewable energy and the recovery of waste heat are two crucial strategies in achieving carbon neutrality. As an efficient and reliable heat−to−power conversion technology, the organic Rankine cycle (ORC) has been recognized and accepted by academia and industry for use in solar energy, geothermal energy, biomass energy, and waste heat applications. However, there remain unsolved technical challenges related to the design and operation of the components and system. As the exergy destruction and investment cost of heat exchangers exert significant influence on the performance of ORC, investigations on the performance improvement of heat exchangers are of great significance. The aim of this paper was to provide a review on the performance improvement of ORC in relation to heat transfer enhancement, heat exchanger design optimization, and cycle construction based on a novel heat exchanger. The performance of ORC using different types of heat exchangers was di... [more]

All the energetic management and controlling strategies in ambient air conditioning systems (ACS) are aimed to match design load to current needs. This might be achieved by determining a rational value of design thermal load without overestimation that can minimize its deviation from the actual values. The application of variable refrigerant flow (VRF) systems with speed-regulated compressors (SRC) is considered as the most advanced trend in building air conditioning due to the ability of SRCs to cover changeable heat loads without lowering their efficiency. The level of load regulation by SRC is evaluated as the ratio of the load range, regulated by SCR, to the overall design load range. With this, the range of actual changeable loads is usually supposed to be covered by SRC entirely while keeping the rest, unregulated, and load range unchangeable. However, to confirm this, the rest load range behind the regulated one should be investigated to estimate the efficiency of SRC operation.... [more]

Thermal management has become a crucial issue for the rapid development of electronic devices, and thermal interface materials (TIMs) play an important role in improving heat dissipation. Recently, carbon−based TIMs, including graphene, reduced graphene oxide, and carbon nanotubes (CNTs) with high thermal conductivity, have attracted great attention. In this work, we provide graphene−carbon nanotube composite films with improved electrical and thermal conductivities. The composite films were prepared from mixed graphene oxide (GO) and CNT solutions and then were thermally reduced at a temperature greater than 2000 K to form a reduced graphene oxide (rGO)/CNT composite film. The added CNTs connect adjacent graphene layers, increase the interlayer interaction, and block the interlayer slipping of graphene layers, thereby improving the electrical conductivity, through−plane thermal conductivity, and mechanical properties of the rGO/CNT composite film at an appropriate CNT concentration. T... [more]

The inductor−inductor−capacitor (LLC) resonant converter is a suitable topology for wide output voltage and load range applications with limited circuit parameters. One of the most significant design boundaries of an LLC resonant converter in high-voltage applications is the parasitic capacitance effect of the main circuit components, particularly the transformer and junction capacitances of the secondary rectifier network. Parasitic capacitance effects are much higher in high-voltage applications than in low-voltage applications. Therefore, the use of an LLC resonant converter is limited to high-voltage applications. This study proposes to reduce the capacitive effects of high-voltage transformers and rectification networks with a multi-winding transformer with an integrated rectifier design and to use it in high-voltage applications with the advantages of the LLC resonant converter. For the proposed prototype, comparative experimental measurements were conducted using a conventional... [more]

Climate change and global warming, caused by excessive carbon emissions from transportation and other environmentally hazardous activities, are serious problems for many countries nowadays. Therefore, while some countries are not making optimal use of their resources, others are working hard to preserve a green and clean environment in order to foster long-term growth. Governments and policymakers throughout the world are finally starting to take the risks of climate change and global warming seriously. This paper extends previous literature related to environmental design practices by investigating the impacts of environmental innovation and the deployment of green energy on decreasing carbon dioxide (CO2) emissions for Saudi Arabia during the period 1990−2018. Different CO2 emission measures are incorporated in the analysis, namely per capita CO2 emissions, CO2 intensity, CO2 emissions from liquid fuel use, and CO2 emissions from heat and electricity generation. Overall, the outcomes... [more]

The Taiwan Strait contains a vast potential for wind energy. However, the power grid balance is challenging due to wind energy’s uncertainty and intermittent nature. Wind speed forecasting reduces this risk, increasing the penetration rate. Machine learning (ML) models are adopted in this study for the short-term prediction of wind speed based on the complex nonlinear relationships among wind speed, terrain, air pressure, air temperature, and other weather conditions. Feature selection is crucial for ML modeling. Finding more valuable features in observations is the key to improving the accuracy of prediction models. The random forest method was selected because of its stability, interpretability, low computational cost, and immunity to noise, which helps maintain focus on investigating the essential features from vast data. In this study, several new exogenous features were found on the basis of physics and the spatiotemporal correlation of surrounding data. Apart from the conventiona... [more]

Magnetic flux leakage testing (MFL) is the most widely used nondestructive testing technology in the safety inspection of oil and gas pipelines. The analysis of MFL test data is essential for pipeline safety assessments. In recent years, deep-learning technologies have been applied gradually to the data analysis of pipeline MFL testing, and remarkable results have been achieved. To the best of our knowledge, this review is a pioneering effort on comprehensively summarizing deep learning for MFL detection and evaluation of oil and gas pipelines. The majority of the publications surveyed are from the last five years. In this work, the applications of deep learning for pipeline MFL inspection are reviewed in detail from three aspects: pipeline anomaly recognition, defect quantification, and MFL data augmentation. The traditional analysis method is compared with the deep-learning method. Moreover, several open research challenges and future directions are discussed. To better apply deep le... [more]

In order to optimize the energy management strategy and solve the problem of the power quality degradation of fuel cell hybrid electric ships, a particle swarm optimization algorithm based energy management strategy is proposed in this paper. Taking a fuel cell ship as the target ship, a system simulation model is built in Matlab/Simulink to verify the proposed energy management strategy. Through simulations and comparisons, the bus voltage curve of the optimized hybrid power system fluctuates more gently, and the voltage sag is smaller. The amplitude of the voltage fluctuation under maneuvering conditions is reduced by 55% compared with that of the original ship. The charging and discharging process of the composite energy storage system is optimized under maneuvering conditions, the power quality of the marine power grid is improved, and the use of the energy management strategy can extend the service life of the battery.

The cost of electricity and gas has a direct influence on the everyday routines of people who rely on these resources to keep their businesses running. However, the value of electricity is strongly related to spot market prices, and the arrival of winter and increased energy use owing to the demand for heating can lead to an increase in energy prices. Approaches to forecasting energy costs have been used in recent years; however, existing models are not yet robust enough due to competition, seasonal changes, and other variables. More effective modeling and forecasting approaches are required to assist investors in planning their bidding strategies and regulators in ensuring the security and stability of energy markets. In the literature, there is considerable interest in building better pricing modeling and forecasting frameworks to meet these difficulties. In this context, this work proposes combining seasonal and trend decomposition utilizing LOESS (locally estimated scatterplot smoo... [more]

: Wind speed and solar radiation are two of the most well-known and widely used renewable energy sources worldwide. Coal, natural gas, and petroleum are examples of fossil fuels that are not replenished and are thus non-renewable energy sources due to their high carbon content and the methods by which they are generated. To predict energy production of renewable sources, researchers use energy forecasting techniques based on the recent advances in machine learning approaches. Numerous prediction methods have significant drawbacks, including high computational complexity and inability to generalize for various types of sources of renewable energy sources. Methodology: In this paper, we proposed a novel approach capable of generalizing the prediction accuracy for both wind speed and solar radiation forecasting data. The proposed approach is based on a new optimization algorithm and a new stacked ensemble model. The new optimization algorithm is a hybrid of Al-Biruni Earth Radius (BER) an... [more]

Power outages of the electricity grid threaten the proper operation of critical infrastructure such as hospitals. To cope with this problem, emergency diesel generators (DGs) are often used to guarantee continuous and resilient electricity supply, resulting in increased costs and greenhouse gas (GHG) emissions. Thus, this study aims to investigate the economic feasibility of both reducing and replacing emergency diesel generators with solar photovoltaic (PV) systems, battery energy storage systems (BESS) and demand-side management. A mixed-integer quadratically constrained program is used to find the optimal configuration in terms of capacities of new assets, as well as the optimal scheduling of both BESS and flexible loads, that minimises the levelised cost of energy (LCOE). The model is applied to an existing hospital and its surrounding community located in Gulu, Uganda. The results show that full replacement of the DGs will require an additional 500 kWp of PV and 1591 kWh of BESS.... [more]

This paper proposes a new cascaded fractional-order controller (CC-FOC) to solve the load frequency control (LFC) problem of an interconnected power system. The CC-FOC consists of a three-degree-of-freedom fractional-order proportional-integral-differential (3DOF-FOPID) controller and a fractional-order proportional-integral (FOPI) controller. Each area of the two-area interconnected power system in this study consists of a thermal unit, a hydro unit, a diesel unit, and a doubly-fed induction generator (DFIG). The enhanced particle swarm optimization (PSO) and gravitational search algorithm (GSA) under the chaotic map optimization (CPSOGSA) technique are used to optimize the controller gains and parameters to enhance the load frequency control performance of the cascade controller. Moreover, simulation experiments are conducted for the interconnected power system under load perturbation and random wind speed fluctuations. The simulation results demonstrate that the proposed cascaded fr... [more]

Increasing biogas production in the Three Seas Initiative countries (3SI) is a good way to reduce greenhouse gas emissions and to increase energy self-sufficiency by replacing some of the fossil energy sources. An assessment of the biogas production potential carried out for the 3SI at the NUTS 1 and NUTS 2 level shows that the potential of this energy carrier was stable for the period (from 2010−2021). The results showed that it can cover from approximately 10% (Hungary, Slovakia) to more than 34% (Estonia, Slovenia) of natural gas consumption; moreover, there is strong variation in the value of potential at the regional level (NUTS 2) in most of the countries studied. The biogas production forecast was carried out with the ARIMA model using four regressors, which are GDP, biogas potential utilisation, natural gas consumption and investments in RES (renewable energy sources) infrastructure, including changes in the EU energy policy after 24 February 2022. In the most promising scenari... [more]

The conversion to renewable energy can be achieved when cities and communities start to depend on sustainable resources capable of providing for the basic needs of the community, along with a reduction in the daily problems and issues that people face. These issues, such as poverty, hunger, sanitation, and economic difficulties are highlighted in the Sustainable Development Goals (SDGs), which aim to limit and eradicate these problems along with other environmental obstacles including climate change and Greenhouse Gases (GHGs). These SDGs, containing 17 goals target each sector and provide propositions to solve such devastating problems. Hydrogen contributes to the targets of these sustainable developments, since through its implementation in different industries the levels of GHG will drop and thus contribute to the climate change which Earth is facing. Further, through the usage of such resources, many job opportunities will also be developed, thus enhancing the economy, and lifting... [more]

Due to the large size of offshore wind turbine blades (OWTBs) and the corrosive nature of salt water, OWTs need to be safer and more reliable that their onshore counterparts. To ensure blade reliability, an accurate and computationally efficient structural dynamic model is an essential ingredient. If damage occurs to the structure, the intrinsic properties will change, e.g., stiffness reduction. Therefore, the blade’s dynamic characteristics will differ from those of the intact ones. Hence, symptoms of the damage are reflected in the dynamic characteristics that can be extracted from the damaged blade. Thus, damage identification in OWTBs has become a significant research focus. In this study, modal model characteristics were used for developing an effective damage detection method for WTBs. The technique was used to identify the performance of the blade’s sections and discover the warning signs of damage. The method was based on a vibration-based technique. It was adopted by investiga... [more]