Most old oil and gas fields worldwide are depleted, making drilling in these sedimentary zones extremely difficult, especially in complex pore pressure regimes when they are accompanied by over-pressure zones. Considering that typical wellbore stability studies provide a conservative mud density curve to prevent wellbore failure, dynamic geomechanical approaches are required to provide more flexible and manageable drilling in such complex cases in order to address anticipated drilling obstacles. This study aims to apply the more dynamic concept, known as “depth of damage” (DOD), in the El Morgan oil field, Gulf of Suez Basin, to deliver a more optional mud density window that helps in the safe drilling of different pore pressure regimes within the area, as well as the implications of applying this drilling strategy in the studied basin. In this paper, well logging and downhole measurements were used to develop a 1D geomechanical earth model and infer the in situ stresses in the studied... [more]

Geothermal heat pump systems (GHP) are the spearhead of geothermal achievement and development, and one of the fastest growing applications of renewable energy technologies worldwide. When Swiss GHP activities started in the late 1970s, market introduction and penetration needed science-based proof of reliable, stable, long-term GHP operation. A special, extended project, realized in a field-laboratory setting, provided this proof. Detailed measurements, as well as numerical model simulations, proved the sustainable operation of the installed GHP system. The measurement setup, the recording of the various time series, and their interpretation are presented. Furthermore, basic perceptions were elaborated concerning geothermal resources behavior in production and regeneration. The Swiss GHP was developed from nothing. Early GHP installation costs halved within 20 years; GHP growth was nearly exponential from 1980 to 2020 (8.5% annually). Drilled borehole heat exchanger (BHE) meters are t... [more]

This study aimed at evaluating the economic performances of and carbon footprint associated with innovative systems for the energetic valorization of second cheese whey (SCW), a by-product of whey cheese manufacture, through anaerobic digestion processes. Three systems were modeled: a conventional single-stage anaerobic digester (FAD), located at about 50 km from the dairy factory; an on-site conventional single-stage anaerobic digester (CAD), located at the dairy industry; and an on-site two-stage anaerobic digester (TAD). The TAD technology enables the simultaneous production of hydrogen and methane on site. The biogases produced were combusted in combined heat and power plants (CHP), but only the onsite systems provided process heat to the dairy factory. In the specific conditions assumed, TAD configuration exhibited a higher energy output, which led to a GHG emission reduction of about 60% compared to FAD, mostly thanks to the additional hydrogen (H2) production and the improved en... [more]

In this paper, based on the study of hydrogen accumulation in the electrodes of nickel−cadmium batteries, a high-capacity hydrogen storage system (HSS) is proposed. It has been experimentally proven that hydrogen accumulates in the electrodes of nickel−cadmium batteries in large quantities over the course of their operation. It has been shown that hydrogen accumulates in metal−ceramic matrices of sintered oxide−nickel electrodes in the form of metal hydrides. The gravimetric capacity of the nickel matrix is 20.3 wt% and the volumetric capacity is 406 kg m−3. The obtained gravimetric capacities for metal−ceramic matrices exceed almost four times the criteria for onboard hydrogen storage systems established by the US Department of Energy (DOE), as well as previously obtained results for any reversible hydrogen accumulation materials. In addition, in our previous papers, it was proved that if we use thermal runaway for the desorption of hydrogen from metal hydrides then the kinetic and th... [more]

Solar concentrator collectors have the potential of meeting the medium- and high-temperature thermal energy demands of the world. A heat transfer fluid (HTF) is a vital component of a concentrating system to transfer and store thermal energy. This paper presents the design development of a solar paraboloidal dish concentrator (SPDC) and a study of selected HTFs using the storage receiver system of the concentrator. The locally designed SPDC (diameter 1.21 m and height 0.20 m) has features like light weight, effortless tracking, convenient transportation along with high optical and thermal performance. Three HTFs, silicone oil (SO), engine oil (EO) and ethylene glycol (EG), are selected based on their favorable properties for medium temperature (150−300 °C) applications. The characteristic parameters of HTFs, heating rate (Rh), instant thermal efficiency (ηith) and the overall heat loss coefficient (UL), are illustrated and determined experimentally. A new characteristic parameter, the... [more]

The intermittence and fluctuation of renewable energy aggravate the power fluctuation of the power grid and pose a severe challenge to the frequency stability of the power system. Thermostatically controlled loads can participate in the frequency regulation of the power grid due to their flexibility. Aiming to solve the problem of the traditional control methods, which have limited adjustment ability, and to have a positive influence on customers, a deep reinforcement learning control strategy based on the framework of soft actor−critic is proposed, considering customer satisfaction. Firstly, the energy storage index and the discomfort index of different users are defined. Secondly, the fuzzy comprehensive evaluation method is applied to evaluate customer satisfaction. Then, the multi-agent models of thermostatically controlled loads are established based on the soft actor−critic algorithm. The models are trained by using the local information of thermostatically controlled loads, and... [more]

Microgrids are becoming popular nowadays because they provide clean, efficient, and lowcost energy. Microgrids require bulk storage capacity to use the stored energy in times of emergency or peak loads. Since microgrids are the future of renewable energy, the energy storage technology employed should be optimized to provide power balancing. Batteries play a variety of essential roles in daily life. They are used at peak hours and during a time of emergency. There are different types of batteries i.e., lithium-ion batteries, lead-acid batteries, etc. Optimal battery sizing of microgrids is a challenging problem that limits modern technologies such as electric vehicles, etc. Therefore, it is imperative to assess the optimal size of a battery for a particular system or microgrid according to its requirements. The optimal size of a battery can be assessed based on the different battery features such as battery life, battery throughput, battery autonomy, etc. In this work, the mixed-integer... [more]

Physics-informed neural networks (PINNs) are an emerging technology in the scientific computing domain. Contrary to data-driven methods, PINNs have been shown to be able to approximate and generalize well a wide range of partial differential equations (PDEs) by imbedding the underlying physical laws describing the PDE. PINNs, however, can struggle with the modeling of hyperbolic conservation laws that develop shocks, and a classic example of this is the Buckley−Leverett problem for fluid flow in porous media. In this work, we explore specialized neural network architectures for modeling the Buckley−Leverett shock front. We present extensions of the standard multilayer perceptron (MLP) that are inspired by the attention mechanism. The attention-based model was, compared to the multilayer perceptron model, and the results show that the attention-based architecture is more robust in solving the hyperbolic Buckley−Leverett problem, more data-efficient, and more accurate. Moreover, by utili... [more]

High-temperature superconducting materials have shown great potential for the design of large-scale industry applications. However, they are complicated under AC conditions, resulting in penalties such as power loss or AC loss. This loss has to be considered in order to design reliable and efficient superconducting devices. Furthermore, when superconductors are used in rotating machines, they may be exposed to rotating magnetic fields, which is critical for the design of such machines. Existing AC loss measuring techniques are limited to measuring under one-dimensional AC magnetic fields or transport currents. Therefore, it is essential to develop and investigate robust experimental techniques to investigate the loss mechanism in HTS machines. In this paper, a new and novel experimental technique has been presented to measure AC loss in rotating magnetic field conditions. The loss under rotating magnetic fields is measured and compared by numerical modeling methods, and the results sho... [more]

Increasing economic and population growth has led to a rise in electricity consumption. Consequently, electrical utility firms must have a proper energy management strategy in place to improve citizens’ quality of life and ensure an organization’s seamless operation, particularly amid unanticipated circumstances such as coronavirus disease (COVID-19). There is a growing interest in the application of artificial intelligence models to electricity prediction during the COVID-19 pandemic, but the impacts of clustering methods and parameter selection have not been explored. Consequently, this study investigates the impacts of clustering techniques and different significant parameters of the adaptive neuro-fuzzy inference systems (ANFIS) model for predicting electricity consumption during the COVID-19 pandemic using districts of Lagos, Nigeria as a case study. The energy prediction of the dataset was examined in relation to three clustering techniques: grid partitioning (GP), subtractive cl... [more]

Although it is well known that the magnetic properties of electrical steel can be deeply affected by the cutting process, it is still not clear how to accurately evaluate these effects on a prototyped machine on its final shape, especially at a high frequency or a high power rating. This research provides a more practical method for accurate measurement of magnetic losses in electrical steel with consideration of material degradation effects due to the cutting process. Unlike other similar studies, these investigations are conducted not only on a few laminations but also on a complete electrical machine core. For a fair comparison between both cases, backlack bonding is used for lamination stacking since it is the most non-damaging joining technique. Two different test setups are used to measure the steel performance at a wide range of frequency and input power. Furthermore, a full axial length stator of a switched reluctance machine (SRM) is used as a case study to identify the magnet... [more]

This paper presents a DC/AC converter consisting of two two-level inverters. The complex converter is built using two standard three-phase inverters: the main inverter (MI) and the auxiliary one (AI). The MI is controlled in a simple way to generate the stepped output voltage and the AI works as an active filter limiting the higher harmonics in the MI output voltage. The filtering process is based on the orthogonal space vector theory. A development and modification of the basic solution are presented here. The output voltage of the MI takes the shape of a stepped voltage comparable to the voltage generated by multilevel inverters. The AI operates as a very effective active power filter (APF) of the MI output voltage. The AI power is significantly lower in comparison to the MI power.

Southern Africa has a huge potential for renewable energy sources such as hydro, solar, wind, biomass, and geothermal. However, electricity access remains a key policy issue for most member states, with a global average access to electricity of only 54% in 2019. This low electrification rate is a strong motivation for member states to increase renewable energy use and improve access to electricity for all. The goal of this paper was to present a literature review of methodologies, energy plans, and government programs that have been implemented by the Southern African Development Community member states to address the region’s low average electrification rate and greenhouse gas emission reduction targets. The study presents the most commonly used methodologies for the integration of renewable energies into electrical systems, considering the main grid and distributed generation systems. LCOE minimization methodologies and software options, such as GIS, HOMER, LEAP, and EnergyPLAN, are... [more]

Straw bale building construction is attracting a revived public interest because of its potential for reduced carbon footprint, hygrothermal comfort, and energy savings at an affordable price. The present paper aims to summarize the current knowledge on straw bale construction, using available data from academic, industry, and public agencies sources. The main findings on straw fibers, bales, walls, and buildings are presented. The literature shows a wide variability of results, which reflects the diversity of straw material and of straw construction techniques. It is found that the effective thermal conductivity, density, specific heat, and elastic modulus of straw bales used in construction are in the range 0.033−0.19 W/(m·K), 80−150 kg/m3, 1075−2000 J/(kg·K), and 150−350 kPa respectively. Most straw-based multilayered walls comply with fire resistance regulations, and their U-value and sound reduction index range from 0.11 to 0.28 W/m2 K and 42 to 53 dB respectively, depending on th... [more]

Balancing electricity demand and supply remains a significant challenge for the power systems in developing countries, such as Nigeria. In Nigeria, there is a shortage of adequate power supply, and demand-side management (DSM) plays a minor role in the power balancing mechanism with load shedding being widely used. The paper aims to review and compare various existing and emerging DSM strategies in developing countries. An extensive and systematic review was conducted to evaluate potential solutions using DSM to increase the overall energy efficiency in the Nigerian electricity market. This study found that, although the technical and economic potentials of DSM vary in developed countries, the uptakes of DSM have been severely hampered hence preventing the full exploitation and utilisation of the full potential of DSM. The initiatives of a DSM model in Nigeria and other developing countries can play a significant role in addressing demand and supply challenges but an upgrade of the ene... [more]

There is an increasing interest in improving energy efficiency and reducing operational costs of induction motors in the industry. These costs can be significantly reduced, and the efficiency of the motor can be improved if the condition of the machine is monitored regularly and if monitoring techniques are able to detect failures at an incipient stage. An early fault detection makes the elimination of costly standstills, unscheduled downtime, unplanned breakdowns, and industrial injuries possible. Furthermore, maintaining a proper motor operation by reducing incipient failures can reduce motor losses and extend its operating life. There are many review papers in which analyses of fault detection techniques in induction motors can be found. However, all these reviewed techniques can detect failures only at developed or advanced stages. To our knowledge, no review exists that assesses works able to detect failures at incipient stages. This paper presents a review of techniques and metho... [more]

The accurate prediction of building heat demand plays the critical role in refined management of heating, which is the basis for on-demand heating operation. This paper proposed a prediction model framework for building heat demand based on reinforcement learning. The environment, reward function and agent of the model were established, and experiments were carried out to verify the effectiveness and advancement of the model. Through the building heat demand prediction, the model proposed in this study can dynamically control the indoor temperature within the acceptable interval (19−23 °C). Moreover, the experimental results showed that after the model reached the primary, intermediate and advanced targets in training, the proportion of time that the indoor temperature can be controlled within the target interval (20.5−21.5 °C) was over 35%, 55% and 70%, respectively. In addition to maintaining indoor temperature, the model proposed in this study also achieved on-demand heating operati... [more]

In generation expansion planning, reliability level is the key criterion to ensure enough generation above peak demand in case there are any generation outages. This reliability criterion must be appropriately optimized to provide a reliable generation system with a minimum generation cost. Currently, a method to determine an optimal reliability criterion is mainly focused on reserve margin, an accustomed criterion used by several generation utilities. However, Loss of Load Expectation (LOLE) is a more suitable reliability criterion for a generation system with a high proportion of renewable energy since it considers both the probabilistic characteristics of the generation system and the entire load’s profile. Moreover, it is also correlated with the reserve margin. Considering the current fuel supply situation, a probabilistic model based on Bayes’ Theorem is also proposed to incorporate fuel supply unavailability into the probabilistic criterion. This paper proposes a method for dete... [more]

Renewable energy forecasting is a key for efficient resource use in terms of power generation and safe grid control. In this study, we investigated a short-term statistical forecasting model with 1 to 3 h horizons using photovoltaic operation data from 215 power plants throughout South Korea. A vector autoregression (VAR) model-based regional photovoltaic power forecasting system is proposed for seven clusters of power plants in South Korea. This method showed better predictability than the autoregressive integrated moving average (ARIMA) model. The normalized root-mean-square errors of hourly photovoltaic generation predictions obtained from VAR (ARIMA) were 8.5−10.9% (9.8−13.0%) and 18.5−22.8% (21.3−26.3%) for 1 h and 3 h horizon, respectively, at 215 power plants. The coefficient of determination, R2 was higher for VAR, at 4−5%, than ARIMA. The VAR model had greater accuracy than ARIMA. This will be useful for economical and efficient grid management.

For the various climatic zones of India, machine learning (ML) models are created in the current work to forecast monthly-average diffuse solar radiation (DSR). The long-term solar radiation data are taken from Indian Meteorological Department (IMD), Pune, provided for 21 cities that span all of India’s climatic zones. The diffusion coefficient and diffuse fraction are the two groups of ML models with dual input parameters (sunshine ratio and clearness index) that are built and compared (each category has seven models). To create ML models, two well-known ML techniques, random forest (RF) and k-nearest neighbours (KNN), are used. The proposed ML models are compared with well-known models that are found in the literature. The ML models are ranked according to their overall and within predictive power using the Global Performance Indicator (GPI). It is discovered that KNN models generally outperform RF models. The results reveal that in diffusion coefficient models perform well than diff... [more]

Permanent magnet synchronous machines (PMSMs) with an overhang structure can increase power density by compensating for the increased magnetic energy of permanent magnets. To analyze the overhang structure, a three-dimensional (3D) analysis of PMSMs is essential. However, 3D analysis takes a long time and the modeling process is complicated in the initial design stage. To overcome these problems, a magnetic equivalent circuit technique is applied to the 2D model. In this paper, an optimal design method for PMSMs with an overhang structure is proposed based on the semi 3D magnetic equivalent circuit (MEC) and random walk method. By using semi 3D MEC, it is possible to quickly analyze PMSM and obtain accurate electromagnetic analysis results considering the overhang effect. Moreover, the volume and weight of PMSM can be minimized by optimizing the rotor’s four design parameters using a random walk algorithm. To obtain high efficiency, the objective function is selected so that copper los... [more]

An e-bike sharing system (e-BSS) solves many of the shortcomings of BSS but requires high financial investments compared to BSS. This article proposes a sustainable and targeted extension of the existing BSS with e-bikes and charging piles. The existing BSS in the selected city area is divided into sub-areas using the Voronoi diagram and reference points (landmarks). Then, the integrated approach of the Analytic Hierarchy Process (AHP) and Data Envelopment Analysis (DEA) is used to assess the adequacy of the existing bike-sharing stations for updating with e-bikes and charging piles. The joint approach allows decision-makers to look at the whole process and highlight the link between the criteria assessment and user preferences in the context of the chosen reference point. This can encourage future users to use e-BSSs. Based on a thorough literature review, the defined system of criteria takes into account all dimensions of sustainability: the requirements of most stakeholders and the... [more]

For over a decade, distributed generations (DGs) have sufficiently convinced the researchers that they are the economic and environment-friendly solution that can be integrated with the centralized generations. The optimal planning of distributed generations requires the appropriate location and sizing and their corresponding control with various power network types to obtain the best of the technical, economical, commercial, and regulatory objectives. Most of these objectives are conflicting in nature and require multi-objective solutions. Therefore, this paper brings a comprehensive literature review and a critical analysis of the state of the art of the optimal multi-objective planning of DG installation in the power network with different objective functions and their constraints. The paper considers the adoption of optimization techniques for distributed generation planning in radial distribution systems from different power system performance viewpoints; it considers the use of d... [more]

Most of the world’s energy requirements are still derived from natural resources. This will result in a catastrophic energy crisis with negative environmental consequences. The increased energy supply will result in greater consumption of non-renewable sources. The production of biomass producer gas (BPG) from biomass gasification has received significant attention as an alternative fuel due to the depletion of non-renewable resources. This experimental study aimed to determine the flame propagation, flame propagation speed, and chamber pressure trace of BPG at different equivalence ratios. Understanding the characteristics of the BPG’s combustion, finding lower greenhouse gas emissions of BPG, and minimizing the use of fossil fuels is necessary to mitigate these problems. Using the direct visualization technique, an optical constant volume combustion chamber (CVCC) was developed to measure combustion characteristics. Liquid petroleum gas (LPG) was used to compare the flame propagation... [more]

Environmental protection is currently one of the key priority areas of the European Union (EU). The search for effective solutions for the supply and use of energy in cities is currently a key topic. The reduction in gas emissions and the use of renewable energy sources are goals that result from environmental aspects. The purpose of this publication is to conduct a literature review in the area of municipal energy management. Municipal energy management systems integrate many areas, from energy supply systems and the modernization of public transport to the energy demand reduction of residential and commercial facilities. The results of the literature review research have allowed for the classification of articles based on the following criteria: research methodology, research purpose, research data collection method, use of research results article type, and research subject area.