Conventional Energy Research Articles

The impact of interest rate uncertainty on renewable energy investments: Compared with conventional energy investments

The impact of interest rate uncertainty on renewable energy investments: Compared with conventional energy investments

On identifying suitable hydrogen power plant location under [formula omitted]-spherical fuzzy hypersoft matrix structures

In recent decades, the prime objective of the energy sector has been to replace conventional energy sources with renewable energy sources such as hydrogen power, solar energy, etc. The objective of the present communication is to computationally locate the best site for the establishment of the hydrogen power plant given the various uncertainty parameters in terms of inexact and incomplete information. The uncertainty components of the information are well dealt with by the incorporation of T-spherical fuzzy hypersoft information. In accordance, we present the new concept of T-spherical fuzzy hypersoft matrix (TSFHSM) with different matrix-theoretic structured possibilities having useful computational setups. Some standard matrix operations with their algebraic properties have also been studied. Next, the structure of the proposed matrix has been utilized in presenting two new methodologies for the decision-making selection problems — one with the help of choice/weighted choice T-spherical fuzzy hypersoft matrices and the other with the value & score T-spherical fuzzy hypersoft matrices. Further, an illustrative example where the set of sites for the selection of hydrogen power plants has been computationally studied with the help of the presented novel algorithms given the available criteria. The efficacy of the proposed algorithms and their implementations have been discussed along with a comparative analysis, advantages and a characteristic comparison table.

Achieving environmental sustainability goals through capitalizing on renewable energy channels: Role of green finance, resources productivity and geopolitical situation in the MENA region

Environmental sustainability is essential to the country's financial position and economic growth. Geopolitical situations and green activities significantly contribute to enhancing sustainable development goals. The purpose of this study is to evaluate the impact of green finance, investment in renewable energy sources and geopolitical risk on the environmental sustainability of the Middle East and North America (MENA) region over the period 2000–2021. When using a cross‐sectional dependence autoregressive distributed lag model (CS‐ARDL), it is discovered that a rise in geopolitical risk will decrease environmental performance in the form of carbon dioxide emission. At the same time, the other factors (green finance and investment in renewable energy) have a positive relationship with sustainability. This observation can be ascribed to the association between increased geopolitical risk and the inclination of crude oil consumers, who are most affected by such risk, to contemplate renewable energy as an alternative to conventional energy sources. This finding could also be attributed to the fact that clean energy is becoming more affordable. In addition, the augmented mean group model findings provide more evidence that a negative linkage is found between geopolitical risk and environmental sustainability. The findings have repercussions for regulators as well as investors who are active in the renewable energy markets.

Development Status and Future Prospects of Photovoltaic Cells

With the rapid development of social economy, the consumption of conventional energy is growing at an amazing rate. The energy shortage crisis and the environmental problems brought by conventional energy will seriously restrict social development and affect the daily lives of residents. Therefore, paying attention to the creation and use of new energy, protecting the environment, improving efficiency, controlling the emission of pollutants and realizing sustainable development have become the main research topics in the new era of the energy sector. Photovoltaic energy has the advantages of economic energy saving, green environmental protection, wide application and sustainability, and is an ideal new energy, that has been developed to the third generation. This paper mainly combs the development process of photovoltaic technology, summarizes the characteristics, advantages and disadvantages of the third generation of photovoltaic technology, analyzes the current situation and prospects of photovoltaic technology development, and analyzes the problems and challenges faced. This research finds that as the economy and technology continue to advance, photovoltaic cell technology is developing rapidly, and the application cost is constantly reduced. The photovoltaic cell industry will get more attention and better development, and its application prospect is very broad. The research of this topic is helpful in enhancing the comprehensive and objective understanding of the development of photovoltaic cell technology, and will provide a valuable reference in order to advance the photovoltaic sector in the future, which has important practical significance.

Low-cost dual-energy CBCT by spectral filtration of a dual focal spot X-ray source

Dual-energy cone beam computed tomography (DE-CBCT) has been shown to provide more information and improve performance compared to a conventional single energy spectrum CBCT. Here we report a low-cost DE-CBCT by spectral filtration of a carbon nanotube x-ray source array. The x-ray photons from two focal spots were filtered respectively by a low and a high energy filter. Projection images were collected by alternatively activating the two beams while the source array and detector rotated around the object, and were processed by a one-step materials decomposition and reconstruction method. The performance of the DE-CBCT scanner was evaluated by imaging a water-equivalent plastic phantom with inserts containing known densities of calcium or iodine and an anthropomorphic head phantom with dental implants. A mean energy separation of 15.5 keV was achieved at acceptable dose rates and imaging time. Accurate materials quantification was obtained by materials decomposition. Metal artifacts were reduced in the virtual monoenergetic images synthesized at high energies. The results demonstrated the feasibility of high quality DE-CBCT imaging by spectral filtration without using either an energy sensitive detector or rapid high voltage switching.

Design and Implementation on Industrial Automation with the help of Renewable Energy Sources

Abstract: In the quest for a sustainable future, we’ve identified that traditional street lighting consumes more electricity than necessary. To address this, we’ve conceptualized an energy-efficient street lighting system. Our prototype leverages a Light Detecting Resistor (LDR) to optimize power usage, paving the way for an eco-friendly world. Fire alarms are crucial for timely fire detection, safeguarding lives and property. Our simplified circuit design enhances reliability, forming an integral part of a comprehensive security system that relies on sensor technology for prompt fire detection. The demand for automation is surging in both industrial and domestic spheres. This paper aims to minimize manual intervention by introducing self-operating systems powered by renewable energy sources. We’re integrating solar technology and piezoelectric sensors to harness electricity. This approach not only fuels industrial automation but also contributes to the global shift from finite conventional energy to renewable sources. By employing sensors, we ensure safety and efficiency in industrial zones while generating clean energy.

QUBO Problem Formulation of Fragment-Based Protein–Ligand Flexible Docking

Protein–ligand docking plays a significant role in structure-based drug discovery. This methodology aims to estimate the binding mode and binding free energy between the drug-targeted protein and candidate chemical compounds, utilizing protein tertiary structure information. Reformulation of this docking as a quadratic unconstrained binary optimization (QUBO) problem to obtain solutions via quantum annealing has been attempted. However, previous studies did not consider the internal degrees of freedom of the compound that is mandatory and essential. In this study, we formulated fragment-based protein–ligand flexible docking, considering the internal degrees of freedom of the compound by focusing on fragments (rigid chemical substructures of compounds) as a QUBO problem. We introduced four factors essential for fragment–based docking in the Hamiltonian: (1) interaction energy between the target protein and each fragment, (2) clashes between fragments, (3) covalent bonds between fragments, and (4) the constraint that each fragment of the compound is selected for a single placement. We also implemented a proof-of-concept system and conducted redocking for the protein–compound complex structure of Aldose reductase (a drug target protein) using SQBM+, which is a simulated quantum annealer. The predicted binding pose reconstructed from the best solution was near-native (RMSD=1.26 Å), which can be further improved (RMSD=0.27 Å) using conventional energy minimization. The results indicate the validity of our QUBO problem formulation.

Nonlinear impedance characteristics of a gas hydraulic energy absorber and performance prediction for railway transportation of valuable goods

It is meaningful to investigate the nonlinear impedance characteristics of gas hydraulic energy absorbers (GHEAs) and their potential application in modern railway transportation of valuable goods. Fluid-mechanics-based full parametric modelling of a GHEA used in a high-speed train is performed, both simulations with the developed mathematic model and physical experiments are carried out on the static and dynamic characteristics of the GHEA. The agreement between the results of the simulation and the experiment with tolerable deviations validates the nonlinear mathematic model. Longitudinal train dynamics (LTD) modelling and simulation of a Chinese rapid freight train with the validated GHEA model or the conventional MT-2 friction-type energy absorber model is finally conducted. The results show that when the train uses GHEAs instead of MT-2 energy absorbers, the coupler forces and vehicle accelerations of the train are significantly reduced, and the vehicles operate more steadily in situations such as train startup, emergency braking and shunting operations; thus, gas hydraulic energy absorber is protective and would be alternative for equipping rapid freight trains for the transportation of valuable goods. The obtained nonlinear mathematic model in terms of the structural, oil and gas property parameters of the GHEA is useful and meaningful in further parameter design optimization of GHEAs and optimal specification of GHEAs for rapid freight trains.

Geothermal Heat Pump for Space Cooling and Heating in Kuwaiti Climate

Kuwait stands as one of the hottest locations globally, experiencing scorching temperatures that can soar to 50 °C during the summer months. Conversely, in the winter months of December and January, temperatures may plummet to less than 10 °C. Maintaining a comfortable temperature indoors necessitates a substantial amount of energy, particularly during the scorching summer seasons. In Kuwait, most of the electrical energy required for functions such as air conditioning and lighting is derived from fossil fuel resources, contributing to escalating air pollution and global warming. To reduce dependence on conventional energy sources for heating and cooling, this article presents a case study to explore the potential of using geothermal energy for space heating and cooling in Kuwait. The case study involves utilizing a geothermal heat pump (water-sourced heat pump) in conjunction with a vertical-borehole ground heat exchanger (VBGHE). The mentioned system is deployed to regulate the climate in a six-floor apartment block comprising a small two-bedroom apartment on each level, each with a total floor area of 57 m2. Two geothermal heat pumps, each with a cooling capacity of 2.58 kW and a heating capacity of 2.90 kW, connected to two vertical-borehole heat exchangers, were deployed for each apartment to maintain temperatures at 22 °C in summer and 26 °C in winter. The findings indicate that the estimated annual energy loads for cooling and heating for the apartment block are 42,758 kWh and 113 kWh, respectively. The corresponding electrical energy consumption amounted to 9294 kWh for space cooling and 113 kWh for space heating. The observed peak cooling load was approximately 9300 kJ/h (2.58 kW) per apartment, resulting in a power density of 45 W/m2. Moreover, the HP system achieved a 22% reduction in annual electric energy consumption compared to conventional air conditioning systems. This reduction in electric energy usage led to an annual CO2 reduction of 6.6 kg/m2.

Online Estimation of Three-Phase Induction Motor Parameters Using an Extended Kalman Filter for Energy Saving

In this paper, the online estimation of three-phase induction motor parameters using an extended Kalman filter for energy saving is proposed. The optimal value of the stator current on the d-axis is calculated to obtain the minimum power loss. Accurate motor parameters are required to calculate the optimal stator current value for energy saving. Hence, to estimate motor parameters in real time, an online estimator known as the extended Kalman filter is applied. The energy consumption results for the motor using the proposed approach (estimated parameters with extended Kalman filter) are compared with those obtained using the conventional approach and energy saving (fixed parameters without parameter estimation) approach. As revealed by the comparison results from implementation in a laboratory, the proposed approach can provide minimum power losses for the three-phase induction motor drive, and the maximum energy-saving percentage is 60.18% compared with using the conventional drive approach.

ANFIS-based improved GWO: Rapid prototyping of low-power solar energy system under fast-changing solar radiation conditions

The increasing need for energy, coupled with progress in technology, has emphasized the importance of renewable energy sources around the world. Solar energy systems harness the power of sunlight to generate electricity, offering a renewable and environmentally friendly alternative to conventional energy sources. Maximum Power Point Tracking (MPPT) algorithms are employed to achieve optimal efficiency from the PV systems. This paper introduces a new method for controlling Maximum Power Point (MPP) in battery charging systems using an Adaptive Neuro-Fuzzy Inference System (ANFIS)-based improved Grey Wolf Optimization (ANFIS-GWO) algorithm. The study involves the application and evaluation of the IGWO algorithm under fast-changing solar radiation conditions (1000 w/m2, 600 w/m2, 800 w/m2) and constant ambient temperature (25 °C). An analysis was performed to evaluate the behavior of the system in the laboratory environment using rapid prototyping. The proposed IGWO algorithm demonstrates improved accuracy compared to traditional methods in the current literature. The study aims to enhance the efficiency of MPPT control in photovoltaic (PV) systems, offering a potential solution for optimizing performance in different solar radiation conditions.

Design, construction, and field testing of a spiral water wheel pump

The global expansion in farmland and the increase in the world population has compounded the need for more efficient water use. The spiral water wheel pump can be a valuable and low-cost option for pumping water for surface and subsurface irrigation for farmland near flowing water bodies. This low-cost water-lifting device, which uses the kinetic energy of a flowing stream/river to lift water to homes and farmlands, can help smallholder farmers expand the growing season into the dry season. It is more cost-effective than conventional energy sources. It can be used in areas with limited access to electricity or fossil fuels because the energy of pumping is derived from the kinetic energy of flowing water. Its simplicity, adaptability, and low maintenance requirements make it a valuable tool for communities seeking water security and improved livelihoods. The main objective of this study was to develop performance curves for a version of the pump fabricated from polyvinyl chloride (PVC) and wood, materials that are readily accessible to smallholder farmers in Africa, to optimize its performance for different field conditions. Laboratory and field tests were performed in Illinois, United States of America, and Sierra Leone, West Africa, with pumps with several pipe diameters/pipe configurations and wheel diameters. During the laboratory tests, a 0.6m diameter single-layer pump with a 2.5cm pipe diameter (18 coils) lifted water to a maximum height of 3.4m. When a 3.8cm pipe diameter (10 coils) was used, the maximum height was reduced to 2.7m. Field tests at an experimental site in Fulton County, Illinois, generated a maximum height of 3.4m and 3.1m when 2.5cm pipe diameters were used on 1.22m and 0.6m diameter wheels, respectively. In Sierra Leone, the maximum height generated was 16m and 8.5m for the 1.22m and 0.6m diameter wheels, respectively, with a 1.9cm pipe diameter. In all the field tests, the pumps only worked when the water velocity exceeded 0.6 ms-1, smaller streams with a velocity less than 0.6 ms-1 can be channeled if necessary. These results indicate that this pump can improve dry season productivity for farmland near the flowing water bodies in developing countries like Sierra Leone. Key words: Wheel diameter, pipe diameters, pipe configuration, discharge rate, stream velocity

Nanoscale mapping of residual stresses in Al 2024 alloys using correlative and multimodal scanning transmission electron microscopy

A methodology for the mapping of residual stresses in metal alloys has been developed by analyzing an isotropic and homogeneous Al2024 alloy with scanning transmission electron microscopy (STEM), combined with diffraction (4DSTEM) and electron energy loss spectroscopy (STEM-EELS) techniques of TEM. The investigations on the alloy's microstructure and elemental distributions were also carried out with conventional dark-field STEM (DFSTEM) and X-ray energy dispersive (EDS) techniques, respectively. Using the STEM-EELS technique, the Young's modulus (YM) is mapped in the (001) plane of the Al alloy in the same regions where the residual strain maps are generated in [1‾ 00] and [010] directions by using 4DSTEM technique. The YM vs. residual strain plot for the Al 2024 alloy revealed that the value of YM decreased by about ∼ 7 % after the tensile residual strain reached 0.02 %. Whereas such a decrease in YM happens after the compressively residual strain reaches −0.015 %. The residual stress maps were also obtained in accordance with the Hooke's law i.e., by multiplying YM map with the corresponding residual strain maps.

Thermogravimetric Analysis of Eucalyptus Leaves as An Alternative Fuel for Rural Areas

The utilization of biomass waste as a substitute for conventional energy sources has gained popularity, and one possible source is the litter generated by eucalyptus plantations. The present study used thermogravimetric analysis (TGA) gain insight into the thermochemical characteristics of eucalyptus leaves. It was identified by heating the sample in a nitrogen environment from ambient temperature to 850oC at a rate of 10 oC/minute. Eucalyptus leaves have a high volatile matter (VM) content and a calorific value (CV) of 17.26 MJ/kg, according to the ultimate and proximate analysis. Additionally, the TGA results showed that eucalyptus leaves had a lower ignition temperature than other biomasses. Eucalyptus leaves began to devolatilize at 119 oC, reaching a peak temperature of 326 oC, and losing 68% of their weight as a result.

Maximum Power Point Tracking with Artificial Neural Network

The urgent depletion of fossil fuel resources and the pressing need for environmental preservation have spurred a critical examination of alternative energy solutions. In response, this study focuses on the development of innovative approaches to mitigate the overreliance on conventional energy sources and transition towards sustainable alternatives. As part of a final year project, the research draws inspiration from this imperative and endeavors to design a prototype model that integrates advanced techniques for harnessing solar energy. Index Terms–Maximum Power Point, Buck-Boost Converter, Neural Network Architecture

Low-cost Mobile Solar Operated Lift Irrigation System : A Case Study

Effective and judicious use of irrigation water contributes a lot for the management of crop growth and increase in productivity. In the light of increasing demand for irrigation in the state of Assam(India) and to cover the non irrigated area as well as to continue the supplies for the irrigated command area, it becomes imperative to look for a holistic and people centric Low Cost Innovative Irrigation technique. Irrigation water can be assured at every crop field provided we set our mind and put concerted efforts to address it. This paper highlights the Irrigation scenario in Assam with a case study on Low Cost Solar Operated Mobile Lift Irrigation in Assam, for its continuance and contribution towards growth in Agricultural Productivity. This innovation in Irrigation Sector can cause Social transformation by bringing in the development of Agriculture and other allied Sectors. An attempt was also made to establish the economic and operational benefits of the system by making a comparison amongst the different lift Irrigation Schemes in the State. The study advocates for utilization of the non conventional solar energy for irrigating the multiple crops by lifting the surface water sources in the State of Assam by using the Low Cost Solar Operated Mobile Surface Lift Irrigation System. The paper also presents the financial analysis and Key Performance Indicators of the System with a highlight on its diversified application for disaster preparedness and mitigation on the part of Stakeholder Departments with a primary aim to increase Irrigated agriculture productivity

Chemically Self–chargeable Batteries and Devices Beyond Energy Installation

AbstractSelf–charging devices integrating ambient energy conversion technologies into batteries are attracting extensive attention in interdisciplinary research fields. However, the integrated devices such solar/mechanical/heat chargeable systems rely on the accessibility of the energy and possess rather complicated configuration. In recent years, the chemically self–chargeable batteries and devices have attracted wide attention due to its self–powering functionality, simplified pact structure and environment adaptability. This minireview will focus on the connotation and denotation of the chemically self–chargeable batteries and representative applications beyond conventional energy installations.

Renewable energy for women empowerment: Experiences from rural West Bengal

Unreliable supply and frequent failures of grid electricity are common in rural and disaster-prone areas in India. Furthermore, the households living below the poverty line have limited ability to pay the electricity charges regularly. Under these circumstances, access to clean and renewable energy is expected to provide significant socio-economic and environmental benefits vis-à-vis conventional energy sources, contributing to socially inclusive and sustainable development immensely. In particular, access to renewable energies in rural areas can potentially facilitate income-generating activities by the women and, hence, their socio-economic empowerment. Given this backdrop, the study examines if the socialization of solar energy through the installation of micro solar domes can lead to women empowerment in rural West Bengal. Two blocks, namely Hirbandh and Ranibandh, in the Bankura district are selected for carrying out detailed analysis. It is found that the MSDs seem to have improved users' standard of living and enhanced women's participation in the decision-making process along with their mobility, financial autonomy and social activities. Nevertheless, emphasis should be given to designing appropriate structures towards creating markets for such technologies for promoting socially inclusive cleaner energy transition.

Performance analysis of ARIMA Model for wind speed forecasting in Jerusalem, Palestine

Palestine lacks sufficient conventional energy sources that meet the daily needs of the Palestinian people, and consequently, it heavily relies on neighboring countries for its supply with energy compensations. Wind energy is recognized as an abundant, effective, and eco-friendly power source, but it poses several challenges in harnessing due to the inherent variability of wind characteristics. The main objective of this research study is to delve into the wind energy landscape in Palestine, and to offer some insights into the feasibility of wind speed forecasting for implementing sustainable energy solutions, with a special focus on ARIMA; a widely used statistical method for time series forecasting. It specifically explores the potential of using ARIMA models to forecast wind speed using a data captured from a meteorological station located in east Jerusalem, Palestine for a duration of 2 years—January 1, 2021 to December 31, 2022. To find the optimal values of ARIMA parameters (p, d, q) for the considered study site, a set of experiments were conducted and the model's forecasting accuracy was evaluated using three metrics: RMSE, MAE, and the coefficient of determination (R2). The results have shown that ARIMA (21,2) emerges as the most accurate structure with an input period that demonstrates superior estimation with minimal RMSE (1.74), minimal MAE (1.58) and higher R2 (0.76) values. This means that the optimal estimation is achieved when an autoregressive process is based on the previous two lagged observations and the moving average process incorporates the dependency between the observation and the residual error from a second-order moving average applied to the lagged observations. These findings give valuable insights into the feasibility and precision of wind speed forecasting models for sustainable energy solutions, and emphasize the potential for harnessing wind energy in the region as clarified by ARIMA forecasting accuracy.

Investment Portfolio Optimization in Renewable Energy Stocks in Indonesia Using Mean-Variance Risk Aversion Model

Climate change is a phenomenon that has been occurring for quite some time. However, the increasingly felt impacts of climate change necessitate human action to mitigate these effects. One way to address this issue is by transitioning from conventional or non-renewable energy sources to renewable energy. This step undoubtedly has implications for various aspects, such as investments. Naturally, investors are beginning to turn their attention to the field of renewable energy as a new target. Investments are inherently associated with risks and returns One approach to maximizing returns is through portfolio optimization. One well-known method in portfolio optimization is the Mean-Variance method, also known as the Markowitz method, as it was first introduced by Harry Markowitz. In this research, an optimal portfolio is generated with weights of 0.1470 for ADRO; 0.1939 for MEDC; 0.2143 for ITMG and 0.4449 for RAJA. With this composition of optimal portfolio weights, the expected return is obtained at 0.002252, and the return variance is 0.000496.