Volume 11, Issue 1

Since the PVSYST simulator is the most well-known software among researchers and PV experts, we chose to compare its results to those of the manual method. Thus, the objective of the article was to obtain the degree of similarity between the results of the PVSYST simulation and the manual calculation of the same parameters, based on the study of the photovoltaic systems of the University Ibn Tofail. Those installations are installed in the Faculty of Letters, Science, the Presidency and CFC. The later used in our study, have different parameters. Hence, to collect these parameters and their distinct data we used multiple sources. The datasheets of each components of the PV system contains the parameters that distinguish the devices therefore it was mandatory to look for that information, since it will facilitate our study. The meteorological database PVGIS, was our reference for the temperature and irradiation data. What’s more is the PVSYST software that helps in the simulation of the PV system and thus having a detailed report with massive information. All this collection of data was aiming to help us comparing the results of yields and other parameters by manual calculation versus simulation in PVSYST. Morocco has demonstrated a strong commitment to combat climate change by embracing renewable energy, particularly photovoltaic systems. In this pursuit, universities like Ibn Tofail University (UIT) play a crucial role in addressing climate challenges and developing research solutions for mitigation. UIT actively participates in projects related to environmental protection and sustainable development, contributing to Morocco’s growth and higher education advancement. As part of its efforts, UIT has been involved in implementing sustainable green projects and promoting renewable energy technologies. A specific study at UIT aimed to compare PVSYST simulation results with manual calculations for four PV systems on campus, considering parameters such as orientation, electrical installation, and panel types. The International Energy Agency (IEA) Photovoltaic Systems Program has established standards and a key concept, the yield factor, measuring the net energy production over a facility’s lifetime compared to the energy used for construction, operation, and supply. By evaluating the accuracy and efficiency of PVSYST, researchers sought to advance the use of PV systems and contribute to Morocco’s renewable energy goals. Such research not only aids in the progression of renewable energy technology but also aligns with Morocco’s vision for sustainable development and environmental protection.

The population growing faster than before, and availability of transportation options is increasing. Automobiles require combustion engines, which require fuel obtained from underground storage. This underground fuel storage is limited and depleting day-by-day. Many nations have set deadlines up to 2040 to stop producing automobiles that run on underground fuels. Researchers have concentrated on alternative modes of fuel for transportation. The world’s largest Sedan marketplaces will transition to all-electric vehicles by 2035, providing a glimpse of greener future other than a significant financial prospect. Not only Sedan, the entire world is focussing on only green electric vehicles to maintain sustainability. However, electric vehicle charging stations are operated by using many conventional resources. Therefore, this paper aims to show how self-charging electric vehicles can help to reduce emissions caused by the direct use of conventional resources in charging stations along with the up-to-date status quo of the EV market. The key descriptions of electric vehicles on top of the battery’s type which is randomly used in EVs, how the batteries are proficient in preserving and supplying power continuity itself in vehicles are talked about. Finally, the paper is consulting about charging-discharging system of electric vehicles to make the environment cleaner.

In addition to traditional piezoelectric polymers, mono-crystals and ceramics, piezoelectrets or charged voided polymers have shown an interesting piezoelectric response by converting the mechanical energy into electrical and vice versa, therefore being incorporated in a number of advanced electromechanical transducers. This article is a review on the different phases for the elaboration of pseudo piezoelectric films based on passive polymers. First, several methods for the elaboration of the cellular structure of these materials are explained in the main text, with the morphological representation of the reached porosity. The porosity represents a cell to embed the positive and negative electrical charges created by the most common electrical charging processes, which are subsequently mentioned. Different theoretical models are emphasized as well to predict the piezoelectric behavior of this porous polymers. Finally, some of the latest harvesting energy applications based on porous polymers are collected. All the considerations cited above make Piezoelectric porous polymers open access materials that can be developed and optimized by the control of the porosity then used in energy harvesting applications.

Solar power and photovoltaic (PV) systems have become crucial components of the world’s energy portfolio. The PV systems may be engineered in a number of ways, including off-grid, on-grid, and tracking. Incorporating PV systems with traditional sources of power like diesel generators (DGs) or other renewable sources, like windmills, is possible. In this situation, developers, investigators, and experts are striving to create the best design that accommodates the load demand in regards to technological, financial, ecological, and social aspects. To assist in figuring out the best PV size and design, numerous tools, models, and heuristics were created and rolled out. The majority of the tools, models, and techniques used to build PV systems over the past 70 years were described, assessed, and evaluated in this article. It was observed that methods for optimising PV system designs evolved with time and demand. Tool design is often divided into segments such as artificial and classical, solo and hybrid approaches, and others. Hybrid approaches, nevertheless, gained prominence to become the most popular approach because of its adaptability and capacity for handling challenging issues. This paper’s evaluation also helps the readers choose a PV system design tool (approximately 46) that is suited for their needs.

Due to greenhouse gas emissions and the energy crisis, the conventional way of generation of electricity using fossil fuels is being substituted with Renewable Energy Sources (RES) like solar photovoltaics (SPV), fuel cells, wind, etc. The voltage produced by RES is very small in magnitude; therefore, the choice of DC–DC converter is critical for regulating and improving the output of RES to its maximum level. To meet the power requirement for the utility grid and electric vehicles (EV), the voltage must be enhanced. So far, various types of high-gain DC–DC boost converter (HG-BC) topologies have been suggested. An overview of HG-BC topologies for RES and EV applications is presented in this paper, which provides a unique, extensive, perceptive, and comparative analysis of HG-BC topologies. The mathematical modeling and operating principles of each converter topology have been analyzed and discussed. The boost factor (B) and component count for various HG-BC are thoroughly compared for a 0.5 duty cycle using the MATLAB/Simulink tool.

The study examines the methods for producing hydrogen using solar energy as a catalyst. The two commonly recognised categories of processes are direct and indirect. Due to the indirect processes low efficiency, excessive heat dissipation, and dearth of readily available heat-resistant materials, they are ranked lower than the direct procedures despite the direct procedures superior thermal performance. Electrolysis, bio photosynthesis, and thermoelectric photodegradation are a few examples of indirect approaches. It appears that indirect approaches have certain advantages. The heterogeneous photocatalytic process minimises the quantity of emissions released into the environment; thermochemical reactions stand out for having low energy requirements due to the high temperatures generated; and electrolysis is efficient while having very little pollution created. Electrolysis has the highest exergy and energy efficiency when compared to other methods of creating hydrogen, according to the evaluation.

This comprehensive review delves into the burgeoning field of green hydrogen production through the utilization of renewable resources. As the global demand for clean and sustainable energy escalates, green hydrogen has emerged as a promising solution, garnering significant attention due to its potential to decarbonize various sectors. The study encapsulates a thorough exploration of the key methodologies employed in harnessing renewable sources such as wind, solar, and hydroelectric power for hydrogen generation. The analysis encompasses both technological aspects and environmental implications, shedding light on efficiency, scalability, and feasibility. Moreover, the review evaluates the economic viability and policy frameworks that underpin the integration of green hydrogen into existing energy systems. By synthesizing findings from a multitude of research endeavors, this study underscores the current advancements, challenges, and future prospects in the realm of green hydrogen production. Ultimately, this review not only contributes to a deeper understanding of sustainable energy pathways but also provides insights that can guide the evolution of green hydrogen technologies toward a more environmentally conscious and energy-abundant future.

The earth natural carrying capacity is being surpassed, and there is an urgent need to develop new alternatives, notably in regards to energy supplies, carbon dioxide emissions, and nitrogen supplies to the ecosystem. Hydrogen gas, produced from renewable energy by water electrolysis, may serve as a platform molecule for the 21st century low-carbon economy and electrification. The ability to utilise hydrogen metabolic processes is quite diverse, and this offers up a vast array of avenues for innovative biotechnological advancements and applications. A strategy focusing on the major role of hydrogen throughout the production of bio-based foundational element compounds through the hydrocarbon pathway would avoid the inherent low economic value of hydrocarbons in favour of products with greater value. Furthermore, hydrogen could serve as a crucial carbon-neutral source for the manufacture of third-generation proteins while allowing carbon capture and nutritional recovery immediately at the site of emission. Using these methods to deal with the seasonal changes in renewable energy sources makes the use of alternative energy as efficient as possible. The outcomes demonstrated the production technologies of bio-hydrogen is a good way to make renewable hydrogen that is both cost-effective and good for the environment compared to other ways of making hydrogen.

Demand-side management (DSM) with Internet of Things (IoT) integration has become a vital path for optimizing photovoltaic (PV) power generating systems. This systematic review synthesizes and evaluates the latest advancements in IoT-based DSM strategies applied to PV power generation. The review encompasses a comprehensive analysis of recent literature, focusing on the key elements of IoT implementation, data analytics, communication protocols, and control strategies in relation to solar energy DSM. The combined results show how IoT-driven solutions are changing and how they might improve PV power systems’ sustainability, dependability, and efficiency. The review also identifies gaps in current research and proposes potential avenues for future investigations, thereby contributing to the ongoing discourse on leveraging smart DSM in the solar energy domain using IoT technology.

Solar energy is the most effective substitute for fossil fuels when it comes to Produce electricity among the numerous renewable energy sources. The efficiency may drop as a result of overheating, and the PV cell may also be harmed. Therefore, increasing the output of a solar PV system at a lower cost is essential to improving its efficiency. Additionally, by using cooling methods, the PV cells’ lifetime is extended. By lowering the working temperature of a PV panel’s surface, you may increase efficiency and slow the thermal deterioration rate. This may be done by module cooling and lowering the heat that the PV cells generate while operating. Hence, an active cooling technology known as optimization-aided water spraying technique is employed to increase efficiency. This method enables the PV panels to provide their maximum output power while taking less time to drop down to a lower surface temperature. Beluga Whale assisted Jellyfish Optimization (BWJO) model is suggested as a means of achieving these goals. Finally, Simulink/MATLAB is used to implement the suggested method and optimize the PV system cooling. The performances of the two components were compared using a variety of metrics.

Developing renewable energy sources has gained considerable attention recently. Solar energy is the fastest-growing alternative renewable energy source. A solar energy harvesting-based built-in backpack charger is introduced here. The proposed system aims to utilise the surrounding solar energy and overcome the power limitations of batteries installed in mobile phones in cases where power sockets are unavailable. A 6 cm × 6 cm solar module is employed. Additionally, current, voltage, and power were measured under the two scenarios; the first scenario is when the electrical load is 100 Ω, and the second scenario is when the load is a power bank. The maximum harvested power noticed in the first scenario of the resistive load was 140 mW by the proposed system in the southeast direction from 10:30 a.m. to 4:30 p.m. Moreover, the top-generated output voltage and current in this scenario were 3.6 V and 36 mA. On the other hand, 55 mW was the top value for the second scenario of the power bank as a load in the flat direction with the highest generated output voltage and current of 4.1 V and 13 mA, whereas 4.27 V was the highest generated voltage in this scenario in the west direction.

Mobile and wearable devices are now the main part of our lives. The power consumed by these devices is usually in the range of μW or mW. Due to the requirement of periodic recharging, this work tries to present an economic renewable energy harvesting source for the process of charging. In this paper, authors exploit a huge amount of energy dissipated daily in the form of loud noise through streets up to 85 dB to generate a sufficient rate of energy to recharge the lithium batteries of wearable and mobile devices (more than 4.01 V). The piezoelectric model 7BB-27-4 was used in this work through a proposed design circuit. Suitable software was used to simulate the design. In comparison to previous research findings, the authors’ findings are sufficiently satisfactory.

The current study aims to utilize population expansion by introducing a specially designed footsteps tiles mechanism capable of converting kinetic energy from footsteps into electricity. A rack and pinion mechanism was implemented due to its straightforward installation process and relatively high-power generation. However, addressing user comfort was crucial, as the mechanism caused significant deflections. As a result, a footstep tile mechanism was devised, manufactured, and thoroughly examined through both experimental and simulation methods. The CAD design of the mechanism was developed in SOLIDWORKS, dynamic models were created, and the system characteristics were analyzed using the simulation tool SIMULINK MATLAB ® . Based on the optimal design obtained through dynamic simulations, the mechanism was fabricated, tested, and analyzed. The testing phase demonstrated an average of 9 V generated per footstep, yielding an estimated mechanical output power of 8.5 W per footstep, with a mechanical-to-electrical conversion efficiency of 15.6 %. The proposed setup presents a promising roadmap for large-scale electricity generation in densely populated areas such as institutes, hospitals, railway stations, and similar locations.

Heat exchanger (HE) is an instrument that facilitates the operation of HE between two fluids that are at various temperatures. Double-pipe HEs are used in many organizations because of their low installation, design, maintenance costs, flexibility, and their suitability for high pressure applications. Heat transfer (HT) augmentation techniques (passive, active or compound techniques) are used in heat exchangers to reduce the HT surface area, to increase HT capacity and to reduce pumping power. Passive augmentation techniques are much cheaper and do not involve any external power input. They aim to improve the effective surface area, the residence time of the HT fluid and its thermal conductivity by the usage of nanofluids. Nanofluids are used for cooling applications in organizations, transportation, nuclear reactors, electrical and electronic devices and for biomedical applications. Hybrid nanofluids have higher thermal conductivity, low PD and frictional losses and pumping power as compared to the mono nanofluids. In this present work, experiments are conducted in a double pipe HE using TiO 2 , and SiC-water nanofluids by varying the volume concentration and cold fluid mass flow rate ranging from 17.5 to 34.5 lpm by making constant hot fluid mass flow rate. Further, experiments are conducted using TiO 2 –SiC/water hybrid nanofluids. Influence of nano and hybrid nanofluids on the overall HTC and friction factor are experimentally investigated. From the experiments, TiO 2 –SiC/water hybrid nanofluid with nanoparticle ratio TiO 2 :SiC = 1:2 is found to be optimum as the heat transfer enhancement is more with less improvement in friction factor. The overall heat transfer, and friction factor enhancement is 22.92 %, and 11.20 % higher respectively when compared with base fluid for TiO 2 :SiC = 1:2.

An energy generation system that is highly appealing is the integration of a photovoltaic system with linear Fresnel reflectors, especially when combined with a cooling thermal system. This research study involves a comparative analysis of energy and exergy of a CPV/T system that uses traditional linear Fresnel reflectors. The calculations indicate that, given the prevailing weather conditions and an average instantaneous solar radiation of 559 W/m 2 at the location, the system can generate an average of 271.23 kWh of electricity and 613.63 kWh of thermal energy per month by utilizing highly efficient, long-lasting, and cost-effective monocrystalline solar cells in the considered the CPV/T system. The overall efficiency of the system is determined to be 54.1 %. According to exergy analysis, the setup experiences some loss of exergy in both its thermal and electrical components. The overall exergy efficiency is calculated as 54.96 %. Thus, on average, the system experiences an exergy loss of 1.01 kWh per day due to thermal factors and 1.70 kWh due to electrical factors. Although the system appears to be more efficient in exergy than energy, the exergy values highlight the need to reduce energy and exergy losses in order to improve the overall system performance.

Clean sustainable energy and proper utilization of the available natural resources are of paramount importance for the modern societies. In this work, green composite materials were designed, fabricated and utilized as back sheets for the solar photovoltaic panels to investigate their effects on the output voltage of the solar cell unit. Such replacement of the back sheet of the solar cells would improve their efficiency while reducing the cost and enhancing better environmental conservations. Green back sheet composites were designed with 25 wt% and 50 wt% of high-density polyethylene with all Rhus typhina , Punica granatum and Piper nigrum powders. Investigations of the effect of green composite back sheet materials on solar panel output voltage harvesting have been carried out in Jordan at Zarqa city (latitude 32.07°, longitude 36.08°). Results have revealed that R. typhina and P. nigrum based composites with 25 wt% fiber loading have demonstrated much better output voltage comparable to the original back sheet cell. The maximum output voltage was found to be enhanced about 58 % with the green composite back sheets. This in order would improve the efficiency of such solar cell units and enhance better environmental indices.

Efficiency of the battery pack largely depends on the resistive losses and heat generation between the interconnections of the battery cells. Grouping of battery cells usually is done in different ways in industries. However, losses vary depending on applications or states of electric vehicle (EV). Therefore, it is necessary to determine the efficiency and heat generation in battery cells as well as battery packs. In practical situations, some battery cells are charged rapidly in comparison to other battery cells. On the other hand, when an EV is in running condition some battery cells are discharged rapidly. As a results battery pack cannot provide better efficiency and its life span is reduced. As an alternative option the inter-cell connection of battery package is needed to reconfigure in an optimized way. In this paper firstly, a battery pack with switches is modeled and then efficiency and temperature variation with respect to time are determined. Then, an experimental setup is investigated to measure the efficiency and temperature rise with respect to time. Results, explained in the paper, demonstrate that battery pack with switches increases the efficiency if it is measured after switching (97–98 %), while temperature increases from 25 °C to 50 °C for different C-rates.

The energy management system is established in the microgrid system for optimally integrating the Distributed Energy Resources (DERs) and generating the power distribution grids. At last, diverse mechanisms have been highly concentrated on cost reduction and at the same time, both the technical indices and economic factors are considered. Thus, this research work suggests a new heuristic algorithm termed Modified Sandpiper optimization algorithm (M-SOA) for optimal integration of DER-like Photo Voltaic (PV), wind turbines, and Energy Storage Systems (ESS) into microgrids. Here, the techno-economical optimization with ISOA is designed for determining the optimal capacity of PV, Wind Turbine, and ESS via the multi-objective function concerning measures like network power losses, voltage fluctuations, Electricity Supply Costs, initial cost, operation cost, fuel cost, and demand side management. Finally, the optimal energy management is done on distributed energy resources, and this developed model experiments on the IEEE-33 bus network. Throughout the result analysis, the developed M-SOA obtains 3.84 %, 0.98 %, 5.72 %, and 4.63 % better performance with less latency than the AGTO, BOA, WOA, and SOA. Finally, the result evaluation is done for minimizing the Electricity Supply Costs, initial cost, operation cost, and fuel cost and maximize energy efficiency.

Harvesting the dissipated environmental mechanical energy to generate electrical energy is subject of the new research in the field of clean energy. In this paper, a triboelectric nanogenerator based on vertical two-electrode structure was fabricated using KAPTON and PDMS polymers. The nanogenerator outputs were measured and plotted by applying a mechanical vibration with the frequency of 8 Hz. The results indicated the ability of producing a voltage of 3.5 V and a current of 0.025 μA by this nanogenerator. To effectively simulate the performance of the device in different structural and environmental conditions, the ordinary capacitance model of the device was modified considering three effective capacitances. The simulation results showed a very good agreement between calculated and actual outputs when the edge effect capacitor was included in the ordinary model. Finally, based on the corrected model for the nanogenerator, the effect of the environmental conditions on the device output was studied. The innovative point of this text is the investigation of the effect of edge capacitors in the performance of triboelectric nanogenerators, and it has also been tried to collect a collection of studies that I have done in the field of triboelectric nanogenerators.

This paper presents a new approach to improve the performance of Zeta converters, which are commonly used in cost-sensitive circuits to manage unregulated power supply. The converters are designed to produce positive output voltages based on input voltages, and they use a buck controller to power a PMOS-based FET for high-side control. Compared to other converters, such as SEPIC, Zeta converters are smaller and more scalable for micro applications due to the use of coupled inductor circuits. The performance of Zeta converters is heavily influenced by the ratings of their passive components. To optimize component rating choices, researchers have developed several pattern analysis models. However, these models often require context-specific ratings and lack a parameter selection method for continual reconfigurations, making them difficult to deploy in practice for different use cases. To address these limitations, the authors propose a hybrid soft computing methodology for passive component selection in multiple load Zeta converters. The proposed approach combines Particle Swarm Optimization (PSO) to determine initial component ratings and Grey Wolf Optimization (GWO) to improve conversion efficiency, output gain, and Total Harmonic Distortion (THD). This is achieved by modeling a fitness function that incorporates output metrics and optimizes them incrementally for real-time deployments. The results show that the suggested methodology can reduce THD by 6.5 %, increase conversion efficiency by 3.4 %, and maintain a gain improvement of 1.5 % across numerous use cases. These improvements make the model suitable for real-time use applications. Overall, the proposed approach provides a promising solution to the challenges of passive component selection in Zeta converters, which can lead to more efficient and cost-effective power management in various circuits.

The importance of diversified energy production lies in addressing the fuel shortage resulting from high prices, high temperatures, and environmental pollution associated with its production and consumption. Vibrational energy plays a crucial role in generating electrical power. This paper introduces a new concept based on utilizing the vibration forces of chimneys caused by wind and earthquakes. A mechatronic energy-absorbing system was designed, analyzed, and the output power was calculated using SolidWorks and Matlab programs. The design of the Regenerative Damping Chimney (RDC) primarily focuses on converting vibrations into rotational movement of the chimney, which is generated by wind forces. This is achieved by using a metal rope and pulleys to transmit motion to a set of gears. The opposite direction rotation is facilitated by bevel gears and clutches, and a planetary gearbox is employed to increase the rotation of the DC 24 V 400 W generator. The use of a high-watt generator aims to enhance energy production and the damping factor, ensuring the stability of the chimney during storms and vortex winds. The results show the efficiency of 35 % may reach 45 % watts under test to verify that the proposed system is effective and suitable for chimneys and renewable energy applications in factories and companies.

As the world’s attention turns to cleaner, more dependable, and sustainable resources, the renewable energy sector is rising quickly. The decline in world energy use and climate change are the two most significant factors nowadays. PV forecasting was essential to enhancing the efficiency of the real-time control system and preventing any undesirable effects. The smart energy management systems of distributed energy resources, the forecasting model of irradiation received from the sun, and therefore PV energy production might mitigate the impact of uncertainty on PV energy generation, improve system dependability, and increase the incursion level of solar power generation. Smart sensors and Internet of Things technologies are essential for monitoring and controlling applications in a broad range of fields. As a result, solar power generation forecasting was essential for microgrid stability and security, as well as solar photovoltaic integration in a strategic approach. This paper examines how to use IoT, a solar photovoltaic system being monitored, and shows the proposed monitoring system is a potentially viable option for smart remote and in-person monitoring of a solar PV system.

The research study provides a techno-economic analysis for the green hydrogen generation based solar radiation data for both the single and hybrid alkaline water electrolyzer and energy storage system systems. In addition, a carbon footprint study is conducted to estimate the developed system carbon dioxide emissions. The optimal size of the alkaline water electrolyzer and energy storage system is determined by a genetic algorithm that takes into account a carbon tax on carbon emissions. Based on itemized cost estimating findings, unit hydrogen production costs for a single system and a hybrid system were $6.88/kg and $8.32/kg respectively. Furthermore, capital cost it has been found as a key element in determining the optimal scale of the alkaline water electrolyzer and energy storage system, which are essential for minimizing the unit hydrogen production cost. Lastly, an effort to minimize the capital cost of producing green hydrogen is required when the rising trend of the carbon dioxide tax is taken into account.

An injection mechanism which is split injection was found to reduce emissions in Diesel engines. In this mechanism, split injection proportion and split injection timing was varied and analyzed to reduce engine emissions. Injection proportion was varied at 25% of the pilot and 75% of the fuel as main injection and timing as 54° ATDC (after top dead center) and 40° ATDC for split injection. Since a homogeneous mixture occurs in this pilot injection, combustion is becoming complete for Diesel Engine. Hence, BTE was increased by 1.5% for timing 40° ATDC and 12° BTDC (before top dead center) and reduced by 1.4% for timing 54° ATDC and 12° BTDC. The reduction in BTE for 54° ATDC is because the increase in timing increases cooling effect of air and combustion rating was reduced. Also, combustion takes place at low temperature itself due to homogeneous mixture. So, NOx emission was also reduced by 8.4% and 18.6% for 40° ATDC and 54° ATDC injection timing respectively. The other emissions like HC and CO were also observed to be reduced upto 35% and 11% respectively due to increase in homogeneous mixture in Diesel Engine.

This article presents an energy management system (EMS) in a DC microgrid (MG) operating in an islanded mode to control the power flow in the distribution network. The microgrid system considered in this research consists of distributed generation sources like a solar photovoltaic system, a fuel cell energy system, and an energy storage system controlled by an optimized energy management system. As the distributed energy sources used are primarily renewable, unpredictable weather conditions may cause irregular energy generation. These variations impact the power flow in the DC bus, making it challenging to maintain a supply and demand balance. Therefore, an intelligent energy management system using the Harris Hawks Optimization (HHO) is implemented to enhance the microgrid’s performance and efficiency. The HHO algorithm is based on the hunting nature of the Harris Hawks, and the EMS is developed to maintain the optimal power flow and to handle the constraints. The performance of the presented system is analyzed with the particle swarm optimization (PSO) based Proportional Integral (PI) controller in different operating scenarios to validate the effectiveness of the DC microgrid system.

In the present work, numerical investigations are conducted with 22 % cut segmental baffle heat exchanger (SB), 20°, 30°, and 40° helical baffles shell and tube heat exchangers (STHX) to estimate the overall heat transfer coefficient (OHTC), pressure drop (PD) and friction factor. Among the studied heat exchangers (HE), 40° helical baffles STHX provided the highest OHTC with minimum pressure drop. Hence, further investigations are conducted experimentally with 40° helical baffles STHX. OHTC increased by 2.65 % for 20° helical baffles, 5.37 % for 30° helical baffles, 9.78 % for 40° helical baffles when compared with 22 % cut segmental baffle heat exchanger. The deviation between experimental and numerical OHTC is 2.64 % 40° helical baffles.

The major power quality issues in grid are voltage fluctuations and harmonics. For better power quality of the power system during disturbances on the grid, the UPQC device is utilized to maintain voltage magnitude and reduced harmonics. At the DC link of UPQC along with the capacitor, a renewable PV source is connected which contributes in voltage compensation by the series VSC and harmonics compensation by the shunt VSC. For stable DC voltage generation from PV source a modified P&O MPPT with DC reference is included controlling the boost converter connected to PV source. The controllers of VSCs are operated by feedback loop synchronized schematics with voltage reference generation in series VSC control and current reference generation in shunt VSC control. The shunt control is updated with hybrid Fuzzy-PI controller replacing the traditional PI controller further improving the power quality of the grid. The hybrid Fuzzy-PI varies the K p and K i gains as per the error generated by the DC voltage comparison concerning 25 rule-base for each gain. A comparative performance analysis is done with both the controllers in the shunt converter and the results are generated using MATLAB Simulink software.

Using the Neural Networks to predict solar harvestable energy would contribute to prolonging the duration of the effective operation and thus less consumption in solar-harvesting sensor nodes. The NNs with higher prediction accuracy have the longest effective operation. Till now, the NNs that use the zenith angle function as input have been utilized with only two terms. This paper shows the advantages of using a multi-term zenith angle function on the energy management in the nodes. To this end, this paper considers two, three, and four terms for the function of the zenith angle. The results showed that the case of four terms has the lowest prediction mistakes on average (0.83%) compared to (2.13% and 1.75%) for the cases of two and three terms, respectively. This is followed by a reduction in energy consumption in favor of four terms case. For one month simulation period with hourly prediction, the sensor node worked at the higher consumption mode (M2) in the case of four terms 4 hours less than three terms and 7 hours less than two terms case. Thus, increasing the number of terms in the zenith angle function leads to higher accuracy and less energy consumption.

Computation of transmission system efficiency of electromagnetic radiation becomes inaccurate when Friis formula is used in Fresnel zone (near-field zone) of wireless power transmission (WPT). A novel methodology has been proposed in this paper for estimation of the power density, received power and transmission system efficiency at a particular operating frequency in the near-field zone. The power transfer and transmission system efficiency need to be maximized for minimal dimensions of transmitter and receiver. Utilization of negative refractive index metamaterials (MM) between transmitter and receiver is proposed to achieve maximum power transfer. In the present paper, variation of received power and system efficiency with respect to transmitting distance is computed and compared for WPT system with and without metamaterials. The variation of system efficiency is studied for varied location of metamaterial from transmitter by assuming metamaterial diameter at a given location is greater than or equal to the beam diameter at that location. Different configurations with varied input power and transmitting distances from shorter to longer range are considered in the study to analyse parameters that affect system efficiency. The approach for identifying optimal number of metamaterials and their placement between transmitter and receiver for maximum power transfer has also been discussed.

The future of energy is of global concern, with hydrogen emerging as a potential solution for sustainable energy development. This paper provides a comprehensive analysis of the current hydrogen energy landscape, its potential role in a decarbonized future, and the hurdles that need to be overcome for its wider implementation. The first elucidates the opportunities hydrogen energy presents, including its potential for decarbonizing various sectors, in addition addresses the challenges that stand in the way of hydrogen energy large-scale adoption. The obtained results provide a comprehensive overview of the hydrogen energy horizon, emphasizing the need to balance opportunities and challenges for its successful integration into the global energy landscape. It highlights the importance of continued research, development, and collaboration across sectors to realize the full potential of hydrogen as a sustainable and low-carbon energy carrier.

The development of renewable energy-based applications is nowadays a forced demand of society, for chasing the target set by the governments and the concerned organizations, to reduce or limit the carbon penetration in the environment. Sincere efforts are being made by academics and researchers to create applications based on renewable energy that are reliable and efficient. Green revolutions increase agricultural fields and alter grain production rates, but they also increase energy consumption since agricultural machinery is used more efficiently, mostly for irrigation needs. The purpose of this work is to introduce a hybrid renewable energy system (HRES) that can take the place of the diesel pump often used for time-bound crop irrigation. This HRES system consists of a photovoltaic generator as the main power source supported by a battery energy storage system. For this hybrid system, the development of a Proportional & Integral (PI)-based integrated hybrid controller is proposed to regulate the charge/discharge cycle of the battery energy with maintaining the load demand simultaneously. Controlling of this hybrid system is carried out in the LabVIEW environment.

The generation of power from solar energy by using Photovoltaic (PV) systems to convert the irradiation of the sun into electricity has been adopted over the past years. However, the PV system’s P–V and I–V characteristics become unstable when solar irradiation and temperature change. In this paper, the incremental conductance (INC) has been improved using signals to measure the current and voltage from the PV systems directly which quickly changes with the environmental conditions, and the conventional particle swarm optimization (PSO) is modified so that under multiple shaded peak PV array curves with fast-changing solar irradiance and temperature, more power is extracted at a faster rate without any tracking failure at high-speed tracking of both individual maximum power point (IMPP) and global maximum power point (GMPP) under varying solar irradiance and temperature at a longer distance to enhance the power generated. The individual and global coefficients are also improved to change with multiple shaded peak PV array curves with fast-changing solar irradiance and temperature. DC-DC converter converts DC power from one circuit to another and DC-AC inverter converts DC power to AC power. Simulation was carried out in MATLAB Simulink with different solar irradiance and temperature whereby the conventional INC and PSO were compared with the proposed INC and PSO. An experiment was carried out for a whole day from 8 am to 5 pm to test the validity of the proposed algorithm and compared it with the conventional INC and PSO by using the solar irradiance and temperature received. From both the simulation and experimental results, the proposed INC and PSO performed better by attaining high power and tracking speed with stable output results than the conventional INC and PSO.

In this paper, an experimental and numerical investigation of thermoelectric generator for energy harvesting performance of screw compressors has been studied. The sources of heat recovery from compressors are recognized and a heat exchanger to mount the Thermoelectric Generator (TEG) module assembly is designed to adapt for implementation in this work. Computational fluid dynamics (CFD) is used to find out the temperature distribution in the heat exchanger and experimental work is carried out to validate CFD results. The heat exchangers, consisting of five TEG modules, temperature profile and voltage value have been studied numerically and experimentally. The parametric study has been studied to understand the influence of various system parameters on energy harvesting performance TEG based heat exchanger. An average of 1.6 V is generated by each TEG module and heat exchanger consists of five TEG and an average of 8 V is generated continuously by the heat exchanger. Also, it is proved that the usages of steel foam with 90 % porosity in heat exchanger improves the heat transfer rate and maximize the output from 8 V to 24 V in heat exchanger.

Solar energy is an important power source. Given this, the development in the direction of converting solar radiation into electrical energy using holographic concentrators is of great importance. The purpose of the study is to determine the electrical characteristics of the solar cell inside the solar cells. To determine the electrical characteristics of the solar cell inside the photovoltaic panel, digital sensors HC-SR04, INA219 and the “Arduino Nano” microprocessor controller were used. The paper presents the results of experimental studies of a solar panel with a holographic concentrator and photovoltaic cells based on gallium arsenide. The high efficiency of converting solar energy into electrical power is shown when dispersing and focusing different wavelengths on a photocell. During elaboration of the obtained volt-ampere characteristics of solar photovoltaic conversion elements, which determine the output power of the photovoltaic panel, the high potential of the developed design of the photovoltaic panel has been revealed. The practical value of the study lies in the fact that with the help of a holographic concentrator it is possible to increase the efficiency of solar energy conversion.

In this paper the coupled differential equations governing the vibration of nonlinear electromagnetic energy harvesters are solved by the homotopy perturbation method. The amplitudes of odd harmonics of displacement of the magnet, coil current, and load voltage are derived up to the 5th harmonic. The frequency response of output power is plotted and it peaks at the linear mechanical resonance frequency. It should be noted that the optimum design of coil and load parameters, optimum electromagnetic coupling coefficient, and optimum vibration frequency of the magnet attached to a non-linear spring resulted in a stationary or non-transient vibration. Paying insufficient attention to this point and using typical parameters instead of optimum ones will result in transient vibration. The research aims at a rigorous semi-analytical method on a nonlinear problem which has previously solely investigated by numerical or experimental method.

The gas turbines (GTs), model M3142R/GE MS 3002, equipping the natural gas compression and crude oil pumping stations of SONATRACH’s pipeline transport of hydrocarbons activity are robust despite their dilapidation and state of service, but mediocre in terms of energy efficiency and power output. According to the manufacturer, for temperatures ranging from 15 to 47 °C, the efficiency of these machines drops from 26.78 to 25.03 % and their power drops from 11.29 to 8.9191 MW. It should be noted, however, that the number of these turbines exceeds 80 units and that their operation dates from 1974. The intention of this paper is to improve the gas turbine performance, mainly the efficiency and shaft power, by an evaporative cooling process of the compressor intake air. Besides, it is proposed to lower the upper limit power in periods of high temperatures to reduce gas consumption. To achieve these objectives, a mathematical model was implemented under Matlab R16, which reproduced the real behavior of these machines. It follows that this simulation made it possible to highlight relevant gains in terms of power and efficiency of the order of 1.361 MW and 3.4 % at a temperature of 47 °C.

In order to effectively monitor transmission lines and transmission towers, a number of different types of sensors are needed. A lot of times, these sensors along with the transmission lines and transmission towers are in inaccessible or hard-to-access areas and replacing their batteries is difficult. Yet they need consistent power supply. By harvesting energy directly from these medium and high voltage power lines, these devices can become self-sustaining while the overall system is more friendly to the environment. This paper presents a novel approach to high energy harvesting based on capacitive coupling between the power line and the harvesting line. This technique has several advantages, namely high output voltage, easy adjustment of coupling coefficient, and low cost. The validation and implantation of this harvesting system are proposed with the support of experimental results. This energy-harvesting ability of W and mA levels is achieved for the power line monitoring devices, with higher power output depending on the length and the size of the harvesting line.

Telecommand (TC) plays a crucial role in the success of high-altitude balloon experiments. Bose, Ray-Chaudhuri, Hocquenghem (BCH) codes are commonly employed to ensure reliable command operation. The Balloon Facility (BF) of Tata Institute of Fundamental Research (TIFR) uses a TC system based on BCH (31,16) coding technique, to control balloon and payload operations. This paper presents prototyping and implementation of TC encoder and decoder using Spartan 6 Field Programmable Gate Array (FPGA). The code is written in Very high-speed integrated circuit Hardware Description Language (VHDL). Simulation and synthesis are done using Xilinx ISE 14.7 design suite. Simulation results show the design is robust. The TC encoder is implemented in a commercial FPGA development board and the TC decoder is implemented in a specially designed FPGA board, successfully. This paper presents the salient features of the TC system in use and the implementation of the system using FPGA.

The expanding need for electricity has stimulated research and development of novel supply sources for energy production, conversion, and storage. Many studies are being done to increase the effectiveness of conversion systems as renewable energy is integrated into power networks on a larger scale. The global challenge is to minimize manufacturing costs and increase the use of sustainable resources. In this sense, photovoltaics is viewed as a particularly promising source due to the low cost of implementation and the wide range of applications it could be used for. This research focuses on the analysis, modeling, and simulation of a smart controller for a step-up converter that uses an artificial neural network (ANN) as a maximum power point tracking (MPPT) technique to provide maximum power. The proposed ANN-based algorithm is performed in Matlab/Simulink software, and its effectiveness has been demonstrated under varying climatic conditions.

The study provided a techno-economic optimization technique for acquiring the ideal battery storage capacity in conjunction with a solar array capable of meeting the desired residential load with high levels of self-sufficiency. Moreover, the viability of a proposed photovoltaic battery system was evaluated. With a resolution of one minute, the annual energy consumption, irradiance, and ambient temperature for 2021 have been measured. Simulations of a stationary economic model are run from 2021 to 2030. Based on the experimental evaluation of the annual energy consumption, which was 3755.8 kWh, the study reveals that the photovoltaic array with a capacity of 2.7 kWp is capable of producing an annual energy production of 4295.5 kWh. The optimal battery capacity determined was 14.5 kWh, which can satisfy 90.2% of self-consumption at the cost of energy $0.25/kWh. Additionally, two third-order polynomial relationships between self-consumption and net present costs and energy cost were established.

Solar energy is an excellent source of renewable power, but designing photovoltaic (PV) systems can be challenging without proper knowledge of solar radiation. The amount of energy received at the installation site plays a crucial role in determining the number of panels required to meet the electrical demand. For a given electrical demand, higher levels of received energy imply a reduced number of panels required, and vice versa. Hence, having knowledge of this irradiance is of paramount importance in the design and sizing of solar energy systems. The primary objective of this article is to provide an accurate estimation of electricity production in a PV installation when it is affected by shading. To achieve this, we performed calculations of the irradiation (direct and diffuse) received by our installation using the “Hottel” method, which integrates relevant local site parameters for our study. Subsequently, we study the impact of shading by conducting shade mask measurements on our installation. This enables us to obtain an accurate estimation of the irradiance received by the PV panels. The measurements include surveys of the geometry of obstacles and shade measurements taken at various times of the day. Additionally, a practical study of shading effects will be conducted using “close shading masks.” This method was applied to a 1.44 kW p PV installation located at the Faculty of Science and Technology of Settat (Morocco), where the output energy of PV panels was calculated. Finally, the effect of shading on the PV installation was quantified.

An overshot water wheel is considered as a low-cost and simple alternative for rural electrification. Hence, the aim of this study is to develop a noncomplex geometrical design of an overshot water wheel, namely, bottle blade overshot water wheel (BOWW), yet effectively operated for pico hydropower generation. The BOWW and hydro system were assessed at very low water head conditions, namely, 0.3, 0.4, and 0.5 m water head using a water test rig. According to the experimental results, the BOWW equipped with eight blades when operated at 0.5 m head produced significant mechanical power and electrical power up to 48.58 and 15.55 W. Analytically, the turbine with eight blades has 26.8–49.1% efficiency. Meanwhile, the effectiveness of four blades is between 5.66 and 28.96%. The results showed that eight blades performed well. Finally, it proves that, with a very low water head and low flow rate, the proposed system can perform and produce a significant power output for power generation.

The present work deals with energy-harvesting devices, which are useful in scavenging power using piezoelectric materials. Utilizing classical beam theory and classical plate theory, finite element modelling has been carried out to optimize the performance of output power of a cantilever beam and a flexible rectangular plate. Harmonic oscillations and base excitation will be the two different forcing functions used to drive the system. Based on this, numerical investigations of the performance of output power for the piezoelectric cantilever beam and flexible rectangular plate with different cases are considered. The present work is also useful for designing the piezoelectric cantilever beams and plates to extract maximum output power within the frequency ranges from 0 to 200 Hz. Numerical investigations on the piezoelectric cantilever beam and flexible rectangular plate with different cases reveal that the performance of output power is influenced by factors like load resistance, applications of with and without host structures, and different design parameters like unimorph, bimorph, embedded, line- and cross-type piezoelectric patch arrangements.

With the development of sustainable and energy-efficient buildings and cities, scavenging indoor light energy to power Internet of Things has become an increasingly attractive solution. However, the energy that can be harvested from an indoor light environment is limited compared to natural, outdoor sunlight, emphasizing the importance of efficiency of the entire energy harvesting system rather than that of individual harvesters. Power management circuitry plays a crucial role here but there has not been a system-level study for different power management schemes when connected to both harvesters and batteries whilst working under real lighting conditions. This study evaluates four integrated indoor light energy harvesting systems containing two distinctive types of photovoltaic cells connected to a switched capacitor (SC) and an inductor-based (IN) boost converter, respectively, as well as a Li-ion battery. Charging efficiencies of the entire systems, in addition to those of individual components, are assessed. Results suggest that for an indoor light energy harvesting system, although the IN converter tends to be cumbersome, it provides unbeatably high and stable battery charging efficiency across a broad range of light intensities compared to the SC converter even though the latter is specifically designed for low-power applications competing with the IN counterpart.

Wireless power transfer (WPT) has emerged as a groundbreaking technology that enables the transmission of electrical energy without the need for physical wires. WPT has the potential to revolutionize the charging infrastructure of electric scooters, providing a convenient and efficient method for charging the battery without using wires. This study provides an overview of the application of WPT in electric scooters, exploring the benefits, challenges, and future prospects of this technology. The study then delves into the underlying principles of WPT, including magnetic resonance and inductive coupling, which allow for efficient power transfer between the charging infrastructure and the scooter's onboard receiver. In conclusion, WPT holds great promise for electric scooters by enabling convenient and efficient charging methods. With ongoing advancements in technology and growing interest in sustainable transportation, WPT has the potential to transform the charging infrastructure of electric scooters, contributing to a cleaner and more convenient urban mobility ecosystem.

There is an increasing dependence on electronic devices in the battlefield, including equipment for communications, positioning and navigation, and combat situation awareness. These devices are usually powered by batteries because they are reliable and have good power density (energy per kilogram). Nevertheless, batteries are heavy and bulky, which reduces agility and increases fatigue of the ground troops. An alternative is to extract energy from renewable sources (like the sun and the wind) or harvest energy from the human body itself (like temperature gradients and walking). This article studies the feasibility of a piezoelectric generator, stimulated by human gait, to power electronic devices on the battlefield. Tests were carried out to measure the energy harvested from several piezoelectric ceramics placed under the sole of a soldier’s boot. Different materials and arrangements were tried to maximize the power, leading to the development of a prototype. The prototype was able to harvest 875  μ J {\rm{\mu }}{\rm{J}} on each step, on average. Walking 1 h, at a pace of 40 steps/min, leads to 2.1 J of energy, enough to supply a 3.3 V device consuming 10 mA for around a minute. These results are interesting for any situation that requires emergency power on the battlefield (e.g., trigger a device, call for rescue, acquire localization).

The relevance of the study of technical means for the production, management, application, and conversion of heat is conditioned by the rapid development of the energy sector, the global challenges of climate change, and the need for sustainable and efficient solutions for providing thermal energy, in connection with the need for energy efficiency, optimization of resource use, sustainability, and environmental compatibility, as well as technological progress and innovation. The purpose of this study is to investigate the problems associated with technical means for heat generation, identify shortcomings related to the production, use, and management of thermal energy flows, and consider technical devices for converting alternative types of energy into thermal energy to identify recommendations that would allow them to be used more efficiently. The main results of the study were the analysis of technical means and devices in the field of thermal power engineering and alternative energy, the main problems and shortcomings that lead to a decrease in the efficiency of the operation of technical means, heat loss, reduced comfort, and emissions of harmful substances into the environment, which can lead to a negative impact on human health, a decrease in quality, and other environmental problems.

In this article, we theoretically analyze the one-dimensional model of a piezoceramic energy harvester that uses piezoelectric transduction in the 3-3 mode to convert ultrasonic pressure waves into electrical energy. Our approach to this problem is new because we did not use impedance approach which is a common method in many other articles. Nonetheless, our solution accounts for loss of acoustic environment. Our goal here is to extract maximum power from output load. Based on our simulations, the frequencies that the acoustic strength peaks are as same as frequencies that the pressure at receiver side peaks, and between these frequencies, the resonance occurs at a frequency that the pressure at the receiver side has a maximum peak. We propose two boundary conditions for radiating acoustical waves. In this article for a square shape transducer with a thickness of 2.1 mm and length of 1.46 cm, the resistive output load gave the most power, in which its value for free-fixed and free-free boundary conditions are 13.75 W and 17.37 W respectively, and at output resistances of 8.51 Ω and 13.11 Ω respectively. The required acoustic strengths to produce these powers for free-fixed and free-free boundary conditions are 424.944 × 1 0 7 m 3 s 2 424.944\times 1{0}^{7}\frac{{{\rm{m}}}^{3}}{{{\rm{s}}}^{2}} and 129.977 × 1 0 8 m 3 s 2 129.977\times 1{0}^{8}\frac{{{\rm{m}}}^{3}}{{{\rm{s}}}^{2}} . The resonance frequencies are 9.13545 MHz and 14.3617 MHz respectively, and the pressures at receiver side in the distance of 5 cm from transmitter transducer are 623.968 MPa and 1382.39 MPa respectively.

Timely prediction of wind turbine states is valuable for reduction of potential significant losses resulting from deterioration of health condition. To enhance the accuracy of fault diagnosis and early warning, data collected from supervisory control and data acquisition (SCADA) system of wind turbines is graphically processed and used as input for a deep learning mode, which effectively reflects the correlation between the faults of different components of wind turbines and the multi-state information in SCADA data. An improved stacked autoencoder (ISAE) framework is proposed to address the issue of ineffective fault identification due to the scarcity of labeled samples for certain fault types. In the data augmentation module, synthetic samples are generated using SAE to enhance the training data. Another SAE model is trained using the augmented dataset in the data prediction module for future trend prediction. The attribute correlation information is embedded to compensate for the shortcomings of SAE in learning attribute relationships, and the optimal factor parameters are searched using the particle swarm optimization (PSO) algorithm. Finally, the state of wind turbines is predicted using a CNN-based fault diagnosis module. Experimental results demonstrate that the proposed method can effectively predict faults and identify fault types in advance, which is helpful for wind farms to take proactive measures and schedule maintenance plans to avoid significant losses.

The power system operation and control data are from a wide range of sources. The relevant data acquisition equipment is disturbed by the complex electromagnetic environment on the power system operation and control lines, resulting in data errors and affecting the application and analysis of data. Therefore, a power data integrity verification method based on chameleon authentication tree algorithm and missing trend value is proposed. Get 2D data from different sensors and place it in the space environment. After data conversion, convert heterogeneous data into the same structure, expand the scope of power data acquisition, and conduct power system operation and control node layout and integrity data acquisition; The chameleon authentication tree algorithm is used to deal with the heterogeneous information of the power data, and the true value of the data is determined in the heterogeneous conflict of the power data at the same site; Query the integrity data based on the power system operation and control positioning node, creatively calculate the missing trend value of power data, evaluate the importance of data integrity, obtain the priority of power data integrity verification, and complete the integrity verification of power data. The experimental results show that the optimal clustering number is 9.05, the distribution coefficient is 16.30, the absolute error of validity analysis is 2.80, all test indicators are close to the preset standard, and the trend of the validation curve is close to the trend of the set demand covariance curve. Ensuring the integrity of power data and determining the important indicators of power lines are more conducive to the safe and stable operation of the power data center.

The times are progressing. Facing the increasing number of electric vehicles, they use power batteries as energy storage power sources. As a core component of electric vehicle, the drive motor is related to the normal operation of the vehicle. If the driving motor fails, passengers may be irreversibly hurt, so it is very important to diagnose the driving motor of electric vehicle. This paper mainly analyzes the faults of electric vehicles, and makes use of diagnostic signals to diagnose the faults. A novel fault diagnosis method of automobile drive based on deep neural network is proposed. In this method, CNN-LSTM model is constructed. Firstly, the vibration signals are transformed into time-frequency images by fast Fourier transform, and then the time-frequency images are input into the proposed model to obtain the fault classification results. In addition, CNN, LSTM and BP neural network are introduced to compare with the methods proposed in this paper. The results show that CNN-LSTM model is superior to the other three models in the fault diagnosis of automobile drive, reaching 99.02 % of the fault accuracy rate, showing excellent fault diagnosis performance. And when the same learning rate is used for training, the rate of loss reduction is obviously better than that of the other three types of vehicle drive fault diagnosis method based on CNN-LSTM.

In order to improve the practical effect of the power environmental protection platform, this paper combines the big data technology to develop and design the power environmental protection platform. In this paper, a power factor correction (PFC) and resonant half-bridge joint controller is used to combine the traditional two-level topology into one-level topology. Moreover, this paper adopts a fixed frequency half-bridge LLC resonant converter with a simple control circuit to obtain a stable resonant half-bridge controller with a fixed output voltage. The choice of this overall power topology architecture can not only meet the design requirements, save costs and simplify the control of the circuit, but also improve the efficiency of the whole machine and the performance of the power environmental protection platform. The experimental research shows that the power environmental protection platform based on big data proposed in this paper can effectively improve the effectiveness of power environmental protection strategies.

This paper develops a coupling model of the relationship between chemical reaction, temperature and stress/strain for Li (Ni 0.6 Mn 0.2 Co 0.2 ) O 2 cathode materials. With the process of reaction, the concentration of electrolyte salt changes rapidly at the beginning of diffusion and tends to dynamic equilibrium. The concentration of electrolyte LiPF 6 in electrode materials diffuses from bottom to top with the process of lithium intercalation. In the process of Li-ion intercalation, the temperature rise of porous electrode materials increases sharply at first, then decreases and then increases slowly. The rate of temperature rise in the cathode material increases with the temperature decreases. The volume of electrode material deformed with the expansion along the X -axis and the radial bending along the Y -axis. And the law of stress variation with time is consistent with the temperature-time curve. By the stress-strain distribution nephogram, it is found that the position where the maximum stress is located at the edge of the upper surface, and which is most vulnerable to failure.

The significance of this study is underscored by the immense potential of binary power plants in the contemporary world. These plants have a pivotal role to play in supplying heat to homes, facilitating greenhouse heating, and supporting air conditioning systems. The purpose of the study is to provide recommendations on eliminating errors in the processes of improving and implementing geothermal plants and analysing their functioning during electricity generation. The analytical method, classification, functional, statistical, synthesis, and others should be noted among the methods used. The features of geothermal plants in Kazakhstan were noted, their differences were analysed, and errors that are made during the operation of power plants to increase the energy efficiency of consumers and the causes of errors were analysed. Uncertainties in the development and their impact on the functioning of geothermal power plants were identified. The practical value lies in the application of the identified results, solving errors in the development and implementation of a binary power plant to improve the energy efficiency of consumers, the reliability of the use of geothermal plants in the region, considering various factors, which will help provide recommendations for the appropriate use of the mechanism.

To control water quality and seawater desalination dosage, modeling the coagulation process of saltwater is crucial. With a focus on the features of seawater coagulation with a long lag, a machine-learning sequence-based modeling approach is suggested. The link between influent and effluent turbidities, flow rates, flocculant and coagulant dosages, and other parameters is modeled using structured units such as a gate recurrent unit encoder and a linear network decoder. The model’s validity is confirmed by numerical experiments based on real operating data, which also offer a solid foundation for managing flocculant and coagulant assistance reduction.