Energy Consumption Rate Research Articles

Predictive machine learning for optimal energy management in sustainable transportation systems

This study explores the use of predictive machine learning techniques to enhance energy management in sustainable transportation systems, with a specific emphasis on electric vehicles (EVs). The analysis of EV specifications has shown a wide variety of battery capacities, ranging from 55 kWh to 75 kWh. These capacities have a direct impact on the energy storage capacity and the possible driving range of the vehicles. The range of vehicle weights, ranging from 1400 kg to 1700 kg, emphasized the possible effects on energy consumption rates and overall efficiency. The performance capabilities were shown with maximum speeds ranging from 160 km/h to 200 km/h. The energy consumption rates ranged from 0.18 kWh/km to 0.25 kWh/km, suggesting different levels of efficiency. An analysis of energy management data revealed that the lengths traveled varied from 180 km to 220 km, while the average speeds ranged from 50 km/h to 60 km/h. These variations directly affected the rates at which energy was used. The vehicles exhibited higher efficiency metrics by attaining energy consumption rates of 4.0 km/kWh to 5.6 km/kWh. The analysis of ambient variables indicated temperature fluctuations ranging from 20°C to 30°C, as well as a variety of terrain types that impact driving conditions and energy requirements. Predictive machine learning models demonstrated high accuracies, with Mean Absolute Error (MAE) values ranging from 0.13 to 0.18 kWh/km, Root Mean Squared Error (RMSE) values ranging from 0.18 to 0.22 kWh/km, and R-squared (R^2) scores ranging from 0.80 to 0.88. These results emphasize the need of using predictive machine learning to estimate energy consumption, optimize energy management systems, and address sustainable transportation concerns in order to improve the efficiency and sustainability of electric vehicles.

Anaerobic Co-Digestion of Vegetable Waste with Cattle Dung and Fruit Waste for Biogas Generation

India is a developing country and its rate of energy consumption is increasing with economic and industrial development. Most of the countries are dependent on non-renewable energy sources that have many limitations and demerits. The use of renewable energy resources is beneficial from socioeconomic and ecological point of view that can help to achieve sustainable development goals. India is agro-based country and produces huge quantities of organic waste per day. The disposal of these wastes by unscientific treatment methods causes serious environmental pollution. Anaerobic digestion and co-digestion are considered as ecofriendly technology of energy generation and waste disposal. The co-digestion is more beneficial over anaerobic digestion and has several advantages. The present work was undertaken to study anaerobic co-digestion of vegetable waste with cattle dung and fruit waste with the objectives of treating the waste to generate biogas and to decrease its environmental pollution potential.

Solar To Hydrogen Production Barriers and Opportunities in Oman: A Case Study in The Dhofar Region

The energy demand has increased rapidly worldwide due to the depletion of fossil fuels. Recently, the rate of energy consumption has become unsustainable, providing a strong incentive for many countries to pursue renewable energy sources. By 2030, Oman's national energy strategy aims to generate 20% of its electricity from renewable sources. In the same context, Oman has the target to join the front rank of countries that aim to capitalize on their renewable resources to produce green hydrogen for export to the global market and domestic utilization. This study investigates the prospects for creating green hydrogen using solar energy in Oman's Dhofar region. The key obstacles to solar-to-hydrogen generation are discussed in this paper.

Optimal consumer capacity investment in solar panel system under supply and demand uncertainty

Our paper analyzes the optimal capacity investment in solar panels system for consumers. During the daytime, solar panel system absorbs energy from the sun and supplies the energy generated to the building structure. Our model takes into consideration the variations in the daily consumption of electricity and the variations in the daily available sun energy. We model these variations in our paper as uncertainty in energy demand and uncertainty in energy supply. Excessive usage of electricity that is beyond the energy generation of the solar panels are bought at a higher price from the utility company than the payment received from the utility company for excess energy sold to the grid. We analytically solve for the optimal quantity of solar panels to purchase and install. Our paper fills the research gap in quantifying the impact changes in solar energy yield rate, consumption, and sell-back rate has on the consumer’s optimal investment decision in solar panels. We find that the optimal quantity of solar panels increases with the cost of energy during the daytime and payment for excess energy sold to the grid. Interestingly, when solar yield increases, the optimal solution only increases initially, and then it will eventually decrease. Furthermore, our analytical models provide consumers with a decision support system to determine the optimal number of solar panels to purchase and install while taking into consideration the random yield of solar panels, variations in energy consumption, and potential for sell back of excess unused energy generated under complex billing structures from the utility company. Our mathematical models are adaptable to policy changes such as rebates and purchase and sell back rates for electricity. Our numerical study validates the mathematical models and further analyzes the impact changes in solar energy yield rate, energy consumption, and sell-back coefficient have on the consumer’s capacity investment decision in solar panels. Our numerical studies find that the lower the reliability factor of solar yield, the more impact the daytime energy cost has on the optimal quantity. When the sell-back coefficient exceeds a certain threshold, the optimal quantity of solar panels increases exponentially.

Evaluating the contribution of demand response to renewable energy exploitation in smart distribution grids considering multi-dimensional behavior-driven uncertainties

Demand Response (DR) is recognized as an efficient method for reducing operational uncertainties and promoting the efficient incorporation of renewable energy sources. However, since the effectiveness of DR is greatly influenced by consumer behavior, it is crucial to determine the degree to which DR programs can offer adaptable capability and facilitate the use of renewable energy resources. To address this challenge, the present paper proposes a methodological framework that characterizes the uncertainties in DR modeling. First, the demand-side activities within DR are segmented into distinct modules, encompassing load utilization, contract selection, and actual performance, to enable a multifaceted analysis of the impacts of physical and human variables across various time scales. On this basis, a variety of data-driven methods such as the regret matching mechanism is introduced to establish the analysis model to evaluate the impact of various factors on DR applicability. Finally, a multi-attribute evaluation framework is proposed, and the effects of implementing DR on the economic viability and environmental sustainability of distribution systems are examined. The proposed framework is demonstrated on an authentic regional distribution system. The simulation results show that compared to scenarios without considering uncertainty, the proposed method can fully consider the impact of DR uncertainty, thereby enabling a more realistic assessment of the benefits associated with DR in enhancing renewable energy accommodation for smart distribution grids. From the comparative analysis of new energy installation scenarios, with the integration of photovoltaic and wind power into the system, the presence of DR can increase the renewable energy consumption rate by 6.39% and 37.44%, respectively, and reduce the system operating cost by 1.37% and 3.32%. Through the comparative analysis of different load types, when DR is a shiftable load and a two-way interactive load, the renewable energy consumption rate increases by 20.57% and 26.35%, and the system operating cost decreases by 2.12% and 4.68%. In this regard, the proposed methodology, hopefully, could provide a reliable tool for utility companies or government regulatory agencies to improve power sector efficiency based on a refined evaluation of the potential for demand-side flexibility in future power grids incorporating renewable energies.

Enhancing electric vehicle efficiency through model predictive control of power electronics

This study examines the improvement of electric vehicle (EV) economy by using Model Predictive Control (MPC) in power electronics, with the goal of optimizing system performance. Experimental assessments done on different battery parameters have identified a spectrum of capacities, ranging from 55 kWh to 75 kWh, and voltages, ranging from 380V to 450V, that impact the total energy storage and power production capabilities. The efficiency percentages recorded in the battery systems ranged from 90% to 95%, suggesting differences in energy losses throughout the operations of charging and discharging. Furthermore, examinations of power electronics control configurations highlighted the significance of PWM frequencies (varying from 8 kHz to 12 kHz) and modulation indices (0.75 to 0.85) on the efficiency of power conversion. The results indicated efficiency rates ranging from 94% to 97%, emphasizing the efficacy of MPC-based techniques in improving power flow. The assessment of electric vehicle (EV) performance parameters demonstrated driving ranges ranging from 140 km to 180 km, with energy consumption rates ranging from 50 kWh to 60 kWh. The efficiency metrics ranged from 2.5 km/kWh to 3.0 km/kWh, and were directly affected by the battery properties and improvements in power electronics. Moreover, there was a little change in the link between temperature variations (ambient temperature ranging from 23°C to 29°C and battery temperature from 32°C to 40°C) and efficiency. This highlights the system's sensitivity to external variables. In summary, this relationship between battery characteristics, power electronics control, and environmental conditions in determining the efficiency of electric vehicles (EVs). The results emphasize the importance of customized setups and control techniques based on model predictive control (MPC) in optimizing energy use and increasing the distance electric cars can travel. These findings provide valuable knowledge for the development of sustainable transportation solutions in the electric vehicle industry.

Formation process and characteristics of an amorphous SiO2 ceramic coating on 6061 aluminum alloy by plasma electrolytic oxidation in organosilicon electrolyte

An amorphous silica ceramic coating with thicknesses exceeding 100 μm (adjustable thickness) was prepared on 6061 aluminum alloy by plasma electrolytic oxidation in organosilicon electrolyte. To investigate its formation process and structural characteristics, the digital microscope system, SEM, X-ray diffractometer and microhardness tester were used to characterize morphology, structure and hardness at different voltages and times. The results show that it thickens rapidly after the voltage is raised to 480–500 V, and its surface begins to roughen and the micropores appear to enlarge. In organosilicon electrolyte, unlike conventional electrolytes, the coarse Al–Fe–Si second phase particles in the matrix do not negatively affect the PEO treatment. The produced coatings increase the surface hardness of 6061 aluminum alloy by more than 6 times and are stable in common acid solutions such as HCl and HNO3. Furthermore, the energy consumption rate of PEO treatment can be significantly reduced to 0.24–0.31 kJ cm−2 μm−1. The potentiodynamic polarization curves measured in 1 mol L−1 HCl solution show that the ceramic coating can reduce the corrosion current density of 6061 aluminum alloy from 3.74 × 10−2 A cm−2 to 2.24 × 10−6 A cm−2. And its corrosion resistance can be further improved by adding a 2nd low-voltage PEO treatment.

Optimized Scheduling of an Integrated Energy System with an Electric Truck Battery Swapping Station

Currently, the focus of integrated energy system scheduling research is the multi-objective’s optimized operational strategies that take into account the economic benefits, carbon emissions, and new energy consumption rates of such systems. The integration of electric trucks with battery charging and swapping capabilities, along with their corresponding battery swapping stations, into an integrated energy system can not only optimize system operation, but also reduce investment costs associated with building energy storage equipment. This study first constructs an operational model for the electric trucks, as well as an electric truck battery swapping station, of the flexible charging and discharging; then, an optimized scheduling model of an integrated energy system is proposed, including an electric truck battery swapping station and using stepped carbon trading. On the basis of meeting the charging and battery swapping needs of electric trucks and coordinating the system’s electrical, thermal and cooling energies, the goal of the optimized scheduling model is to reduce the system’s carbon emissions, improve its economics, and optimize its ability to absorb new energy. Finally, a simulation model of the integrated energy system including an electric truck battery swapping station is built on the MATLAB platform, and commercial software package CPLEX is used to solve the model. In the calculation example, compared to the integrated energy system of disorderly charging and battery swapping of electric trucks and electric truck battery swapping stations, the proposed optimized model of the integrated energy system with the flexible charging and discharging of electric trucks and electric truck battery swapping stations reduces the operating costs by CNY 819, reduces carbon emissions by 414 kg, improves the utilization rate of wind and solar power by 0.3%, and fully utilizes wind and photovoltaic power. Therefore, the rational dispatching of the electric trucks and their battery swapping stations with flexible charging and discharging mentioned in this article can effectively optimize system operations.

A quantitative study between HPGR and cone crusher aided ball mill grinding: mathematical modeling by evaluating the possible microfracture effect produced by HPGR technology and cone crusher

High Pressure Grinding Rolls (HPGR) have been used in the mining industry for decades. However, there are limited quantifications of the particle properties after comminution. Furthermore, the influence of microcracks in grinding provided by this technology has not been extensively quantified. In the recent work, there were two comminution paths tested: 1 (Jaw crusher + cone crusher + ball mill) and 2 (Jaw crusher + HPGR + ball mill). The possible weakening effect aiding ball mill grinding due to microcracks of HPGR path was shown via specific energy, fines generation and breakage rate measurements. To achieve a quantification about the impact of microcracks and the high rate of reduction rate of HPGR technology, first the product was reconstructed using Rosin Rammler's Weibull double formula and the similar particle size distribution was obtained by a conventional cone crusher. By this way the feed size distribution to the grinding stage remained constant regardless of the type of crushing process (HPGR or cone crusher). The results showed that the microfractures generated by the HPGR technology influence the specific energy consumption, fines generation and breakage rates. Ball mill after HPGR consumed 12.46 kWh/t of specific energy, however ball mill after cone crusher consumed 14.36 kWh/t of specific energy. The experimental methodology proposed in this paper maintains a consistent feed size range (-1500 to +41.31 µm) to show that the size reduction observed in the sample undergoing HPGR grinding is not the primary factor contributing to reduced energy consumption and increased fines generation. Instead, it is predominantly associated with the microfractures generated through the compression in HPGR technology; the energy reduction (optimization) of a grinding path is shown in the study.

Enerji Verimli Aydınlatma Tasarımı: Farklı Pencere Boyutlarında Optimum Gün Işığı Kullanımı Üzerine Bir Araştırma

In recent years, with the frequently discussed concept of sustainability, designers have been increasingly demanded to improve spatial comfort conditions. The growing emphasis on energy efficiency in design has led designers to consider these issues at earlier stages of the design process. Daylight, seen as a clean, uninterrupted energy source and a cost-effective alternative to artificial lighting, also ensures visual comfort for individuals due to its good color rendering. Despite all these well-known benefits, design criteria have not been established to reduce the energy consumption rate caused by artificial lighting while taking into account the factors affecting daylight, an important input. This study presents an investigation aimed at achieving energy savings in lighting by using the ideal window concept and other parameters to optimally benefit from daylight. The study has been applied under cloudy sky and deep room conditions, which represent the worst-case scenarios. As an alternative to time-consuming mathematical calculations, the Velux Daylight Visualizer lighting simulation program was used to create three-dimensional designs for horizontal, vertical, square, and roof windows separately, and the effects of these windows on the daylight factor were analyzed. The impact of different furniture colors in the interior space was also examined. Following the investigations, it was observed that roof windows produced more daylight compared to others. However, since roof windows cannot be used in multi-story buildings, a comparison was made between horizontal, vertical, and square windows, and it was concluded that horizontal windows placed close to the upper wall were more efficient than the others. In addition, it was observed that lighter-colored furniture, among the light and dark furniture, produced more daylight compared to the other.

Narrow band of vehicular things communication system using hybrid pelican-beetle swarm optimization approach for intelligent transportation system

Congestion is caused by the continually expanding number of vehicles worldwide. Intelligent Transportation Systems (ITSs) could be used to build a system that efficiently uses the existing infrastructure and current technological advancements. Several Vehicular applications use the restricted vehicle battery in V2X systems, and a key concern is communication secrecy. Earlier research has focused on channel measurement, autonomous piloting, high-speed transmissions, secretive communications, and QoS analysis but battery-limited V2X has received far less attention. Therefore, resolving the abovementioned complications in the current model is imperative. Thus, a new V2X communication model is developed based on NB-IoT (NarrowBand Internet of Things) approaches. NB -IoT is utilized in the V2X communication model to offer low-cost, high-range, and minimal power to the communication environment. The objective of the proposed NarrowBand of Vehicular Things Communication (NBVTCS)System is to analyze the performance metrics of vehicular communication including energy efficiency rate with different SNR, bit error rate with different vehicular positions, and overall throughput of the system. The simulation was carried out to attain an effective energy efficiency rate, the system's transmit power, bit error rate, and overall system throughput. The proposed vehicular architecture also optimized the abovementioned vehicular metrics with the help of the proposed Hybrid Pelican Beetle Swarm Optimization (HPBSO) approach to achieve a higher accuracy in communication parameters. Finally, the simulation outcome demonstrates that the developed vehicular model is achieved with a minimal energy consumption rate and maximum throughput and also compares the proposed HPBSO technique with other optimization techniques including DOX, EFO, POA, and BSO.

KATI ATIK ARITIMINA KISA BİR BAKIŞ VE TÜRKİYE'DEKİ GÜNCEL UYGULAMALAR

High rates of energy and goods consumption, combined with increasing population growth and high living standards, lead to the ever-increasing production of solid waste. The amount of solid waste generated today has reached a level that poses serious threats to the environment and the sustainable management of the country's economies. Although action plans are being prepared and implemented by countries, unions and institutions for the environmentally friendly and sustainable management of solid waste, it is seen that the threat still exists for the near future. Within the scope of solid waste, management of household waste is undoubtedly one of the most important issues today. The MSW EU average for 2021 reached 530 million tons. Similarly, a total of 104.8 million tons of waste was generated in Turkey in 2020, 32.3 million tons of which were domestic waste. Although, today, the most common method of solid waste control globally is storage in open or controlled landfills, it is seen that Thermal conversion, MTB or Liquefaction applications, which enable energy production especially within the cyclical economy and production model, are increasingly increasing.
 The aim of this compilation study, in which global and country-based statistics are briefly presented, is to raise awareness of the increasing threat.

Evaluation of facade features in green building certified office buildings in terms of energy efficiency

The energy crisis in the world and reaching the point of depletion of resources have pushed the construction industry to seek the use of renewable energy resources. The sustainability approach that comes to the fore with this has gained an important place in the construction sector as well as in all other sectors. The construction of office buildings, which have a high energy consumption rate among the building groups, within the framework of sustainability principles is a result of this search. From this point of view, the aim of this study is to evaluate the facade features of sustainable office buildings with green building certificate within the scope of energy efficiency and to reveal the current practices. Within the scope of the study, 20 office buildings located in the world and in the literature were analyzed in detail in terms of their facade features. These analyzes are grouped under the titles of building envelope, facade material, integration of active and passive systems. In the light of the data obtained, it has been revealed that sustainable office buildings have facade applications for the use of renewable energy sources.

THE INFLUENCE OF POPULATION AGING ON ENERGY CONSUMPTION QUANTITY MECHANISM RESEARCH

Abstract The adjustment of population structure and household size is one of the important factors affecting the amount of household energy consumption. Influenced by the deepening of aging degree and the acceleration of aging development, the amount of energy consumption has also produced a relatively obvious change. Based on the provincial panel data from 2008 to 2017 in China, we used fixed effects and random effects models for regression analysis to further analyze the spatial differences and trends of energy consumption quantity distribution, and explore the mechanism of population aging’s influence on energy consumption quantity. In addition, we explore the path of population aging affecting energy consumption through intermediary effect analysis. Besides, we also analyzes the aging rate of population, energy consumption and environmental protection policies in different countries. It is found that, under the premise of controlling the influence of other variables, population aging rate has a negative impact on the amount of energy consumption, which is different between urban and rural areas. The increase of population aging rate in urban areas may lead to the increase of energy consumption, while the increase of population aging rate in rural areas may lead to the decrease of energy consumption. Household size and household consumption level are important intermediary variables between population aging and energy consumption. Population aging can indirectly affect energy consumption through affecting household size and household consumption level.

Research on the Estimation Model of Energy Consumption Capacity for Reinforced Concrete Components with Axial Force

The research group utilized the estimation model of energy consumption capacity for reinforced concrete components without axial force to assess the energy consumption capacity of 92-reinforced concrete components from the PEER database, which were subjected to axial force and bending. The study also examined the impact of design parameters, including longitudinal reinforcement ratio, transverse reinforcement ratio, axial compression ratio, and shear-span ratio, on the estimation results. The research findings revealed that when applying the estimation model of energy consumption capacity for reinforced concrete components without axial force to calculate the energy consumption capacity of reinforced concrete components with axial force, there was a significant deviation rate in the estimation of cumulative energy consumption. The relationship between the deviation rate of cumulative energy consumption and longitudinal reinforcement ratio, axial compression ratio, and shear-span ratio remained unclear. However, a more apparent linear relationship was observed with the transverse reinforcement ratio. By conducting a quantitative analysis of the transverse reinforcement ratio, the researchers proposed an modified estimation model of energy consumption capacity for reinforced concrete components with axial force. Nonetheless, the accuracy of the modified estimation model was found to be high within the range of 0–250,000 kN mm of cumulative energy consumption. For cumulative energy consumption exceeding 250,000 kN mm, further experimental and theoretical research is still required to enhance the reliability of the modified estimation model.

Condensation of refrigerant R450A inside a mini-channel of rectangular cross section with an internal longitudinal groove

The increase in jeopardizing the natural life and environmental resources together with high rates of energy consumption are still in focus of international agencies and scientific communities. For this issue, global awareness has been oriented to uncover alternatives to harmful species and to magnify effectiveness of thermal systems. For the present study, the refrigerant R450A was investigated as a potential substitute to R134a during condensation inside two mini-channels which are rectangular cross section channel (SRC) and a modified channel (MRC). The latter was characterized by an internal longitudinal groove. Wall subcooling, vapor superheat, and mass velocity were considered while the condensing temperature was kept constant. Numerical CFD simulation was realized for the condensation inside the channel using ANSYS-CFX 15.0 with additional user defined expressions to describe condensate layer thickness inside the channel, which in turn was utilized for the condensation heat transfer coefficient (HTC). Predicted data was compared with experimental one in terms of HTC and flow patterns. The predicted data of HTC showed an average deviation by about 6.6% compared to experimental data for R134a.The refrigerant R450A resulted in lower condensation HTC than R134a. The MRC resulted in an average enhancement in the HTC by about 55.7% and a reduction in the pressure drop by about 10.4% compared to the SRC. The enhancement of the MRC in HTC was remarkable at high degree of superheat, low mass velocity, and low wall subcooling. Accordingly, the novel MRC represents a successful potential design for condensation of refrigerants in mini-channels.

Low‐carbon economic optimal operation strategy of rural multi‐microgrids based on asymmetric Nash bargaining

AbstractThe multi‐microgrids operation can greatly improve the proportion of renewable energy integration and power reliability of rural microgrids through energy trading between adjacent microgrids. Therefore, this paper proposes an optimization method for the low‐carbon economic operation of rural microgrids which contain wind power, photovoltaic, biogas, and other common rural renewable energy sources. Using the asymmetric Nash bargaining model which can form the non‐linear energy mapping function to quantify the bargaining power of each microgrid to establish the multi‐microgrids energy trading model, and the non‐convex trading optimization problem is equivalently transformed into two convex optimization subproblems, subproblem 1 is microgrids alliance costs containing the emission costs, and subproblem 2 is cooperative benefits distribution. Then, the accelerated Alternating Direction Method of Multipliers (ADMM) method is used to solve subproblem 1 and subproblem 2, respectively, and the privacy of transaction information is also protected. The results show that: compared with the single‐microgrid operation, the combined operation of rural multi‐microgrids with biogas can greatly improve the renewable energy consumption rate, reduce carbon emission, and improve the profit income of the alliance and each microgrid. Meanwhile, the accelerated ADMM algorithm used can greatly improve the solution speed.

Energy consumption and wear rate of diamond beads during operation of a diamond wire saw

Energy consumption and wear rate of diamond beads during operation of a diamond wire saw

Operation optimization of electricity-steam coupled industrial energy system considering steam accumulator

Steam system plays a crucial role in industrial energy usage. Steam generation in the industry domain is transferring from coal-fired or gas-fired plant/boiler to green-electricity steamer for net-zero purpose. The increasing coupling of the electricity-steam energy system in the industry domain, called electricity-steam coupled industrial energy system (ES-IES), brings enormous challenges to the system day-ahead operation optimization due to the uncertainties of renewable generation and the nonlinearities of the system mathematical model. Therefore, this paper introduces the steam accumulator (SA) into the steam system to mitigate the renewable fluctuations, proposes an isothermal linearization method of the steam flow model, and optimizes the operation based on an interactive iteration scheme between optimization and simulation for the global optimum and a balance between accuracy and speed. Results show that considering the storage characteristics of SA and the complementary coordination of electricity and steam through coupling equipment can significantly optimize the operation of ES-IES with an increase in the renewable energy consumption rate by 23.81 % and a decrease in the total operating cost by 11.39 %. The static payback period for the investment of EB and SA is 7 years, indicating a favorable application prospect.

ANALYTICAL REVIEW OF MODERN NON-CONVENTIONAL ENERGY SOURCES

The structure of the world energy economy has developed in such a way that 80 % of the electricity consumed is obtained by burning fuel at power plants, where the chemical energy of the fuel is first converted into heat, heat into work, and work into electricity. Hydropower also provides a significant percentage (about 15 %), the rest is covered by other sources, mainly nuclear power plants. Human needs are growing, there are more and more people, and this causes gigantic volumes of energy production and growth rates of its consumption. Today, traditional energy sources (various fuels, hydro resources) and technologies for their use are no longer able to provide the required level of energy availability of society, because these are non-renewable sources. And although the explored reserves of natural fuels are very large, the problem of depletion of natural reserves at the current and projected rates of their development is moving into a real and near future. Even today, a number of fields, due to depletion, turn out to be unsuitable for industrial development, and for oil and gas, for example, one has to go to hard-to-reach, remote territories, to ocean shelves, etc. The forecast proves that while maintaining the current volumes and growth rates of energy consumption at 5–7 %, fossil fuel reserves will completely run out in 70–150 years. Another factor limiting a significant increase in energy production through fuel combustion is the ever-increasing environmental pollution from energy production waste. These wastes are significant in mass and contain a large number of various harmful components. This is where acid rain comes from, the disappearance of ozone, the poisoning of farmland and water bodies. Moreover, nature is no longer able to process these pollution and self-repair by natural physico-chemical and microbiological methods.
 In nuclear power, environmental problems of a different kind arise. They are associated with the need to exclude the ingress of nuclear fuel into the environment and the reliable disposal of nuclear waste, which, with the current level of development of technology and technology, is associated with great difficulties.
 No less harmful is the thermal pollution of the environment, which can lead to global warming of the Earth's climate, melting of glaciers and rising sea levels.
 In the light of the above, the widespread practical use of non-traditional and renewable energy sources, which are also environmentally friendly and do not pollute the environment, is becoming increasingly relevant.
 The article briefly presents an analytical review of modern non-traditional and renewable energy sources.