Power Engineering Research Articles

Utility-Scale Grid-Connected Microgrid Planning Framework for Sustainable Renewable Energy Integration

Microgrids have emerged as a crucial focus in power engineering and sustainable energy research, with utility-scale microgrids playing a significant role in both developed and developing countries like the Philippines. This study presents a comprehensive framework for utility-scale microgrid planning, emphasizing the sustainable integration of renewable energy resources to the distribution grid. The framework addresses the operational modes of grid-connected and islanded microgrids, emphasizing the seamless transition between these modes to ensure a continuous power supply. By leveraging local distributed energy resources, the microgrid aims to reduce dependence on the main transmission grid while enhancing resilience and reliability. The proposed planning framework not only eases the economic burden of constructing renewable energy sources but also aids distribution utilities in maximizing local resources to achieve sustainable energy goals. Through a detailed network analysis and modeling, the framework provides a robust foundation for optimizing the energy mix and enhancing the overall system performance. This research contributes to advancing microgrid technology as a key driver towards achieving UN Sustainable Development Goals, particularly in promoting clean and affordable energy access.

Evaluation of green residues management of selected grape varieties

The paper presents the possibilities of energy management of residues from the cultivation of grapes of the ‘Regent’, ‘Rondo’ and ‘Seyval Blanc’ cultivars. The research was conducted in southeastern Poland in the Sandomierska Upland in 2022. The aim of the research was to demonstrate the influence of grape variety on yield capacity in relation to the extraction of biomass residues in the form of leaves. An attempt was made to identify the variety that is characterised by obtaining the most effective and average parameters, i.e. yield size and quality, leaf mass and surface area, and their impact on energy and fuel parameters. The study analysed the following crop parameters, i.e. number and mass of grapes, number and mass of berries; leaf quality parameters, i.e. mass including petioles and area. An energy assessment in Laboratory in Department of Power Engineering and Transportation was carried out by performing proximate and ultimate analysis and estimating emission factors and volumetric composition of exhaust gas. The study showed that the material with the highest energy potential was characterised by ‘Regent’, while the lowest potential was shown for ‘Rondo’. Grapevines of the ‘Rondo’ cultivar were characterised by the highest obtained biomass among the evaluated varieties. The research showed that the most effective in practical cultivation is the use of the Regent variety, which was characterised by the average parameters of the obtained yield and growth values, and the highest fuel energy potential.

Evaluation of Advanced Biofuels in Internal Combustion Engines: Diesel/Fusel Oil/Vegetable Oil Triple Blends

In this research work, the feasibility of using fusel oil, a by-product of the sugar–alcohol industry, as an LVLC solvent in blends with straight vegetable oils (SVOs) and diesel was investigated. Concretely, diesel/fusel oil/sunflower oil (D/FO/SO) and diesel/fusel oil/castor oil (D/FO/CO) triple blends were prepared and characterized by measuring the most important physicochemical properties, i.e., viscosity, density, cold flow properties, flash point and cetane number. An appreciable improvement in cold flow values has been achieved with triple blends, without compromising properties such as calorific value and cetane number. Likewise, the triple blends meet the viscosity and density requirements specified by the European quality standard EN 14214 and the American standard ASTM D6751. After characterization, the triple blends were used on a diesel engine, evaluating different parameters such as power output, opacity, exhaust emissions (CO and NOx) and consumption at different engine loads. The results indicate that as the biofuel content in the blend increases, engine power decreases while fuel consumption rises. Nevertheless, the values obtained with D/FO/CO are better than those for D/FO/SO and are also very similar to those of fossil diesel. Regarding opacity values and NOx emissions obtained with the utilization of the triple blends, they are lower than those produced by diesel. However, in the case of CO emissions, it depends on the type of oil used, with the samples prepared with castor oil exhibiting the best results.

Analysis of Energy Efficiency Parameters of a Hybrid Vehicle Powered by Fuel with a Liquid Catalyst

A notable trend in the modern automotive market is the increased interest in hybrid cars. Hybrid cars combine a standard internal combustion engine with an electric motor solution. Research into increasing the energy efficiency of a conventional unit while meeting increasingly stringent exhaust emission standards is becoming a key postulate in this matter. This article discusses an analysis of modifying the fuel used by hybrid vehicles using the example of a selected drive unit equipped with a spark-ignition engine. This effect was tested after the Eco Fuel Shot liquid catalyst was added to the fuel. The research process was carried out in two stages, as follows: in road conditions using the Dynomet road dynamometer; and on the V-tech VT4/B2 chassis dynamometer. Tests were carried out to replicate road tests with a catalytic additive in the fuel. A mathematical model was created and the following energy efficiency parameters of the hybrid vehicle were calculated: the torque of the internal combustion engine, electric motor, and generator; the rotational speeds of the internal combustion engine, electric motor, and generator; the power of the internal combustion engine, electric motor, and generator; the equivalent fuel consumption of the electric motor and generator; the fuel consumption of the internal combustion engine, electric motor, and generator; and the mileage fuel consumption of the internal combustion engine, electric motor, and generator. The results of the tests made it possible to identify the benefits of using the tested liquid catalyst on the operation of the drive system of the analyzed hybrid vehicle. This research will be of benefit to both the demand side in the form of users of this category of vehicles, and the supply side represented by the manufacturers of power units.

Analysis of Thermal Isotropy of Parallelepiped Shape of Bronze Samples for Mechanical Engineering Applications

Objective: The need to find out whether the specimens are ‘thermally thin’ or not is the basis for applying the law of conservation of energy or the Fourier differential equation of heat conduction in finding the time dependence of the specimen temperature. The aim of this study is to find out the thermal field distribution in a parallelepiped shaped bronze specimen and to verify the Bio number. Methods: A number of external variables make it difficult to maintain a monotonic change in sample temperature during the ‘heating’ stage. These factors led to the use of the cooling method to study tiny samples with low inertia of the thermal process. We used the cooling method to experimentally verify the isotropy of the thermal field in the sample and to study the kinetics of cooling relative to the sample axes over a wide range of temperatures. Results: It was found out that in natural air cooling the main mechanisms are conductive, convective and radiative heat transfer. The contribution of thermal radiation to the cooling process is noticeable at high temperatures. It was found that the typical cooling time increases with sequential radiative, conductive and convective heat transfer. By extending the temperature study area to, for the first time, we were able to observe each component of the heat transfer process independently. The values of the typical cooling time on all axes correspond to the experimental error bounds. It was found that the temperature value of the sample is independent of the coordinates and depends only on time. In this case, the law of conservation of energy can be used to explain the dependence of body temperature on cooling time. Conclusion: It is shown that the sample under study is ‘thermally thin’, i.e. the thermal field is constant in all directions. In this situation, the thermal balance equation should be applied rather than the Fourier differential equation of heat conduction, since the temperature gradient inside the body is practically zero. The results obtained are of great importance for the study of cooling processes of metallic products in thermal power engineering, heat engineering and thermophysics.

Proposal automatic water purging system for machinery in high humidity environments controlled by an ECU

This paper presents an advanced automatic water discharge system tailored for diesel-powered machinery, particularly for vehicles operating in diverse climates, including humid coastal regions. The system is designed to protect fuel circuits in tanks and diesel engines of boats, offering either automatic or semi-automatic protection against oxidation and corrosion. This enhancement extends the lifespan of diesel components and pipelines while simultaneously reducing maintenance costs and intervention times. Additionally, the system improves fuel purity, resulting in increased engine power and efficiency. The proposed solution was experimentally validated using an Arduino board coupled with a water-sensitive detector in diesel fuel, suitable for installation in diesel filters or tanks. Experimental findings demonstrated a remarkably swift separation time of 150 microseconds for diesel and water at a pressure of 1 bar, achieving an impressive efficiency of 99.84%. The system's rapid and effective separation capability highlights its practical value, particularly in scenarios where efficient water removal is critical to sustaining engine performance and longevity.

Large-scale annotation of biochemically relevant pockets and tunnels in cognate enzyme–ligand complexes

Tunnels in enzymes with buried active sites are key structural features allowing the entry of substrates and the release of products, thus contributing to the catalytic efficiency. Targeting the bottlenecks of protein tunnels is also a powerful protein engineering strategy. However, the identification of functional tunnels in multiple protein structures is a non-trivial task that can only be addressed computationally. We present a pipeline integrating automated structural analysis with an in-house machine-learning predictor for the annotation of protein pockets, followed by the calculation of the energetics of ligand transport via biochemically relevant tunnels. A thorough validation using eight distinct molecular systems revealed that CaverDock analysis of ligand un/binding is on par with time-consuming molecular dynamics simulations, but much faster. The optimized and validated pipeline was applied to annotate more than 17,000 cognate enzyme–ligand complexes. Analysis of ligand un/binding energetics indicates that the top priority tunnel has the most favourable energies in 75% of cases. Moreover, energy profiles of cognate ligands revealed that a simple geometry analysis can correctly identify tunnel bottlenecks only in 50% of cases. Our study provides essential information for the interpretation of results from tunnel calculation and energy profiling in mechanistic enzymology and protein engineering. We formulated several simple rules allowing identification of biochemically relevant tunnels based on the binding pockets, tunnel geometry, and ligand transport energy profiles.Scientific contributionsThe pipeline introduced in this work allows for the detailed analysis of a large set of protein–ligand complexes, focusing on transport pathways. We are introducing a novel predictor for determining the relevance of binding pockets for tunnel calculation. For the first time in the field, we present a high-throughput energetic analysis of ligand binding and unbinding, showing that approximate methods for these simulations can identify additional mutagenesis hotspots in enzymes compared to purely geometrical methods. The predictor is included in the supplementary material and can also be accessed at https://github.com/Faranehhad/Large-Scale-Pocket-Tunnel-Annotation.git. The tunnel data calculated in this study has been made publicly available as part of the ChannelsDB 2.0 database, accessible at https://channelsdb2.biodata.ceitec.cz/.

An integrated binary metaheuristic approach in dynamic unit commitment and economic emission dispatch for hybrid energy systems

The current generation portfolio is obligated to incorporate zero-emissions energy sources, predominantly wind and solar, due to the depletion of fossil fuels and the alarming rate of global warming. In the current scenario, power engineers must devise a compromised solution that not only advocates for the adoption of renewable energy sources (RES) but also efficiently schedules all conventional power generation units to balance the increasing load demand while simultaneously minimizing fuel costs and harmful emissions that are currently addressed by Unit Commitment (UC) and Combined Economic Emission Dispatch (CEED) problem solutions. However, the integration of renewable energy resources (RES) further complicates the UC-CEED problem due to their intermittent nature. Recently, metaheuristic algorithms are acquiring momentum in resolving constrained UC-CEED problems due to their improved global solution ability, adaptability, and derivative-free construction. In this research, a computationally efficient binary hybrid version of crow search algorithm and improvised grey wolf optimization is proposed, namely Crow Search Improved Binary Grey Wolf Optimization Algorithm (CS-BIGWO) by inclusion of nonlinear control parameter, weight-based position updating, and mutation approach. Statistical results on standard mathematical functions prove the supremacy of the proposed algorithm over conventional algorithms. Further, a novel optimization strategy is devised by integrating enhanced lambda iteration with the CS-BIGWO algorithm (CS-BIGWO-λ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\lambda$$\\end{document}) to solve a day-ahead UC-CEED problem of the hybrid energy system incorporating cost functions of RES. For the model, a day-ahead forecast of wind power and solar photovoltaic power is obtained by using the Levy-Flight Chaotic Whale Optimization Algorithm optimized Extreme Learning Machines(LCWOA-ELM). The proposed algorithm is tested for the UC-CEED solution of an IEEE-39 bus system with two distinct cases: (1) without RES integration and (2) with RES integration. Several independent trial runs are executed, and the performance of the algorithms is assessed based on optimal UC schedules, fuel cost, emission quantization, convergence curve, and computational time. For case 1, the proposed algorithm resulted in a percentage reduction of 0.1021% in fuel cost and 0.7995% in emission. In contrast, for test case 2, it resulted in a percentage reduction of 0.12896% in fuel cost and 0.772% in emission with the proposed algorithm. The results validate the dominance of the proposed methodology over existing methods in terms of lower fuel costs and emissions.

Fossil Diesel, Soybean Biodiesel and Hydrotreated Vegetable Oil: A Numerical Analysis of Emissions Using Detailed Chemical Kinetics at Diesel Engine Like Conditions

Nowadays, emissions from internal combustion engines are a relevant topic of investigation, taking into account the continuous reduction of emission limits imposed by environmental regulatory agencies around the world, obviously as the result of earnest studies that have pointed out the impact on the human health of high levels of contaminants released into the environment. Over recent years, the use of biofuels has contributed to attenuating this environmental issue; however, new problems have been raised, such as NOx emissions tend to increase as the biofuel percentage in the fuel used in engines increases. In this research, the emissions of a compression ignition internal combustion engine modeled as a variable volume reactor with homogeneous combustion were numerically investigated. To analyze the combustion process, a detailed kinetics model tailored specifically for this purpose was used. The kinetics model comprised 30,975 chemical reactions involving 691 chemical species. Mixtures of fuel surrogates were then created to represent the fuel used in the Brazilian fuel marketplace, involving (i) fossil diesel—“diesel A”, (ii) soybean diesel—“biodiesel”, and (iii) hydrotreated vegetable oil— “HVO”. Surrogate species were then selected for each of the aforementioned fuels, and blends of those surrogates were then proposed as mixture M1 (diesel A:biodiesel:HVO—90:10:0), mixture M2 (diesel A:biodiesel:HVO—85:15:0), and mixture M3 (diesel A:biodiesel:HVO—80:15:5). The species allowed in the kinetics model included all the fuel surrogates used in this research as well as the target emission species of this study: total hydrocarbons, non-methane hydrocarbons, carbon monoxide, methane, nitrogen oxides, carbon dioxide, soot, and soot precursors. When compared to experimental trends of emissions available in the literature, it was observed that, for all the proposed fuel surrogates blends, the numerical approach performed in this research was able to capture qualitative trends for engine power and the target emissions in the whole ranges of engine speeds and engine loads, despite the CO and NOx emissions at specific engine speeds and loads.

Dynamics of tracked vehicles during nonuniform turning on level terrain and on slopes

This paper presents a detailed kinematic and dynamic model of nonuniform skid steering for tracked vehicles on level terrain and uniform skid steering slopes. The objective is to find the required forces applied on both tracks to achieve the desired turning, aiding in determining the needed engine power for effective turning operation. The vehicle kinematics during turning is presented, followed by a complete dynamic analysis that considers the effect of centrifugal and inertia forces, as well as adhesion with the ground. The dynamic analysis of turning on slopes is developed, where the cases of turning while moving uphill and downhill are considered. Moreover, simulation analysis using MATLAB model is conducted to investigate the main turning characteristics on both level terrain and slopes. The model can accurately predict the required forces on both tracks for effective turning, and can aid in the design of more efficient tracked vehicles. Generally, the findings of this study can inform the design of more efficient tracked vehicles by providing insights into the needed driving forces and the required power to achieve the desired radius of turning at a specific vehicle speed.

Structural Performance Analysis and Optimization of Small Diesel Engine Exhaust Muffler

In recent years, the optimization of diesel engine exhaust mufflers has predominantly targeted acoustic performance, while the impact on engine power performance has often been overlooked. Therefore, this paper proposes a parallel perforated tube expansion muffler and conducts a numerical analysis of its acoustic and aerodynamic performance using the finite element method. Then, a Kriging model is established based on the Design of Experiments to reveal the impact of different parameter couplings on muffler performance. With transmission loss (TL) and pressure loss (PL) as the optimization objectives, a multi-objective optimization study is carried out using the competitive multi-objective particle swarm optimization (CMOPSO). The optimization results indicate that this method can simplify the optimization model and improve optimization efficiency. After CMOPSO calculation, the average TL of the muffler increased from 27.3 dB to 31.6 dB, and the PL decreased from 1087 Pa to 953 Pa, which reduced the exhaust noise and improved the fuel economy of the engine, thus enhancing the overall performance of the muffler. This work provides a reference and guidance for the optimal design of mufflers for small agricultural diesel engines.

Modern Prospects for the Application of Mechatronics and Robotics Capabilities

This article explores the application of mechatronics and robotics capabilities. In recent years a new quickly developing scientific and technical activity was created. It is called Mechatronics and represents an innovative field of science and equipment where the high-precision mechanics connects to the same exact electronics under control of the most modern computer programs [1],[2]. As a result difficult mechanisms of computer motion control with tremendous functionality are created. Industrial robots are striking examples of such mechanisms. Besides, there are mechanisms of retracting plane flaps and the chassis, many systems of a modern car and "smart houses". Technical and technological progress is impossible without mechatronics [3],[4]. Robotics and industrial automatic equipment in various branches of economy, automation of technological processes, systems of planning and business management, automation of transport, dispatching and other systems falls within the scope of its interests. Nowadays “Mechatronics” is one of the most demanded educational majors in the world. Mechatronics specialists are demanded in different areas: in power engineering, machine-tool design and production of the equipment, automation of technological processes, robotics and automotive industry. Security systems, military equipment, the medical equipment can't be designed without mechatronics.

Shock Wave and Aeroelastic Coupling in Overexpanded Nozzle

The growing demand for increasing the engine power of a liquid rocket is driving the development of high-power De-Laval nozzles, which is primarily achieved by increasing the expansion ratio. A high-expansion-ratio for De-Laval nozzles can cause flow separation, resulting in unsteady, asymmetric forces that can limit nozzle life. To enhance nozzle performance, various separation control methods have been proposed, but no methods have been fully implemented thus far due to the uncertainties associated with simulating flow phenomena. A numerical study of a high-area-ratio rocket engine is performed to analyze the aeroelastic performance of its structure under flow separation conditions. Based on numerical methodology, the flow inside a rocket nozzle (the VOLVO S1) is analyzed, and different separation patterns are comprehensively discussed, including both free shock separation (FSS) and restricted shock separation (RSS). Since the location of the flow separation point strongly depends on the turbulence model, both the single transport equation and two-transport-equation turbulence models are simulated, and the findings are compared with the experimental results. Therefore, the Spalart–Allmaras (SA) turbulence model is the ideal choice for this rocket nozzle geometry. A wavelet is used to analyze the amplitude frequencies from 0 to 100 Hz under various pressure fluctuation conditions. Based on a clear understanding of the flow field, an aeroelastic coupling method is carried out with loosely coupled computational fluid dynamics (CFD)/computational structural dynamics (CSD). Some insights into the aeroelasticity of the nozzle under separated flow conditions are obtained. The simulation results show the significant impact of the structural response on the inherent pressure pulsation characteristics resulting from flow separation.

Green performance enhancement of marine engines via turbocharger compression ratio optimization

This study investigates the performance dynamics of a six-cylinder, inline compression ignition engine, focusing on its response to varying turbocharger compressor pressure ratios (TCPRs). At a constant speed of 1500 RPM, the engine's power output, braking mean effective pressure, and brake torque increase significantly, ranging from 280 kW, 11.7 bar, and 1779.7 N m at a TCPR of 2–1042.6 kW, 43.7 bar, and 6637.8 N m at a TCPR of 10. This demonstrates a direct relationship between TCPR and engine performance metrics. Additionally, mechanical efficiency improves with increasing TCPR, indicating enhanced adaptability and efficiency of the engine. The study analyzes the effects of turbochargers, exhaust and intake characteristics, NOx emissions, combustion dynamics, and compressor settings, providing a comprehensive understanding of the relationship between turbocharging and compression ignition engines. These insights can support future research aimed at optimizing engine performance across various TCPR settings.

Preface

International Conference on Hydrodynamics, Energy and Electric Power System (HEEPS) is an annually held conference, it aims to provide a forum for participants to exchange their experiences, share research results in all aspects about Hydrodynamics, Energy and Electric Power System and discuss the encountered practical challenges and the adopted solutions. The 2024 8th International Conference on Hydrodynamics, Energy and Electric Power System (HEEPS 2024) was held in Beijing, China from June 28th to 30th, 2024. This esteemed conference, as the eighth in its series, continues to serve as a premier platform for researchers, scholars, and industry professionals to converge, share insights, and collaborate on the latest advancements in hydrodynamics, water resources and hydropower engineering, energy systems, and electric power technologies. HEEPS 2024 was organized with the aim of fostering interdisciplinary dialogue and innovation within the rapidly evolving fields of fluid mechanics, energy systems, and power engineering. Building upon the success of the previous seven editions, this conference attracted a diverse and vibrant community of participants from around the world. The event was hosted with the support of esteemed institutions such as the University of Chinese Academy of Sciences and Universiti Putra Malaysia, further enhancing its international reach and impact. HEEPS 2024 was an outstanding three-day conference and a reference that attracted many remarkable keynote speakers, including: Professor Jizhong Zhu (South China University of Technology, China), Professor Ishak Bin Aris (Universiti Putra Malaysia, Malaysia), Professor Lin Chen (Chinese Academy of Sciences, China), Associate Professor Sohrab Mirsaeidi (Beijing Jiaotong University, China), as well as Assistant Professor Jianxiao Wang (Peking University, China). The program kicked off with a series of keynote lectures delivered by renowned experts in their respective fields, setting the tone for an intellectually stimulating conference. These presentations covered a broad spectrum of topics, ranging from fundamental research in hydrodynamics and fluid mechanics to the latest developments in energy systems and power grid technologies. Besides, during all parts of the conference, the attendees actively interacted with the speakers and each other on specific topics. The conference’s Proceedings of HEEPS 2024 contains the papers accepted and presented at this great conference. All these contributions were carefully reviewed by program committee members and took into consideration the breadth and depth of the research topics that fall into HEEPS scope. On behalf of the conference organizers, we would like to take this opportunity to express our sincere thanks to all the editors and reviewers for their tremendous efforts and dedication to the conference. We also wish to thank all the authors and speakers for their great contributions to this conference and the conference’s Proceedings. And we believe that with such earnest support and contributions, the future HEEPS conferences will also scale new heights. The Committee of HEEPS 2024 List of Committee Member are available in this pdf.

Design and optimization of the exhaust system for an aviation piston engine

Abstract To further enhance the performance of an aviation piston engine, an engine performance simulation analysis model was constructed by using GT-Power software to design improvements to its exhaust system. The impacts of different exhaust system schemes on the exhaust process, the in-cylinder combustion, and the heat release process at a cruising speed of 5500 RPM were analyzed. Based on the results, under cruising speed conditions, a new exhaust system was designed for the engine by referring to the structural form of a resonant exhaust system. The D-optimal Latin hypercube sampling method was used to obtain sample data for the experimental design of the structural parameters of the designed exhaust system. The response surface approximation models characterizing power and fuel consumption rate were established by using the least squares method. The significance of the impact of each structural parameter on engine performance was analyzed through a multifactor analysis of variance. The key structural parameters of the designed exhaust system were then subjected to multi-objective optimization. The results indicate that at 5500 RPM, the designed exhaust system can increase engine power by 2.88%; after optimization, engine power can be further increased by 3.15%, and the fuel consumption rate is reduced by 4.07%.

The influence of longitudinal duct profiling on unsteady gas dynamics and the heat transfer of pulsating gas flows in the outlet system of reciprocating-engine

Heat machines based on reciprocating-engines remain in demand in various fields of engineering and technology. Therefore, further research is needed to improve the efficiency, reliability, and environmental friendliness of engines. The thermomechanical improvement of non-stationary processes in outlet systems is an appropriate way to improve engine performance. The purpose of this research is to obtain and analyse the gas-dynamic and heat transfer characteristics of pulsating gas flows in an outlet system with ducts of various designs, using a laboratory model to simulate the outlet process in an engine. Thermal anemometry is used to receive data on the instant velocity values and local heat transfer coefficient of unsteady flows in ducts. The article examines two designs of outlet ducts, namely cylindrical (basic) and conical (with a taper of 0.0225) ducts. Spectral analysis of velocity, pressure and heat transfer coefficient pulsations, assessment of turbulence intensity, and calculation of flow characteristics of pulsating flows were performed to obtain detailed information on gas dynamics in the outlet system. The use of a conical duct (in comparison with a cylindrical one) leads to a slight increase in the turbulence intensity by up to 12 %, a decrease in the heat transfer coefficient by 15–20 %, and a change in volumetric gas flow within ± 7.5 %. Thus, the use of a conical duct will lead to the stabilisation of the flow in the outlet system, improved cleaning of the cylinder from outlet gases, a reduction in thermal stress, and a slight growth in the specific power of engines.

Applying deep reinforcement learning to solve the low-carbon economic dispatch problem in smart microgrids

Abstract Smart microgrid (SMG) technology can effectively integrate the advantages of new and renewable energy power generation - distributed generation, and, at the same time, provide a new technical approach for the large-scale application of new and renewable energy grid-connected power generation. Smart microgrids can improve the comprehensive utilization efficiency of energy and serve as an effective complementary power grid of the primary power grid to enhance the reliability of power supply and power quality, which is the latest frontier topic in power engineering research. This paper, aiming at the characteristics of distributed generation such as solar power generation, wind power generation, fuel cell power generation, and micro gas turbine in the smart microgrid system, considering the fuel, efficiency, operation, and maintenance costs of different types and capacities, the different greenhouse gas emissions, and the particularity of solar power generation and wind power generation, a mathematical model of low-carbon economic dispatch of smart microgrid that comprehensively considers the cost of power generation and emission is proposed. This paper presents a scheduling decision model based on an improved dual-delay depth deterministic strategy gradient algorithm. The improved double-delay deep deterministic strategy gradient algorithm is used to construct and train the neural network to avoid overestimation and improve the stability of the network output. At the same time, to improve the efficiency of network training, the historical experience data in the training process were stored, and the experience was replayed and sampled. Examples verify the superiority and practicability of the method proposed in this paper.

Correlation relationships of processes in the combustion engine in the RDE test

The article presents considerations on the processes taking place in the combustion engine in the in real driving operating conditions of a vehicle performing the RDE (Real Driving Emissions) test. The tests were carried out using a passenger car with a spark-ignition engine. The processes considered in the article were related to the engine operating states, exhaust emissions and fuel consumption, and the vehicle speed, which determines the engine operating conditions. The RDE test were carried out using PEMS (Portable Emissions Measurement System) equipment, and the following variables were recorded: vehicle speed, control, rotational speed, relative torque and relative engine power, emission pollutant intensity of: carbon monoxide, hydrocarbons, nitrogen oxides and carbon dioxide, the intensity of particle number and the fuel consumption intensity. The recorded signals were digitally processed, and the statistical properties of the variables and the mutual relation between the engine operating states were examined. The properties of the measured variables were investigated in the entire RDE test and in its constituent phases: the first, corresponding to vehicle movement in cities, the second – outside cities, and the third – on highways and expressways. The pollutant specific distance emission and the particle number specific distance as well as the specific distance fuel consumption were determined in relation to the average vehicle speed, and based on these results, the exhaust emissions and fuel consumption characteristics were created. Correlational studies of the considered variables were also performed. Pearson's linear correlation coefficients for the measured variables combinations were determined.

The experimental investigation of performance behaviors of a beta-type Stirling engine with bell-crank motion mechanism

The current study aims to develop a novel power generation system that is capable of working with a Stirling engine. Within this context, a β-type Stirling engine design has been created with a bell-crank motion mechanism and a 365 cm3 swept volume. The engine has been manufactured, and then a detailed assessment has been conducted to determine the impact of the motion mechanism on engine performance characteristics. The designed and manufactured engine has been tested using a range of working fluids, such as air, argon, carbon dioxide, helium, and nitrogen gases. The performance tests of this engine have been carried out at 1000 K (±10) heater and 300 K (±5) coolant temperatures. Based on the outcomes of the experimental studies, the highest engine power and torque values have been obtained at a charge pressure of 4 bar using helium gas, with 143.5 W at 267 rpm and 7.75 Nm at 100 rpm, respectively. Moreover, the maximum engine power values obtained from other tests with nitrogen, air, carbon dioxide and argon gases have been compared with helium gas. Helium gas has been found to outperform nitrogen, air, carbon dioxide, and argon gases in tests by 67.3%, 73.9%, 197.1%, and 200.2%, respectively. Finally, the highest thermal efficiency value has been obtained with helium gas as 48.7% at a charge pressure of 4 bar.