Photothermal conversion is an environmentally friendly process that harvests energy from the sun and has been attracting growing research interest in recent years. However, nanostructured strategies to improve light capture performance deserve further development, and the application of solar heating effects for clean energy needs to be explored. Herein, a multiscale nanomaterial was prepared by in situ polymerizing the polyaniline (PANI) nanoparticles into porous anodic aluminum oxide (AAO) membrane. As a result, the as-prepared PANI-AAO shows broadband solar absorption and provides a platform for efficient photothermal conversion. What is more, we introduced a typical thermoelectricity generator (TEG) with excellent output performance and combined it with PANI-AAO to prepare a solar thermoelectric generator (s-TEG). The s-TEG harvests solar energy and converts it into electricity, showing an outstanding power generation capability in outdoor conditions. Thus, the nanostructured broad... [more]

The use of HVDC systems is increasing in number due to technological innovations, increasing power capacity and increasing customer demand. The characteristics of insulation systems under composite DC and LI voltage must be examined and clarified. In this study, firstly, experimental circuits were designed to generate and measure composite DC and LI high voltage using a simulation program. The coupling elements used were chosen according to simulation results. Afterward, experimental circuits were established in the laboratory according to the simulation results of the designed experimental circuit. Then, breakdown voltages under composite DC and LI voltage for less uniform and non-uniform electric fields were measured with four different electrode systems for positive and negative DC voltage pre-stresses with different amplitudes. The 50% breakdown voltage was calculated using the least-squares method. Finally, 3D models were created for the electrode systems used in the experiments u... [more]

The article concerns the issue of the existence of non-obvious relationships and of potential correlations between the emission of greenhouse gases and particulate matter (PM), renewable energy and corruption perceptions. Additionally, it analyses the possible impact of these above-mentioned connections on the economic, environmental and social situation in the context of further economic development, including during the COVID-19 pandemic and in relation to European countries. The issue of reducing dirty energy sources and corrupt activities is not only a problem considered at the state level, but it is very closely related to the operation of many private enterprises. The conducted research applied methods of desk research as well as comparative quantitative analyses and used extensive statistical data of most European Union member states as well as the United Kingdom and Norway. The ambiguity of the results obtained in the research does not allow for an explicit verification of the... [more]

Energy demand has grown explosively in recent years, leading to increased attention of energy efficiency (EE) research. Demand response (DR) programs were designed to help power management entities meet energy balance and change end-user electricity usage. Advanced real-time meters (RTM) collect a large amount of fine-granular electric consumption data, which contain valuable information. Understanding the energy consumption patterns for different end users can support demand side management (DSM). This study proposed clustering algorithms to segment consumers and obtain the representative load patterns based on diurnal load profiles. First, the proposed method uses discrete wavelet transform (DWT) to extract features from daily electricity consumption data. Second, the extracted features are reconstructed using a statistical method, combined with Pearson’s correlation coefficient and principal component analysis (PCA) for dimensionality reduction. Lastly, three clustering algorithms a... [more]

Energy security education explores various issues, such as a secure and competitive economy and nuclear safety. In the context of energy transition and sustainable development, it also addresses the world’s reliance on nonrenewable and renewable energy sources. The aim of this study was to identify research trends pertaining to energy security education, paying particular attention to renewable and nonrenewable sources. This was accomplished with the use of mixed-method research in two steps. The first step was a text-mining and content analysis of publications on energy security education published on the Web of Science platform between 2016 and 2021. From 660 publications on energy security education, titles, abstracts, and keywords were extracted and analysed with NVivo software to identify the most frequent concepts on energy sources in publications. The concepts were associated with nonrenewable energy sources (coal, natural gas, uranium, petroleum, and fossil fuels), nuclear powe... [more]

Background: Understanding the market competition is one of the most important factors for examining and assessing competition issues, and is of growing interest in business sustainability research. Markets in the energy industry, which are notoriously harder to monitor, are often presented with scenarios in which the strength of various market parties varies, making harmonization a significant problem. This article’s aim is to find the feasibility of measuring the HHI in the implementation of business strategies in order to avoid market distortions in the energy industry. The uniqueness of this article is that it outlines the capabilities of the fuzzy VIKOR approach for assessing the HHI in order to avoid a distorted market by examining the most important economic parameters in the energy market. This paper’s contribution is compiling the HHI evaluation system in the energy sector, with the goal of identifying the market conditions of corporate entity and assisting in the attainment of... [more]

Hydraulic hybrid drivetrains, which are fluid power technologies implemented in automobiles, present a popular alternative to conventional drivetrain architectures due to their high energy savings, flexibility in power transmission, and ease of operation. Hydraulic hybrid drivetrains offer multiple environmental benefits compared to other power transmission technologies. They provide heavy-duty vehicles, e.g., commercial transportation, construction equipment, wagon handling, drilling machines, and military trucks, with the potential to achieve better fuel economy and lower carbon emissions. Despite the preponderance of hydraulic hybrid transmissions, state-of-the-art hydraulic hybrid drivetrains have relatively low efficiencies, around 64% to 81%. This low efficiency is due to the utilization of conventional variable displacement pumps and motors that experience high power losses throughout the drive cycle and thus fail to maintain high operating efficiency at lower volumetric displac... [more]

Linear hybrid excited flux switching machines (LHEFSM) combine the features of permanent magnet flux switching machines (PMFSM) and field excited flux switching machines (FEFSM). Because of the widespread usage of rare-earth PM materials, their costs are steadily rising. This study proposes an LHEFSM, a dual stator LHEFSM (DSLHEFSM), and a dual mover LHEFSM (DMLHEFSM) to solve this issue. The employment of ferrite magnets rather than rare-earth PM in these suggested designs is significant. Compared to traditional designs, the proposed designs feature greater thrust force, power density, reduced normal force, and a 25% decrease in PM volume. A yokeless primary structure was used in a DSLHEFSM to minimize the volume of the mover, increasing the thrust force density. In DMLHELFSM, on the other hand, a yokeless secondary structure was used to lower the secondary volume and the machine’s total cost. Single variable optimization was used to optimize all of the proposed designs. By completing... [more]

In an open electricity market, increased accuracy and real-time availability of electricity price forecasts can help market parties participate effectively in market operations and management. As the penetration of clean energy increases, it brings new challenges to electricity price forecasting. An electricity price forecasting model is constructed in this paper for markets containing a high proportion of wind and solar power, where the scenario with a high coefficient of variation (COV) caused by the high frequency of low electricity prices is particularly concerned. The deep extreme learning machine optimized by the sparrow search algorithm (SSA-DELM) is proposed to make predictions on the model. The results show that wind−load ratio and solar−load ratio are the key input variables for forecasting in power markets with high proportions of wind and solar energy. The SSA-DELM possesses better electricity price forecasting performance in the scenario with a high COV and is more suitabl... [more]

Today, the energy sector requires special attention, and the widespread introduction of digital technologies, including gamification, allows key problems related to the energy policies of the European Union to be solved. The literature analysis presented here discusses the use of gamification among home energy production customers. However, there is a lack of analysis on the use of this tool in the management of energy sector companies. When considering the advantages of gamification elements in the training process, there was mention of this tool potentially being able to be used in HR management to realize the EU’s energy goals. The relevance of the topic has been explored in international studies that have shown that gamification increases employee productivity and motivation. In the article, the directions of gamification in the practices of Ukrainian organizations are investigated. The main principles of effective gamification implementation in HR management, at energy enterprises... [more]

We introduce the industrial portfolio of a wind farm of a hypothetical company and its valuation consistent with the financial market. Next, we propose a static risk management policy originating from hedging against volumetric risk due to drops in wind intensity and we discuss the consequences. The hedging effectiveness firstly requires adequate modeling calibration and an extensive knowledge of these atypical financial (commodity) markets. In this hedging experiment, we find significant benefits for weather-sensitive companies, which can lead to new business opportunities. We provide a new financial econometrics approach to derive weather risk exposure in a typical wind farm. Our results show how accurate risk management can have a real benefit on corporate revenues. Specifically, we apply the spot market price simulation (SMaPS) model for the spot price of electricity. The parameters are calibrated using the prices of the French day-ahead market, and the historical series of the tot... [more]

The expansion of renewable energy with its volatile feed-in character places higher demands on the power grid of the future. Large-scale storage systems (LSS) are a promising option for supporting the electricity grid and have been gaining importance in the last years, both on the market for frequency containment reserve (FCR) and in research. The majority of publications investigating the interaction between storage and FCR are based on simulations rather than on field measurements. This paper presents the analyses of multi-year, high-resolution field measurements of the hybrid 6 MW/7.5 MWh battery storage “M5BAT” to address this issue. The influence of FCR operation on the operation and degradation of the hybrid LSS and the individual battery technologies is investigated via a statistical evaluation of the historical operating data between 2017 and 2021. The data-based analysis of the LSS and the individual battery technologies reveals a high availability of the LSS of over 96.5%. Fu... [more]

As on many other European islands, the energy system of Mayotte suffers from low reliability of supply, low share of renewable energies, and high costs of supply. Residential Demand Response (DR) schemes can significantly increase the flexibility of the inherent weak power grid, increasing the potential for renewable energy integration. Given that active involvement of the population is required to unlock the potential of DR, pre-assessing the population’s preferences in DR is vital to tailor favorable schemes and assure long-term uptake of the solution. As a fundamental study, this paper assesses the population’s preferences on direct load control (DLC), electricity tariffs, major motivation, and remuneration goods by processing findings from a survey of 146 residents on Mayotte. Advanced k-means cluster analysis, multinomial logistic regression, one-way analysis of variance, and Chi-square tests were applied to the survey responses to identify socio-demographic influencers. The resul... [more]

The present research article focuses on an analytically based method for the optimal allocation and sizing of a renewable energy source (RES) capable of injecting both active and reactive powers in the distribution network. The placement of distributed generation (DG) in the distribution network reduces the magnitude of branch current in between the reference bus and the bus where DG is to be installed. Due to this, system power loss decreases significantly. The proposed method considers different levels of load in addition to peak load demand. The goal of the developed method is to minimize system losses by optimal DG allocations. In the proposed method, the optimum size of the DG is obtained on the basis of maximum loss saving criterion. For the execution of proposed method, only a base case load flow solution is required. The developed method has been tested on IEEE 69-bus and 33-bus radial distribution networks. On the basis of obtained results, it has been realized that the develo... [more]

Blades in strong wind conditions are prone to various failures and damage that is due to the action of random variable amplitude loads. In this study, we analyze the failure of 1.5 MW horizontal axis wind turbine blades. The computational fluid dynamics unsteady calculation method is used to simulate the aerodynamic load distribution on the blade. Fluid−structure coupling methods are applied to calculate the blade stress. The results show that the equivalent stress of the blade is the largest when the azimuth angle is 30°, and the maximum equivalent stress is 20.60 MPa. There are obvious stress peaks in six sections, such as r/R = 0.10 (the span length of blade/the full length of the blade = 0.10). The frequency of damage that is caused by the stress in each area of the blade is determined based on the blade damage. The frequency of gel coat cracking in the blade tips and leaves is 77.78% and 22.22%, respectively, and the frequency of crack occurrence is 87.75%, 10.20% and 2.05%, respe... [more]

This paper presents the results of research on heat transfer during fluid flow in a heat exchanger with two rectangular mini-channels. There was Fluorinert FC-72 flow, heated by the plate in the hot mini-channel, and co-current flow of distilled water in the cold mini-channel. Both fluids were separated by the copper plate. A thermal imaging camera was used to measure the temperature distribution of the outer surface of the heated plate. The purpose of the calculations was to determine the heat transfer coefficients at the contact surfaces: the heated plate—FC-72 and FC-72—the copper plate. Two mathematical models have been proposed to describe the heat flow. In the 1D approach, only the heat flow direction perpendicular to the fluid flow direction was assumed. In the 2D model, it was assumed that the temperature of the heated plate and FC-72 and the copper plate meet the appropriate energy equation, supplemented by the boundary conditions system. In this case, the Trefftz functions we... [more]

The article is the first in a series of works presenting the potential and possibilities of using for energy purposes wood waste and wood by-products generated at various stages of production in companies of the wood industry. The management of all wood waste and wood by-products is a pending issue due to the growing importance of the circular economy and broadly understood environmental protection. It is the environmental aspects and the climate targets defined by the EU that are the basis to determine the precise courses of action for the Member States and, as a result, also for companies. The article proves that regardless of the decisions taken by governments of individual countries in terms of broadly understood environmental protection, companies are free to implement pro-environmental solutions as part of their business activity. Due to the broad subject of the management of waste and by-products generated in different units of the wood industry, the possibilities of their use i... [more]

Greenhouse gas emissions need to be drastically reduced to mitigate the environmental impacts caused by climate change, and to lead to a transformation of the European energy system. A model landscape consisting of four final energy consumption sector models with high spatial (NUTS-3) and temporal (hourly) resolution and the multi-energy system model ISAaR is extended and applied to investigate the transformation pathway of the European energy sector in the deep emission mitigation scenario solidEU. The solidEU scenario describes not only the techno-economic but also the socio-political contexts, and it includes the EU27 + UK, Norway, and Switzerland. The scenario analysis shows that volatile renewable energy sources (vRES) dominate the energy system in 2050. In addition, the share of flexible sector coupling technologies increases to balance electricity generation from vRES. Seasonal differences are balanced by hydrogen storage with a seasonal storage profile. The deployment rates of... [more]

Different risks are associated with the operation and maintenance of wind farms in cold climate regions, mainly due to the harsh weather conditions that wind farms experience in that region such as the (i) increased stoppage rate of wind turbines due to harsh weather conditions, (ii) limited accessibility to wind farms due to snow cover on roads, and (iii) cold stress to workers at wind farms. In addition, there are risks that are caused by wind farms during their operation, which impact the surrounding environment and community such as the (iv) risk of ice throw from wind turbines, (v) environmental risks caused by the wind farms, and (vi) social opposition risk to installing wind farms in cold climate regions, such as the Arctic. The analysis of these six risks provides an overall view of the potential risks encountered by designers, operators, and decision makers at wind farms. This paper presents a methodology to quantify the aforementioned risks using fuzzy logic method. At first,... [more]

The contribution of power generation from converter-dominated renewable energy sources (RES) has increased enormously. Consequently, the system inertia is decreasing, and it impacts the frequency of the system. With large-scale integration of power electronic inverter-based power generation from RES, inertia from energy storage devices would be unavoidable in future power grids. In this paper, the inertia emulator is formed with a supercapacitor (IE−SC) to improve inertia in a low inertia grid. To emulate the inertia in a low inertia grid, this paper proposes a fuzzy logic controller-based emulated inertia controller (FL-EIC) for an inverter attached to IE−SC. The proposed fuzzy logic controller estimates the inertial power required based on the frequency deviation and rate of change of frequency (ROCOF). The output of the fuzzy controller adds to the conventional emulated inertia control (EIC) technique to alter the load angle for the power electronic inverter of IE−SC. Specifically,... [more]

Electromagnetic radiation can have a negative effect on electronic circuits, for example, by disrupting their work and communication. Therefore, there is a need to reduce or eliminate electromagnetic interference using shields. This paper focuses on using waste materials in the form of iron scale, which is easy and inexpensive to obtain for shielding. Iron scale is the result of gaseous or aqueous corrosion, due to which a superficial layer of metal oxides formed on the surface of heated metal objects as a result of their contact with air or water during an industrial process is developed. In this study, morphology, chemical, and phase composition measurements were carried out. The results show that all the iron-based materials investigated are mainly composed of iron oxides and pure iron. The polymer−iron composites with different quantitative and qualitative compositions were prepared to verify the shielding effectiveness. The electrical resistance, impact strength, and magnetic prop... [more]

The article presents a comparison of the influence of price change of the components of pyrotechnic compositions producing an acoustic effect on their manufacturing costs. The analysis was based on the prices of raw materials in 1981 and 2021. The influence of price fluctuations of individual raw materials on the final cost of composites was determined. The impact of price changes on the profitability of pyrotechnic composition manufacturing was evaluated for the adopted models. The conducted economic analysis allowed for the determination of pyrotechnic compositions characterised by the lowest manufacturing costs, in terms of the unit cost, and for the assumed industrial models.

Infrared spectroscopy (IR) quantitative analysis technology has shown excellent development potential in the field of oil and gas logging. However, due to the high overlap of the IR absorption peaks of alkane molecules and the offset of the absorption peaks in complex environments, the quantitative analysis of IR spectroscopy applied in the field puts forward higher requirements for modelling speed and accuracy. In this paper, a new type of fast IR spectroscopy quantitative analysis method based on adaptive step-sliding partial least squares (ASS-PLS) is designed. A sliding step control function is designed to change the position of the local PLS analysis model in the full spectrum band adaptively based on the relative change of the current root mean square error and the global minimum root-mean-square error for rapid modelling. The study in this paper reveals the influence of the position and width of the local modelling window on the performance, and how to quickly determine the opti... [more]

Vehicle electrification demands a deep analysis of the thermal problems in order to increase vehicle efficiency and battery life and performance. An efficient thermal management of an electrified vehicle has to involve every system of the vehicle. However, it is not sufficient to optimize the thermal behavior of each subsystem, but thermal management has to be considered at system level to optimize the global performance of the vehicle. The present paper provides an organic review of the current aspects of thermal management from a system engineering perspective. Starting from the definition of the requirements and targets of the thermal management system, each vehicle subsystem is analyzed and related to the whole system. In this framework, problems referring to modeling, simulation and optimization are considered and discussed. The current technological challenges and developments in thermal management are highlighted at vehicle and component levels.

Although the recent development of solar power forecasting through machine learning approaches, such as the machine learning models based on numerical weather prediction (NWP) data, has been remarkable, their extreme error requires an increase in the amount of reserve capacity procurement used for the power system safety. Hence, a reduction of the serious overestimation is necessary for efficient grid operation. However, despite the importance of the above issue, few studies have focused on the model design, suppressing serious errors, to the best of the authors’ knowledge. This study investigates a prediction model that can reduce the huge overestimation of the solar irradiance, which poses a risk to the power system. The specific approaches used are as follows: the employment of Support Vector Quantile Regression (SVQR), the utilization of Meso-scale Ensemble Prediction System (MEPS, Meso-scale EPS for the regions of Japan) data, which is based on the forecasts from Meso-scale Model... [more]