An excessive increase in reactive power consumption is unfavorable from the point of view of a power system. For this reason, devices compensating reactive power consumption are used. The capacitor is one such device. Capacitors must be tested regularly during their exploitation. One of the activities that should be performed is testing the degree of heating of the cells of a capacitor bank. Thermography can be used to perform such tests. This non-contact method has its limitations. Due to the angular emissivity and the change in the distance between the lens and the object under observation, the temperature measured with a thermographic camera may differ from the actual temperature. This phenomenon is visible on cylindrical capacitor cases. Consequently, depending on the location of the observation point on the capacitor case, the result of the thermographic temperature measurement may be different. To investigate this phenomenon, experimental work has been undertaken.

With the increase in the share of solar energy in the sustainable development, accurate parameter identification plays a significant role in designing optimal solar photovoltaic systems. For this purpose, this paper extensively implements and evaluates the grey wolf optimizer with a dimension learning-based hunting search strategy, an improved version of GWO named I-GWO, in the parameter extraction of photovoltaic cells and modules. According to the experimental results, the double-diode model leads to better fitness than the other diode models in representing the physical behaviors of both photovoltaic cells and photovoltaic modules. For further performance validation, firstly, the internal parameters extracted by the I-GWO algorithm and the corresponding output current data are compared with a number of widely-used parameter extraction methods in the literature. Then, the best goodness-of-fit results achieved by the I-GWO algorithm are evaluated considering many state-of-the-art meta... [more]

This paper proposes a methodology to develop generation expansion plans considering energy storage systems (ESSs), individual generation unit characteristics, and full-year hourly power balance constraints. Generation expansion planning (GEP) is a complex optimization problem. To get a realistic plan with the lowest cost, acceptable system reliability, and satisfactory CO2 emissions for the coming decades, a complex multi-period mixed integer linear programming (MILP) model needs to be formulated and solved with individual unit characteristics along with hourly power balance constraints. This problem requires huge computational effort since there are thousands of possible scenarios with millions of variables in a single calculation. However, in this paper, instead of finding the globally optimal solutions of such MILPs directly, a simplification process is proposed, breaking it down into multiple LP subproblems, which are easier to solve. In each subproblem, constraints relating to ren... [more]

This study examines the mechanism by which pro-environmental self-identity (PESI) affects green energy purchase intention (GEPI) through different dimensions of consumption values. The concept of pro-environmental self-identity is rarely discussed in the context of green energy purchase intention. Additionally, the amount of research concerning consumers’ attitudes and behaviours towards photovoltaic panels is limited. We fill this cognitive gap by testing a relation between pro-environmental self-identity and green energy purchase intention. The data collection was carried out based on an indirect method of gathering information—using an online survey. Research was conducted among 250 Polish customers. The partial least squares structural equation modelling technique was applied. The research results show that the relations between PESI and GEPI is mediated totally by social and partially by emotional values. The mediating impact of functional values was not confirmed. The results of... [more]

This paper analyzes the impact of the fall in household consumption after an economic crisis in Spain on greenhouse gas emissions. To this end, household consumption is differentiated by the age of the main provider by using a conversion matrix that relates consumption groups to activity sectors. A multisectoral model was used to quantify and compare the environmental impact caused by the consumption of each age group, indicating that the older the age of the main household provider, the smaller the reduction in GHG emissions associated with their consumption. The results facilitate an analysis of how the greenhouse gas emissions of the different sectors of the Spanish economy, associated with the population under study, varied before and after the 2008 crisis, and confirm that the sectors with the greatest reduction in emissions were, in this order, extractive industries, construction, manufacturing industry, wholesale and retail trade and transport and storage. This is relevant for d... [more]

The Ecuador’s expansion plans for the power sector promote the exploitation of hydro power potential, natural gas and a small share of alternative renewable energies. In 2019, electricity generation reached 76.3% from hydroelectric power, 21.9% from thermal plants and 1.8% from other renewable resources. Although the power energy mix is mainly based on renewable technologies, the total energy demand is still dependent on fossil fuels, which is the case of the transport sector that alone accounted for 50% of the total primary energy consumed in the country. This paper analyzes the pathway to develop a clean and diversified electricity mix, covering the demand of three specific development levels of electric transportation. The linear optimization model (urbs) and the Ecuador Land Use and Energy Netwrok Analysis (ELENA) are used to optimize the expansion of the power system in the period from 2020 to 2050. Results show that reaching an electricity mix 100% based on renewable energies is... [more]

As in other countries of the world, the Turkish government is implementing many preventive partial and total lockdown practices against the virus’s infectious effect. When the first virus case has been detected, the public authorities have taken some restriction to reduce people and traffic mobility, which has also turned into some positive affect in air quality. To this end, the paper aims to examine how this pandemic affects traffic mobility and air quality in Istanbul. The pandemic does not only have a human health impact. This study also investigates the social and environmental effects. In our analysis, we observe, visualize, compare and discuss the impact of the post- and pre-lockdown on Istanbul’s traffic mobility and air quality. To do so, a geographic information system (GIS)-based approach is proposed. Various spatial analyses are performed in GIS with the statistical data used; thus, the environmental effects of the pandemic can be better observed. We test the hypothesis tha... [more]

This paper aims to present an innovative approach based on two newly developed Multi-Criteria Decision-Making (MCDM) methods: COMET combined with TOPSIS and SPOTIS, which could be the basis for a decision support system (DSS) in the problem of selecting solar panels. Solar energy is one of the most promising and environmentally friendly energy sources because of the enormous potential of directly converting available solar radiation everywhere into electricity. Furthermore, ever-lower prices for photovoltaic systems make solar electricity more competitive with power from conventional energy sources, increasing interest in solar panels among companies and households. This fact generates the need for a user-friendly, objective, fully automated DSS to support the multi-criteria selection of solar panels. Both MCDM methods chosen for this purpose are rank-reversal-free and precise. First, the objective entropy weighting method was applied for determining criteria weights. Final rankings we... [more]

Power suppliers in a dynamic power market can achieve full benefit by introducing a bidding strategy mechanism. In the power sector, renewable resources have significant gradual usage and their effect on the production of detailed bidding approaches is becoming further complicated in the industry. Due to the irregular nature of these renewable resources and because they are subject to several fluctuations, there is an inherent issue with generating electricity. Taking these considerations into account, attempts have been made to create a model of bidding strategy to optimize the benefit of the electricity producers using the oppositional gravitational search algorithm. The Weibull and Beta distribution functions are utilized to describe the stochastic characteristics of the wind-speed profile and solar-irradiation, respectively. For the IEEE-30 and IEEE-57 frameworks, the suggested method is being checked and explained. In comparison to other optimization approaches, the results of thi... [more]

Hydraulic fracturing (HF) is a well-known stimulation method used to increase production from conventional and unconventional hydrocarbon reservoirs. In recent years, HF has been widely used in Enhanced Geothermal Systems (EGS). HF in EGS is used to create a geothermal collector in impermeable or poor-permeable hot rocks (HDR) at a depth formation. Artificially created fracture network in the collector allows for force the flow of technological fluid in a loop between at least two wells (injector and producer). Fluid heats up in the collector, then is pumped to the surface. Thermal energy is used to drive turbines generating electricity. This paper is a compilation of selected data from 10 major world’s EGS projects and provides an overview of the basic elements needed to design HF. Authors were focused on two types of data: geological, i.e., stratigraphy, lithology, target zone deposition depth and temperature; geophysical, i.e., the tectonic regime at the site, magnitudes of the prin... [more]

Energy system modelling is an essential practice to assist a set of heterogeneous stakeholders in the process of defining an effective and efficient energy transition. From the analysis of a set of open-source energy system models, it emerged that most models employ an approach directed at finding the optimal solution for a given set of constraints. On the contrary, a simulation model is a representation of a system used to reproduce and understand its behaviour under given conditions without seeking an optimal solution. In this paper, a new open-source energy system model is presented. Multi Energy Systems Simulator (MESS) is a modular, multi-energy carrier, multi-node model that allows the investigation of non optimal solutions by simulating an energy system. The model was built for urban level analyses. However, each node can represent larger regions allowing wider spatial scales to be represented as well. In this work, the tool’s features are presented through a comparison between... [more]

The characterization of competent intermediates of metal complexes, involved in catalytic transformations for the activation of small molecules, is an important target for mechanistic comprehension and catalyst design. Iron complexes deserve particular attention, due to the rich chemistry of iron that allows their application both in oxidation and reduction processes. In particular, iron complexes with tetradentate Schiff base ligands show the possibility to electrochemically generate FeI intermediates, capable of reacting with carbon dioxide. In this work, we investigate the electronic and spectroscopic features of FeI intermediates in five Fe(LN2O2) complexes, and evaluate the electrocatalytic reduction of CO2 in the presence of phenol (PhOH) or trifluoroethanol (TFE) as proton donors. The main findings include: (i) a correlation of the potentials of the FeII/I couples with the electronic character of the LN2O2 ligand and the energy of the metal-to-ligand charge transfer absorption o... [more]

The present work addresses the modelling, control, and simulation of a microgrid integrated wind power system with Doubly Fed Induction Generator (DFIG) using a hybrid energy storage system. In order to improve the quality of the waveforms (voltages and currents) supplied to the grid, instead of a two level-inverter, the rotor of the DFIG is supplied using a three-level inverter. A new adaptive algorithm based on combined Direct Reactive Power Control (DRPC) and fuzzy logic controls techniques is applied to the proposed topology. In this work, two topologies are proposed. In the first one, the active power injected into the grid is smoothened by using an economical hybrid battery and supercapacitor energy storage system. However, in the second one, the excess wind energy is used to produce and store the hydrogen, and then a solid oxide fuel cell system (SOFC) is utilized to regenerate electricity by using the stored hydrogen when there is not enough wind energy. To avoid overcharging,... [more]

The public’s awareness of threats to the natural environment, as well as the hazard to human lives and health posed by the use of fossil fuels to generate energy has resulted in the growing interest in renewable energy sources, thus promoting attempts to reduce the dependency on conventional energy sources. Among the former, solar energy is one of the most promising. The aim of this study is to assess the macroeconomic efficiency of investments in photovoltaic installations to meet the demand for electricity of farms and agricultural production. Calculations were prepared for 48 variants comprising three farm types (dairy farms, field cropping farms, and mixed production farms), as well as 16 locations throughout Poland. The obtained results indicate high efficiency of electricity production using photovoltaic installations to cover the needs of farms in Poland. In macroeconomic accounting, NPV ranges from EUR 8200 to almost EUR 23,000, with the payback period depending on the farm typ... [more]

The dynamic dimensioning of frequency restoration reserves based on probabilistic criteria is becoming increasingly relevant in European power grid operations, following the guidelines of European legislation. This article compares dynamic dimensioning based on k-means clustering to static dimensioning on a case study of the Greek electricity market. It presents a model of system imbalances which aims to capture various realistic features of the stochastic behavior of imbalances, including skewed distributions, the dependencies of the imbalance distribution on various imbalance drivers, and the contributions of idiosyncratic noise to system imbalances. The imbalance model was calibrated in order to be consistent with historical reserve requirements in the Greek electricity market. The imbalance model was then employed in order to compare dynamic dimensioning based on probabilistic criteria to static dimensioning. The analysis revealed potential benefits of dynamic dimensioning for the... [more]

Frequency response analysis (FRA) is a powerful and widely used tool for condition assessment in power transformers. However, interpretation schemes are still challenging. Studies show that FRA data can be influenced by parameters other than winding deformation, including temperature. In this study, a machine-learning approach with temperature as an input attribute was used to objectively identify faults in FRA traces. To the best knowledge of the authors, this has not been reported in the literature. A single-phase transformer model was specifically designed and fabricated for use as a test object for the study. The model is unique in that it allows the non-destructive interchange of healthy and distorted winding sections and, hence, reproducible and repeatable FRA measurements. FRA measurements taken at temperatures ranging from −40 °C to 40 °C were used first to describe the impact of temperature on FRA traces and then to test the ability of the machine learning algorithms to discri... [more]

In both the private and public sectors, green hydrogen is treated as a promising alternative to fossil energy commodities. However, building up production capacities involves significant carbon production, especially when considering secondary infrastructure, e.g., renewable power sources. The amount of required capacity as well as the carbon production involved is calculated in this article. Using Germany as an example we show that the switch to purely green hydrogen involves significant bow waves in terms of carbon production as well as financial and resource demand. An economic model for an optimal decision is derived and—based on empirical estimates—calibrated. It shows that, even if green hydrogen is a competitive technology in the future, using alternatives like turquoise hydrogen or carbon capture and storage is necessary to significantly reduce or even avoid the mentioned bow waves.

A laboratory-scale chamber is convenient for combustion scenarios in the practical analysis of industrial explosions and devices such as internal combustion engines. The safety risks in hazardous areas can be assessed and managed during accidents. Increased hydrogen usage in renewable energy production requires increased attention to the safety issues since hydrogen produces higher explosion overpressures and flame speed and can cause more damage than methane or propane. This paper reports numerical simulation of turbulent hydrogen combustion and flame propagation in the University of Sydney's small-scale combustion chamber. It is used for the investigation of turbulent premixed propagating flame interaction with several solid obstacles. Obstructions in the direction of flow cause a complex flame front interaction with the turbulence generated ahead of it. For numerical analysis, OpenFOAM CFD software was chosen, and a custom-built turbulent combustion solver based on the progress vari... [more]

In this study, a thorough and definitive evaluation of Predictive Optimal Energy Management Strategy (POEMS) applications in connected vehicles using 10 to 20 s predicted velocity is conducted for a Hybrid Electric Vehicle (HEV). The presented methodology includes synchronous datasets gathered in Fort Collins, Colorado using a test vehicle equipped with sensors to measure ego vehicle position and motion and that of surrounding objects as well as receive Infrastructure to Vehicle (I2V) information. These datasets are utilized to compare the effect of different signal categories on prediction fidelity for different prediction horizons within a POEMS framework. Multiple artificial intelligence (AI) and machine learning (ML) algorithms use the collected data to output future vehicle velocity prediction models. The effects of different combinations of signals and different models on prediction fidelity in various prediction windows are explored. All of these combinations are ultimately addr... [more]

We carried out several numerical experiments to analyze how different boundary conditions affect the ability to detect small pipeline leaks. Our method is based on determining the soil temperature gradient above a buried district heating channel. The equivalent thermal conductivity of a wet insulation (λeq) value of 0.5 W/(m·K) was used to mimic a small water leakage. To evaluate the heat loss through the channel cross section, the heat conduction model was used for the pipe insulation, the concrete, and the soil, while the convection model was considered within the channel. The following effects were used to simulate different operating conditions: heat convection at the soil surface, leakage only from the supply or return pipe, soil height above the channel, soil thermal conductivity, and pipe diameter. With the exception of leakage only from the return pipe and low soil thermal conductivity 0.4 W/(m·K), the results showed a doubling of the soil temperature gradient when compared wit... [more]

The yokeless and segmented armature axial flux machine is considered an excellent topology for electric vehicles application. However, its performance is severely limited by the stator cooling system. The heat pipe, as the small size, lightweight, but highly efficient passive phase-change cooling element, has been attracting more and more attention in the thermal management methods of electric motors. Therefore, the relationship between the thermal performance of the heat pipe with temperature is measured in detail through an experimental test platform in this paper. Further, a novel stator cooling structure that combines the heat pipe with the housing water-cooling method is introduced to improve the temperature distribution of the stator. Computational fluid dynamics (CFD) simulation verifies that the proposed cooling structure can accelerate the release of heat from the stator and reduce the temperature of the stator significantly.

This study is an investigation of air pollutant emission abatement in the electricity generation sector from fossil-fuel power plants in Taiwan in 2014 and 2018. PM concentrations are determined by the results of regular tests, while SOx and NOx are determined by continuous emission monitoring systems (CEMS) of flue gas from power plants. The results indicate that electricity generation from fossil-fuel power plants increased by 13.8% from 2014 to 2018. However, emissions of air pollutants from fossil-fuel power plants declined during this period. The results indicate that the annual emissions of SOx, NOx, and PM were 40,826, 59,196, and 5363 tons per year (TPY), respectively, in 2014. The emissions decreased to 30,097 TPY (28% reduction) for SOx, 48,530 TPY (18% reduction) for NOx, and 4496 TPY (16% reduction) for PM in 2018. The ensemble mean values of each air pollutant emission factor also decreased significantly. SOx emissions decreased from 0.2443 to 0.1583 mg/kWh (35% reduction)... [more]

Due to the existence of a Dean vortex in a U-tube, the flow and heat transfer process of supercritical methane is complex, and its thermophysical property are greatly influenced by different factors. Based on computational fluid dynamics theory, the numerical simulation of the turbulent flow and heat transfer characteristics of supercritical methane in a U-tube with an inner diameter of 10 mm and a radius of curvature of 27 mm carried out by using the finite volume method. On the basis of verifying the reliability of the model, the influences of inlet mass flux (G), heat flux on the tube wall boundary (q), pressure on the outlet (P), and gravity acceleration factors (g) on heat transfer characteristics were analyzed. The calculation results show that the sensitivity of the effects of G, q, P, and g on the heat transfer coefficient is, from large to small, in the order of P, G, g, and q. Compared with a horizontal straight tube, a U-tube can significantly improve heat transfer in the el... [more]

The processing of Chirp data is limited by the usual recording of the signal envelope, which enhances its immediate visibility but prevents applying methods based on wave equations. This is normally not the case for Boomer data. However, both systems are monochannel instruments, which cannot estimate properly the propagation velocity of the signal in the rocks. In this paper, we present two theorems: the first one links the Chirp or Boomer source spectrum with an expected amplitude decay curve; the second one defines conditions for the deconvolution stability of the enveloped Boomer signal when the full waveform of the source signal is known. In this way, we can jointly process and integrate heterogeneous surveys including both data types. We validated the proposed algorithms by applying them to synthetic and real data. The presented tools can improve the image resolution and the characterization of geological formations in marine surveys by reflectivity anomalies, which are distorted... [more]

The global increase in energy demand and the decreasing number of newly discovered hydrocarbon reservoirs caused by the relatively low oil price means that it is crucial to exploit existing reservoirs as efficiently as possible. Optimization of the reservoir control may increase the technical and economic efficiency of the production. In this paper, a novel algorithm that automatically determines the intelligent control maximizing the NPV of a given production process was developed. The idea is to build an auto-adaptive parameterized decision tree that replaces the arbitrarily selected limit values for the selected attributes of the decision tree with parameters. To select the optimal values of the decision tree parameters, an AI-based optimization tool called SMAC (Sequential Model-based Algorithm Configuration) was used. In each iteration, the generated control sequence is introduced into the reservoir simulator to compute the NVP, which is then utilized by the SMAC tool to vary the... [more]