Energies, Volume 13, Issue 7 (April-1 2020) – 326 articles

A fractal discrete fracture network based model was proposed for the gas production prediction from a fractured shale reservoir. Firstly, this model was established based on the fractal distribution of fracture length and a fractal permeability model of shale matrix which coupled the multiple flow mechanisms of slip flow, Knudsen diffusion, surface diffusion, and multilayer adsorption. Then, a numerical model was formulated with the governing equations of gas transport in both a shale matrix and fracture network system and the deformation equation of the fractured shale reservoir. Thirdly, this numerical model was solved within the platform of COMSOL Multiphysics (a finite element software) and verified through three fractal discrete fracture networks and the field data of gas production from two shale wells. Finally, the sensitivity analysis was conducted on fracture length fractal dimension, pore size distribution, and fracture permeability. This study found that cumulative gas production increases up to 113% when the fracture fractal length dimension increases from 1.5 to the critical value of 1.7. The gas production rate declines more rapidly for a larger fractal dimension (up to 1.7). Wider distribution of pore sizes (either bigger maximum pore size or smaller minimum pore size or both) can increase the matrix permeability and is beneficial to cumulative gas production. A linear relationship is observed between the fracture permeability and the cumulative gas production. Thus, the fracture permeability can significantly impact shale gas production. Full article

In order to improve the Direct Current (DC) bus utilization ratio and realize harmonic suppression of a five-phase induction motor, the SVPWM (Space Vector Pulse Width Modulation) algorithm was researched in depth. Based on an analysis of the present SVPWM algorithm and the volt-second balance principle, a dynamic and adjustable new pattern four-vector SVPWM algorithm was proposed. The algorithm uses the modulation index and zero vector to improve the characteristics of the inductor motor, the function relationship with real-time dynamic ratio between the action–time ratio of the space voltage vector and the modulation index was proposed to maximize DC bus utilization ratio, and the random zero-vector dynamic modulation mode was used to reduce harmonic influence, being able to spread harmonics concentrated around certain frequencies across a wider frequency band and thus produce a more continuous and uniform power spectrum. The new algorithm model was built using Matlab/Simulink, and the simulation and experimental results demonstrated that the algorithm is effective and feasible. Full article

Three-level converters have drawn extensive attention due to their ability to deliver high-quality power. High semiconductor count is the main drawback of three-level converters. As a solution to this, a 10-switch converter is presented, that has advantages over both two- and three-level converters, simultaneously, plus it is applicable to a variety of power ranges. However, the switching pattern of 10-switch converter is not as simple as standard three-level converter due to lack of medium vectors. This paper presents a novel space vector modulation (SVM) for a 10-switch converter to reduce total harmonic distortion (THD) and common mode voltage (CMV) of this converter in comparison to prior carrier-based modulation methods. A simplified, low-cost modulation algorithm for the converter is proposed. The designed switching sequence has aimed at a low output THD and enhancement of DC bus voltage utilization. The performance of the proposed SVM is then compared to upgraded sinusoidal PWM. AC power quality and CMV of a 10-switch converter based on two modulation methods are investigated via simulation models. It was validated via simulation and experimental models that the proposed SVM utilized DC bus voltage more efficiently, generated remarkably less THD compared to other methods, and had a lower peak and rms CMV. Full article

This paper presents the results of numerical experiments on fire development and the backdraft phenomenon. The numerical model of fire development built with the use of Ansys Fluent was then validated based on literature data taken from real fire experiments. Some theoretical foundations of airflow and combustion modelling were added. Some features of the numerical model, which allowed for its high accuracy to be achieved, were widely discussed. Since large buoyancy forces were involved, to reproduce the decrease of the atmospheric pressure with height, a variable static pressure was applied using UDF (user-defined function).The results showed good accordance taking into account both the temperature profiles and the distribution of the airflow velocity. Once the model was validated, the research was extended to examine the backdraft phenomenon. The results revealed characteristic phases of the phenomenon and the occurrence of the gravity current as well, which were reported by empirical experiments. Full article

Railways around the world are experiencing growth in traffic flow, but the problem concerning how to optimize the utilization of capacity is still demands significant research. To accommodate the increasing traffic demand, the high-speed railway operator in China is interested in understanding the potential benefit of adopting reasonable headway to balance the safety and efficiency of train operations. In this study, a compress timetable scheduling model based on the UIC Code 406 method is presented to evaluate the line capacity. In this model, train headway is not pre-fixed as in the existing research, but considers the actual operating conditions and is calculated using actual running data. The results of the case study show that refined headway calculations generally have positive capacity effects. Full article

Crude oil is one of the strategic energies and plays an increasingly critical role effecting on the world economic development. The fluctuations of crude oil prices are caused by various extrinsic and intrinsic factors and usually demonstrate complex characteristics. Therefore, it is a great challenge for accurately forecasting crude oil prices. In this study, a self-optimizing ensemble learning model incorporating the improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN), sine cosine algorithm (SCA), and random vector functional link (RVFL) neural network, namely ICEEMDAN-SCA-RVFL, is proposed to forecast crude oil prices. Firstly, we employ ICEEMDAN to decompose the raw series of crude oil prices into a group of relatively simple subseries. Secondly, RVFL is used to forecast the target values for each decomposed subseries individually. Due to the complex parameter settings of ICEEMDAN and RVFL, SCA is introduced to optimize the parameters for ICEEMDAN and RVFL in the above decomposition and prediction stages simultaneously. Finally, we assemble the predicted values of all individual subseries as the final predicted values of crude oil prices. Our proposed ICEEMDAN-SCA-RVFL significantly outperforms the single and ensemble benchmark models, as demonstrated by a case study conducted using the time series of West Texas Intermediate (WTI) daily crude oil spot prices. Full article

This paper deals with the application of an electric vehicle (EV) motor inverter and its batteries as an energy storage device supporting the operation of home electrical installation. This additional functionality of EV is called a Vehicle-to-Home (V2H) service. Two kind of services are considered: a peak shaving and an emergency power supply. The simulation model developed in the PSCAD program is presented. It allows for the examination of the EV battery control and operation during EV driving and parking. Additionally, it allows an evaluation of the availability of home installation for the V2H service. Control algorithms enabling the implementation of discussed work options are presented. Results of simulations are presented illustrating the EV control and operation in different operational modes. Full article

The whey is a byproduct of the dairy industry that, if not treated properly, can cause serious environmental pollution problems. Anaerobic treatment is an alternative for its recovery, since, in addition to reducing the organic load. it allows the generation of value-added products such as volatile fatty acids (VFA) and biogas. However, the process is very complex and requires specific operating conditions that guarantee its stability and favor the production of value-added compounds. In this work, an unstructured mathematical model is proposed to evaluate the dynamic behavior of the stages of the anaerobic degradation process of the whey (i.e., hydrolysis, acidogenesis, acetogenesis and methanogenesis). The proposed model considers the dynamic variation in pH during the experiment. To validate the model, an experimental set was carried out at pH and temperature conditions that favor the production of VFAs. Experimental results show that the anaerobic treatment of the raw cheese whey favors pH = 5.5; for T = 40 °C, the maximum VFA production is obtained (30.71 g_COD L⁻¹), and for T = 35 °C, a 45.81% COD degradation is reached. The proposed model considers the effect of pH and temperature and it is validated in the region where the experimental tests were carried out. The model parameters were estimated using the Levenberg–Marquardt method, obtaining coefficients of determination R² > 0.94. The proposed model can describe the dynamic behavior of the key variables in the anaerobic treatment of raw cheese whey at different pH and temperature conditions, finding that VFA production is favored at pH ≥ 7, while the highest COD removal results in acidic conditions Full article

In this paper a comparison of the wideband power sources of a pulse width modulation (PWM) inverter and a power supply composed of an audio power amplifier and a two-channel arbitrary generator is discussed. Their application is to supply a step-up current transformer for generation of the distorted current required to test the transformation accuracy of the distorted currents of the inductive current transformers. The proposed equations allow to calculate the maximum rms values of higher harmonic of distorted currents for its required main harmonic component. Moreover, they also enable the calculation of the maximum rms values of the main harmonic of the distorted current for which the required higher harmonic component may be obtained. This defines the usable bandwidth of the tested power source for their specific load. During work on high inductive impedance, the maximum voltage is the limitation that determines the higher harmonic value. While for resistive loads, the maximum current and the transistor’s slew rate are the limiting factors. The usage of the compensation system for the inductive reactance of the step-up current transformer under supply significantly increased its maximum output current. Its rms value with a 10% higher harmonic component up to 5 kHz was almost 400 A instead 100 A for the PWM-based power source and about 800 A instead 200 A for the power supply system with the audio amplifier. Full article

Demand response (DR) is an integral component of smart grid operations that offers the necessary flexibility to support its decarbonisation. In incentive-based DR programs, deviations from the scheduled DR capacity affect the grid’s energy balance and result in revenue losses for the DR participants. This issue aggravates with increasing DR delivery from participants such as large consumer buildings who have limited standard methods to follow for DR capacity scheduling. Load curtailment based DR capacity availability from such consumers can be forecasted reliably with the help of supervised machine learning (ML) models. This study demonstrates the development of data-driven ML based total and flexible load forecast models for a retail building. The ML model development tasks such as data pre-processing, training-testing dataset preparation, cross-validation, algorithm selection, hyperparameter optimisation, feature ranking, model selection and model evaluation are guided by deployment-centric design criteria such as reliability, computational efficiency and scalability. Based on the selected performance metrics, the day-ahead and week-ahead ML based load forecast models developed for the retail building are shown to outperform the timeseries persistence models used for benchmarking. Furthermore, the deployment of these models for DR capacity scheduling is proposed as an ML pipeline that can be realised with the help of ML workflows, computational resources as well as systems for monitoring and visualisation. The ML pipeline ensures faster, cost-effective and large-scale deployment of forecast models that support reliable DR capacity scheduling without affecting the grid’s energy balance. Minimisation of revenue losses encourages increased DR participation from large consumer buildings, ensuring further flexibility in the smart grid. Full article

With the global increase in demand for energy, energy conservation of research and development buildings has become of primary importance for building owners. Knowledge based on the patterns in energy consumption of previous years could be used to predict the near-future energy usage of buildings, to optimize and facilitate more effective energy consumption. Hence, this research aimed to develop a generic model for predicting energy consumption. Air-conditioning was used to exemplify the generic model for electricity consumption, as it is the process that often consumes the most energy in a public building. The purpose of this paper is to present this model and the related findings. After causative factors were determined, the methods of linear regression and various machine learning techniques—including the earlier machine learning techniques of support vector machine, random forest, and multilayer perceptron, and the later machine learning techniques of deep neural network, recurrent neural network, long short-term memory, and gated recurrent unit—were applied for prediction. Among them, the prediction of random forest resulted in an R² of 88% ahead of the first month and 81% ahead of the third month. These experimental results demonstrate that the prediction model is reliable and significantly accurate. Building owners could further enrich the model for energy conservation and management. Full article

This paper presents the wind energy potential and wind characteristics for 25 wind sites in Eritrea, based on wind data from the years 2000–2005. The studied sites are distributed all over Eritrea, but can roughly be divided into three regions: coastal region, western lowlands, and central highlands. The coastal region sites have the highest potential for wind power. An uncertainty, due to extrapolating the wind speed from the 10-m measurements, should be noted. The year to year variations are typically small and, for the sites deemed as suitable for wind power, the seasonal variations are most prominent in the coastal region with a peak during the period November–March. Moreover, Weibull parameters, prevailing wind direction, and wind power density recalculated for 100 m above ground are presented for all 25 sites. Comparing the results to values from the web-based, large-scale dataset, the Global Wind Atlas (GWA), both mean wind speed and wind power density are typically higher for the measurements. The difference is especially large for the more complex-terrain central highland sites where GWA results are also likely to be more uncertain. The result of this study can be used to make preliminary assessments on possible power production potential at the given sites. Full article

Successful transitioning to a circular economy city requires a holistic and inclusive approach that involves bringing together diverse actors and disciplines who may not have shared aims and objectives. It is desirable that stakeholders work together to create jointly-held perceptions of value, and yet cooperation in such an environment is likely to prove difficult in practice. The contribution of this paper is to show how collaboration can be engendered, or discord made transparent, in resource decision-making using a hybrid Game Theory approach that combines its inherent strengths with those of scenario analysis and multi-criteria decision analysis. Such a methodology consists of six steps: (1) define stakeholders and objectives; (2) construct future scenarios for Municipal Solid Waste Management; (3) survey stakeholders to rank the evaluation indicators; (4) determine the weights for the scenarios criteria; (5) reveal the preference order of the scenarios; and (6) analyse the preferences to reveal the cooperation and competitive opportunities. To demonstrate the workability of the method, a case study is presented: The Tyseley Energy Park, a major Energy-from-Waste facility that treats over two-thirds of the Municipal Solid Waste of Birmingham in the UK. The first phase of its decision-making involved working with the five most influential actors, resulting in recommendations on how to reach the most preferred and jointly chosen sustainable scenario for the site. The paper suggests a supporting decision-making tool so that cooperation is embedded in circular economy adoption and decisions are made optimally (as a collective) and are acceptable to all the stakeholders, although limited by bounded rationality. Full article

An increase in the neutral current results in a malfunction of the low energy over current (LCO) protective relay and raises the neutral-to-ground voltage in three-phase, four-wire radial distribution feeders. Thus, the key point for mitigating its effect is to keep the current under a specific level. The most common approach for reducing the neutral current caused by the inherent imbalance of distribution feeders is to rearrange the phase connection between the distribution transformers and the load tapped-off points by using the metaheuristics algorithms. However, the primary task is to obtain the effective load data for phase rearrangement; otherwise, the outcomes would not be worthy of practical application. In this paper, the effective load data can be received from the feeder terminal unit (FTU) installed along the feeder of Taipower. The net load data consisting of customers’ power consumption and the power generation of distributed energy resources (DERs) were measured and transmitted to the feeder dispatch control center (FDCC). This paper proposes a method of establishing the equivalent full-scale net load model based on FTU data format, and the long short-term memory (LSTM) was adopted for monthly load forecasting. Furthermore, the full-scale net load model was built by the monthly per hour load data. Next, the particle swarm optimization (PSO) algorithm was applied to rearrange the phase connection of the distribution transformers with the aim of minimizing the neutral current. The outcomes of this paper are helpful for the optimal setting of the limit current of the LCO relay and to avoid its malfunction. Furthermore, the proposed method can also improve the three-phase imbalance of distribution feeders, thus reducing extra power loss and increasing the operating efficiency of three-phase induction motors. Full article

In the power industry, the deployment of smart grid resources in power systems has become an issue of major interest. The deployment of smart grid resources represents an additional uncertainty in the integrated generation and transmission planning that raises uncertainties in investment-related decision making. This paper presents a new power system planning method for the integration of electric vehicles (EVs) and wind power generators into power systems. An interval-stochastic programming method is used to account for the heterogeneous uncertainties attributable to natural variability and lack of knowledge. The numerical results compare the multiple integration scenarios and verifies the effectiveness of the proposed method in terms of cost distribution and regret cost. Full article

The major drawback of photovoltaic (PV) systems is their dependence on environmental conditions, such as solar radiation and temperature. Because of this dependency, maximum power point tracking (MPPT) control methods are used in PV systems in order to extract maximum power from the PV panels. This study proposes a controller with a hybrid structure based on angle of incremental conductance (AIC) method and Interval Type-2 Takagi Sugeno Kang fuzzy logic controller (IT2-TSK-FLC) for MPPT. MPPT performance of proposed hybrid controller is evaluated via detailed simulation studies and dSPACE-based experimental study. The results validate that the proposed hybrid controller offers fast-tracking speed, high stability, and robust performance against uncertainties arising from disturbance to inputs of the PV system. Full article

The effects of particle shape differences on binary mixture shear flows are investigated using the Discrete Element Method (DEM). The binary mixtures consist of frictionless rods and disks, which have the same volume but significantly different shapes. In the shear flows, stacking structures of rods and disks are formed. The effects of the composition of the mixture on the stacking are examined. It is found that the number fraction of stacking particles is smaller for the mixtures than for the monodisperse rods and disks. For binary mixtures with small particle shape differences, the mixture stresses are bounded by the stresses of the two corresponding monodisperse systems. However, for binary mixtures with large particle shape differences, the stresses of the mixtures can be larger than the stresses of the monodisperse systems at large solid volume fractions because larger differences in particle shape cause geometrical interference in packing, leading to stronger particle–particle interactions in the flow. The stresses in dense binary mixtures are found to be exponential functions of the order parameter, which is a measure of particle alignment. Based on the simulation results, an empirical expression for the bulk friction coefficient (ratio of the shear stress to normal stress) for dense binary flows is proposed by accounting for the effects of particle alignment and solid volume fraction. Full article

Considering the fact that electric vehicle battery charging based on the current charging station is time-consuming, the charging technology needs to improve in order to increase charging speed, which could reduce range anxiety and benefit the user experience of electric vehicle (EV). For this reason, a 1 MW battery charging station is presented in this paper to eliminate the drawbacks of utilizing the normal 480 VAC as the system input to supply the 1 MW power, such as the low power density caused by the large volume of the 60 Hz transformer and the low efficiency caused by the high current. The proposed system utilizes the grid input of single-phase 8 kVAC and is capable of charging two electric vehicles with 500 kW each, at the same time. Therefore, this paper details how high-voltage SiC power modules are the key enabler technology, as well as the selection of a resonant-type input-series, output-parallel circuitry candidate to secure high power density and efficiency, while intelligently dealing with the transient processes, e.g., pre-charging process and power balancing among modules, and considering the impact on the grid, are both of importance. Full article

Data Distribution Service (DDS) has emerged as a potential solution for data communication challenges in smart grids. DDS is designed to support quality communication for large scale real-time systems through a wide range of QoS policies. However, a smart grid involves various types of communication applications running on different computing environments. Some environments have limited computing resources such as small memory and low performance, which makes it difficult to accommodate DDS. In this paper, we present a feature-based approach for tailoring DDS to configure lightweight DDS by selecting only the necessary features for the application in consideration of the resource constraints of its running environment. This allows DDS to serve as a uniform communication middleware across the smart grid, which is critical for interoperability. We analyze DDS in terms of features and design them using Unified Modeling Language (UML) and Object Constraint Language (OCL) based on inheritance and overriding. We define a formal notion of feature composition to build DDS configurations. We implemented the approach in OpenDDS and demonstrate its application to different application environments. We also experimented the approach for the efficiency of configured DDS in terms of resource utilization. The results show that configured DDS is viable for efficient and quality data communication for applications that run on an environment with limited computing capability. Full article

This paper presents the results of a research project aimed at evaluating the unconventional natural gas potential of the autochthonous Miocene sediments in the Polish part of the Carpathian Foredeep. The primary objective of the study was to re-evaluate the biogenic gas generation system within Miocene sediments, paying special attention to unconventional gas resources accumulated in tight mudstone formations. The four-dimensional (4D) petroleum system modeling method (PetroMod software) was used to reconstruct the basin geometry and three-dimensional (3D) evolution through a geological timescale, in particular the progress of gas generation, migration, and accumulation processes, as well as their consequences for gas exploration and development. Special attention was paid to the dynamics of gas generation processes and the advancement of sediment compaction and their time dependence, as well as to the progress and outcomes of gas migration and accumulation processes. The results indicate significant potential for unconventional gas accumulations in mudstone reservoirs. However, part of the biogenic gas resources occurs in a dispersed form. Analysis of the dynamics of biogenic gas generation and accumulation conducted on a basin scale and within particular sedimentary complexes and depth intervals allowed an indication of the premises regarding the most favorable zones for mudstone–claystone reservoir exploration. Full article

Hydraulic hybrid powertrains provide an opportunity for specific applications, such as heavy-duty vehicles based on high-power density, which has not been included in other types of hybrid powertrains. Among the various architectures of hybrid vehicles, power-split hybrids have a greater possibility of producing better fuel efficiency than other hybrid architectures. This study analyzed the possible energy-saving characteristics of power-split hydraulic hybrid vehicles (HHVs); this has not been comprehensively described in previous studies. A typical configuration of power-split HHVs was modeled with the FTP-72 driving cycle using a novel simulation method that considered the dynamic and thermal behaviors together. The characteristics were analyzed in comparison to a power-split hydrostatic transmission (HST), which is designed with the same conditions except for hydraulic energy storage. The power-split HHV not only has a better fuel efficiency, but it also shows system energy-saving characteristics. The power-split HHV has more chances for engine idling, which is directly related to fuel consumption savings due to engine stop. Additionally, more engine idling time enables the system to operate in a more efficient area on the engine map by load leveling. The results for the system temperature show that the power-split HHV offers the possibility to deliver better thermal management because it prevents the waste of braking power, which is especially crucial for hydraulic systems in comparison to other power systems such as electric or mechanical power systems. The ease of thermal management results in less energy consumption for cooling down the system temperature by minimizing the cooling system, as well as in a better thermal stability for the hydraulic system. The power-split HHV characteristics analyzed in this study can be used to design and organize the system control logic while developing power-split HHVs. Full article

Eco-driving is one of the most important strategies for significantly reducing the energy consumption of railways with low investments. It consists of designing a way of driving a train to fulfil a target running time, consuming the minimum amount of energy. Most eco-driving energy savings come from the substitution of some braking periods with coasting periods. Nowadays, modern trains can use regenerative braking to recover the kinetic energy during deceleration phases. Therefore, if the receptivity of the railway system to regenerate energy is high, a question arises: is it worth designing eco-driving speed profiles? This paper assesses the energy benefits that eco-driving can provide in different scenarios to answer this question. Eco-driving is obtained by means of a multi-objective particle swarm optimization algorithm, combined with a detailed train simulator, to obtain realistic results. Eco-driving speed profiles are compared with a standard driving that performs the same running time. Real data from Spanish high-speed lines have been used to analyze the results in two case studies. Stretches fed by 1 × 25 kV and 2 × 25 kV AC power supply systems have been considered, as they present high receptivity to regenerate energy. Furthermore, the variations of the two most important factors that affect the regenerative energy usage have been studied: train motors efficiency ratio and catenary resistance. Results indicate that the greater the catenary resistance, the more advantageous eco-driving is. Similarly, the lower the motor efficiency, the greater the energy savings provided by efficient driving. Despite the differences observed in energy savings, the main conclusion is that eco-driving always provides significant energy savings, even in the case of the most receptive power supply network. Therefore, this paper has demonstrated that efforts in improving regenerated energy usage must not neglect the role of eco-driving in railway efficiency. Full article

Organic Rankine Cycle (ORC) turbogenerators are a well-established technology to recover from medium to ultra-low grade heat and generate electricity, or heat and work as cogenerative units. High firmness, good reliability and acceptable efficiency guarantee to ORCs a large range of applications: from waste heat recovery of industrial processes to the enhancement of heat generated by renewable resources like biomass, solar or geothermal. ORC unit coupled with biomass boiler is one of the most adopted arrangements. However, despite biomass renewability, it is mandatory to evaluate the environmental impact of systems composed by boilers and ORCs taking into account the entire life cycle. To this purpose, the authors perform a life cycle assessment of a commercially available 150 kW cogenerative ORC unit coupled with a biomass boiler to assess the global environmental performance. The system is modelled in SimaPro using different approaches. Results show that the most impacting processes in terms of CO₂ equivalent emissions are the ones related to biomass production and organic fluid leakages with 71% and 19% of the total. Therefore, being fluid release in the environment high impacting, a comparison among three fluids is also performed. Analysis shows that adopting a hydrofluoroolefin fluid with a low global warming potential instead of the hydrocarbon fluid as already used in the cycle guarantees a significant improvement of the environmental performance. Full article

As an important driving force to promote the energy revolution, the emergence of the energy internet has provided new ideas for the marketization and flexibility of multi-energy transactions. How to realize multi-energy joint trading is a key issue in the development of the energy market. An urban energy internet market trading model among energy suppliers, energy service providers and the large users in the urban area, based on tripartite game theory, is established in this paper. Considering the cost–income function of each market entity and the basic market trading mechanism, a new game-tree search method is proposed to solve the Nash equilibria for the game model. The Nash equilibria of the tripartite game can be obtained, and the market transaction status corresponding to the Nash equilibria is analyzed from the perspective of the market transactions. The multi-energy joint transaction and market equilibria can be easily implemented for the bids and offers of the multiple energy entities in the urban energy internet market. Full article

One of the established unstable power swing (out-of-step) detection algorithms in micro grid/smart grid power systems uses a trajectory of apparent impedance in the R-X plane. However, this algorithm is not suitable for fast out-of-step conditions and it is hard to detect out-of-step conditions exactly. Another algorithm for out-of-step detection is using phasor measurement units (PMUs). However, PMUs need extra equipment. This paper presents the out-of-step detection algorithm using the trajectory of complex power. The trajectory of complex power and generator mechanical power is used to identify out-of-step conditions. A second order low pass digital filter is used to extract the generator mechanical power from the complex power. Variations of complex power are used to identify equilibrium points between stable and unstable conditions. The proposed out-of-step algorithm is based on the modification of assessment of a transient stability using equal area criterion (EAC). The proposed out-of-step algorithm is verified and tested by using alternative transient program/electromagnetic transient program (ATP/EMTP) MODELS. Full article

While the vast majority of the wind energy market is dominated by megawatt-size wind turbines, the increasing importance of distributed electricity generation gives way to small, personal-size installations. Due to their situation at relatively low heights and above-ground levels, they are forced to operate in a low energy-density environment, hence the important role of rotor optimization and flow studies. In addition, the small wind turbine operation close to human habitats emphasizes the need to ensure the maximum reliability of the system. The present article summarizes a case study of a small wind turbine (rated power 350 W @ 8.4 m/s) from the point of view of aerodynamic performance (efficiency, flow around blades). The structural strength analysis of the blades milled for the prototype was performed in the form of a one-way Fluid–Structure Interaction (FSI). Blade deformations and stresses were examined, showing that only minor deformations may be expected, with no significant influence on rotor aerodynamics. The study of an unorthodox material (PA66 MO polyamide) and application of FSI to examine both structural strength and blade deformation under different operating conditions are an approach rarely employed in small wind turbine design. Full article

A hydrophobic perfluoropolyether (PFPE)-based polymer, namely Fluorolink^® P56, was studied instead of the commonly used polytetrafluoroethylene (PTFE), in order to enhance gas diffusion media (GDM) water management behavior, on the basis of a previous work in which such polymers had already proved to be superior. In particular, an attempt to optimize the GDM production procedure and to improve the microporous layer (MPL) adhesion to the substrate was carried out. Materials properties have been correlated with production routes by means of both physical characterization and electrochemical tests. The latter were performed in a single PEM fuel cell, at different relative humidity (namely 80% on anode side and 60%/100% on cathode side) and temperature (60 °C and 80 °C) conditions. Additionally, electrochemical impedance spectroscopy measurements were performed in order to assess MPLs properties and to determine the influence of production procedure on cell electrochemical parameters. The durability of the best performing sample was also evaluated and compared to a previously developed benchmark. It was found that a final dipping step into PFPE-based dispersion, following MPL deposition, seems to improve the adhesion of the MPL to the macro-porous substrate and to reduce diffusive limitations during fuel cell operation. Full article

Engines waste a major part of their fuel energy in the jacket water and exhaust gas. Transcritical Rankine cycles are a promising technology to recover the waste heat efficiently. The working fluid selection seems to be a key factor that determines the system performances. However, most of the studies are mainly devoted to compare their thermodynamic performances of various fluids and to decide what kind of properties the best-working fluid shows. In this work, an active working fluid selection instruction is proposed to deal with the temperature match between the bottoming system and cold source. The characters of ideal working fluids are summarized firstly when the temperature match method of a pinch analysis is combined. Various selected fluids are compared in thermodynamic and economic performances to verify the fluid selection instruction. It is found that when the ratio of the average specific heat in the heat transfer zone of exhaust gas to the average specific heat in the heat transfer zone of jacket water becomes higher, the irreversibility loss between the working fluid and cold source is improved. The ethanol shows the highest net power output of 25.52 kW and lowest electricity production cost of $1.97/(kWh) among candidate working fluids. Full article

In Poland, various solar collector systems are used; among them, the most popular are flat plate collectors (FPCs) and evacuated tube collectors (ETCs). The work presents two installations located at a distance of 80 km apart, working in similar external conditions. One of them contains 120 flat plate collectors and works for the preparation of hot water in a swimming pool building; the second one consists of 32 evacuated tube collectors with a heat pipe and supports the preparation of domestic hot water for a multi-family house. During the comparison of the two quite large solar installations, it was confirmed that the use of evacuated tube solar collectors shows a much better solar energy productivity than flat plate collectors for the absorber area. Higher heat solar gains (by 7.9%) were also observed in the case of the gross collector area. The advantages of evacuated tube collectors are observed mainly during colder periods, which allows for a steadier thermal energy production. Full article

Electric vehicles (EVs) have been around for more than a hundred years. Nevertheless, their deployment has not been a sustainable success up until now. Many scientists, engineers and policymakers argue that EVs are a promising, maybe even indispensable option to achieve ambitious decarbonization goals, if powered by electricity from renewable energy sources. At the moment, the EVs market is gaining a lot of momentum and we may be near the point of no return for a sustained mass market deployment of electric vehicles. Many papers exist that describe future prospects of EVs. In our commentary we try to provide a bigger picture view and look at market and societal aspects. We analyze why previous generations of EVs were not successful and how current electric vehicles could become a sustainable success. We perform a semi-quantitative Strengths, Weaknesses, Opportunities, Threats (SWOT) analysis and find that current electric vehicle designs are technologically on par with or better than conventional alternatives. Car buyers go electric when the economics make sense to them. We conclude that incentives are needed for electric vehicles until battery costs lower—as much as to allow EVs to become cheaper—from a total cost of ownership (TCO) perspective, than other alternatives. Other policy measures are needed to overcome remaining barriers, especially in supporting the setup and operation of publicly accessible recharging points to overcome range anxiety. EVs in isolation may not be the next mobility killer app. The real next mobility killer app may emerge as an autonomous shared EV in a world where the border between public and private transport will cease to exist. The findings of our commentary are relevant for scientists, policymakers and industry. Full article