Inventions, Volume 5, Issue 4 (December 2020) – 14 articles

The present inquiry studies the influence of mass transfer in magnetohydrodynamics (MHD) upper-convected Maxwell (UCM) fluid flow on a stretchable, porous subsurface. The governing partial differential equations for the flow problem are reformed to ordinary differential equations through similarity transformations. The numerical outcomes for the arising non-linear boundary value problem are determined by implementing the successive linearization method (SLM) via Matlab software. The accuracy of the SLM is confirmed through known methods, and convergence analysis is also presented. The graphical behavior for all the parametric quantities in the governing equations across the velocity and concentration magnitudes, as well as the skin friction and Sherwood number, is presented and debated in detail. A comparability inquiry of the novel proposed technique, along with the preceding explored literature, is also provided. It is expected that the current achieved results will furnish fruitful knowledge in industrious utilities and correlate with the prevailing literature. Full article

This paper reviews the energy storage participation for ancillary services in a microgrid (MG) system. The MG is used as a basic empowering solution to combine renewable generators and storage systems distributed to assist several demands proficiently. However, because of unforeseen and sporadic features of renewable energy, innovative tasks rise for the consistent process of MGs. Power management in MGs that contain renewable energy sources (RES) can be improved by energy storage. The energy storage systems (ESSs) have several merits, such as supply and demand balancing, smoothing of RES power generation, enhancing power quality and reliability, and facilitating the ancillary services like voltage and frequency regulation in MG operation. The integration of ESS technology has become a solution to the challenges the power distribution networks face in achieving improved performance. By simplifying a smooth and robust energy balance within the MG, storage devices match energy generation to consumption. MG, and its multidisciplinary portrait of current MG drivers, tasks, real-world applications, and upcoming views are elucidated in this paper. Full article

This paper presents the effect of grinding wheel contact stiffness on the plunge grinding cycle. First, it proposes a novel model of the generalized plunge grinding system. The model is applicable to all plunge grinding operations including cylindrical, centerless, shoe-centerless, internal, and shoe-internal grinding. The analysis of the model explicitly describes transient behaviors during the ramp infeed and the spark-out in the plunge grinding cycle. Clarification is provided regarding the premise that the system stiffness is composed of machine stiffness and wheel contact stiffness, and these stiffnesses significantly affect productivity and grinding accuracy. The elastic deflection of the grinding wheel is accurately measured and formulas for representing the deflection nature under various contact loads are derived. The deflection model allows us to find the non-linear contact stiffness with respect to the normal load. The contact stiffnesses of four kinds of grinding wheels with different grades and bond materials are presented. Both cylindrical grinding and centerless grinding tests are carried out, and it is experimentally revealed that the time constant at ramp infeed and spark-out is significantly prolonged by reducing the grinding force. It is verified that a simulation of the grinding tests using the proposed model can accurately predict critical parameters like forces and machine deflection during plunge grinding operations. Finally, this paper provides a guideline for grinding cycle design in order to achieve the required productivity and grinding accuracy. Full article

In recent years, machine learning (ML) tools have gained tremendous momentum and received wide-spread attention in different segments of modern-day life. As part of digital transformation, the power system industry is one of the pioneers in adopting such attractive and efficient tools for various applications. Apparently, a nonthreatening, but slow-burning issue of the electric power systems is the low-frequency oscillations (LFO), which, if not dealt with appropriately and on time, could result in complete network failure. This paper addresses the role of a prominent ML family member, particle swarm optimization (PSO) tuned adaptive neuro-fuzzy inference system (ANFIS) for real-time enhancement of LFO damping in electric power system networks. It adopts and models two power system networks where in the first network, the synchronous machine is equipped with only a power system stabilizer (PSS), and in the other, the PSS of the synchronous machine is coordinated with the unified power flow controller (UPFC), a second-generation flexible alternating current transmission system (FACTS) device. Then, it develops the proposed ML approach to enhance LFO damping for both adopted networks based on the customary practices of statistical judgment. The performance measuring metrics of power system stability, including the minimum damping ratio (MDR), eigenvalue, and time-domain simulation, were used to analyze the developed approach. Moreover, the paper presents a comparative analysis and discussion with the referenced works’ achieved results to conclude the proposed PSO-ANFIS technique’s ability to enhance power system stability in real-time by damping out the unwanted LFO. Full article

For footwear insoles, high rebound performance is required in some instances such as for running, while softness for comfort is of higher importance during normal walking and standing to minimize high stress. Hence, materials with rebound performance in some scenarios and softness for other scenarios are desired. In this paper, we investigate rebound performance and hardness of composites made of a shear-thickening material and elastic foam. First, a hydrogel type of shear-thickening material (Slime) is characterized to investigate the influence of water content. After that, two particular shear-thickening hydrogels with better rebound performance (but not outstanding in the shear-thickening effect) are selected and integrated into the elastic foam to produce a composite insole. It is found that, as compared with the commercial elastic insole and commercial shear-thickening insole, softer and superior rebound performance can be achieved simultaneously only if the right shear-thickening material is used in the composite. Full article

Nowadays, by increasing energy demand and considering the importance of environmental issues in recent decades, the use of renewable energies is expanding. Among renewable energies, wind power and its technology are growing and evolving more rapidly. Resource assessment in Iran has revealed the significant potential of wind energy around the country. To further develop wind energy in the country and create large-scale wind power plants, the consideration of distributed power generation using small wind turbines for applications in agricultural and residential use is needed. Conventional small wind turbines and small wind lens turbines have been developed in recent years. In this research project, a small wind lens turbine is designed. The advantages of this turbine are an increased production capacity and reduced cut-in speed and noise pollution. In this study, a lens (or shroud) is added to a small turbine, and the maximized annual energy production (AEP) and minimization of the levelized cost of energy (LCOE) are modeled. We applied the NSGA-II algorithm for optimization to find the best answer. The input parameters in the objective function of the AEP are cut-in, cut-out, rated speeds, scale factor, and shape factor. Additionally, the input parameters in the objective function of the LCOE are the power production, initial capital cost, annual operating expenses, and balance of energy. The results indicate that installing a wind lens turbine in Kish Island led to an LCOE decrease of 56% on average, and we can see an 83% increase in the AEP. In the Firoozkooh area, an average reduction of 59% in the LCOE and 74% increase in the AEP for a wind lens turbine is observed. Full article

Data security of present-day power systems, such as the electricity market, has spurred global interest in both industry and academia. The electricity market can either be regulated (state-controlled entrance, policies, and pricing) or deregulated (open for competitors). While the security threats in a deregulated electricity market are commonly known and have been investigated for years, those in a regulated market still have scope for extensive research. Our current work focuses on exploring the data security of the regulated electricity market, and the regulated New Zealand Electricity Market (NZEM) has been considered for this research. Although the chances of cyberattacks on state-controlled regulated electricity market are relatively less, different layers of the current SCADA systems do pose some threats. In this context, we propose a decentralized Ethereum Blockchain-based end-to-end security prototype for a regulated electricity market such as the NZEM. This prototype aims to enhance data security between the different layers of the current SCADA systems. The detailed operation process and features of this prototype are presented in this work. The proposed prototype has prospects of offering improved data security solutions for the regulated electricity market. Full article

The recent advancement in computational capabilities and deployment of smart meters have caused non-intrusive load monitoring to revive itself as one of the promising techniques of energy monitoring. Toward effective energy monitoring, this paper presents a non-invasive load inference approach assisted by feature selection and ensemble machine learning techniques. For evaluation and validation purposes of the proposed approach, one of the major residential load elements having solid potential toward energy efficiency applications, i.e., water heating, is considered. Moreover, to realize the real-life deployment, digital simulations are carried out on low-sampling real-world load measurements: New Zealand GREEN Grid Database. For said purposes, MATLAB and Python (Scikit-Learn) are used as simulation tools. The employed learning models, i.e., standalone and ensemble, are trained on a single household’s load data and later tested rigorously on a set of diverse households’ load data, to validate the generalization capability of the employed models. This paper presents a comprehensive performance evaluation of the presented approach in the context of event detection, feature selection, and learning models. Based on the presented study and corresponding analysis of the results, it is concluded that the proposed approach generalizes well to the unseen testing data and yields promising results in terms of non-invasive load inference. Full article

Vast expansion in consumption is leading to natural resource scarcity and global warming. The integrated management of natural resources, such as food, energy, food (FEW) as one of the most important aspects has been proposed as a solution to meet these challenges. The FEW nexus is a world-wide solution for simultaneously assessing the development and implementation of various approaches focusing on energy, water and food security, sufficiency. This approach is intended to foster sustainable development and improve the quality of life of communities while preserving the natural, human and social capital, address the long-term sustainability challenges and protecting all-natural resources. This paper tries to review some recent research on this topic. For this purpose, first, we describe some facts about demand growth and exponential consumption in these three areas, with emphasis on presented statistics. Then, the most critical research published in this field is reviewed, considering that it took a decade or so before that the original idea was introduced. The most important policymakers of this emerging concept, including committees and conferences, and finally significant challenges and opportunities to the implementation along with future insights, are addressed. Full article

The monitoring of waste disposal sites is important in order to minimize leakages of biogas, produced by anaerobic digestion and potentially explosive and detrimental to the environment. In this research, thermal imaging from unmanned aerial vehicles (UAVs) has been proposed as a diagnostic tool to monitor urban landfills. Since the anaerobic decomposition produces heat along with biogas, thermal anomalies recorded over the soil are likely to be associated with local biogas escaping from the landfill terrain and leaving a local thermal print. A simple and novel approach, based only on the processing of thermal maps gathered by the remote sensing surveys, has been proposed for the estimation of the fugitive methane emissions from landfills. Two case studies, concerning two Italian landfills, have been presented. For one of them (Mount Scarpino, Genoa), significant thermal anomalies were identified during several UAV flights and the relevant thermal images processed to obtain a rough estimation of the associated methane leakages. For the second landfill (Scala Erre, Sassari), the thermal map did not reveal any anomaly attributable to local biogas emission. Despite some limitations outlined in the paper, the present approach is proposed as an innovative method to identify significant biogas leakages from an urban landfill and to provide a preliminary evaluation of the methane production potential. Full article

The aim of this paper is to address the gap in the academic literature towards the development of methodological approaches to the industrial ecosystem sustainability assessment. This study was focused on the industrial ecosystems formed based on an entropy model and implementing the principles of complex systems. This article systematizes the problem of applying the ecosystem approach to cross-industry interaction. A contribution to the literature was achieved by providing a systemic perspective on the sustainable industrial process. In this paper, we develop the methodological foundations to improve the understanding of integration processes’ influence on the industrial ecosystem potential. For a relevant analysis of industrial ecosystem potential, the existing patterns of system functioning were taken into account, including entropy equilibrium and the Harrington model. We illustrate our assumptions with an empirical case study of the National University of Science and Technology (NUST) “MISIS” ecosystem—“Green technologies for resource conservation” (Russia), with an assessment of ecosystem sustainability through the actors’ collaboration level. The propositions arising from this analysis provide information to help academics, policymakers, government, and individual enterprises with a more adequate understanding of the practical mechanisms and tools that help trigger the self-organization and sustainability of the industrial ecosystems. Full article

The world is targeting fully renewable power generation by the middle of the century. Distributed generation is the way to increase the penetration level of renewable energies. This paper presents load frequency control of a hybrid tidal, wind, and wave microgrid to feed an isolated island. This research is a step towards 100% renewable energy communities in remote seas/oceans islands. The wave and tidal generation systems model are presented. The study presents load frequency control through three supplementary control strategies: conventional integrators, fractional order integrator, and non-linear fractional order integrator. All the controllers of the microgrid are designed by using a novel black widow optimization technique. The applied technique is compared to other existing state-of-the-art algorithms. The results show that the black widow non-linear fractional integrator has a better performance over other strategies. Coordination between the unloaded tidal system and blade pitch control of both wind and tidal systems are adopted in the microgrid to utilize the available reserve power for the frequency support. Simulation and optimization studies are performed using the MATLAB/SIMULINK 2017a software application. Full article

The field of energy, specifically renewable energy sources (RES), is considered vital for a sustainable society, a fact that is clearly defined by the European Green Deal. It will convert the old, conventional economy into a new, sustainable economy that is environmentally sound, economically viable, and socially responsible. Therefore, there is a need for quick actions by everyone who wants to move toward energy-efficient development and new environmentally friendly behavior. This can be achieved by setting specific guidelines of how to proceed, where to start, and what knowledge is needed to implement such plans and initiatives. This paper seeks to contribute to this very important issue by appraising the ability of full-scale implementation of RES combined with energy storage in an island power system. The Greek island power system of Astypalaia is used as a case study where a battery energy storage system (BESS), along with wind turbines (WTs), is examined to be installed as part of a hybrid power plant (HPP). The simulation’s results showed that the utilization of HPP can significantly increase RES penetration in parallel with remarkable fuel cost savings. Finally, the fast response of BESS can enhance the stability of the system in the case of disturbances. Full article

Forest owners will be able to solve the problem of protecting small forest seeds from mechanical and atmospheric influences during aerial sowing, as well as the problem of manufacturing capsules in the field, saving financial, time and material resources. The process of creating a capsule by freezing the seed in a water-saturated dispersed system—immersion freezing—allows you to organize the technological properties of forest seeds depending on the initial requirements. In most cases, the quality of the seed capsule is determined by the thermophysical and mechanical properties of the components. The technological process of obtaining seed capsules for aerial seeding and the choice of freezing modes is based on a priori mathematical modeling of heat-and-mass transfer processes. The main purpose of the study is to predict the duration of the seed freezing process in a capsule with a water-saturated dispersed medium, depending on the external temperature conditions, the geometric parameters of the capsule and the seed. The cooling agent is carbon dioxide. The research is based on the use of numerical modeling methods on the platform COMSOL Multiphysics. A mathematical model is proposed that allows us to obtain the dynamics of the distribution of temperature and moisture content fields in the dispersed system and seed depending on a complex of geometric and thermophysical factors. The time of immersion freezing of the capsule with the common pine seed for the conditions considered should be in the range of 150 to 250 s. Full article