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Inventions, Volume 4, Issue 3 (September 2019)

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Cover Story (view full-size image) Measuring accurate structural response is important for condition assessment. Contact sensors are [...] Read more.
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Open AccessArticle
Determining Information Security Threats for an IoT-Based Energy Internet by Adopting Software Engineering and Risk Management Approaches
Inventions 2019, 4(3), 53; https://doi.org/10.3390/inventions4030053 - 11 Sep 2019
Viewed by 283
Abstract
This paper introduces an information security threat modeling (ISTM) scheme, which leverages the strengths of software engineering and risk management approaches, called I-SERM. The proposed I-SERM scheme effectively and efficiently prioritizes information security threats for IT systems that utilize a large number of [...] Read more.
This paper introduces an information security threat modeling (ISTM) scheme, which leverages the strengths of software engineering and risk management approaches, called I-SERM. The proposed I-SERM scheme effectively and efficiently prioritizes information security threats for IT systems that utilize a large number of sensors, such as Internet of Things (IoT)-based energy systems. I-SERM operations include determining functional components, identifying associated threat types, analyzing threat items, and prioritizing key threats with the use of software engineering tools such as product flow diagrams, use case diagrams, and data flow diagrams. By simultaneously referring to a proposed STRIDE+p matrix and a defined threat breakdown structure with reference score (TBS+r) scheme, the I-SERM approach enables systematic ISTM. To demonstrate the usability of I-SERM, this study presents a practical case aimed at electricity load balancing on a smart grid. In brief, this study indicates a substantive research direction that combines the advantages of software engineering and risk management into a systematic ISTM process. In addition, the demonstration of I-SERM in practice provides a valuable and practical reference for I-SERM application, and contributes to research in the field of information security designs for IoT-based Energy Internet systems. Full article
(This article belongs to the Special Issue IoT and Energy Internet)
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Open AccessArticle
An Internet of Things-Based Low-Power Integrated Beekeeping Safety and Conditions Monitoring System
Inventions 2019, 4(3), 52; https://doi.org/10.3390/inventions4030052 - 09 Sep 2019
Viewed by 310
Abstract
This paper proposes a holistic management and control system for the apiculture industry (Integrated Beekeeping System of holistic Management and Control – IBSMC). This integrated beehive array system mainly focuses on the regulation of bees living conditions, targeting both minimizing bee swarm mortality [...] Read more.
This paper proposes a holistic management and control system for the apiculture industry (Integrated Beekeeping System of holistic Management and Control – IBSMC). This integrated beehive array system mainly focuses on the regulation of bees living conditions, targeting both minimizing bee swarm mortality and maximizing productivity. Within the proposed IBSMC system architecture, additional security functionalities are implemented for bee monitoring, low energy consumption and incidents response. As a complete unit, the proposed IBSMC system is both a hive conditions monitoring and safety system. It communicates with the outer world using low power RF data transmission and the LoRaWAN transceivers. This paper presents the proposed IBSMC architecture consisting of new beehive cells embedded with functionalities for integrated conditions regulation and security provisions, as well as the communication protocols used for facility-conditions management, incidents’ acquisition and incidents’ response. Full article
(This article belongs to the Special Issue IoT and Energy Internet)
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Open AccessArticle
Unsteady Viscous Incompressible Bingham Fluid Flow through a Parallel Plate
Inventions 2019, 4(3), 51; https://doi.org/10.3390/inventions4030051 - 27 Aug 2019
Viewed by 375
Abstract
Numerical investigation for unsteady, viscous, incompressible Bingham fluid flow through parallel plates is studied. The upper plate drifts with a constant uniform velocity and the lower plate is stationary. Both plates are studied at different fixed temperatures. To obtain the dimensionless equations, the [...] Read more.
Numerical investigation for unsteady, viscous, incompressible Bingham fluid flow through parallel plates is studied. The upper plate drifts with a constant uniform velocity and the lower plate is stationary. Both plates are studied at different fixed temperatures. To obtain the dimensionless equations, the governing equations for this study have been transformed by usual transformations. The obtained dimensionless equations are solved numerically using the explicit finite difference method (FDM). The studio developer Fortran (SDF) 6.6a and MATLAB R2015a are both used for numerical simulations. The stability criteria have been established and the system is converged for Prandtl number P r 0.08 with Δ Y = 0.05 and Δ τ = 0.0001 as constants. As a key outcome, the steady-state solutions have been occurred for the dimensionless time τ   =   4.00 The influence of parameters on the flow phenomena and on shear stress, including Nusselt number, are explained graphically. Finally, qualitative and quantitative comparison are shown. Full article
(This article belongs to the Special Issue Recent Trends in Nanofluids)
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Open AccessReview
Modeling and Optimization of Energy Hubs: A Comprehensive Review
Inventions 2019, 4(3), 50; https://doi.org/10.3390/inventions4030050 - 23 Aug 2019
Viewed by 533
Abstract
The concept of energy hubs has grown in prominence as a part of future energy systems, driven by the spread of Distributed Energy Resources (DERs) and the inception of the smart grid. This paper systematically reviews 200 articles about energy hubs, published from [...] Read more.
The concept of energy hubs has grown in prominence as a part of future energy systems, driven by the spread of Distributed Energy Resources (DERs) and the inception of the smart grid. This paper systematically reviews 200 articles about energy hubs, published from 2007 to 2017, and summarizes them based on their modeling approach, planning and operation, economic and environmental considerations, and energy hub applications. The common applications of energy hubs are considered, such as distributed energy resources, the consideration of Plug-in Hybrid Electric Vehicles (PHEVs), and the hydrogen economy. This paper examines modeling approaches towards energy hubs, including storage and its network models; it mentions some of the optimization strategies used to tackle the efficient operation and control of energy hubs. The novelty of this work lies in the classification of research papers related to energy hubs, the development of a generic framework for modeling these multiple energy flow carriers with storage and network considerations, and the provision of solution techniques in line with energy hub optimization. Full article
(This article belongs to the Special Issue Advances in Grid Integration of Renewable Energy Systems)
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Open AccessTutorial
A Tutorial on Robust Control, Adaptive Control and Robust Adaptive Control—Application to Robotic Manipulators
Inventions 2019, 4(3), 49; https://doi.org/10.3390/inventions4030049 - 23 Aug 2019
Viewed by 396
Abstract
A tutorial on robust control, adaptive control, robust adaptive control and adaptive control of robotic manipulators is presented in a systematic manner. Some limitations of the above methods are also illustrated. The relationships between the robust control, adaptive control and robust adaptive control [...] Read more.
A tutorial on robust control, adaptive control, robust adaptive control and adaptive control of robotic manipulators is presented in a systematic manner. Some limitations of the above methods are also illustrated. The relationships between the robust control, adaptive control and robust adaptive control are demonstrated. Basic information on the joint space control, operational space control and force control is also given. This tutorial summarizes the most advanced control techniques currently in use in a very simple manner, and applies to robotic manipulators, which can provide an informative guideline for students who have little knowledge of controls or who want to understand the adaptive control of robotics in a systematic way. Full article
(This article belongs to the Special Issue Automatic Control and System Theory)
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Open AccessPatent Summary
Chronometric Quantitation of Analytes in Paper-Based Microfluidic Devices (MicroPADs) via Enzymatic Degradation of a Metastable Biomatrix
Inventions 2019, 4(3), 48; https://doi.org/10.3390/inventions4030048 - 21 Aug 2019
Viewed by 432
Abstract
The following article summarizes United States Patent Application No. US20180052155A1, titled ‘Assay Devices and Methods’ (filed 16 August 2016, published 22 February 2018). While lateral flow assays (LFAs) have revolutionized point-of-care diagnostics by enabling accurate, inexpensive, and rapid detection of biomarkers, they typically [...] Read more.
The following article summarizes United States Patent Application No. US20180052155A1, titled ‘Assay Devices and Methods’ (filed 16 August 2016, published 22 February 2018). While lateral flow assays (LFAs) have revolutionized point-of-care diagnostics by enabling accurate, inexpensive, and rapid detection of biomarkers, they typically do not provide quantitative results. Hence, there is a significant need for quantitative assays at the point of care. This patent summary describes a novel method of chronometric biomarker quantitation via enzymatic degradation of a metastable gelatin-based biomatrix, principally suited for use in paper-based microfluidic devices (microPADs). This new quantitation mechanism was designed to meet the ASSURED criteria for point-of-care diagnostic devices laid forth by the World Health Organization and may ultimately provide increased access to healthcare, at a significantly reduced cost, around the world. Full article
(This article belongs to the Special Issue Microfluidic Devices)
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Open AccessArticle
A Low-Cost Robotic Camera System for Accurate Collection of Structural Response
Inventions 2019, 4(3), 47; https://doi.org/10.3390/inventions4030047 - 21 Aug 2019
Viewed by 514
Abstract
Vision-based technologies are becoming ubiquitous when considering sensing systems for measuring the response of structures. Availability of proprietary camera systems has opened up the scope for many bridge monitoring projects. Even though structural response can be measured at high accuracies when analyzing target [...] Read more.
Vision-based technologies are becoming ubiquitous when considering sensing systems for measuring the response of structures. Availability of proprietary camera systems has opened up the scope for many bridge monitoring projects. Even though structural response can be measured at high accuracies when analyzing target motions, the main limitations to achieving even better results are camera costs and image resolution. Conventional camera systems capture either the entire structure or large/small part of it. This study introduces a low-cost robotic camera system (RCS) for accurate measurement collection of structural response. The RCS automatically captures images of parts of a structure under loading, therefore, (i) giving a higher pixel density than conventional cameras capturing the entire structure, thus allowing for greater measurement accuracy, and (ii) capturing multiple parts of the structure. The proposed camera system consists of a modified action camera with a zoom lens, a robotic mechanism for camera rotation, and open-source software which enables wireless communication. A data processing strategy, together with image processing techniques, is introduced and explained. A laboratory beam subjected to static loading serves to evaluate the performance of the RCS. The response of the beam is also monitored with contact sensors and calculated from images captured with a smartphone. The RCS provides accurate response measurements. Such camera systems could be employed for long-term bridge monitoring, in which strains are collected at strategic locations, and response time-histories are formed for further analysis. Full article
(This article belongs to the Special Issue Structural Health Monitoring and Their Applications Across Industry)
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Open AccessArticle
Noise Cancellation for HIPERLAN/2 with Open Loop Transmit Diversity Technique
Inventions 2019, 4(3), 46; https://doi.org/10.3390/inventions4030046 - 12 Aug 2019
Viewed by 574
Abstract
A new proposed method is presented, where multiple antennas have been applied into HIPERLAN/2 system in addition to employing space-time diversity technique, especially the Alamouti technique. The suggested approach is used to cancel or reduce the effect of the transmitted power using a [...] Read more.
A new proposed method is presented, where multiple antennas have been applied into HIPERLAN/2 system in addition to employing space-time diversity technique, especially the Alamouti technique. The suggested approach is used to cancel or reduce the effect of the transmitted power using a feedback signal process within the transceiver unit, especially when the antennas are closely located and working in full-mode duplexing. Several parameters including the transmitted power, the received power, and the feedback accuracy have been considered for testing the performance of the system in term of the signal to noise ratio (SNR) versus bit error rate (BER). A software programme using MATLAB and Simulink is implemented to evaluate the proposed method. The results showed that the system performance is heavily dependent on the amount of the mismatch in the feedback, the received power, and the transmitted power. The performance of the system decreases as the feedback accuracy increases when the transmitted power and the received power are constant. At the same time, the performance of the system decreases as the transmitted power increases when the received power and the mismatch are constant. Finally, the increase in the received power enhances the system performance when the other parameters are constant. Full article
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Open AccessArticle
Prediction of Solar Irradiance Based on Artificial Neural Networks
Inventions 2019, 4(3), 45; https://doi.org/10.3390/inventions4030045 - 10 Aug 2019
Viewed by 656
Abstract
Prediction of solar irradiance plays an essential role in many energy systems. The objective of this paper is to present a low-cost solar irradiance meter based on artificial neural networks (ANN). A photovoltaic (PV) mathematical model of 50 watts and 36 cells was [...] Read more.
Prediction of solar irradiance plays an essential role in many energy systems. The objective of this paper is to present a low-cost solar irradiance meter based on artificial neural networks (ANN). A photovoltaic (PV) mathematical model of 50 watts and 36 cells was used to extract the short-circuit current and the open-circuit voltage of the PV module. The obtained data was used to train the ANN to predict solar irradiance for horizontal surfaces. The strategy was to measure the open-circuit voltage and the short-circuit current of the PV module and then feed it to the ANN as inputs to get the irradiance. The experimental and simulation results showed that the proposed method could be utilized to achieve the value of solar irradiance with acceptable approximation. As a result, this method presents a low-cost instrument that can be used instead of an expensive pyranometer. Full article
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Open AccessArticle
2-Stroke Scavenging in Conventional and Minimally-Modified 4-Stroke Engines for Heavy Duty Applications at Low to Medium Speeds
Inventions 2019, 4(3), 44; https://doi.org/10.3390/inventions4030044 - 09 Aug 2019
Viewed by 611
Abstract
The transformation of a standard 4-stroke cylinder head into a torque-improved and gradually more efficient 2-stroke design is discussed. The concept with an effective loop scavenging via an extended inlet valve holds promise for engines at low- to medium-rotational speeds for typical designs [...] Read more.
The transformation of a standard 4-stroke cylinder head into a torque-improved and gradually more efficient 2-stroke design is discussed. The concept with an effective loop scavenging via an extended inlet valve holds promise for engines at low- to medium-rotational speeds for typical designs of conventional 4-stroke cylinder heads. Calculations, flow simulations, and visualizations of experimental flows in relevant geometries and time scales indicate feasibility, followed by a small engine demonstration. Based on presumably long-forgotten and outdated patents, and the central topic of this contribution, an additional jockey rides on the inlet valve’s disk (facing away from the combustion chamber) and reshapes the in-cylinder flow into a reverted tumble. A quick gas exchange with a well-suppressed shortcut into the open exhaust is approached. For overall mechanical efficiency, the required charge pressure for scavenging is of paramount importance due to the short scavenging time and the intake’s reduced cross-section. Herein, still acceptable charging pressures are reported for scavenging periods equivalent to low or medium rotational speeds, as characteristic for heavy-duty applications. Using widely available components (charger, direct injection, variable camshaft angles) an increased engine efficiency is suggested due to the 2-stroke’s downsizing effect (relatively less internal friction as well as the promise of more torque and a decreased size). Full article
(This article belongs to the Special Issue Automatic Control and System Theory)
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Open AccessArticle
The Impact of the Covariance Matrix Sampling on the Angle of Arrival Estimation Accuracy
Inventions 2019, 4(3), 43; https://doi.org/10.3390/inventions4030043 - 08 Aug 2019
Viewed by 623
Abstract
Several works show that the linear Angle of Arrival (AoA) methods such as Projection Matrix (PM) have low computational complexity compared to the subspace methods. Although the PM method is classified as a subspace method, it does not need decomposition of the measured [...] Read more.
Several works show that the linear Angle of Arrival (AoA) methods such as Projection Matrix (PM) have low computational complexity compared to the subspace methods. Although the PM method is classified as a subspace method, it does not need decomposition of the measured matrix. This work investigates the effect of the sampled columns within the covariance matrix on the projection matrix construction. To the authors’ knowledge, this investigation has not been addressed in the literature. Unlike the subspace methods such as Multiple Signal Classification (MUSIC), Estimation of Signal Parameters via Rotational Invariance Technique (ESPRIT), Minimum Norm, Propagator, etc., which have to use a specific number of columns, we demonstrate this aspect is not applicable in the PM method. To this end, the projection matrix is formed based on a various number of sampled columns to estimate the arrival angles. A theoretical analysis is accomplished to illustrate the relationship between the number of the sampled columns and the degrees of freedom (DOFs). The analysis shows that with the same aperture size, the DOFs can be increased by increasing only the number of sampled columns in the projection matrix calculation step. An intensive Monte Carlo simulation for different scenarios is presented to validate the theoretical claims. The estimation accuracy of the PM method, based on the proposed selected sampling methodology outperforms all the other techniques with less complexity compared to the Capon and MUSIC methods. The estimation accuracy is evaluated in terms of Root Mean Square Error (RMSE) and the Probability of Successful Detection (PSD). The results are presented and discussed. Full article
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Open AccessArticle
Change Point Detection for Diversely Distributed Stochastic Processes Using a Probabilistic Method
Inventions 2019, 4(3), 42; https://doi.org/10.3390/inventions4030042 - 08 Aug 2019
Viewed by 620
Abstract
Unpredicted deviations in time series data are called change points. These unexpected changes indicate transitions between states. Change point detection is a valuable technique in modeling to estimate unanticipated property changes underlying time series data. It can be applied in different areas like [...] Read more.
Unpredicted deviations in time series data are called change points. These unexpected changes indicate transitions between states. Change point detection is a valuable technique in modeling to estimate unanticipated property changes underlying time series data. It can be applied in different areas like climate change detection, human activity analysis, medical condition monitoring and speech and image analyses. Supervised and unsupervised techniques are equally used to identify changes in time series. Even though change point detection algorithms have improved considerably in recent years, several undefended challenges exist. Previous work on change point detection was limited to specific areas; therefore, more studies are required to investigate appropriate change point detection techniques applicable to any data distribution to assess the numerical productivity of any stochastic process. This research is primarily focused on the formulation of an innovative methodology for change point detection of diversely distributed stochastic processes using a probabilistic method with variable data structures. Bayesian inference and a likelihood ratio test are used to detect a change point at an unknown time (k). The likelihood of k is determined and used in the likelihood ratio test. Parameter change must be evaluated by critically analyzing the parameters expectations before and after a change point. Real-time data of particulate matter concentrations at different locations were used for numerical verification, due to diverse features, that is, environment, population densities and transportation vehicle densities. Therefore, this study provides an understanding of how well this recommended model could perform for different data structures. Full article
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Open AccessArticle
Comparison of Lithium-Ion Battery Models for Simulating Storage Systems in Distributed Power Generation
Inventions 2019, 4(3), 41; https://doi.org/10.3390/inventions4030041 - 06 Aug 2019
Viewed by 618
Abstract
Lithium-ion batteries are well known in numerous commercial applications. Using accurate and efficient models, system designers can predict the behavior of batteries and optimize the associated performance management. Model-based development comprises the investigation of electrical, electro-chemical, thermal, and aging characteristics. This paper focuses [...] Read more.
Lithium-ion batteries are well known in numerous commercial applications. Using accurate and efficient models, system designers can predict the behavior of batteries and optimize the associated performance management. Model-based development comprises the investigation of electrical, electro-chemical, thermal, and aging characteristics. This paper focuses on the analysis of models describing the electrical behavior. In particular, it investigates how cell voltage and state of charge can be determined with sufficient accuracy for a given load profile. For this purpose, the Thevenin-based, the Rint, and the Shepherd’s models, as well as a generic library model of an electronic circuit simulation software package, are compared. The procedure for determining model parameters is discussed in detail. All models are evaluated for the application in the analysis of distributed power generation. The validation is carried out by comparing simulation and measurement results with the help of a case study. Full article
(This article belongs to the Special Issue Innovative Battery Systems and Energy Storage)
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Open AccessArticle
Characterization of Material Properties Based on Inverse Finite Element Modelling
Inventions 2019, 4(3), 40; https://doi.org/10.3390/inventions4030040 - 02 Aug 2019
Viewed by 657
Abstract
This paper describes a new approach that can be used to determine the mechanical properties of unknown materials and complex material systems. The approach uses inverse finite element modelling (FEM) accompanied with a designed algorithm to obtain the modulus of elasticity, yield stress [...] Read more.
This paper describes a new approach that can be used to determine the mechanical properties of unknown materials and complex material systems. The approach uses inverse finite element modelling (FEM) accompanied with a designed algorithm to obtain the modulus of elasticity, yield stress and strain hardening material constants of an isotropic hardening material model, as well as the material constants of the Drucker–Prager material model (modulus of elasticity, cap yield stress and angle of friction). The algorithm automatically feeds the input material properties data to finite element software and automatically runs simulations to establish a convergence between the numerical loading–unloading curve and the target data obtained from continuous indentation tests using common indenter geometries. A further module was developed to optimise convergence using an inverse FEM analysis interfaced with a non-linear MATLAB algorithm. A sensitivity analysis determined that the dual spherical and Berkovich (S&B) approach delivered better results than other dual indentation methods such as Berkovich and Vickers (B&V) and Vickers and spherical (V&S). It was found that better convergence values can be achieved despite a large variation in the starting parameter values and/or material constitutive model and such behaviour reflects the uniqueness of the dual S&B indentation in predicting complex material systems. The study has shown that a robust optimization method based on a non-linear least-squares curve fitting function (LSQNONLIN) within MATLAB and ABAQUS can be used to accurately predict a unique set of elastic plastic material properties and Drucker–Prager material properties. This is of benefit to the scientific investigation of properties of new materials or obtaining the material properties at different locations of a part which may be not be similar because of manufacturing processes (e.g., different heating and cooling rates at different locations). Full article
(This article belongs to the Special Issue Modern Grinding Technology and Systems 2019)
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Open AccessArticle
How May Location Analytics Be Used to Enhance the Reliability of the Smart Grid?
Inventions 2019, 4(3), 39; https://doi.org/10.3390/inventions4030039 - 02 Aug 2019
Viewed by 716
Abstract
The United States (U.S.) electric infrastructure urgently needs renovation, as highlighted by recent major outages in California, New York, Texas, and Florida. The media has discussed the aging power infrastructure, and the Public Utilities Commission called for a comprehensive review of the causes [...] Read more.
The United States (U.S.) electric infrastructure urgently needs renovation, as highlighted by recent major outages in California, New York, Texas, and Florida. The media has discussed the aging power infrastructure, and the Public Utilities Commission called for a comprehensive review of the causes of recent power outages. Without optimization algorithms to account for the many operating parameters and outage scenarios, planning engineers may inadvertently choose non-optimal locations for new components such as automated distribution switches, thereby impacting circuit reliability. This study aims to address this problem by answering the research question: “How may location analytics should be used to enhance the reliability of the smart grid?” To address this problem, Insights for ArcGIS was used to build worksheets using a geographic information systems (GIS)-based approach to resolve the challenges faced by utilities to reduce power outage frequency. Three case studies demonstrate various risk scenarios wherein a utility can prepare for the unexpected. An artefact in Insights for ArcGIS was created using a design science research methodology. This research proposes a solution to facilitate storm/disaster planning and vegetation management, identify optimal grid locations needing inspection or work, and detect regions where new distribution switches may provide benefits, considering the many operating parameters and outage scenarios. The artefact demonstrates that GIS can play an integral role in resolving this problem. Full article
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Open AccessArticle
Effect of Hybrid Power Station Installation in the Operation of Insular Power Systems
Inventions 2019, 4(3), 38; https://doi.org/10.3390/inventions4030038 - 31 Jul 2019
Viewed by 732
Abstract
Greece has a large number of islands that are isolated from the main interconnected Greek power system; however, a majority of them are to be interconnected in the mainland grid over the next decade. A large number of these islands present a significant [...] Read more.
Greece has a large number of islands that are isolated from the main interconnected Greek power system; however, a majority of them are to be interconnected in the mainland grid over the next decade. A large number of these islands present a significant amount of wind and solar potential. The nature of load demand and renewable production is stochastic; thus, the operation of such isolated power systems can be improved significantly by the installation of a large-scale energy storage system. The role of storage is to compensate for the long and short-term imbalances between power generation and load demand. Pumped hydro storage (PHS) systems represent one of the most mature technologies for large-scale energy storage. However, their advantages have not been proven in practice for cases of medium and small-sized isolated insular systems. Regarding Greece, which contains a large number of isolated insular systems, a PHS system in the island of Ikaria started its test operation in 2019, whereas in Europe only one PHS system operates in El Hierro (Canary Islands). This paper studies the effect of installing a wind-PHS hybrid power station in the operation of the insular power system of Samos, Greece, according to the latest regulatory framework. The implemented analysis uses real hourly data for a whole year, and examines the effects of such an installation considering investors’ and power system operators’ viewpoints. More specifically, the economic viability of this project under different billing scenarios is compared, and its impact on the insular power system operation for various PHS sizes is examined. Full article
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Open AccessArticle
An Innovative Stochastic Multi-Agent-Based Energy Management Approach for Microgrids Considering Uncertainties
Inventions 2019, 4(3), 37; https://doi.org/10.3390/inventions4030037 - 29 Jul 2019
Viewed by 754
Abstract
In microgrids a major share of the energy production comes from renewable energy sources such as photovoltaic panels or wind turbines. The intermittent nature of these types of producers along with the fluctuation in energy demand can destabilize the grid if not dealt [...] Read more.
In microgrids a major share of the energy production comes from renewable energy sources such as photovoltaic panels or wind turbines. The intermittent nature of these types of producers along with the fluctuation in energy demand can destabilize the grid if not dealt with properly. This paper presents a multi-agent-based energy management approach for a non-isolated microgrid with solar and wind units and in the presence of demand response, considering uncertainty in generation and load. More specifically, a modified version of the lightning search algorithm, along with the weighted objective function of the current microgrid cost, based on different scenarios for the energy management of the microgrid, is proposed. The probability density functions of the solar and wind power outputs, as well as the demand of the households, have been used to determine the amount of uncertainty and to plan various scenarios. We also used a particle swarm optimization algorithm for the microgrid energy management and compared the optimization results obtained from the two algorithms. The simulation results show that uncertainty in the microgrid normally has a significant effect on the outcomes, and failure to consider it would lead to inaccurate management methods. Moreover, the results confirm the excellent performance of the proposed approach. Full article
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Open AccessArticle
Development of a Fuzzy Economic Order Quantity Model of Deteriorating Items with Promotional Effort and Learning in Fuzziness with a Finite Time Horizon
Inventions 2019, 4(3), 36; https://doi.org/10.3390/inventions4030036 - 22 Jul 2019
Viewed by 789
Abstract
This study investigates an economic order quantity model of deteriorating items, where demand is fuzzy in nature and depends on promotional effort with full backorder for a given time horizon. The learning effect in the fuzzy environment is added in this model. A [...] Read more.
This study investigates an economic order quantity model of deteriorating items, where demand is fuzzy in nature and depends on promotional effort with full backorder for a given time horizon. The learning effect in the fuzzy environment is added in this model. A constant deterioration rate is assumed. Under these circumstances, a mathematical model is developed to curtail the total cost over a finite time horizon by determining the replenishment order quantity, number of replenishments, and the fraction of the replenishment cycle when inventory is positive. A solution algorithm is developed to find the optimal solutions. The applicability of the proposed model is illustrated through numerical examples. To get further insights, sensitivity analysis is carried out for the main parameters in crisp, fuzzy, and fuzzy-learning environments. Full article
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Open AccessArticle
Comparative Study of DDS with Different Types of Phase Accumulators
Inventions 2019, 4(3), 35; https://doi.org/10.3390/inventions4030035 - 17 Jul 2019
Viewed by 753
Abstract
The paper deals with the problems of delayed transfer signals in the direct digital synthesizer (DDS) phase accumulator adders. Transfer delay is one of the factors that affect the maximum output frequency of the DDS synthesizer. The main types of adders used in [...] Read more.
The paper deals with the problems of delayed transfer signals in the direct digital synthesizer (DDS) phase accumulator adders. Transfer delay is one of the factors that affect the maximum output frequency of the DDS synthesizer. The main types of adders used in DDS synthesizers are described. Separately, attention was paid to the adder with a consistent transfer of the transfer signal, adders with a transmission carry signal with a fixed block length, adders with a signal transmission delay with a variable block length, and a mathematical analysis of the origin and duration of the delay of the transfer signal in them. It was found that the use of a transfer adder with a variable length of a block in the core of a direct digital synthesizer would increase the maximum output frequency by 2.4 times compared to the adder with a parallel transfer, and by 1.43 times as compared with the adder with a fixed length the block. Full article
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Open AccessReview
Will the Machine Like Your Image? Automatic Assessment of Beauty in Images with Machine Learning Techniques
Inventions 2019, 4(3), 34; https://doi.org/10.3390/inventions4030034 - 28 Jun 2019
Cited by 1 | Viewed by 1133
Abstract
Although the concept of image quality has been a subject of study for the image processing community for more than forty years (where, with the term “quality”, we are referring to the accuracy with which an image processing system captures, processes, stores, compresses, [...] Read more.
Although the concept of image quality has been a subject of study for the image processing community for more than forty years (where, with the term “quality”, we are referring to the accuracy with which an image processing system captures, processes, stores, compresses, transmits, and displays the signals that compose an image), notions related to aesthetics of photographs and images have only appeared for about ten years within the community. Studies devoted to aesthetics of images are multiplying today, taking advantage of the latest machine learning techniques and mostly due to the proliferation of huge communities and websites, specialized in digital photography sharing and archiving, such as Flickr, Imgur, DeviantArt, and Instagram. In this review, we examine the latest advances of computer methods that aim at computationally distinguishing high-quality from low-quality photos and images, relying on machine learning techniques. The paper is organized as follows: First, we introduce many approaches to aesthetics, studied in philosophy, neurobiology, experimental psychology, and sociology, to see what lighting they propose to researchers. Such points of view let us explain the weakness of the current consensus on the difficult aesthetics problem and the importance of the ongoing debates on it. Then, we analyze the work done in the community of pattern recognition and artificial intelligence on the task of automatic aesthetic assessment, and we both compare and critically examine the presented results. Finally, we describe many issues that have not been addressed, and starting from these, we outline some possible future directions. Full article
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Open AccessArticle
Maximum Power Point Tracking for Photovoltaic System by Using Fuzzy Neural Network
Inventions 2019, 4(3), 33; https://doi.org/10.3390/inventions4030033 - 26 Jun 2019
Cited by 1 | Viewed by 1054
Abstract
The electrical energy from the sun can be extracted using solar photovoltaic (PV) modules. This energy can be maximized if the connected load resistance matches that of the PV panel. In search of the optimum matching between the PV and the load resistance, [...] Read more.
The electrical energy from the sun can be extracted using solar photovoltaic (PV) modules. This energy can be maximized if the connected load resistance matches that of the PV panel. In search of the optimum matching between the PV and the load resistance, the maximum power point tracking (MPPT) technique offers considerable potential. This paper aims to show how the modelling process of an efficient PV system with a DC load can be achieved using a fuzzy neural network (FNN) controller. This is applied via an innovative methodology, which senses the irradiance and temperature of the PV panel and produces an optimal value of duty ration for the boost converter to obtain the MPPT. The coefficients of this controller have been refined based upon previous data sets using the irradiance and temperature. A gradient descent algorithm is employed to improve the parameters of the FNN controller to achieve an optimal response. The validity of the PV system using the MPPT technique based on the FNN controller is further demonstrated via a series of experimental tests at different ambient conditions. The simulation results show how the MPPT technique based on the FNN controller is more effective in maintaining the optimal power values compared with conventional techniques. Full article
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