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Energies, Volume 12, Issue 14 (July-2 2019)

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Open AccessFeature PaperArticle
Modelling Interaction Decisions in Smart Cities: Why Do We Interact with Smart Media Displays?
Energies 2019, 12(14), 2840; https://doi.org/10.3390/en12142840 (registering DOI)
Received: 3 June 2019 / Revised: 16 July 2019 / Accepted: 16 July 2019 / Published: 23 July 2019
PDF Full-text (596 KB)
Abstract
This study examined the personal characteristics and preferences of individuals that encourage interactions with smart media displays (media façades). Specifically, it aimed to determine which key aspects of a smart display “media façade” enhance intuitive interactions. A range of smart display technologies and [...] Read more.
This study examined the personal characteristics and preferences of individuals that encourage interactions with smart media displays (media façades). Specifically, it aimed to determine which key aspects of a smart display “media façade” enhance intuitive interactions. A range of smart display technologies and their effects on interaction decisions were considered. Data were drawn from a survey of 200 randomly sampled residents and/or visitors to a smart building, One Central Park, in Sydney, Australia. A binomial logistic regression analysis was undertaken to establish links between a range of design, perceptions and socio-demographic variables and individuals’ decisions to interact with a smart media display. The results showed that the aesthetics of an installation, the quality of an installation’s content and the safety of the operation-friendly environment significantly affected respondents’ decisions to interact with the media display. Interestingly, respondents born overseas were more likely to interact with a smart display than those born in Australia. Respondents who expressed a preference for photograph-based interactions were also more likely to interact with the display. Somewhat surprisingly, age, residency and levels of familiarity with digital technology did not significantly affect respondents’ decisions to interact with the display. Full article
Open AccessArticle
Analysis of Subjective Qualitative Judgement of Passenger Vehicle High Speed Drivability due to Aerodynamics
Energies 2019, 12(14), 2839; https://doi.org/10.3390/en12142839 (registering DOI)
Received: 17 June 2019 / Revised: 16 July 2019 / Accepted: 19 July 2019 / Published: 23 July 2019
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Abstract
The flow created by the shape of a vehicle and by environmental conditions, such as cross-winds, will influence the dynamics of a vehicle. The objective of this paper is to correlate the driver’s subjective judgement of drivability with quantities which are measurable during [...] Read more.
The flow created by the shape of a vehicle and by environmental conditions, such as cross-winds, will influence the dynamics of a vehicle. The objective of this paper is to correlate the driver’s subjective judgement of drivability with quantities which are measurable during a vehicle test. For this purpose, a sedan vehicle, fitted with different aerodynamic external devices that create disturbances in the flow field, were assessed on a test track. These configurations intend to result in substandard straight line drivability. The aerodynamic devices investigated are an inverted wing, an inverted wing with an asymmetric flat plate and an asymmetric air curtain attached under the bumper. The devices generate more lift and asymmetric forces resulting in increased vehicle sensitivity to external disturbances. Pairs of configurations with and without bumper side-kicks are also tested. The side-kicks create a defined flow separation which helps to stabilize the flow and increase drivability. Plots of mean and standard deviation and ride diagram of lateral acceleration, yaw velocity, steering angle and steering torque are used to understand vehicle behaviour for the different configurations. Ride diagrams are used to visualize vehicle excitations with transient events separated from the stationary signal. The range of the measured quantities for understanding the drivability is not predicted in advance and it turns out that the error margins of the measurements are smaller than the measurement uncertainty of the Inertia Measurement Unit. Although the outcome lacks the ability to objectively quantify subjective judgements, it provides a useful qualitative assessment of the problem as the trends agree well with the subjective judgement of the driver. Full article
(This article belongs to the Special Issue Recent Advances in Vehicle Aerodynamics)
Open AccessArticle
Power Production Estimates from Geothermal Resources by Means of Small-Size Compact Climeon Heat Power Converters: Case Studies from Portugal (Sete Cidades, Azores and Longroiva Spa, Mainland)
Energies 2019, 12(14), 2838; https://doi.org/10.3390/en12142838 (registering DOI)
Received: 23 May 2019 / Revised: 15 July 2019 / Accepted: 19 July 2019 / Published: 23 July 2019
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Abstract
Renewable forms of energy are increasingly penetrating the electricity market, particularly, geothermal energy. A wide range of resource temperatures and fluid quality are converted mostly using traditional binary power plants and, recently, using Climeon modular units. Portuguese natural geothermal resources are far from [...] Read more.
Renewable forms of energy are increasingly penetrating the electricity market, particularly, geothermal energy. A wide range of resource temperatures and fluid quality are converted mostly using traditional binary power plants and, recently, using Climeon modular units. Portuguese natural geothermal resources are far from precise estimations. Despite the parameter uncertainties, electric power resource estimations of two natural geothermal reservoirs are presented: a volcanic sourced heated high-enthalpy geothermal reservoir in Sete Cidades, São Miguel Island, Azores; and a low-enthalpy geothermal reservoir linked to a fractured zone in a granitic setting in Longroiva, in the northern part of the Portuguese mainland. Based on the volumetric method, we assessed the power potential of geothermal resources in Sete Cidades and Longroiva using a probabilistic methodology—Monte Carlo simulation. The average reserve estimations for Climeon module were 5.66 MWe and 0.64 MWe for Sete Cidades and Longroiva, respectively. This figure was by far higher when compared to traditional binary technology; those differences were mostly attributed to distinct conversions efficiency factors. Full article
(This article belongs to the Special Issue Innovation in Geothermal Energy Exploration and Production)
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Open AccessArticle
Environmental Challenges in the Residential Sector: Life Cycle Assessment of Mexican Social Housing
Energies 2019, 12(14), 2837; https://doi.org/10.3390/en12142837 (registering DOI)
Received: 5 July 2019 / Revised: 19 July 2019 / Accepted: 19 July 2019 / Published: 23 July 2019
PDF Full-text (1174 KB)
Abstract
Social Housing (SH) in Mexico has a potentially important role in reducing both the emission of greenhouse gases and the use of non-renewable resources, two of the main challenges facing not only Mexico but the planet as a whole. This work assesses the [...] Read more.
Social Housing (SH) in Mexico has a potentially important role in reducing both the emission of greenhouse gases and the use of non-renewable resources, two of the main challenges facing not only Mexico but the planet as a whole. This work assesses the environmental impact generated by the embodied stages of a typical SH throughout its life cycle (cradle to grave), by means of a Life Cycle Assessment (LCA). Two types of envelope and interior walls and three types of windows are compared. It was found that SH emits 309 kg CO2 eq/m2 and consumes 3911 MJ eq/m2 in the product stages (A1 to A3) and construction process (A4 to A5); the most important stages are those referring to the products, namely, A1 to A3, B4 (replacement) and B2 (maintenance). Additionally, benefits were found in the use of lightweight and thermal materials, such as concrete blocks lightened with pumice or windows made of PVC or wood. Although the use of LCA is incipient in the housing and construction sector in Mexico, this work shows how its application is not only feasible but recommended as it may become a basic tool in the search for sustainability. Full article
(This article belongs to the Special Issue Life Cycle Energy Assessment on Buildings)
Open AccessArticle
Continuous Battery Health Diagnosis by On-Line Internal Resistance Measuring
Energies 2019, 12(14), 2836; https://doi.org/10.3390/en12142836 (registering DOI)
Received: 28 June 2019 / Revised: 13 July 2019 / Accepted: 19 July 2019 / Published: 23 July 2019
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Abstract
Energy storage in an uninterruptible power supply (UPS) is one of the most frequent applications of batteries. This can be found in hospitals, communication centers, public centers, ships, trains, etc. Most frequent industrial methods for battery state-of health estimation require a technician to [...] Read more.
Energy storage in an uninterruptible power supply (UPS) is one of the most frequent applications of batteries. This can be found in hospitals, communication centers, public centers, ships, trains, etc. Most frequent industrial methods for battery state-of health estimation require a technician to move to the battery’s location and, in some cases, require the use of heavy equipment and disconnection of the battery from the UPS. For example, in railway applications, trains must stop at the maintenance depot producing significant total costs. This article proposes a new method to assess a battery’s health by measuring the battery’s internal resistance, based on the measurement of its voltage ripple in response to the current ripple imposed by the charger which in most UPS applications is permanently connected to the battery. Unlike most traditional methods, this system makes it possible a continuous on-line and on-board monitoring, and, therefore, it eases condition-based maintenance (CBM). To verify its viability, a low cost measuring prototype has been built and measurements in a railway battery with its charger have been carried out. Full article
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Open AccessArticle
Close Nozzle Spray Characteristics of a Prefilming Airblast Atomizer
Energies 2019, 12(14), 2835; https://doi.org/10.3390/en12142835 (registering DOI)
Received: 14 June 2019 / Revised: 15 July 2019 / Accepted: 19 July 2019 / Published: 23 July 2019
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Abstract
The formation of pollutant emissions in jet engines is closely related to the fuel distribution inside the combustor. Hence, the characteristics of the spray formed during primary breakup are of major importance for an accurate prediction of the pollutant emissions. Currently, an Euler–Lagrangian [...] Read more.
The formation of pollutant emissions in jet engines is closely related to the fuel distribution inside the combustor. Hence, the characteristics of the spray formed during primary breakup are of major importance for an accurate prediction of the pollutant emissions. Currently, an Euler–Lagrangian approach for droplet transport in combination with combustion and pollutant formation models is used to predict the pollutant emissions. The missing element for predicting these emissions more accurately is well defined starting conditions for the liquid fuel droplets as they emerge from the fuel nozzle. Recently, it was demonstrated that the primary breakup can be predicted from first principles by the Lagrangian, mesh-free, Smoothed Particle Hydrodynamics (SPH) method. In the present work, 2D Direct Numerical Simulations (DNS) of a planar prefilming airblast atomizer using the SPH method are presented, which capture most of the breakup phenomena known from experiments. Strong links between the ligament breakup and the resulting spray in terms of droplet size, trajectory and velocity are demonstrated. The SPH predictions at elevated pressure conditions resemble quite well the effects observed in experiments. Significant interdependencies between droplet diameter, position and velocity are observed. This encourages to employ such multidimensional interdependence relations as a base for the development of primary atomization models. Full article
(This article belongs to the Special Issue Experimental and Numerical Analysis of Fuel Spray in Engines)
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Open AccessArticle
Investigations of AC Microgrid Energy Management Systems Using Distributed Energy Resources and Plug-in Electric Vehicles
Energies 2019, 12(14), 2834; https://doi.org/10.3390/en12142834 (registering DOI)
Received: 4 April 2019 / Revised: 11 May 2019 / Accepted: 21 May 2019 / Published: 23 July 2019
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Abstract
The world has witnessed a rapid transformation in the field of electrical generation, transmission and distribution. We have been constantly developing and upgrading our technology to make the system more economically efficient. Currently, the industry faces an acute shortage of energy resources due [...] Read more.
The world has witnessed a rapid transformation in the field of electrical generation, transmission and distribution. We have been constantly developing and upgrading our technology to make the system more economically efficient. Currently, the industry faces an acute shortage of energy resources due to overconsumption by industries worldwide. This has compelled experts to look for alternatives to fossil fuels and other conventional sources of energy to produce energy in a more sustainable manner. The microgrid concept has gained popularity over the years and has become a common sight all over the world because of the ability of a microgrid to provide power to a localized section without being dependent on conventional resources. This paper focuses on development of such an AC hybrid microgrid, which receives power from distributed energy resources (DERs) such as a PV array alongside a battery storage system, and also uses an emergency diesel generator system and an online uninterruptible power supply (UPS) system to provide power to predefined loads under different conditions. This paper also addresses on the power flow to the loads under two main modes of operation—on grid and off grid—and investigates the microgrid in different states and sub-states. The final objective is to design an efficient microgrid model such that it can sustain the multiple loads simultaneously under all operating conditions. Full article
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Open AccessArticle
Short-Term Forecasting of Wake-Induced Fluctuations in Offshore Wind Farms
Energies 2019, 12(14), 2833; https://doi.org/10.3390/en12142833 (registering DOI)
Received: 21 May 2019 / Revised: 10 July 2019 / Accepted: 17 July 2019 / Published: 23 July 2019
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Abstract
The increasing share of offshore wind energy traded at the spot market requires short term wind direction forecasts to determine wake losses and increased power fluctuations due to multiple wakes in certain wind directions. The information on potential power fluctuations can be used [...] Read more.
The increasing share of offshore wind energy traded at the spot market requires short term wind direction forecasts to determine wake losses and increased power fluctuations due to multiple wakes in certain wind directions. The information on potential power fluctuations can be used to issue early warnings to grid operators. The current work focuses on analyzing wind speed and power fluctuation time series for a German offshore wind farm. By associating these fluctuations with wind directions, it is observed that the turbines in double or multiple wake situations yield higher fluctuations in wind speed and power compared to the turbines in free flow. The wind direction forecasts of the European Center for Medium-Range Weather Forecast model are compared with Supervisory Control and Data Acquisition (SCADA) data observations of the turbine yaw. The cumulative probability distribution of the difference in forecasted and observed wind directions shows that for a tolerance of +/−10 , 71% of the observations are correctly forecasted for a lead time of 1 day, which drops to 54% for a lead time of 3 days. The circular continuous rank probability score of the observed wind directions doubles over the lead time of 72 h. Full article
(This article belongs to the Section Wind, Wave and Tidal Energy)
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Open AccessArticle
Optimization of Two-Stage Combined Thermoelectric Devices by a Three-Dimensional Multi-Physics Model and Multi-Objective Genetic Algorithm
Energies 2019, 12(14), 2832; https://doi.org/10.3390/en12142832 (registering DOI)
Received: 9 June 2019 / Revised: 8 July 2019 / Accepted: 19 July 2019 / Published: 23 July 2019
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Abstract
Due to their advantages of self-powered capability and compact size, combined thermoelectric devices, in which a thermoelectric cooler module is driven by a thermoelectric generator module, have become promising candidates for cooling applications in extreme conditions or environments where the room is confined [...] Read more.
Due to their advantages of self-powered capability and compact size, combined thermoelectric devices, in which a thermoelectric cooler module is driven by a thermoelectric generator module, have become promising candidates for cooling applications in extreme conditions or environments where the room is confined and the power supply is sacrificed. When the device is designed as two-stage configuration for larger temperature difference, the design degree is larger than that of a single-stage counterpart. The element number allocation to each stage in the system has a significant influence on the device performance. However, this issue has not been well-solved in previous studies. This work proposes a three-dimensional multi-physics model coupled with multi-objective genetic algorithm to optimize the optimal element number allocation with the coefficient of performance and cooling capacity simultaneously as multi-objective functions. This method increases the accuracy of performance prediction compared with the previously reported examples studied by the thermal resistance model. The results show that the performance of the optimized device is remarkably enhanced, where the cooling capacity is increased by 23.3% and the coefficient of performance increased by 122.0% compared with the 1# Initial Solution. The mechanism behind this enhanced performance is analyzed. The results in this paper should be beneficial for engineers and scientists seeking to design a combined thermoelectric device with optimal performance under the constraint of total element number. Full article
(This article belongs to the Section Thermal Management)
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Open AccessArticle
Robust Sensor Fault Reconstruction via a Bank of Second-Order Sliding Mode Observers for Aircraft Engines
Energies 2019, 12(14), 2831; https://doi.org/10.3390/en12142831 (registering DOI)
Received: 12 June 2019 / Revised: 5 July 2019 / Accepted: 13 July 2019 / Published: 23 July 2019
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Abstract
This paper deals with sensor faults of aircraft engines under uncertainties using a bank of second-order sliding mode observers (SMOs). In view of the effect of inevitable uncertainties on the fault reconstruction, a method combining H concepts and linear matrix inequalities (LMIs) [...] Read more.
This paper deals with sensor faults of aircraft engines under uncertainties using a bank of second-order sliding mode observers (SMOs). In view of the effect of inevitable uncertainties on the fault reconstruction, a method combining H concepts and linear matrix inequalities (LMIs) is proposed, in which a scaling matrix is designed to minimize the gain of the transfer function matrix from uncertainty to reconstruction. However, robust design generally requires that engine outputs outnumber faults. In the case where the above-mentioned requirement is not satisfied, a bank of sliding mode observers is proposed to ensure the degrees of freedom available in robust design. In specific, each observer corresponds to a certain sensor with the hypothesis that the corresponding sensor will not have faults, to create one degree of design freedom for each observer. After fault occurrence, a large estimation error is expected in the observers with wrong hypothesis, and then a logic module is designed to detect sensor faults and obtain the optimal robust sensor fault reconstruction at the same time. The proposed approach is applied to a nonlinear engine component-level-model (CLM) simulation platform, and a numerical study is performed to validate the effectiveness. Full article
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Open AccessEditorial
Permanent Magnet Synchronous Machines
Energies 2019, 12(14), 2830; https://doi.org/10.3390/en12142830 (registering DOI)
Received: 2 July 2019 / Accepted: 22 July 2019 / Published: 23 July 2019
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Abstract
Interest in permanent magnet synchronous machines (PMSMs) is continuously increasing worldwide, especially with the increased use of renewable energy and electrification of transports. This special issue contains the successful invited submissions of fifteen papers to a Special Issue of Energies on the subject [...] Read more.
Interest in permanent magnet synchronous machines (PMSMs) is continuously increasing worldwide, especially with the increased use of renewable energy and electrification of transports. This special issue contains the successful invited submissions of fifteen papers to a Special Issue of Energies on the subject area of “Permanent Magnet Synchronous Machines”. The focus is on permanent magnet synchronous machines and the electrical systems they are connected to. The presented work represents a wide range of areas. Studies of control systems, both for permanent magnet synchronous machines and for brushless DC motors, are presented and experimentally verified. Design studies of generators for wind power, wave power and hydro power are presented. Finite element method simulations and analytical design methods are used. The presented studies represent several of the different research fields on permanent magnet machines and electric drives. Full article
(This article belongs to the Special Issue Permanent Magnet Synchronous Machines)
Open AccessArticle
An Energy-Efficient Cross-Layer Routing Protocol for Cognitive Radio Networks Using Apprenticeship Deep Reinforcement Learning
Energies 2019, 12(14), 2829; https://doi.org/10.3390/en12142829 (registering DOI)
Received: 26 June 2019 / Revised: 15 July 2019 / Accepted: 18 July 2019 / Published: 22 July 2019
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Abstract
Deep reinforcement learning (DRL) has been successfully used for the joint routing and resource management in large-scale cognitive radio networks. However, it needs lots of interactions with the environment through trial and error, which results in large energy consumption and transmission delay. In [...] Read more.
Deep reinforcement learning (DRL) has been successfully used for the joint routing and resource management in large-scale cognitive radio networks. However, it needs lots of interactions with the environment through trial and error, which results in large energy consumption and transmission delay. In this paper, an apprenticeship learning scheme is proposed for the energy-efficient cross-layer routing design. Firstly, to guarantee energy efficiency and compress huge action space, a novel concept called dynamic adjustment rating is introduced, which regulates transmit power efficiently with multi-level transition mechanism. On top of this, the Prioritized Memories Deep Q-learning from Demonstrations (PM-DQfD) is presented to speed up the convergence and reduce the memory occupation. Then the PM-DQfD is applied to the cross-layer routing design for power efficiency improvement and routing latency reduction. Simulation results confirm that the proposed method achieves higher energy efficiency, shorter routing latency and larger packet delivery ratio compared to traditional algorithms such as Cognitive Radio Q-routing (CRQ-routing), Prioritized Memories Deep Q-Network (PM-DQN), and Conjecture Based Multi-agent Q-learning Scheme (CBMQ). Full article
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Open AccessArticle
Realization of Licensed/Unlicensed Spectrum Sharing Using eICIC in Indoor Small Cells for High Spectral and Energy Efficiencies of 5G Networks
Energies 2019, 12(14), 2828; https://doi.org/10.3390/en12142828 (registering DOI)
Received: 15 June 2019 / Revised: 17 July 2019 / Accepted: 19 July 2019 / Published: 22 July 2019
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Abstract
In this paper, we show how to realize numerous spectrum licensing policies by means of time-domain enhanced inter-cell interference coordination (eICIC) technique to share both the licensed and unlicensed spectrums with small cells in order to address the increasing demand of capacity, spectral [...] Read more.
In this paper, we show how to realize numerous spectrum licensing policies by means of time-domain enhanced inter-cell interference coordination (eICIC) technique to share both the licensed and unlicensed spectrums with small cells in order to address the increasing demand of capacity, spectral efficiency, and energy efficiency of future mobile networks. Small cells are deployed only in 3-dimensional (3D) buildings within a macrocell coverage of a mobile network operator (MNO). We exploit the external wall penetration loss of each building to realize traditional dedicated access, co-primary shared access (CoPSA), and licensed shared access (LSA) techniques for the licensed spectrum access, whereas, for the unlicensed spectrum access, the licensed assisted access (LAA) technique operating in the 60 GHz unlicensed band is realized. We consider that small cells are facilitated with dual-band, and derive the average capacity, spectral efficiency, and energy efficiency metrics for each technique. We perform extensive evaluation of various performance metrics and show that LAA outperforms considerably all other techniques concerning particularly spectral and energy efficiencies. Finally, we define an optimal density of small cells satisfying both the spectral efficiency and energy efficiency requirements for the fifth-generation (5G) mobile networks. Full article
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Open AccessArticle
Maximum Power Point Tracker Based on Fuzzy Adaptive Radial Basis Function Neural Network for PV-System
Energies 2019, 12(14), 2827; https://doi.org/10.3390/en12142827
Received: 14 June 2019 / Revised: 15 July 2019 / Accepted: 16 July 2019 / Published: 22 July 2019
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Abstract
In this article, a novel maximum power point tracking (MPPT) controller for a photovoltaic (PV) system is presented. The proposed MPPT controller was designed in order to extract the maximum of power from the PV-module and reduce the oscillations once the maximum power [...] Read more.
In this article, a novel maximum power point tracking (MPPT) controller for a photovoltaic (PV) system is presented. The proposed MPPT controller was designed in order to extract the maximum of power from the PV-module and reduce the oscillations once the maximum power point (MPP) had been achieved. To reach this goal, a combination of fuzzy logic and an adaptive radial basis function neural network (RBF-NN) was used to drive a DC-DC Boost converter which was used to link the PV-module and a resistive load. First, a fuzzy logic system, whose single input was based on the incremental conductance (INC) method, was used for a variable voltage step size searching while reducing the oscillations around the MPP. Second, an RBF-NN controller was developed to keep the PV-module voltage at the optimal voltage generated from the first stage. To ensure a real MPPT in all cases (change of weather conditions and load variation) an adaptive law based on backpropagation algorithm with the gradient descent method was used to tune the weights of RBF-NN in order to minimize a mean-squared-error (MSE) criterion. Finally, through the simulation results, our proposed MPPT method outperforms the classical P and O and INC-adaptive RBF-NN in terms of efficiency. Full article
(This article belongs to the Section Solar Energy and Photovoltaic Systems)
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Open AccessArticle
Optimal Investment Strategies for Solar Energy Based Systems
Energies 2019, 12(14), 2826; https://doi.org/10.3390/en12142826
Received: 20 June 2019 / Revised: 18 July 2019 / Accepted: 18 July 2019 / Published: 22 July 2019
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Abstract
Solar energy, as an inexhaustible renewable energy, can be used to produce heat and electricity. It is of great importance to examine the strategy for investment on solar energy technology. In response to varying electricity price in the electricity market, the battery energy [...] Read more.
Solar energy, as an inexhaustible renewable energy, can be used to produce heat and electricity. It is of great importance to examine the strategy for investment on solar energy technology. In response to varying electricity price in the electricity market, the battery energy storage system (BESS) can be used to get price arbitrage. This paper proposes an optimal configuration model for a photovoltaic (PV) system, solar heating system, and BESS in order to obtain maximum profit for investors. The investment potential of these systems is compared and analyzed based on return on investment (ROI) index which is defined to evaluate economic profitability. A bi-level programming is adopted to optimize the operation strategy of batteries (inner layer), the size of PV system and solar heating system, and the size of batteries (outer layer) including their maximum discharge/charge power and capacity. Sequential quadratic programming (SQP) method and particle swarm optimization (PSO) are used as optimization methods. In the case study, five investment strategies are investigated in order to decide how to invest in PV modules, batteries, and solar thermal collectors. The results show that the BESS may be a preferable choice for the investors if the investment cost of BESS goes down a lot in the future. Investing in solar energy for both heat and power may be not reasonable because the ROI of this strategy is always higher than either investing in heat or in power. The optimal strategy may be changed with the fluctuation of heat and electricity prices. Full article
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Open AccessArticle
Reducing Computational Load for Mixed Integer Linear Programming: An Example for a District and an Island Energy System
Energies 2019, 12(14), 2825; https://doi.org/10.3390/en12142825
Received: 2 July 2019 / Revised: 18 July 2019 / Accepted: 19 July 2019 / Published: 22 July 2019
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Abstract
The complexity of Mixed-Integer Linear Programs (MILPs) increases with the number of nodes in energy system models. An increasing complexity constitutes a high computational load that can limit the scale of the energy system model. Hence, methods are sought to reduce this complexity. [...] Read more.
The complexity of Mixed-Integer Linear Programs (MILPs) increases with the number of nodes in energy system models. An increasing complexity constitutes a high computational load that can limit the scale of the energy system model. Hence, methods are sought to reduce this complexity. In this paper, we present a new 2-Level Approach to MILP energy system models that determines the system design through a combination of continuous and discrete decisions. On the first level, data reduction methods are used to determine the discrete design decisions in a simplified solution space. Those decisions are then fixed, and on the second level the full dataset is used to ex-tract the exact scaling of the chosen technologies. The performance of the new 2-Level Approach is evaluated for a case study of an urban energy system with six buildings and an island system based on a high share of renewable energy technologies. The results of the studies show a high accuracy with respect to the total annual costs, chosen system structure, installed capacities and peak load with the 2-Level Approach compared to the results of a single level optimization. The computational load is thereby reduced by more than one order of magnitude. Full article
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Open AccessFeature PaperArticle
A General Framework for Voltage Sag Performance Analysis of Distribution Networks
Energies 2019, 12(14), 2824; https://doi.org/10.3390/en12142824
Received: 3 July 2019 / Revised: 17 July 2019 / Accepted: 18 July 2019 / Published: 22 July 2019
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Abstract
The proliferation of more sensitive loads has obliged distribution companies to pay greater attention to the voltage sag mitigation potential of different design alternatives in network planning studies. In doing so, a company has to have effective tools for estimating the voltage sag [...] Read more.
The proliferation of more sensitive loads has obliged distribution companies to pay greater attention to the voltage sag mitigation potential of different design alternatives in network planning studies. In doing so, a company has to have effective tools for estimating the voltage sag performance of its network. In this regard, this paper establishes a three-step framework for evaluating voltage sag performance of a distribution network. The first step, designated as state selection, is to select a network state in which voltage sag is likely. Although voltage sags have various causes, those that originated from faults in distribution networks are considered in this paper. The stochastic nature of fault location, type, resistance, and duration as well as the response of the protection system are taken into account. The second step, called state evaluation, deals with sag characteristics during the fault clearing time and the protection system response. The third step, named index calculation, is to estimate indices reflecting the sag performance of the network. A number of indices are proposed in this paper to reflect both system and load point-oriented issues. In light of the indices, companies may find effective solutions for voltage sag mitigation and customers choose appropriate solutions to provide ride-through support for their critical processes. Full article
(This article belongs to the Section Electrical Power and Energy System)
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Open AccessArticle
Diesel Mean Value Engine Modeling Based on Thermodynamic Cycle Simulation Using Artificial Neural Network
Energies 2019, 12(14), 2823; https://doi.org/10.3390/en12142823
Received: 27 May 2019 / Revised: 12 July 2019 / Accepted: 18 July 2019 / Published: 22 July 2019
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Abstract
This study aims to construct a reduced thermodynamic cycle model with high accuracy and high model execution speed based on artificial neural network training for real-time numerical analysis. This paper proposes a method of constructing a fast average-value model by combining a 1D [...] Read more.
This study aims to construct a reduced thermodynamic cycle model with high accuracy and high model execution speed based on artificial neural network training for real-time numerical analysis. This paper proposes a method of constructing a fast average-value model by combining a 1D plant model and exhaust gas recirculation (EGR) control logic. The combustion model of the detailed model uses a direct-injection diesel multi-pulse (DI-pulse) method similar to diesel combustion characteristics. The DI-pulse combustion method divides the volume of the cylinder into three zones, predicting combustion- and emission-related variables, and each combustion step comprises different correction variables. This detailed model is estimated to be within 5% of the reference engine test results. To reduce the analysis time while maintaining the accuracy of engine performance prediction, the cylinder volumetric efficiency and the exhaust gas temperature were predicted using an artificial neural network. Owing to the lack of input variables in the training of artificial neural networks, it was not possible to predict the 0.6–0.7 range for volumetric efficiency and the 1000–1200 K range for exhaust gas temperature. This is because the mean value model changes the fuel injection method from the common rail fuel injection mode to the single injection mode in the model reduction process and changes the in-cylinder combustion according to the injection timing of the fuel amount injected. In addition, the mean value model combined with EGR logic, i.e., the single-input single-output (SISO) coupled mean value model, verifies the accuracy and responsiveness of the EGR control logic model through a step-transient process. By comparing the engine performance results of the SISO coupled mean value model with those of the mean value model, it is observed that the SISO coupled mean value model achieves the desired target EGR rate within 10 s. The EGR rate is predicted to be similar to the response of volumetric efficiency. This process intuitively predicted the main performance parameters of the engine model through artificial neural networks. Full article
(This article belongs to the Special Issue Modelling of Thermal and Energy Systems)
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Open AccessArticle
Estimation of the Biot Number Using Genetic Algorithms: Application for the Drying Process
Energies 2019, 12(14), 2822; https://doi.org/10.3390/en12142822
Received: 28 May 2019 / Revised: 11 July 2019 / Accepted: 17 July 2019 / Published: 22 July 2019
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Abstract
The Biot number informs researchers about the controlling mechanisms employed for heat or mass transfer during the considered process. The mass transfer coefficients (and heat transfer coefficients) are usually determined experimentally based on direct measurements of mass (heat) fluxes or correlation equations. This [...] Read more.
The Biot number informs researchers about the controlling mechanisms employed for heat or mass transfer during the considered process. The mass transfer coefficients (and heat transfer coefficients) are usually determined experimentally based on direct measurements of mass (heat) fluxes or correlation equations. This paper presents the method of Biot number estimation. For estimation of the Biot number in the drying process, the multi-objective genetic algorithm (MOGA) was developed. The simultaneous minimization of mean absolute error (MAE) and root mean square error (RMSE) and the maximization of the coefficient of determination R2 between the drying model and experimental data were considered. The Biot number can be calculated from the following equations: Bi = 0.8193exp(-6.4951T−1) (and moisture diffusion coefficient from D/s2 = 0.00704exp(-2.54T−1)) (RMSE = 0.0672, MAE = 0.0535, R2 = 0.98) or Bi = 1/0.1746log(1193847T) (D/s2 = 0.0075exp(-6T−1)) (RMSE = 0.0757, MAE = 0.0604, R2 = 0.98). The conducted validation gave good results. Full article
(This article belongs to the Special Issue Heat and Mass Transfer in Energy Systems)
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Open AccessArticle
The Self-Degradation Mechanism of Polyvinyl Chloride-Modified Slag/Fly Ash Binder for Geothermal Wells
Energies 2019, 12(14), 2821; https://doi.org/10.3390/en12142821
Received: 23 April 2019 / Revised: 13 July 2019 / Accepted: 18 July 2019 / Published: 22 July 2019
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Abstract
Polyvinyl chloride (PVC) releases hydrochloric acid (HCl) during its thermal degradation, and hydrochloric acid can react with hydration products of alkali-activated binders. According to this characteristic of PVC and the temperature change that occurs during the development of a geothermal well, the PVC [...] Read more.
Polyvinyl chloride (PVC) releases hydrochloric acid (HCl) during its thermal degradation, and hydrochloric acid can react with hydration products of alkali-activated binders. According to this characteristic of PVC and the temperature change that occurs during the development of a geothermal well, the PVC was added into slag/fly ash binder to develop self-degradable materials. The thermal degradation properties of PVC, compressive strength, hydration products, and microstructure of binders at different stages were tested, in order to study the degradation mechanism of the material. It was found that 20% PVC reduced the compressive strength, decreasing the level of binder from 13.95% to 76.63%. The mechanism of PVC promoting the material degradation mainly includes the following: (1) the thermal degradation of PVC increases the number of multiple damage pores in the material, at a high temperature; (2) HCl generated by the PVC thermal degradation reacts with the binder gels, and breaks them into particles; and (3) HCl also reacts with other substances in the binder, including CaCO3 and NaOH in the pore solution. Full article
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Open AccessArticle
Exploring the Profitability and Efficiency of Variable Renewable Energy in Spot Electricity Market: Uncovering the Locational Price Disadvantages
Energies 2019, 12(14), 2820; https://doi.org/10.3390/en12142820
Received: 25 May 2019 / Revised: 13 July 2019 / Accepted: 18 July 2019 / Published: 22 July 2019
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Abstract
While variable renewable energy (VRE) has been developed for decades, VRE market participation is developing relatively slowly, despite the potential economic efficiency it may bring. This paper tries to specify the efficiency of VRE in a deregulated pool-based electricity market. Based on standard [...] Read more.
While variable renewable energy (VRE) has been developed for decades, VRE market participation is developing relatively slowly, despite the potential economic efficiency it may bring. This paper tries to specify the efficiency of VRE in a deregulated pool-based electricity market. Based on standard pool-based market design, this paper built a direct current optimal power flow (DC-OPF) based simplified 2-settlement spot electricity market model conjugating electricity and ancillary service clearing. To address the outcomes of the imperfect market in the real world, this paper studied the consequences brought by agents’ learning and strategic behaviors. Simulations under different ancillary service levels and reliability cost levels are carried out. The results show that VRE may be unprofitable in the market, especially when learning and strategic behavior is considered. Learning and strategic market behavior will also hamper the role of VRE as a “better” energy source. This paper shows and proves a locational marginal price (LMP) disadvantage phenomenon, which will lead to low profitability of VRE. Three major suggestions are given based on the results. Full article
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Open AccessArticle
Observer-Based Sliding Mode FTC for Multi-Area Interconnected Power Systems against Hybrid Energy Storage Faults
Energies 2019, 12(14), 2819; https://doi.org/10.3390/en12142819
Received: 24 June 2019 / Revised: 12 July 2019 / Accepted: 15 July 2019 / Published: 22 July 2019
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Abstract
An observer-based sliding mode fault-tolerant controller is developed in this paper, which is applied to an interconnected power system with a hybrid energy storage system (HESS). The model of the interconnected power system with HESS is introduced first. An observer is then proposed [...] Read more.
An observer-based sliding mode fault-tolerant controller is developed in this paper, which is applied to an interconnected power system with a hybrid energy storage system (HESS). The model of the interconnected power system with HESS is introduced first. An observer is then proposed to estimate the unknown but bounded load disturbances and the actuator fault. The sliding mode fault-tolerant controller is further designed based on the observer ensuring that the area control error of the interconnected power system asymptotically converges to zero. The stability and the convergence of the whole system are proven based on the Lyapunov stability theory. Finally, the effectiveness of the proposed fault-control scheme is demonstrated through simulations. Full article
(This article belongs to the Section Electrical Power and Energy System)
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Open AccessArticle
Evaluation of Infrared Radiation Combined with Hot Air Convection for Energy-Efficient Drying of Biomass
Energies 2019, 12(14), 2818; https://doi.org/10.3390/en12142818
Received: 14 June 2019 / Revised: 15 July 2019 / Accepted: 19 July 2019 / Published: 22 July 2019
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Abstract
Cost-effective biomass drying is a key challenge for energy recovery from biomass by direct combustion, gasification, and pyrolysis. The aim of the present study was to optimize the process of biomass drying using hot air convection (HA), infrared (IR), and combined drying systems [...] Read more.
Cost-effective biomass drying is a key challenge for energy recovery from biomass by direct combustion, gasification, and pyrolysis. The aim of the present study was to optimize the process of biomass drying using hot air convection (HA), infrared (IR), and combined drying systems (IR-HA). The specific energy consumption (SEC) decreased significantly by increasing the drying temperature using convective drying, but higher air velocities increased the SEC. Similarly, increasing air velocity in the infrared dryer resulted in a significant increase in SEC. The lowest SEC was recorded at 7.8 MJ/kg at an air velocity of 0.5 m/s and an IR intensity of 0.30 W/cm2, while a maximum SEC (20.7 MJ/kg) was observed at 1.0 m/s and 0.15 W/cm2. However, a significant reduction in the SEC was noticed in the combined drying system. A minimum SEC of 3.8 MJ/kg was recorded using the combined infrared-hot air convection (IR-HA) drying system, which was 91.7% and 51.7% lower than convective and IR dryers, respectively. The present study suggested a combination of IR and hot air convection at 60 °C, 0.3 W/cm2 and 0.5 m/s as optimum conditions for efficient drying of biomass with a high water content. Full article
(This article belongs to the Special Issue Biomass Pretreatment and Biomass Conversion to Biofuels)
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Open AccessArticle
Stochastic Evaluation of Landscapes Transformed by Renewable Energy Installations and Civil Works
Energies 2019, 12(14), 2817; https://doi.org/10.3390/en12142817
Received: 11 June 2019 / Revised: 4 July 2019 / Accepted: 14 July 2019 / Published: 22 July 2019
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Abstract
Renewable energy (RE) installations and civil works are beneficial in terms of sustainability, but a considerable amount of space in the landscape is required in order to harness this energy. In contemporary environmental theory the landscape is considered an environmental parameter and the [...] Read more.
Renewable energy (RE) installations and civil works are beneficial in terms of sustainability, but a considerable amount of space in the landscape is required in order to harness this energy. In contemporary environmental theory the landscape is considered an environmental parameter and the transformation of the landscape by RE works has received increasing attention by the scientific community and affected societies. This research develops a novel computational stochastic tool the 2D Climacogram (2D-C) that allows the analysis and comparison of images of landscapes, both original and transformed by RE works. This is achieved by a variability characterization of the grayscale intensity of 2D images. A benchmark analysis is performed for art paintings in order to evaluate the properties of the 2D-C for image analysis, and the change in variability among images. Extensive applications are performed for landscapes transformed by RE works. Results show that the 2D-C is able to quantify the changes in variability of the image features, which may prove useful in the landscape impact assessment of large-scale engineering works. Full article
(This article belongs to the Section Energy and Environment)
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Open AccessArticle
Health Assessment and Fault Detection System for an Industrial Robot Using the Rotary Encoder Signal
Energies 2019, 12(14), 2816; https://doi.org/10.3390/en12142816
Received: 26 May 2019 / Revised: 30 June 2019 / Accepted: 17 July 2019 / Published: 22 July 2019
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Abstract
In an industrial robot, rotary encoders have been extensively used for dynamic control and positioning. This study shows that the encoder signal, after appropriate processing, can also be efficiently utilized for the health observation of energy performance of industrial robots system. Singular spectrum [...] Read more.
In an industrial robot, rotary encoders have been extensively used for dynamic control and positioning. This study shows that the encoder signal, after appropriate processing, can also be efficiently utilized for the health observation of energy performance of industrial robots system. Singular spectrum analysis (SSA) and Hilbert transform (HT) is proposed in this work, for detecting weak position oscillations to estimate the instantaneous amplitudes (IA) and the instantaneous frequencies (IF) of an industrial robot based on the encoder signal. Compared with empirical mode decomposition (EMD) and HT, the singular spectrum analysis and Hilbert transform (SSAHT) outperforms empirical mode decomposition Hilbert transform (EMDHT) in terms of ability and precision to determine source noise, and it can accurately catch the weak oscillations without signal deformation in both position and speed introduced via mechanical flaws. Combined with SSA, the IA and IF of both oscillations and residual are extracted by HT. They are obtained from the robot arm movement. These features play an important role in improving the performance detecting weak oscillations and the residual, essential information to evaluate the health conditions and fault detection to serve the energy performance for the industrial robot. The efficiency of the proposed system has been verified both numerical simulation and experimental data. The outcomes prove that the proposed SSAHT can detect flaw indications and additionally, it can also identify faulty components. Thus, the study presents a promising tool for the health monitoring of an industrial robot instead of the vibration-based monitoring scheme. Full article
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Open AccessFeature PaperArticle
A Novel Multi-Agent-Based Collaborative Virtual Manufacturing Environment Integrated with Edge Computing Technique
Energies 2019, 12(14), 2815; https://doi.org/10.3390/en12142815
Received: 24 June 2019 / Revised: 17 July 2019 / Accepted: 17 July 2019 / Published: 22 July 2019
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Abstract
This paper proposes a multi-agent-based collaborative virtual manufacturing environment (VME) to save energy consumption and improve efficiency in the manufacturing process. In order to achieve the high autonomy of the manufacturing system, a multi-agent system (MAS) is designed to build a collaborative VME. [...] Read more.
This paper proposes a multi-agent-based collaborative virtual manufacturing environment (VME) to save energy consumption and improve efficiency in the manufacturing process. In order to achieve the high autonomy of the manufacturing system, a multi-agent system (MAS) is designed to build a collaborative VME. In this new VME environment, edge computing is embedded to strengthen the cyber resource utilization and system economy. Moreover, an efficient communication channel between networks is proposed. The subsequent cooperation and collaboration protocols among agents are designed to ensure flexible and process-oriented operations. Furthermore, the fuzzy resolution algorithm is employed to resolve the competition conflicts among function-similar MASs in the distributed manufacturing scenario. Lastly, a simulation and case study are performed to evaluate the performance of the proposed VME in Internet of Things (IoT)-based manufacturing. The analysis results have demonstrated the feasibility and effectiveness of the proposed VME system. Full article
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Open AccessArticle
Intelligent Classification Method for Grid-Monitoring Alarm Messages Based on Information Theory
Energies 2019, 12(14), 2814; https://doi.org/10.3390/en12142814
Received: 31 May 2019 / Revised: 13 July 2019 / Accepted: 16 July 2019 / Published: 22 July 2019
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Abstract
Alarm messages for grid monitoring are an important way to supervise the operation of power grids. Since the use of alarm messages is increasing exponentially due to the continuous expansion of the scale of power grids, a processing method for alarm messages based [...] Read more.
Alarm messages for grid monitoring are an important way to supervise the operation of power grids. Since the use of alarm messages is increasing exponentially due to the continuous expansion of the scale of power grids, a processing method for alarm messages based on statistics is proposed in this study. Entropy theory in information theory is introduced into the calculation of information value in power-grid alarming. By means of multiple entropy definitions, an evaluation index system for information value is constructed. Based on the analytic hierarchy process (AHP), various alarm-message entropies are used as indices to comprehensively assess the information value and level of each alarm message. Finally, an example is given to illustrate the effectiveness and practicality of the proposed method. This study provides a new idea for the intelligent classification of alarm messages. Full article
(This article belongs to the Special Issue Electric Power Systems Research 2019)
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Open AccessArticle
Digital Commons and Citizen Coproduction in Smart Cities: Assessment of Brazilian Municipal E-Government Platforms
Energies 2019, 12(14), 2813; https://doi.org/10.3390/en12142813
Received: 26 June 2019 / Revised: 9 July 2019 / Accepted: 9 July 2019 / Published: 22 July 2019
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Abstract
Good governance practices through electronic government (eGov) platforms can be suitable instruments for strengthening the outcomes of smart city policies. While eGov is the application of information and communication technologies to public services, good governance defines how well public authorities manage public and [...] Read more.
Good governance practices through electronic government (eGov) platforms can be suitable instruments for strengthening the outcomes of smart city policies. While eGov is the application of information and communication technologies to public services, good governance defines how well public authorities manage public and social resources. Contemporary public management views, such as ‘new public service’, include citizen participation as a critical factor to sustainable government in smart cities. Public services, in the age of digital technology, need to not only be delivered through eGov platforms, but also need to be coproduced with the engagement of social players, e.g., citizens. In this sense, eGov platforms act as digital commons, and conceived as digital spaces, where citizens and public agents interact and collaborate. In this paper, we presented the Municipal eGov Platform Assessment Model (MEPA), which is a model specifically developed to evaluate eGov platforms regarding their potential to promote commons in smart cities. The study applied MEPA to 903 municipal websites across Brazil. The results revealed that the majority of investigated Brazilian eGov platforms have only a low level of digital commons maturity. This finding discloses less citizenship coproduction, and fewer opportunities for city smartness. As the MEPA model offers public authorities an instrument to depict weaknesses and strengths of municipal eGov platforms, its adoption provides an opportunity for authorities to plan and manage their platforms to act as promoters of digital commons and citizen coproduction. Full article
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Open AccessArticle
Solution for Voltage and Frequency Regulation in Standalone Microgrid using Hybrid Multiobjective Symbiotic Organism Search Algorithm
Energies 2019, 12(14), 2812; https://doi.org/10.3390/en12142812
Received: 18 June 2019 / Revised: 18 July 2019 / Accepted: 19 July 2019 / Published: 22 July 2019
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Abstract
Voltage and frequency regulation is one of the greatest challenges for proper operation subsequent to the isolated microgrid. To validate the satisfactory electric power quality supply to customers, the proposed manuscript tries to enhance the quality of energy provided by DG (Distributed generation) [...] Read more.
Voltage and frequency regulation is one of the greatest challenges for proper operation subsequent to the isolated microgrid. To validate the satisfactory electric power quality supply to customers, the proposed manuscript tries to enhance the quality of energy provided by DG (Distributed generation) units connected to the subsequent isolated grid. Microgrid and simulation-based control structure including voltage and current control feedback loops is proposed for microgrid inverters to recover voltage and frequency of the system subsequently for any fluctuations in load change. The proportional-integral (PI) controller connected to the voltage controller is an end goal to obtain smooth response in most of the consistent frameworks. The present controller creates the space vector pulse width modulation signals which are given to the three-leg inverter. The objective elements of the multiobjective optimization issue are voltage overshoot and undershoot, rise time, settling time, and integral time absolute error (ITAE). The hybrid Multiobjective Symbiotic Organism Search (MOSOS) calculation is associated for self-tuning of control parameters keeping in mind the end goal to deal with the voltage and frequency. The proposed PI controller, along with the hybrid Multiobjective Symbiotic Organism Search algorithm, provides the solution for the greatest challenge of voltage and frequency regulation in an isolated-microgrid operation. Full article
(This article belongs to the Special Issue Real-time Communications for Smart Grids and Industry)
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Open AccessArticle
Microcontroller-Based Strategies for the Incorporation of Solar to Domestic Electricity
Energies 2019, 12(14), 2811; https://doi.org/10.3390/en12142811
Received: 4 June 2019 / Revised: 28 June 2019 / Accepted: 16 July 2019 / Published: 22 July 2019
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Abstract
Microcontrollers have been largely used in applications that include reducing power consumption. Microcontroller development tools are now readily available. Many countries are faced with energy challenges such as lack of enough power capacity and growth in energy demand. It is therefore important to [...] Read more.
Microcontrollers have been largely used in applications that include reducing power consumption. Microcontroller development tools are now readily available. Many countries are faced with energy challenges such as lack of enough power capacity and growth in energy demand. It is therefore important to introduce innovative methods to reduce reliance on national grid energy and to supplement this source of energy with alternative methods. In this study, the microcontroller is used to monitor the energy consumed by household equipment and then decide, based on the power demand and available solar energy, the type of energy source to be used. In this research, a special circuit was also designed to control geyser power and align it to the capacity of the renewable energy source. This geyser control circuit includes a Dallas temperature sensor and a triode for alternating current (TRIAC) circuit that is included to control output current drawn from a low power, renewable energy source. Alternatively, two heating elements may be used instead of the TRIAC circuit. The first heating element is powered by solar to maintain the water temperature and to save energy. The second heating element is powered by national grid power and is used for the initial heating, and therefore saves water heating time. The strategy used was by adding a programmed microcontroller-based control circuit and a low power element or one current controlled element to a geyser whereby Photovoltaic (PV) energy was used to save the energy geysers consume from the domestic electricity source when they are not in use. A microcontroller, current sensor, battery level sensor, and relay board was used to incorporate solar-based renewable energy to the commercial energy supply. Full article
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