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Energies, Volume 10, Issue 11 (November 2017)

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Cover Story (view full-size image) In this article, PROSA—a new multi-criteria decision-making method—is proposed. While PROSA has [...] Read more.
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Open AccessArticle A Cycle Voltage Measurement Method and Application in Grounding Grids Fault Location
Energies 2017, 10(11), 1929; https://doi.org/10.3390/en10111929
Received: 17 October 2017 / Revised: 12 November 2017 / Accepted: 16 November 2017 / Published: 21 November 2017
Cited by 2 | Viewed by 1233 | PDF Full-text (5865 KB) | HTML Full-text | XML Full-text
Abstract
The corrosion of grounding grids can result in a grounding accident of a power system, and much attentions has been concentrated on the method used to detect a corrosion fault in a grounding grid, in which the methods of voltage measurement and magnetic
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The corrosion of grounding grids can result in a grounding accident of a power system, and much attentions has been concentrated on the method used to detect a corrosion fault in a grounding grid, in which the methods of voltage measurement and magnetic field measurement are usually used. In this paper, a cycle voltage measurement method and L-curve regularization method are proposed to locate the faults in grounding grids. The L-curve method was used to select the appropriate regularization parameter, which can effectively balance the error and stability of the solution to the inverse problem. The uncertainty of the solution due to the ill-posed problem in the inverse problem has been well-solved. Experiments were conducted in a laboratory with two network types. In addition, a field experiment was carried out in a 110-kV substation. Both of the results showed that the method can effectively locate a branch fault with a single branch and multiple branches in the grounding grids. Full article
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Open AccessFeature PaperArticle All-Polyamide Composite Coated-Fabric as an Alternative Material of Construction for Textile-Bioreactors (TBRs)
Energies 2017, 10(11), 1928; https://doi.org/10.3390/en10111928
Received: 15 October 2017 / Revised: 12 November 2017 / Accepted: 14 November 2017 / Published: 21 November 2017
Cited by 2 | Viewed by 1402 | PDF Full-text (3393 KB) | HTML Full-text | XML Full-text
Abstract
All-polyamide composite coated-fabric (APCCF) was used as an alternative material for the construction of textile-bioreactors (TBRs), which are prepared as a replacement of the traditional stainless steel bioreactors (SSBRs) or concrete-based bioreactors. The material characteristics, as well as the fermentation process performance of
[...] Read more.
All-polyamide composite coated-fabric (APCCF) was used as an alternative material for the construction of textile-bioreactors (TBRs), which are prepared as a replacement of the traditional stainless steel bioreactors (SSBRs) or concrete-based bioreactors. The material characteristics, as well as the fermentation process performance of the APCCF-TBR, was compared with a TBR made using the polyvinyl chloride (PVC)-coated polyester fabric (PVCCF). The TBRs were used for the anaerobic fermentation process using baker’s yeast; and, for aerobic fermentation process using filamentous fungi, primarily by using waste streams from ethanol industries as the substrates. The results from the fermentation experiments were similar with those that were obtained from the cultivations that were carried out in conventional bioreactors. The techno-economic analysis conducted using a 5000 m3 APCCF-TBR for a typical fermentation facility would lead to a reduction of the annual production cost of the plant by $128,000,000 when compared to similar processes in SSBR. The comparative analyses (including mechanical and morphological studies, density measurements, thermal stability, ageing, and techno-economic analyses) revealed that the APCCF is a better candidate for the material of construction of the TBR. As the APCCF is a 100% recyclable single-polymer composite, which was prepared from Nylon 66 textile production-line waste, it could be considered as an environmentally sustainable product. Full article
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Open AccessArticle Model-Based Predictive Current Control Method with Constant Switching Frequency for Single-Phase Voltage Source Inverters
Energies 2017, 10(11), 1927; https://doi.org/10.3390/en10111927
Received: 24 October 2017 / Revised: 10 November 2017 / Accepted: 16 November 2017 / Published: 21 November 2017
Cited by 1 | Viewed by 1408 | PDF Full-text (8428 KB) | HTML Full-text | XML Full-text
Abstract
Voltage source inverters operated by predictive control methods generally lead to a variable switching frequency, because predictive control methods generate switching operation based on an optimal voltage state selected at every sampling period. Varying switching frequencies make it difficult to design output filters
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Voltage source inverters operated by predictive control methods generally lead to a variable switching frequency, because predictive control methods generate switching operation based on an optimal voltage state selected at every sampling period. Varying switching frequencies make it difficult to design output filters of voltage source inverters. This paper proposes a predictive control algorithm with a constant switching frequency for the load current control of single-phase voltage source inverters. This method selects two future optimal voltage states used in the subsequent sampling period, which are a zero-voltage state and a future optimal voltage state, based on the slope of the reference current at each sampling period. After selecting the two future voltages, the proposed method distributes them to produce a constant switching frequency and symmetric switching pattern. The performance of the proposed method is validated with both simulation and experimental results for single-phase voltage source inverters. Full article
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Open AccessFeature PaperArticle Optimal Curtailment of Non-Synchronous Renewable Generation on the Island of Tenerife Considering Steady State and Transient Stability Constraints
Energies 2017, 10(11), 1926; https://doi.org/10.3390/en10111926
Received: 2 November 2017 / Revised: 15 November 2017 / Accepted: 16 November 2017 / Published: 21 November 2017
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Abstract
The increasing penetration of non-synchronous, renewable energy in modern power systems displaces synchronous generation and affects transient stability. This is just one of the factors that has led to preventive curtailment of renewable energy sources in an increasing number of electrical grids. Transient
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The increasing penetration of non-synchronous, renewable energy in modern power systems displaces synchronous generation and affects transient stability. This is just one of the factors that has led to preventive curtailment of renewable energy sources in an increasing number of electrical grids. Transient stability constrained optimal power flow (OPF) techniques provide a tool to optimize the dispatch of power systems while ensuring a secure operation. This work proposes a transient stability-constrained OPF model that includes non-synchronous generation with fault ride-through capability and reactive support during voltage dips. The model is applied it to the IEEE 39 Bus benchmark test case and to the power system of the Spanish island of Tenerife, and solved using the open-source library IPOPT that implements a primal-dual interior point algorithm. The solution of the model makes it possible to optimize the dispatch of conventional plants and the curtailment of non-synchronous generation, as well as to explore methods to reduce generation cost. Fault ride-through capability, synchronous inertia and fault clearing times are identified as useful tools to reduce the curtailment of non-synchronous generation, especially during periods of low load and high availability of renewable energy sources. Full article
(This article belongs to the Section Electrical Power and Energy System)
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Open AccessArticle Impact of Reference Years on the Outcome of Multi-Objective Optimization for Building Energy Refurbishment
Energies 2017, 10(11), 1925; https://doi.org/10.3390/en10111925
Received: 15 October 2017 / Revised: 30 October 2017 / Accepted: 16 November 2017 / Published: 21 November 2017
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Abstract
There are several methods in the literature for the definition of weather data for building energy simulation and the most popular ones, such as typical meteorological years and European test reference years, are based on Finkelstein–Schafer statistics. However, even starting from the same
[...] Read more.
There are several methods in the literature for the definition of weather data for building energy simulation and the most popular ones, such as typical meteorological years and European test reference years, are based on Finkelstein–Schafer statistics. However, even starting from the same multi-year weather data series, the developed reference years can present different levels of representativeness, which can affect the simulation outcome. In this work, we investigated to which extent the uncertainty in the determination of typical weather conditions can affect the results of building energy refurbishment when cost-optimal approach is implemented for the selection of energy efficiency measures by means of the NSGA-II genetic algorithm coupled with TRNSYS simulations. Six different reference years were determined for two north Italy climates, Trento and Monza, respectively in the Alpine and in the continental temperate regions. Four types of energy efficiency measures, related to both building envelope and HVAC system, were applied to six existing building typologies. Results showed how the choice of reference year can alter the shape of the Pareto fronts, the number of solutions included and the selection among the alternatives of the energy efficiency measures, for the entire front and, in particular, for energy and economic optima. Full article
(This article belongs to the Section Energy Storage and Application)
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Open AccessArticle Optimization of a Heliostat Field Layout on Annual Basis Using a Hybrid Algorithm Combining Particle Swarm Optimization Algorithm and Genetic Algorithm
Energies 2017, 10(11), 1924; https://doi.org/10.3390/en10111924
Received: 25 October 2017 / Revised: 13 November 2017 / Accepted: 15 November 2017 / Published: 21 November 2017
Cited by 2 | Viewed by 940 | PDF Full-text (2173 KB) | HTML Full-text | XML Full-text
Abstract
Of all the renewable power generation technologies, solar tower power system is expected to be the most promising technology that is capable of large-scale electricity production. However, the optimization of heliostat field layout is a complicated process, in which thousands of heliostats have
[...] Read more.
Of all the renewable power generation technologies, solar tower power system is expected to be the most promising technology that is capable of large-scale electricity production. However, the optimization of heliostat field layout is a complicated process, in which thousands of heliostats have to be considered for any heliostat field optimization process. Therefore, in this paper, in order to optimize the heliostat field to obtain the highest energy collected per unit cost (ECUC), a mathematical model of a heliostat field and a hybrid algorithm combining particle swarm optimization algorithm and genetic algorithm (PSO-GA) are coded in Matlab and the heliostat field in Lhasa is investigated as an example. The results show that, after optimization, the annual efficiency of the heliostat field increases by approximately six percentage points, and the ECUC increases from 12.50 MJ/USD to 12.97 MJ/USD, increased about 3.8%. Studies on the key parameters indicate that: for un-optimized filed, ECUC first peaks and then decline with the increase of the number of heliostats in the first row of the field (Nhel1). By contrast, for optimized field, ECUC increases with Nhel1. What is more, for both the un-optimized and optimized field, ECUC increases with tower height and decreases with the cost of heliostat mirror collector. Full article
(This article belongs to the Section Electrical Power and Energy System)
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Open AccessArticle Energy Management and Control of Plug-In Hybrid Electric Vehicle Charging Stations in a Grid-Connected Hybrid Power System
Energies 2017, 10(11), 1923; https://doi.org/10.3390/en10111923
Received: 13 October 2017 / Revised: 10 November 2017 / Accepted: 10 November 2017 / Published: 21 November 2017
Cited by 6 | Viewed by 2015 | PDF Full-text (4803 KB) | HTML Full-text | XML Full-text
Abstract
The charging infrastructure plays a key role in the healthy and rapid development of the electric vehicle industry. This paper presents an energy management and control system of an electric vehicle charging station. The charging station (CS) is integrated to a
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The charging infrastructure plays a key role in the healthy and rapid development of the electric vehicle industry. This paper presents an energy management and control system of an electric vehicle charging station. The charging station (CS) is integrated to a grid-connected hybrid power system having a wind turbine maximum power point tracking (MPPT) controlled subsystem, photovoltaic (PV) MPPT controlled subsystem and a controlled solid oxide fuel cell with electrolyzer subsystem which are characterized as renewable energy sources. In this article, an energy management system is designed for charging and discharging of five different plug-in hybrid electric vehicles (PHEVs) simultaneously to fulfil the grid-to-vehicle (G2V), vehicle-to-grid (V2G), grid-to-battery storage system (G2BSS), battery storage system-to-grid (BSS2G), battery storage system-to-vehicle (BSS2V), vehicle-to-battery storage system (V2BSS) and vehicle-to-vehicle (V2V) charging and discharging requirements of the charging station. A simulation test-bed in Matlab/Simulink is developed to evaluate and control adaptively the AC-DC-AC converter of non-renewable energy source, DC-DC converters of the storage system, DC-AC grid side inverter and the converters of the CS using adaptive proportional-integral-derivate (AdapPID) control paradigm. The effectiveness of the AdapPID control strategy is validated through simulation results by comparing with conventional PID control scheme. Full article
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Open AccessArticle Analysis of the Potential of Low-Temperature Heat Pump Energy Sources
Energies 2017, 10(11), 1922; https://doi.org/10.3390/en10111922
Received: 27 September 2017 / Revised: 8 November 2017 / Accepted: 15 November 2017 / Published: 21 November 2017
Cited by 1 | Viewed by 855 | PDF Full-text (2402 KB) | HTML Full-text | XML Full-text
Abstract
The paper deals with an analysis of temperatures of ground masses in the proximities of linear and slinky-type HGHE (horizontal ground heat exchanger). It evaluates and compares the potentials of HGHEs and ambient air. The reason and aim of the verification was to
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The paper deals with an analysis of temperatures of ground masses in the proximities of linear and slinky-type HGHE (horizontal ground heat exchanger). It evaluates and compares the potentials of HGHEs and ambient air. The reason and aim of the verification was to gain knowledge of the temperature course of the monitored low-temperature heat pump energy sources during heating periods and periods of stagnation and to analyse the knowledge in terms of the potential to use those sources for heat pumps. The study was conducted in the years 2012–2015 during three heating periods and three periods of HGHEs stagnation. The results revealed that linear HGHE had the highest temperature potential of the observed low-temperature heat pump energy sources. The average daily temperatures of the ground mass surrounding the linear HGHE were the highest ranging from 7.08 °C to 9.20 °C during the heating periods, and having the lowest temperature variation range of 12.62–15.14 K, the relative frequency of the average daily temperatures of the ground mass being the highest at 22.64% in the temperature range containing the mode of all monitored temperatures in a recorded interval of [4.10, 6.00] °C. Ambient air had lower temperature potential than the monitored HGHEs. Full article
(This article belongs to the Section Energy Sources)
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Open AccessArticle Optimal Design of Thermal Radiative Heating of Horizontal Thin Plates Using the Entropy Generation Minimization Method
Energies 2017, 10(11), 1921; https://doi.org/10.3390/en10111921
Received: 26 September 2017 / Revised: 26 October 2017 / Accepted: 13 November 2017 / Published: 21 November 2017
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Abstract
Thermal radiant heating through distinct heat sources is of interest for the thermal loading of thin objects as it is used in residential applications, furnaces, and insulator designs. In this paper, an optimal design for a thermal radiant system by discrete suspended heat
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Thermal radiant heating through distinct heat sources is of interest for the thermal loading of thin objects as it is used in residential applications, furnaces, and insulator designs. In this paper, an optimal design for a thermal radiant system by discrete suspended heat sources is analyzed in a side open cavity used for heating the top plate, while the bottom plate is kept at a constant temperature, using the entropy generation minimization method. To avoid pressure fluctuations, the semi-implicit method for pressure linked equations method is used, which solves the continuity, Navier-Stokes, fluid energy, and surface energy equations simultaneously. The system is optimized based on the characteristic length of discrete heat sources, height of discrete heat sources from the bottom plate, the distance between discrete heat sources, the number of discrete heat sources, and the aspect ratio of the cavity that finds the optimal location of heating elements. In addition to the geometrical parameters, the effects of the thermal loading parameters on the optimal position are investigated. Full article
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Open AccessArticle Kinetics and Mechanism of NaOH-Impregnated Calcined Oyster Shell-Catalyzed Transesterification of Soybean Oil
Energies 2017, 10(11), 1920; https://doi.org/10.3390/en10111920
Received: 25 September 2017 / Revised: 10 November 2017 / Accepted: 15 November 2017 / Published: 21 November 2017
Cited by 2 | Viewed by 1179 | PDF Full-text (4919 KB) | HTML Full-text | XML Full-text
Abstract
The objective of this research is to develop a kinetic model to describe the transesterification of soybean oil with methanol using NaOH-impregnated calcined oyster shell (Na-COS). Batch experiments were performed via a two-factor randomized complete block design using a molar ratio of methanol
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The objective of this research is to develop a kinetic model to describe the transesterification of soybean oil with methanol using NaOH-impregnated calcined oyster shell (Na-COS). Batch experiments were performed via a two-factor randomized complete block design using a molar ratio of methanol to oil (MR) of 6, 12, and 18 and catalyst loadings (CL) (mass of catalyst/mass of oil in %) of 2%, 4%, 6%, and 8% to obtain fatty acid methyl ester yields. In addition, the catalyst was studied by X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and time-of-flight secondary ion spectrometry (TOF-SIMS) to elucidate the role of the catalyst in the transesterification reaction. XRD and XPS analyses suggested that the formation of sodium peroxide (Na2O2) on the surface contributed to catalytic activity. The TOF-SIMS analysis suggested that the transesterification occurred between adsorbed triglyceride and free methanol, similar to the Eley-Rideal mechanism. The transesterification of adsorbed triglyceride to adsorbed diglyceride was found to be the rate-determining step with a rate constant of 0.0059 ± 0.0002 L mol−1 min−1. Full article
(This article belongs to the Section Energy Sources)
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Open AccessArticle Effect of Coal Grain Size on Sorption Capacity with Respect to Propylene and Acetylene
Energies 2017, 10(11), 1919; https://doi.org/10.3390/en10111919
Received: 3 October 2017 / Revised: 17 November 2017 / Accepted: 20 November 2017 / Published: 21 November 2017
Cited by 3 | Viewed by 689 | PDF Full-text (640 KB) | HTML Full-text | XML Full-text
Abstract
Propylene and acetylene are released to mine air with the increase in the temperature of self-heating coal. Concentrations of these gases in mine air are applied as indicators of the progress of the self-heating process. Hydrocarbons emitted from the self-ignition center are sorbed
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Propylene and acetylene are released to mine air with the increase in the temperature of self-heating coal. Concentrations of these gases in mine air are applied as indicators of the progress of the self-heating process. Hydrocarbons emitted from the self-ignition center are sorbed on coal, while migrating through the mine workings. Coal crushed during the mining process is characterized by a high sorption capacity, which facilitates the sorption phenomena. This results in the decrease in hydrocarbons content in mine air, and in the subsequent incorrect assessment of the development of the self-heating process. The results of the experimental study on propylene and acetylene sorption on Polish coals acquired from operating coal mines are presented in this paper. Bituminous coal is characterized by a high sorption capacity with respect to unsaturated hydrocarbons, like propylene and acetylene. The sorbed volumes depend on the grade of metamorphism, porosity, and chemical characteristics of coal. Low level of metamorphism, increased porosity, and oxygen content result in higher sorption capacity of coals. The reduction in grain size of coals also results in the increased sorption capacity with respect to hydrocarbons. The most significant increase in the volumes of sorbed propylene and acetylene with the decrease in grain class was observed for coals of low porosity, high grade of metamorphism, and low to medium sorption capacities. The 10-fold decrease in coal grain size resulted in the 3 to 6-fold increase in the volume of sorbed propylene, and 2-fold increase for acetylene. The decrease in grain size results in higher accessibility of pore structure, increased pore volume and area, and higher number of active centers interacting with hydrocarbons of dipole characteristics. For coals with low grade metamorphism, high porosity, and high sorption capacity the volumes of sorbed propylene and acetylene increased only slightly with the decrease in coal grain size. Full article
(This article belongs to the Section Energy Sources)
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Open AccessArticle Modeling of Electricity Demand for Azerbaijan: Time-Varying Coefficient Cointegration Approach
Energies 2017, 10(11), 1918; https://doi.org/10.3390/en10111918
Received: 31 October 2017 / Revised: 15 November 2017 / Accepted: 17 November 2017 / Published: 21 November 2017
Cited by 2 | Viewed by 869 | PDF Full-text (667 KB) | HTML Full-text | XML Full-text
Abstract
Recent literature has shown that electricity demand elasticities may not be constant over time and this has investigated using time-varying estimation methods. As accurate modeling of electricity demand is very important in Azerbaijan, which is a transitional country facing significant change in its
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Recent literature has shown that electricity demand elasticities may not be constant over time and this has investigated using time-varying estimation methods. As accurate modeling of electricity demand is very important in Azerbaijan, which is a transitional country facing significant change in its economic outlook, we analyze whether the response of electricity demand to income and price is varying over time in this economy. We employed the Time-Varying Coefficient cointegration approach, a cutting-edge time-varying estimation method. We find evidence that income elasticity demonstrates sizeable variation for the period of investigation ranging from 0.48% to 0.56%. The study has some useful policy implications related to the income and price aspects of the electricity consumption in Azerbaijan. Full article
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Open AccessArticle Considering Maintenance Cost in Unit Commitment Problems
Energies 2017, 10(11), 1917; https://doi.org/10.3390/en10111917
Received: 11 August 2017 / Revised: 16 September 2017 / Accepted: 17 November 2017 / Published: 21 November 2017
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Abstract
Electric power systems worldwide are receiving an increasing volume of wind power generation (WPG) because of environmental concerns and cost declines associated with technological innovation. To manage the uncertainty of WPG, a system operator must commit sufficient conventional generators to provide an appropriate
[...] Read more.
Electric power systems worldwide are receiving an increasing volume of wind power generation (WPG) because of environmental concerns and cost declines associated with technological innovation. To manage the uncertainty of WPG, a system operator must commit sufficient conventional generators to provide an appropriate reserve. At times, frequent start and stop operations are applied to certain generators, which incurs maintenance costs associated with thermal-mechanical fatigue. In this paper, we suggest a comprehensive approach to unit commitment (UC) that considers maintenance cost: the parameters of equivalent start (ES) and equivalent base load hours (EBHs) are adopted in the UC problem to determine optimal generation scheduling. A new formulation for the maintenance cost that can be readily combined with an existing mixed integer linear programming algorithm is presented. The effectiveness of the proposed UC method is verified through simulations based on an IEEE 118-bus test system. The simulation results show that considering maintenance cost in the UC problem effectively restricts frequent start and stop operation scheduling. Furthermore, the operating cost is reduced, the required reserve level is maintained, and the computational time is comparable with that of the conventional UC method. Full article
(This article belongs to the Section Electrical Power and Energy System)
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Open AccessArticle Aging Cost Optimization for Planning and Management of Energy Storage Systems
Energies 2017, 10(11), 1916; https://doi.org/10.3390/en10111916
Received: 10 October 2017 / Revised: 11 November 2017 / Accepted: 12 November 2017 / Published: 21 November 2017
Cited by 2 | Viewed by 898 | PDF Full-text (2238 KB) | HTML Full-text | XML Full-text
Abstract
In recent years, many studies have proposed the use of energy storage systems (ESSs) for the mitigation of renewable energy source (RES) intermittent power output. However, the correct estimation of the ESS degradation costs is still an open issue, due to the difficult
[...] Read more.
In recent years, many studies have proposed the use of energy storage systems (ESSs) for the mitigation of renewable energy source (RES) intermittent power output. However, the correct estimation of the ESS degradation costs is still an open issue, due to the difficult estimation of their aging in the presence of intermittent power inputs. This is particularly true for battery ESSs (BESSs), which have been proven to exhibit complex aging functions. Unfortunately, this collides with considering aging costs when performing ESS planning and management procedures, which are crucial for the exploitation of this technology. In order to overcome this issue, this paper presents the genetic algorithm-based multi-period optimal power flow (GA-MPOPF) procedure, which aims to economically optimize the management of ESSs by taking into account their degradation costs. The proposed methodology has been tested in two different applications: the planning of the correct positioning of a Li-ion BESS in the PG& E 69 bus network in the presence of high RES penetration, and the definition of its management strategy. Simulation results show that GA-MPOPF is able to optimize the ESS usage for time scales of up to one month, even for complex operative costs functions, showing at the same time excellent convergence properties. Full article
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Open AccessFeature PaperArticle The Techno-Economics of Small-Scale Residential Heating in Low Carbon Futures
Energies 2017, 10(11), 1915; https://doi.org/10.3390/en10111915
Received: 19 September 2017 / Revised: 16 October 2017 / Accepted: 12 November 2017 / Published: 21 November 2017
Cited by 1 | Viewed by 811 | PDF Full-text (6425 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Existing studies that consider the techno-economics of residential heating systems typically focus on their performance within present-day energy systems. However, the energy system within which these technologies operate will need to change radically if climate change mitigation is to be achieved. This article
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Existing studies that consider the techno-economics of residential heating systems typically focus on their performance within present-day energy systems. However, the energy system within which these technologies operate will need to change radically if climate change mitigation is to be achieved. This article addresses this problem by modelling small-scale heating techno-economics in the context of significant electricity system decarbonisation. The current electricity market price regime based on short run marginal costs is seen to provide a very weak investment signal for electricity system investors, so an electricity price regime based on long run marginal energy costs is also considered, using a case study of the UK in 2035. The economic case for conventional boilers remains stronger in most dwelling types. The exception to this is for dwellings with high annual heat demand. Sensitivity studies demonstrate the impact of factors such as price of natural gas, carbon intensity of the central grid and thermodynamic performance. Fuel cell micro combined heat and power shows most potential under the long run electricity price regime, and heat pumps under the short run electricity price regime. This difference highlights the importance of future electricity market structure on consumer choice of heating systems in the future. Full article
(This article belongs to the Section Energy Fundamentals and Conversion)
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Open AccessArticle An Interval Fuzzy-Stochastic Chance-Constrained Programming Based Energy-Water Nexus Model for Planning Electric Power Systems
Energies 2017, 10(11), 1914; https://doi.org/10.3390/en10111914
Received: 1 October 2017 / Revised: 5 November 2017 / Accepted: 13 November 2017 / Published: 20 November 2017
Cited by 2 | Viewed by 817 | PDF Full-text (5004 KB) | HTML Full-text | XML Full-text
Abstract
In this study, an interval fuzzy-stochastic chance-constrained programming based energy-water nexus (IFSCP-WEN) model is developed for planning electric power system (EPS). The IFSCP-WEN model can tackle uncertainties expressed as possibility and probability distributions, as well as interval values. Different credibility (i.e., γ)
[...] Read more.
In this study, an interval fuzzy-stochastic chance-constrained programming based energy-water nexus (IFSCP-WEN) model is developed for planning electric power system (EPS). The IFSCP-WEN model can tackle uncertainties expressed as possibility and probability distributions, as well as interval values. Different credibility (i.e., γ) levels and probability (i.e., qi) levels are set to reflect relationships among water supply, electricity generation, system cost, and constraint-violation risk. Results reveal that different γ and qi levels can lead to a changed system cost, imported electricity, electricity generation, and water supply. Results also disclose that the study EPS would tend to the transition from coal-dominated into clean energy-dominated. Gas-fired would be the main electric utility to supply electricity at the end of the planning horizon, occupying [28.47, 30.34]% (where 28.47% and 30.34% present the lower bound and the upper bound of interval value, respectively) of the total electricity generation. Correspondingly, water allocated to gas-fired would reach the highest, occupying [33.92, 34.72]% of total water supply. Surface water would be the main water source, accounting for more than [40.96, 43.44]% of the total water supply. The ratio of recycled water to total water supply would increase by about [11.37, 14.85]%. Results of the IFSCP-WEN model present its potential for sustainable EPS planning by co-optimizing energy and water resources. Full article
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Open AccessArticle Failure Prognosis of High Voltage Circuit Breakers with Temporal Latent Dirichlet Allocation
Energies 2017, 10(11), 1913; https://doi.org/10.3390/en10111913
Received: 15 October 2017 / Revised: 11 November 2017 / Accepted: 15 November 2017 / Published: 20 November 2017
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Abstract
The continual accumulation of power grid failure logs provides a valuable but rarely used source for data mining. Sequential analysis, aiming at exploiting the temporal evolution and exploring the future trend in power grid failures, is an increasingly promising alternative for predictive scheduling
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The continual accumulation of power grid failure logs provides a valuable but rarely used source for data mining. Sequential analysis, aiming at exploiting the temporal evolution and exploring the future trend in power grid failures, is an increasingly promising alternative for predictive scheduling and decision-making. In this paper, a temporal Latent Dirichlet Allocation (TLDA) framework is proposed to proactively reduce the cardinality of the event categories and estimate the future failure distributions by automatically uncovering the hidden patterns. The aim was to model the failure sequence as a mixture of several failure patterns, each of which was characterized by an infinite mixture of failures with certain probabilities. This state space dependency was captured by a hierarchical Bayesian framework. The model was temporally extended by establishing the long-term dependency with new co-occurrence patterns. Evaluation of the high voltage circuit breakers (HVCBs) demonstrated that the TLDA model had higher fidelities of 51.13%, 73.86%, and 92.93% in the Top-1, Top-5, and Top-10 failure prediction tasks over the baselines, respectively. In addition to the quantitative results, we showed that the TLDA can be successfully used for extracting the time-varying failure patterns and capture the failure association with a cluster coalition method. Full article
(This article belongs to the Special Issue 2017 Prognostics and System Health Management Conference)
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Open AccessArticle Modeling and Control of Fluid Flow Networks with Application to a Nuclear-Solar Hybrid Plant
Energies 2017, 10(11), 1912; https://doi.org/10.3390/en10111912
Received: 1 November 2017 / Revised: 13 November 2017 / Accepted: 18 November 2017 / Published: 20 November 2017
Cited by 2 | Viewed by 1377 | PDF Full-text (4107 KB) | HTML Full-text | XML Full-text
Abstract
Fluid flow networks (FFNs) can be utilized to integrate multiple once-through heat supply system (OTHSS) modules based on either the same or different energy resources such as the renewable, nuclear and fossil for multi-modular and hybrid energy systems. Modeling and control is very
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Fluid flow networks (FFNs) can be utilized to integrate multiple once-through heat supply system (OTHSS) modules based on either the same or different energy resources such as the renewable, nuclear and fossil for multi-modular and hybrid energy systems. Modeling and control is very important for the safe, stable and efficient operation of the FFNs, whose objective is to maintain both the flowrates and pressure-drops of the network branches within specific bounds. In this paper, a differential-algebraic nonlinear dynamic model for general FFNs with multiple pump branches is proposed based on both the branch hydraulics and network graph properties. Then, an adaptive decentralized FFN flowrate-pressure control law, which takes a proportional-integral (PI) form with saturation on the integral terms, is established. This newly-built control not only guarantees satisfactory closed-loop global stability but also has no need for the values of network hydraulic parameters. This adaptive control is then applied to the flowrate-pressure regulation of the secondary FFN of a two-modular nuclear-solar hybrid energy system and numerical simulation results show the feasibility and high performance of this network control strategy. Due to its concise form, this new flowrate-pressure FFN controller can be easily implemented practically. Full article
(This article belongs to the Special Issue The Future of Solar Thermal Energy)
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Open AccessArticle Economic Analysis of Flat-Plate and U-Tube Solar Collectors Using an Al2O3 Nanofluid
Energies 2017, 10(11), 1911; https://doi.org/10.3390/en10111911
Received: 19 October 2017 / Revised: 9 November 2017 / Accepted: 15 November 2017 / Published: 20 November 2017
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Abstract
In this study, the efficiencies of flat-plate and U-tube solar collectors were investigated experimentally when an Al2O3 nanofluid was used as a working fluid and compared to those of solar collectors using water. The energy savings and CO2 and
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In this study, the efficiencies of flat-plate and U-tube solar collectors were investigated experimentally when an Al2O3 nanofluid was used as a working fluid and compared to those of solar collectors using water. The energy savings and CO2 and SO2 generated were calculated and compared to those of solar collectors using water. In addition, based on the experimental results, an economic analysis of the use of solar collectors in various countries was performed. As the concentration of the Al2O3 nanofluid increased, the performance of the solar collector improved. The highest efficiency for the solar collectors was shown at the concentration of 1.0 vol % with the nanoparticle size of 20 nm. The maximum efficiencies of the flat-plate and U-tube solar collectors using a 1.0 vol %-Al2O3 nanofluid with 20-nm nanoparticles was 74.9% and 72.4%, respectively, when the heat loss parameter was zero. The efficiencies of the flat-plate and U-tube solar collectors using Al2O3 nanofluid were 14.8% and 10.7% higher, respectively, than those using water. When 50 EA (each) flat-plate solar collectors were operated for one year using an Al2O3 nanofluid, the coal use, generated CO2, and generated SO2 were 189.99 kg, 556.69 kg, and 2.03 kg less than those of solar collectors using water, respectively. In addition, the largest electricity cost reduction was in Germany. Full article
(This article belongs to the Section Energy Storage and Application)
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Open AccessArticle Ground-Fault Characteristic Analysis of Grid-Connected Photovoltaic Stations with Neutral Grounding Resistance
Energies 2017, 10(11), 1910; https://doi.org/10.3390/en10111910
Received: 19 October 2017 / Revised: 9 November 2017 / Accepted: 15 November 2017 / Published: 20 November 2017
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Abstract
A centralized grid-connected photovoltaic (PV) station is a widely adopted method of neutral grounding using resistance, which can potentially make pre-existing protection systems invalid and threaten the safety of power grids. Therefore, studying the fault characteristics of grid-connected PV systems and their impact
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A centralized grid-connected photovoltaic (PV) station is a widely adopted method of neutral grounding using resistance, which can potentially make pre-existing protection systems invalid and threaten the safety of power grids. Therefore, studying the fault characteristics of grid-connected PV systems and their impact on power-grid protection is of great importance. Based on an analysis of the grid structure of a grid-connected PV system and of the low-voltage ride-through control characteristics of a photovoltaic power supply, this paper proposes a short-circuit calculation model and a fault-calculation method for this kind of system. With respect to the change of system parameters, particularly the resistance connected to the neutral point, and the possible impact on protective actions, this paper achieves the general rule of short-circuit current characteristics through a simulation, which provides a reference for devising protection configurations. Full article
(This article belongs to the Section Electrical Power and Energy System)
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Open AccessArticle An Optimal Power and Energy Management by Hybrid Energy Storage Systems in Microgrids
Energies 2017, 10(11), 1909; https://doi.org/10.3390/en10111909
Received: 30 September 2017 / Revised: 20 October 2017 / Accepted: 23 October 2017 / Published: 20 November 2017
Cited by 5 | Viewed by 1436 | PDF Full-text (30287 KB) | HTML Full-text | XML Full-text
Abstract
A novel optimal power and energy management (OPEM) for centralized hybrid energy storage systems (HESS) in microgrids is presented in this paper. The proposed OPEM aims at providing multiple grid services by suitably exploiting the different power/energy features of electrochemical batteries (B
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A novel optimal power and energy management (OPEM) for centralized hybrid energy storage systems (HESS) in microgrids is presented in this paper. The proposed OPEM aims at providing multiple grid services by suitably exploiting the different power/energy features of electrochemical batteries (B) and supercapacitors (S). The first part of the paper focuses on the design and analysis of the proposed OPEM, by highlighting the advantages of employing hand-designed solutions based on Pontryagin’s minimum principle rather than resorting to pre-defined optimization tools. Particularly, the B power profile is synthesized optimally over a given time horizon in order to provide both peak shaving and reduced grid energy buffering, while S is employed in order to compensate for short-term forecasting errors and to prevent B from handling sudden and high-frequency power fluctuations. Both the B and S power profiles are computed in real-time in order to benefit from more accurate forecasting, as well as to support each other. Then, the effectiveness of the proposed OPEM is tested through numerical simulations, which have been carried out based on real data from the German island of Borkum. Particularly, an extensive and detailed performance analysis is performed by comparing OPEM with a frequency-based management strategy (FBM) in order to highlight the superior performance achievable by the proposed OPEM in terms of both power and energy management and HESS exploitation. Full article
(This article belongs to the Section Energy Storage and Application)
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Open AccessArticle Influence of Different Types of Obstacles on the Propagation of Premixed Methane-Air Flames in a Half-Open Tube
Energies 2017, 10(11), 1908; https://doi.org/10.3390/en10111908
Received: 21 October 2017 / Revised: 15 November 2017 / Accepted: 17 November 2017 / Published: 20 November 2017
Cited by 1 | Viewed by 954 | PDF Full-text (1406 KB) | HTML Full-text | XML Full-text
Abstract
To understand the propagation characteristics of methane-air deflagration flames and in an obstacle-filled tube, a high-speed color video camera, photoelectric sensors, and pressure transducers were used to test the deflagration flame propagating parameters. The tests were run in a 1500 mm long plexiglass
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To understand the propagation characteristics of methane-air deflagration flames and in an obstacle-filled tube, a high-speed color video camera, photoelectric sensors, and pressure transducers were used to test the deflagration flame propagating parameters. The tests were run in a 1500 mm long plexiglass tube with a 100 × 100 mm square cross-section. The obstacles included four types of repeated baffles and five forms of solid structure obstacles. The results showed that: (1) the flame front was constantly distorted, stretched, and deformed by different types of obstacles and, consequently, the flame propagating parameters increased; (2) plates and triple prisms increased the speed of the flame and overpressure to the highest extent, whereas cuboids and quadrangulars exerted an intermediate effect. However, the effect of cylindrical obstacles was comparatively limited. It was suggested that the obstacle’s surface edge mutation or curvature changes were the main factors stimulating the flame acceleration; (3) the peak pressure of deflagration was relatively low near the ignition end, increased gradually until it reached the maximum at the middle of the tube, and decreased rapidly near the open end; and (4) the fixed obstacles in front of the flame exhibited a blocking effect on flame propagation during the initial stages; the flame speed and overpressure increased when the flame came into contact with the obstacles. This study is of significance because it explains the methane-air propagation mechanism induced by different types of obstacles. The findings have value for preventing or controlling gas explosion disasters. Full article
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Open AccessArticle Investigation of the Effect of Physical and Optical Factors on the Optical Performance of a Parabolic Trough Collector
Energies 2017, 10(11), 1907; https://doi.org/10.3390/en10111907
Received: 30 September 2017 / Revised: 23 October 2017 / Accepted: 2 November 2017 / Published: 20 November 2017
Cited by 2 | Viewed by 1184 | PDF Full-text (5865 KB) | HTML Full-text | XML Full-text
Abstract
The overall thermal performance of a Parabolic Trough Collector (PTC) depends on its optical performance, particularly the uniformity of the irradiance distribution and the resultant optical efficiency of the collector. Local Concentration Ratio (LCR), optical efficiency and average light concentration are three fundamental
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The overall thermal performance of a Parabolic Trough Collector (PTC) depends on its optical performance, particularly the uniformity of the irradiance distribution and the resultant optical efficiency of the collector. Local Concentration Ratio (LCR), optical efficiency and average light concentration are three fundamental parameters of the optical performance of a PTC. These parameters are affected by various optical and physical factors. The effects of these individual factors on the performance parameters were investigated in this study using a verified Monte Carlo ray tracing optical simulation model. The investigation revealed that all three performance parameters are directly related to the optical properties of the collector components. The values decreased gradually with the increase of focal length of the mirror. Uniformity of the LCR profile was observed to decrease with increasing rim angle and geometric concentration. Defocus dislocation of the receiver was found to improve the uniformity of the LCR distribution by decreasing its peak concentrations, Cmax. Off-focus dislocation of the receiver, and inward angular deviation of the mirror profile were observed to increase the Cmax and decrease the uniformity of the LCR distribition. Out-focus dislocation of the receiver and solar tracking error distort the bi-symmetry of a normal LCR profile. Full article
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Open AccessArticle Neural Adaptive Sliding-Mode Control of a Vehicle Platoon Using Output Feedback
Energies 2017, 10(11), 1906; https://doi.org/10.3390/en10111906
Received: 31 October 2017 / Revised: 12 November 2017 / Accepted: 15 November 2017 / Published: 20 November 2017
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Abstract
This paper investigates the output feedback control problem of a vehicle platoon with a constant time headway (CTH) policy, where each vehicle can communicate with its consecutive vehicles. Firstly, based on the integrated-sliding-mode (ISM) technique, a neural adaptive sliding-mode control algorithm is developed
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This paper investigates the output feedback control problem of a vehicle platoon with a constant time headway (CTH) policy, where each vehicle can communicate with its consecutive vehicles. Firstly, based on the integrated-sliding-mode (ISM) technique, a neural adaptive sliding-mode control algorithm is developed to ensure that the vehicle platoon is moving with the CTH policy and full state measurement. Then, to further decrease the measurement complexity and reduce the communication load, an output feedback control protocol is proposed with only position information, in which a higher order sliding-mode observer is designed to estimate the other required information (velocities and accelerations). In order to avoid collisions among the vehicles, the string stability of the whole vehicle platoon is proven through the stability theorem. Finally, numerical simulation results are provided to verify its effectiveness and advantages over the traditional sliding-mode control method in vehicle platoons. Full article
(This article belongs to the Special Issue Networked and Distributed Control Systems)
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Open AccessFeature PaperArticle Machine Learning-Based Short-Term Prediction of Air-Conditioning Load through Smart Meter Analytics
Energies 2017, 10(11), 1905; https://doi.org/10.3390/en10111905
Received: 2 October 2017 / Revised: 31 October 2017 / Accepted: 15 November 2017 / Published: 19 November 2017
Cited by 3 | Viewed by 1186 | PDF Full-text (3102 KB) | HTML Full-text | XML Full-text
Abstract
The present paper is focused on short-term prediction of air-conditioning (AC) load of residential buildings using the data obtained from a conventional smart meter. The AC load, at each time step, is separated from smart meter’s aggregate consumption through energy disaggregation methodology. The
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The present paper is focused on short-term prediction of air-conditioning (AC) load of residential buildings using the data obtained from a conventional smart meter. The AC load, at each time step, is separated from smart meter’s aggregate consumption through energy disaggregation methodology. The obtained air-conditioning load and the corresponding historical weather data are then employed as input features for the prediction procedure. In the prediction step, different machine learning algorithms, including Artificial Neural Networks, Support Vector Machines, and Random Forests, are used in order to conduct hour-ahead and day-ahead predictions. The predictions obtained using Random Forests have been demonstrated to be the most accurate ones leading to hour-ahead and day-ahead prediction with R2 scores of 87.3% and 83.2%, respectively. The main advantage of the present methodology is separating the AC consumption from the consumptions of other residential appliances, which can then be predicted employing short-term weather forecasts. The other devices’ consumptions are largely dependent upon the occupant’s behaviour and are thus more difficult to predict. Therefore, the harsh alterations in the consumption of AC equipment, due to variations in the weather conditions, can be predicted with a higher accuracy; which in turn enhances the overall load prediction accuracy. Full article
(This article belongs to the Section Energy Fundamentals and Conversion)
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Open AccessReview Performance and Reliability of Wind Turbines: A Review
Energies 2017, 10(11), 1904; https://doi.org/10.3390/en10111904
Received: 29 September 2017 / Revised: 22 October 2017 / Accepted: 9 November 2017 / Published: 19 November 2017
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Abstract
Performance (availability and yield) and reliability of wind turbines can make the difference between success and failure of wind farm projects and these factors are vital to decrease the cost of energy. During the last years, several initiatives started to gather data on
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Performance (availability and yield) and reliability of wind turbines can make the difference between success and failure of wind farm projects and these factors are vital to decrease the cost of energy. During the last years, several initiatives started to gather data on the performance and reliability of wind turbines on- and offshore and published findings in different journals and conferences. Even though the scopes of the different initiatives are similar, every initiative follows a different approach and results are therefore difficult to compare. The present paper faces this issue, collects results of different initiatives and harmonizes the results. A short description and assessment of every considered data source is provided. To enable this comparison, the existing reliability characteristics are mapped to a system structure according to the Reference Designation System for Power Plants (RDS-PP®). The review shows a wide variation in the performance and reliability metrics of the individual initiatives. Especially the comparison on onshore wind turbines reveals significant differences between the results. Only a few publications are available on offshore wind turbines and the results show an increasing performance and reliability of offshore wind turbines since the first offshore wind farms were erected and monitored. Full article
(This article belongs to the Section Electrical Power and Energy System)
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Open AccessArticle A Naive Bayesian Wind Power Interval Prediction Approach Based on Rough Set Attribute Reduction and Weight Optimization
Energies 2017, 10(11), 1903; https://doi.org/10.3390/en10111903
Received: 19 October 2017 / Revised: 13 November 2017 / Accepted: 15 November 2017 / Published: 19 November 2017
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Abstract
Intermittency and uncertainty pose great challenges to the large-scale integration of wind power, so research on the probabilistic interval forecasting of wind power is becoming more and more important for power system planning and operation. In this paper, a Naive Bayesian wind power
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Intermittency and uncertainty pose great challenges to the large-scale integration of wind power, so research on the probabilistic interval forecasting of wind power is becoming more and more important for power system planning and operation. In this paper, a Naive Bayesian wind power prediction interval model, combining rough set (RS) theory and particle swarm optimization (PSO), is proposed to further improve wind power prediction performance. First, in the designed prediction interval model, the input variables are identified based on attribute significance using rough set theory. Next, the Naive Bayesian Classifier (NBC) is established to obtain the prediction power class. Finally, the upper and lower output weights of NBC are optimized segmentally by PSO, and are used to calculate the upper and lower bounds of the optimal prediction intervals. The superiority of the proposed approach is demonstrated by comparison with a Naive Bayesian model with fixed output weight, and a rough set-Naive Bayesian model with fixed output weight. It is shown that the proposed rough set-Naive Bayesian-particle swarm optimization method has higher coverage of the probabilistic prediction intervals and a narrower average bandwidth under different confidence levels. Full article
(This article belongs to the Special Issue Wind Generators Modelling and Control)
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Open AccessArticle LNG–Air Mixture as a Supplementary Energy Injection into a Biogas Distribution Network
Energies 2017, 10(11), 1902; https://doi.org/10.3390/en10111902
Received: 21 October 2017 / Revised: 16 November 2017 / Accepted: 17 November 2017 / Published: 19 November 2017
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Abstract
Biogas production efficiency fluctuates with climate variations and agricultural arrangements, which pose a limiting factor upon its single supply to end users via a regional exclusive network, especially in peak demand. In this paper, an appropriate methodology to address the contradiction between biogas
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Biogas production efficiency fluctuates with climate variations and agricultural arrangements, which pose a limiting factor upon its single supply to end users via a regional exclusive network, especially in peak demand. In this paper, an appropriate methodology to address the contradiction between biogas supply and demand is proposed. Methane conditioned by the addition of air is described, and can be a supplementary energy injected into a biogas distribution network. To accomplish the mixing process and also inject the exhaust mixture into the distribution system, a mixer–ejector was introduced and integrated into the biogas grid. Finally, the fundamental combustion behaviors of mixed gases were estimated through the analysis of flame appearance, contamination emissions, and the flame stability region. The results showed that the methane/air mixture with a mixing ratio ranging from 49/51 to 53/47 could interchange biogas commendably, and good combustion behavior was obtained on a typical biogas-burning appliance. Full article
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Open AccessArticle An Intelligent Optimization Method for Vortex-Induced Vibration Reducing and Performance Improving in a Large Francis Turbine
Energies 2017, 10(11), 1901; https://doi.org/10.3390/en10111901
Received: 14 October 2017 / Revised: 10 November 2017 / Accepted: 12 November 2017 / Published: 19 November 2017
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Abstract
In this paper, a new methodology is proposed to reduce the vortex-induced vibration (VIV) and improve the performance of the stay vane in a 200-MW Francis turbine. The process can be divided into two parts. Firstly, a diagnosis method for stay vane vibration
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In this paper, a new methodology is proposed to reduce the vortex-induced vibration (VIV) and improve the performance of the stay vane in a 200-MW Francis turbine. The process can be divided into two parts. Firstly, a diagnosis method for stay vane vibration based on field experiments and a finite element method (FEM) is presented. It is found that the resonance between the Kármán vortex and the stay vane is the main cause for the undesired vibration. Then, we focus on establishing an intelligent optimization model of the stay vane’s trailing edge profile. To this end, an approach combining factorial experiments, extreme learning machine (ELM) and particle swarm optimization (PSO) is implemented. Three kinds of improved profiles of the stay vane are proposed and compared. Finally, the profile with a Donaldson trailing edge is adopted as the best solution for the stay vane, and verifications such as computational fluid dynamics (CFD) simulations, structural analysis and fatigue analysis are performed to validate the optimized geometry. Full article
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Open AccessEditor’s ChoiceArticle Modeling of Supersonic Combustion Systems for Sustained Hypersonic Flight
Energies 2017, 10(11), 1900; https://doi.org/10.3390/en10111900
Received: 16 October 2017 / Revised: 8 November 2017 / Accepted: 9 November 2017 / Published: 18 November 2017
Cited by 4 | Viewed by 1435 | PDF Full-text (15742 KB) | HTML Full-text | XML Full-text
Abstract
Through Computational Fluid Dynamics and validation, an optimal scramjet combustor has been designed based on twin-strut Hydrogen injection to sustain flight at a desired speed of Mach 8. An investigation undertaken into the efficacy of supersonic combustion through various means of injection saw
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Through Computational Fluid Dynamics and validation, an optimal scramjet combustor has been designed based on twin-strut Hydrogen injection to sustain flight at a desired speed of Mach 8. An investigation undertaken into the efficacy of supersonic combustion through various means of injection saw promising results for Hydrogen-based systems, whereby strut-style injectors were selected over transverse injectors based on their pressure recovery performance and combustive efficiency. The final configuration of twin-strut injectors provided robust combustion and a stable region of net thrust (1873 kN) in the nozzle. Using fixed combustor inlet parameters and injection equivalence ratio, the finalized injection method advanced to the early stages of two-dimensional (2-D) and three-dimensional (3-D) scramjet engine integration. The overall investigation provided a feasible supersonic combustion system, such that Mach 8 sustained cruise could be achieved by the aircraft concept in a computational design domain. Full article
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