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Energies, Volume 9, Issue 10 (October 2016) – 99 articles

Cover Story (view full-size image): In this study, we demonstrate that energy storage for desalination powered by renewable energy is not an optimal solution. The desalination plant is sized to secure freshwater demand for a remote island with no grid connection. Water storage is introduced to buffer the fluctuation in supply and demand. This approach presents a more optimal, sustainable and reliable water supply option for remote populations. View the paper
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134 KiB  
Erratum
Erratum: Ghasemi, M.; Choudhury, P.K. Metamaterial Absorber Comprised of Butt-Facing U-Shaped Nanoengineered Gold Metasurface. Energies 2016, 9, 451
by Energies Editorial Office
Energies 2016, 9(10), 858; https://doi.org/10.3390/en9100858 - 24 Oct 2016
Viewed by 2594
Abstract
The Energies Editorial Office wishes to make the following erratum to their paper [1]:[...] Full article
(This article belongs to the Special Issue Dielectric Materials for Energy Storage)
3757 KiB  
Article
Optimal Sizing of Vanadium Redox Flow Battery Systems for Residential Applications Based on Battery Electrochemical Characteristics
by Xinan Zhang, Yifeng Li, Maria Skyllas-Kazacos and Jie Bao
Energies 2016, 9(10), 857; https://doi.org/10.3390/en9100857 - 22 Oct 2016
Cited by 30 | Viewed by 7939
Abstract
The penetration of solar photovoltaic (PV) systems in residential areas contributes to the generation and usage of renewable energy. Despite its advantages, the PV system also creates problems caused by the intermittency of renewable energy. As suggested by researchers, such problems deteriorate the [...] Read more.
The penetration of solar photovoltaic (PV) systems in residential areas contributes to the generation and usage of renewable energy. Despite its advantages, the PV system also creates problems caused by the intermittency of renewable energy. As suggested by researchers, such problems deteriorate the applicability of the PV system and have to be resolved by employing a battery energy storage system (BESS). With concern for the high investment cost, the choice of a cost-effective BESS with proper sizing is necessary. To this end, this paper proposes the employment of a vanadium redox flow battery (VRB), which possesses a long cycle life and high energy efficiency, for residential users with PV systems. It further proposes methods of computing the capital and maintenance cost of VRB systems and evaluating battery efficiency based on VRB electrochemical characteristics. Furthermore, by considering the cost and efficiency of VRB, the prevalent time-of-use electricity price, the solar feed-in tariff, the solar power profile and the user load pattern, an optimal sizing algorithm for VRB systems is proposed. Simulation studies are carried out to show the effectiveness of the proposed methods. Full article
(This article belongs to the Special Issue Selected Papers from 2nd Energy Future Conference)
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2786 KiB  
Article
Determination of Optimized Parameters for the Flexible Operation of a Biomass-Fueled, Microscale Externally Fired Gas Turbine (EFGT)
by Mathhar Bdour, Mohammad Al-Addous, Michael Nelles and Andreas Ortwein
Energies 2016, 9(10), 856; https://doi.org/10.3390/en9100856 - 22 Oct 2016
Cited by 5 | Viewed by 6143
Abstract
Biomass as a source of renewable energy is a promising solution for current problems in energy supply. Olive waste is considered as an interesting option, especially for Mediterranean countries. Within this paper, a microscale externally fired gas turbine (EFGT) technology is presented as [...] Read more.
Biomass as a source of renewable energy is a promising solution for current problems in energy supply. Olive waste is considered as an interesting option, especially for Mediterranean countries. Within this paper, a microscale externally fired gas turbine (EFGT) technology is presented as a decentralized power plant, within the range of 15 kWth, based on olive residues. It was modeled by Aspen Plus 8.6 software to provide a sufficient technical study for such a plant. Optimized parameters for pressure ratio and turbine air-mass flow have been mapped for several loads to provide information for process control. For all cases, mechanical output, efficiency curves, and back-work ratio have been calculated. Using this information, typical plant sizes and an example of power production are discussed. Additionally, achievable energy production from olive waste is estimated on the basis of this data. The results of this study show that such a plant has an electrical efficiency of 5%–17%. This variation is due to the examination being performed under several combustion temperatures, actual load, heat exchanger temperatures, and heat transfer efficiency. A cost estimation of the discussed system showed an estimated capital cost of 33,800 to 65,300 € for a 15 kWth system. Full article
(This article belongs to the Special Issue Economics of Bioenergy 2016)
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4432 KiB  
Article
Mapping the Geothermal System Using AMT and MT in the Mapamyum (QP) Field, Lake Manasarovar, Southwestern Tibet
by Lanfang He, Ling Chen, Dorji, Xiaolu Xi, Xuefeng Zhao, Rujun Chen and Hongchun Yao
Energies 2016, 9(10), 855; https://doi.org/10.3390/en9100855 - 22 Oct 2016
Cited by 22 | Viewed by 8280
Abstract
Southwestern Tibet plays a crucial role in the protection of the ecological environment and biodiversity of Southern Asia but lacks energy in terms of both power and fuel. The widely distributed geothermal resources in this region could be considered as potential alternative sources [...] Read more.
Southwestern Tibet plays a crucial role in the protection of the ecological environment and biodiversity of Southern Asia but lacks energy in terms of both power and fuel. The widely distributed geothermal resources in this region could be considered as potential alternative sources of power and heat. However, most of the known geothermal fields in Southwestern Tibet are poorly prospected and currently almost no geothermal energy is exploited. Here we present a case study mapping the Mapamyum (QP) geothermal field of Southwestern Tibet using audio magnetotellurics (AMT) and magnetotellurics (MT) methods. AMT in the frequency range 11.5–11,500 Hz was used to map the upper part of this geothermal reservoir to a depth of 1000 m, and MT in the frequency range 0.001–320 Hz was used to map the heat source, thermal fluid path, and lower part of the geothermal reservoir to a depth greater than 1000 m. Data from 1300 MT and 680 AMT stations were acquired around the geothermal field. Bostick conversion with electromagnetic array profiling (EMAP) filtering and nonlinear conjugate gradient inversion (NLCGI) was used for data inversion. The AMT and MT results presented here elucidate the geoelectric structure of the QP geothermal field, and provide a background for understanding the reservoir, the thermal fluid path, and the heat source of the geothermal system. We identified a low resistivity anomaly characterized by resistivity in the range of 1–8 Ω∙m at a depth greater than 7 km. This feature was interpreted as a potential reflection of the partially melted magma in the upper crust, which might correlate to mantle upwelling along the Karakorum fault. It is likely that the magma is the heat source of the QP geothermal system, and potentially provides new geophysical evidence to understand the occurrence of the partially melted magmas in the upper crust in Southwestern Tibet. Full article
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4763 KiB  
Article
Thermochemical Characterizations of Novel Vermiculite-LiCl Composite Sorbents for Low-Temperature Heat Storage
by Yannan Zhang, Ruzhu Wang, Tingxian Li and Yanjie Zhao
Energies 2016, 9(10), 854; https://doi.org/10.3390/en9100854 - 22 Oct 2016
Cited by 41 | Viewed by 6786
Abstract
To store low-temperature heat below 100 °C, novel composite sorbents were developed by impregnating LiCl into expanded vermiculite (EVM) in this study. Five kinds of composite sorbents were prepared using different salt concentrations, and the optimal sorbent for application was selected by comparing [...] Read more.
To store low-temperature heat below 100 °C, novel composite sorbents were developed by impregnating LiCl into expanded vermiculite (EVM) in this study. Five kinds of composite sorbents were prepared using different salt concentrations, and the optimal sorbent for application was selected by comparing both the sorption characteristics and energy storage density. Textural properties of composite sorbents were obtained by extreme-resolution field emission scanning electron microscopy (ER-SEM) and an automatic mercury porosimeter. After excluding two composite sorbents which would possibly exhibit solution leakage in practical thermal energy storage (TES) system, thermochemical characterizations were implemented through simulative sorption experiments at 30 °C and 60% RH. Analyses of thermogravimetric analysis/differential scanning calorimetry (TGA/DSC) curves indicate that water uptake of EVM/LiCl composite sorbents is divided into three parts: physical adsorption of EVM, chemical adsorption of LiCl crystal, and liquid–gas absorption of LiCl solution. Energy storage potential was evaluated by theoretical calculation based on TGA/DSC curves. Overall, EVMLiCl20 was selected as the optimal composite sorbent with water uptake of 1.41 g/g, mass energy storage density of 1.21 kWh/kg, and volume energy storage density of 171.61 kWh/m3. Full article
(This article belongs to the Special Issue Renewable Energy Technologies for Small Scale Applications)
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20173 KiB  
Article
A Phase Current Reconstruction Approach for Three-Phase Permanent-Magnet Synchronous Motor Drive
by Hao Yan, Yongxiang Xu and Jibin Zou
Energies 2016, 9(10), 853; https://doi.org/10.3390/en9100853 - 21 Oct 2016
Cited by 13 | Viewed by 8797
Abstract
Three-phase permanent-magnet synchronous motors (PMSMs) are widely used in renewable energy applications such as wind power generation, tidal energy and electric vehicles owing to their merits such as high efficiency, high precision and high reliability. To reduce the cost and volume of the [...] Read more.
Three-phase permanent-magnet synchronous motors (PMSMs) are widely used in renewable energy applications such as wind power generation, tidal energy and electric vehicles owing to their merits such as high efficiency, high precision and high reliability. To reduce the cost and volume of the drive system, techniques of reconstructing three-phase current using a single current sensor have been reported for three-phase alternating current (AC) control system using the power converts. In existing studies, the reconstruction precision is largely influenced by reconstructing dead zones on the Space Vector Pulse Width Modulation (SVPWM) plane, which requires other algorithms to compensate either by modifying PWM modulation or by phase-shifting of the PWM signal. In this paper, a novel extended phase current reconstruction approach for PMSM drive is proposed. Six novel installation positions are obtained by analyzing the sampling results of the current paths between each two power switches. By arranging the single current sensor at these positions, the single current sensor is sampled during zero voltage vectors (ZVV) without modifying the PWM signals. This proposed method can reconstruct the three-phase currents without any complex algorithms and is available in the sector boundary region and low modulation region. Finally, this method is validated by experiments. Full article
(This article belongs to the Special Issue Electric Machines and Drives for Renewable Energy Harvesting)
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5151 KiB  
Article
Numerical Simulations of the Effects of a Tidal Turbine Array on Near-Bed Velocity and Local Bed Shear Stress
by Philip A. Gillibrand, Roy A. Walters and Jason McIlvenny
Energies 2016, 9(10), 852; https://doi.org/10.3390/en9100852 - 21 Oct 2016
Cited by 24 | Viewed by 5319
Abstract
We apply a three-dimensional hydrodynamic model to consider the potential effects of energy extraction by an array of tidal turbines on the ambient near-bed velocity field and local bed shear stress in a coastal channel with strong tidal currents. Local bed shear stress [...] Read more.
We apply a three-dimensional hydrodynamic model to consider the potential effects of energy extraction by an array of tidal turbines on the ambient near-bed velocity field and local bed shear stress in a coastal channel with strong tidal currents. Local bed shear stress plays a key role in local sediment dynamics. The model solves the Reynold-averaged Navier-Stokes (RANS) equations on an unstructured mesh using mixed finite element and finite volume techniques. Tidal turbines are represented through an additional form drag in the momentum balance equation, with the thrust imparted and power generated by the turbines being velocity dependent with appropriate cut-in and cut-out velocities. Arrays of 1, 4 and 57 tidal turbines, each of 1.5 MW capacity, were simulated. Effects due to a single turbine and an array of four turbines were negligible. The main effect of the array of 57 turbines was to cause a shift in position of the jet through the tidal channel, as the flow was diverted around the tidal array. The net effect of this shift was to increase near-bed velocities and bed shear stress along the northern perimeter of the array by up to 0.8 m·s−1 and 5 Pa respectively. Within the array and directly downstream, near-bed velocities and bed shear stress were reduced by similar amounts. Changes of this magnitude have the potential to modify the known sand and shell banks in the region. Continued monitoring of the sediment distributions in the region will provide a valuable dataset on the impacts of tidal energy extraction on local sediment dynamics. Finally, the mean power generated per turbine is shown to decrease as the turbine array increased in size. Full article
(This article belongs to the Special Issue Numerical Modelling of Wave and Tidal Energy)
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4519 KiB  
Article
Efficient Solutions and Cost-Optimal Analysis for Existing School Buildings
by Paolo Maria Congedo, Delia D’Agostino, Cristina Baglivo, Giuliano Tornese and Ilaria Zacà
Energies 2016, 9(10), 851; https://doi.org/10.3390/en9100851 - 21 Oct 2016
Cited by 44 | Viewed by 6193
Abstract
The recast of the energy performance of buildings directive (EPBD) describes a comparative methodological framework to promote energy efficiency and establish minimum energy performance requirements in buildings at the lowest costs. The aim of the cost-optimal methodology is to foster the achievement of [...] Read more.
The recast of the energy performance of buildings directive (EPBD) describes a comparative methodological framework to promote energy efficiency and establish minimum energy performance requirements in buildings at the lowest costs. The aim of the cost-optimal methodology is to foster the achievement of nearly zero energy buildings (nZEBs), the new target for all new buildings by 2020, characterized by a high performance with a low energy requirement almost covered by renewable sources. The paper presents the results of the application of the cost-optimal methodology in two existing buildings located in the Mediterranean area. These buildings are a kindergarten and a nursery school that differ in construction period, materials and systems. Several combinations of measures have been applied to derive cost-effective efficient solutions for retrofitting. The cost-optimal level has been identified for each building and the best performing solutions have been selected considering both a financial and a macroeconomic analysis. The results illustrate the suitability of the methodology to assess cost-optimality and energy efficiency in school building refurbishment. The research shows the variants providing the most cost-effective balance between costs and energy saving. The cost-optimal solution reduces primary energy consumption by 85% and gas emissions by 82%–83% in each reference building. Full article
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4848 KiB  
Article
Hydrogen Production from Sea Wave for Alternative Energy Vehicles for Public Transport in Trapani (Italy)
by Vincenzo Franzitta, Domenico Curto, Davide Rao and Alessia Viola
Energies 2016, 9(10), 850; https://doi.org/10.3390/en9100850 - 21 Oct 2016
Cited by 47 | Viewed by 6037
Abstract
The coupling of renewable energy and hydrogen technologies represents in the mid-term a very interesting way to match the tasks of increasing the reliable exploitation of wind and sea wave energy and introducing clean technologies in the transportation sector. This paper presents two [...] Read more.
The coupling of renewable energy and hydrogen technologies represents in the mid-term a very interesting way to match the tasks of increasing the reliable exploitation of wind and sea wave energy and introducing clean technologies in the transportation sector. This paper presents two different feasibility studies: the first proposes two plants based on wind and sea wave resource for the production, storage and distribution of hydrogen for public transportation facilities in the West Sicily; the second applies the same approach to Pantelleria (a smaller island), including also some indications about solar resource. In both cases, all buses will be equipped with fuel-cells. A first economic analysis is presented together with the assessment of the avoidable greenhouse gas emissions during the operation phase. The scenarios addressed permit to correlate the demand of urban transport to renewable resources present in the territories and to the modern technologies available for the production of hydrogen from renewable energies. The study focuses on the possibility of tapping the renewable energy potential (wind and sea wave) for the hydrogen production by electrolysis. The use of hydrogen would significantly reduce emissions of particulate matter and greenhouse gases in urban districts under analysis. The procedures applied in the present article, as well as the main equations used, are the result of previous applications made in different technical fields that show a good replicability. Full article
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5633 KiB  
Article
Study on the Optimum Design Method of Heat Source Systems with Heat Storage Using a Genetic Algorithm
by Min Gyung Yu and Yujin Nam
Energies 2016, 9(10), 849; https://doi.org/10.3390/en9100849 - 21 Oct 2016
Cited by 1 | Viewed by 4762
Abstract
Recently, a heat source system utilizing a heat storage tank for energy savings in buildings was designed. A heat storage tank is an effective system for solving the qualitative and quantitative differences in the required building energy. On the other hand, the existing [...] Read more.
Recently, a heat source system utilizing a heat storage tank for energy savings in buildings was designed. A heat storage tank is an effective system for solving the qualitative and quantitative differences in the required building energy. On the other hand, the existing design process of a heat storage system is difficult to determine if the air-conditioning time is unclear, and the design in a real-working level is too inaccurate, causing oversizing and a high initial investment cost. This results in inefficient operation despite the introduction of an efficient system. Therefore, this study proposes an optimal design method of a heat source system using a thermal storage tank. To demonstrate the usefulness of the proposed design method, feasibility studies were conducted with the existing system designs. As a result, the optimal solution could reduce the initial cost by approximately 25.6% when following the conventional design process and it was approximately 40% lower than the real-working method. In conclusion, the conventional designs are inefficiently over-designed and the optimal design solution is superior. In this regard, the suggested optimal design method is efficient when designing a heat source system using a thermal storage tank. Full article
(This article belongs to the Special Issue Energy Conservation in Infrastructures 2016)
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3215 KiB  
Article
Revenue Risk of U.S. Tight-Oil Firms
by Luis Mª Abadie and José M. Chamorro
Energies 2016, 9(10), 848; https://doi.org/10.3390/en9100848 - 21 Oct 2016
Cited by 3 | Viewed by 5467
Abstract
American U.S. crude oil prices have dropped significantly of late down to a low of less than $30 a barrel in early 2016. At the same time price volatility has increased and crude in storage has reached record amounts in the U.S. America. [...] Read more.
American U.S. crude oil prices have dropped significantly of late down to a low of less than $30 a barrel in early 2016. At the same time price volatility has increased and crude in storage has reached record amounts in the U.S. America. Low oil prices in particular pose quite a challenge for the survival of U.S. America’s tight-oil industry. In this paper we assess the current profitability and future prospects of this industry. The question could be broadly stated as: should producers stop operation immediately or continue in the hope that prices will rise in the medium term? Our assessment is based on a stochastic volatility model with three risk factors, namely the oil spot price, the long-term oil price, and the spot price volatility; we allow for these sources of risk to be correlated and display mean reversion. We then use information from spot and futures West Texas Intermediate (WTI) oil prices to estimate this model. Our aim is to show how the development of the oil price in the future may affect the prospective revenues of firms and hence their operation decisions at present. With the numerical estimates of the model’s parameters we can compute the value of an operating tight-oil field over a certain time horizon. Thus, the present value (PV) of the prospective revenues up to ten years from now is $37.07/bbl in the base case. Consequently, provided that the cost of producing a barrel of oil is less than $37.07 production from an operating field would make economic sense. Obviously this is just a point estimate. We further perform a Monte Carlo (MC) simulation to derive the risk profile of this activity and calculate two standard measures of risk, namely the value at risk (VaR) and the expected shortfall (ES) (for a given confidence level). In this sense, the PV of the prospective revenues will fall below $22.22/bbl in the worst 5% of the cases; and the average value across these worst scenarios is $19.77/bbl. Last we undertake two sensitivity analyses with respect to the spot price and the long-term price. The former is shown to have a stronger impact on the field’s value than the latter. This bodes well with the usual time profile of tight oil production: intense depletion initially, followed by steep decline thereafter. Full article
(This article belongs to the Special Issue Energy Economics 2016)
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7785 KiB  
Article
Study of Wind Turbine Fault Diagnosis Based on Unscented Kalman Filter and SCADA Data
by Mengnan Cao, Yingning Qiu, Yanhui Feng, Hao Wang and Dan Li
Energies 2016, 9(10), 847; https://doi.org/10.3390/en9100847 - 20 Oct 2016
Cited by 38 | Viewed by 5890
Abstract
Effective wind turbine fault diagnostic algorithms are crucial for wind turbine intelligent condition monitoring. An unscented Kalman filter approach is proposed to successfully detect and isolate two types of gearbox failures of a wind turbine in this paper. The state space models are [...] Read more.
Effective wind turbine fault diagnostic algorithms are crucial for wind turbine intelligent condition monitoring. An unscented Kalman filter approach is proposed to successfully detect and isolate two types of gearbox failures of a wind turbine in this paper. The state space models are defined for the unscented Kalman filter model by a detailed wind turbine nonlinear systematic principle analysis. The three failure modes being studied are gearbox damage, lubrication oil leakage and pitch failure. The results show that unscented Kalman filter model has special response to online input parameters under different fault conditions. Such property makes it effective on fault identification. It also shows that properly defining unscented Kalman filter state space vectors and control vectors are crucial for improving its sensitivity to different failures. Online fault detection capability of this approach is then proved on SCADA data. The developed unsented Kalman filter model provides an effective way for wind turbine fault detection using supervisory control and data acquisition data. This is essential for further intelligent WT condition monitoring. Full article
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2332 KiB  
Article
Use of a Pre-Drilled Hole for Implementing Thermal Needle Probe Method for Soils and Rocks
by So-Jung Lee, Jung-Chan Choi, Seunghun Baek, Tae-Hyuk Kwon, Hee-Hwan Ryu and Ki-Il Song
Energies 2016, 9(10), 846; https://doi.org/10.3390/en9100846 - 20 Oct 2016
Cited by 6 | Viewed by 5525
Abstract
The thermal needle probe method, which is widely used for measuring the thermal conductivity λ of soils, deploys a long and thin metallic probe that houses a line heater and a temperature sensor. However, inserting such probes into consolidated or densely compacted soils [...] Read more.
The thermal needle probe method, which is widely used for measuring the thermal conductivity λ of soils, deploys a long and thin metallic probe that houses a line heater and a temperature sensor. However, inserting such probes into consolidated or densely compacted soils or rocks is difficult, frequently causing buckling of the probe and severe disturbance to the surrounding ground, leading to unreliable measurements. We found that the use of a pre-drilled hole filled with thermally conductive grease for installing a thermal needle probe was feasible to overcome such challenges, and still yielded reliable measurements of thermal conductivity. The proposed method, i.e., the pre-drilling thermal needle probe method, was verified by finite element calculations and laboratory experiments by varying various parameters, such as the pre-drilled hole diameter, probe diameter, and thermal conductivity of thermal grease. It was observed that increases in the pre-drilled hole diameter and probe diameter and a decrease in the thermal conductivity of the thermal grease caused delays in temperature increase owing to the slowed heat transfer. Nevertheless, all the estimated λ values agreed well with the reference λ values with acceptable errors. Thus, the proposed method yields reliable measurements and can be applied for a wide range of soils from compacted soils to hard rocks. Full article
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3200 KiB  
Article
Cost Analysis Method for Estimating Dynamic Reserve Considering Uncertainties in Supply and Demand
by Kyung-bin Kwon, Hyeongon Park, Jae-Kun Lyu and Jong-Keun Park
Energies 2016, 9(10), 845; https://doi.org/10.3390/en9100845 - 20 Oct 2016
Cited by 6 | Viewed by 4188
Abstract
The use of appropriate hourly reserve margins can maintain power system security by balancing supply and demand in the presence of errors in the forecast demand, generation outages, or errors in the forecast of wind power generation. Because the cost of unit commitment [...] Read more.
The use of appropriate hourly reserve margins can maintain power system security by balancing supply and demand in the presence of errors in the forecast demand, generation outages, or errors in the forecast of wind power generation. Because the cost of unit commitment increases with larger reserve margins, cost analysis to determine the most economical reserve margin is an important issue in power system operation. Here, we define the “short-term reliability of balance” and describe a method to determine the reserve margin based on the short-term reliability of balance. We describe a case study, in which we calculate the reserve margin using this method with various standards of short-term reliability of balance. A cost analysis is then performed to determine the most economic standard, and a comparison between our method and a conventional method is carried out. The results show that our method with an economic short-term reliability of balance enables more reliable and efficient operation of the power system. Moreover, with an hourly reserve margin, we show that an increase in wind power generation can result in a significant decrease in the operating cost, which makes wind power generation economically viable. Full article
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8838 KiB  
Article
Comparison of Numerical and Experimental Studies for Flow-Field Optimization Based on Under-Rib Convection in Polymer Electrolyte Membrane Fuel Cells
by Nguyen Duy Vinh and Hyung-Man Kim
Energies 2016, 9(10), 844; https://doi.org/10.3390/en9100844 - 20 Oct 2016
Cited by 17 | Viewed by 6107
Abstract
The flow-field design based on under-rib convection plays an important role in enhancing the performance of polymer electrolyte membrane fuel cells (PEMFCs) because it ensures the uniform distribution of the reacting gas and the facilitation of water. This research focused on developing suitable [...] Read more.
The flow-field design based on under-rib convection plays an important role in enhancing the performance of polymer electrolyte membrane fuel cells (PEMFCs) because it ensures the uniform distribution of the reacting gas and the facilitation of water. This research focused on developing suitable configurations of the anode and cathode bipolar plates to enhance the fuel cell performance based on under-rib convection. The work here evaluated the effects of flow-field designs, including a serpentine flow field with sub channel and by pass and a conventional serpentine flow-field on single-cell performance. Both the experiment and computer simulation indicated that the serpentine flow field with sub channel and by pass (SFFSB) configuration enables more effective utilization of the electrocatalysts since it improves reactant transformation rate from the channel to the catalyst layer, thereby dramatically improving the fuel cell performance. The simulation and experimental results indicated that the power densities are increased by up to 16.74% and 18.21%, respectively, when applying suitable flow-field configurations to the anode and cathode bipolar plates. The findings in this are the foundation for enhancing efficient PEMFCs based on flow field design. Full article
(This article belongs to the Special Issue Polymer Electrolyte Membrane Fuel Cells 2016)
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5186 KiB  
Article
Probability Model Based Energy Efficient and Reliable Topology Control Algorithm
by Ning Li, Jose-Fernan Martinez-Ortega, Lourdes Lopez Santidrian and Juan Manuel Meneses Chaus
Energies 2016, 9(10), 841; https://doi.org/10.3390/en9100841 - 20 Oct 2016
Cited by 1 | Viewed by 4305
Abstract
Topology control is an effective method for improving the performance of wireless sensor networks (WSNs). Many topology control algorithms can achieve high energy efficiency by dynamically changing the transmission range of nodes. However, these algorithms prefer to choose short multihop communication links rather [...] Read more.
Topology control is an effective method for improving the performance of wireless sensor networks (WSNs). Many topology control algorithms can achieve high energy efficiency by dynamically changing the transmission range of nodes. However, these algorithms prefer to choose short multihop communication links rather than the long directly communication links which also energy efficient probabilistic. Note that these fact, in this paper, we propose a mathematic model to explore the probability that the long directly communication links are more energy efficient than the short links. We investigate the properties of this probability and find out the optimal transmission range which has highest probability of energy efficient. Based on this conclusion, we propose the energy efficient and reliable topology control algorithm (ERTC) to maintain the r-range for the nodes instead of the k-connection; moreover, ERTC can achieve energy efficient and network connection at the same time. Full article
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1307 KiB  
Article
New Interval-Valued Intuitionistic Fuzzy Behavioral MADM Method and Its Application in the Selection of Photovoltaic Cells
by Xiaolu Zhang
Energies 2016, 9(10), 835; https://doi.org/10.3390/en9100835 - 20 Oct 2016
Cited by 7 | Viewed by 4039
Abstract
As one of the emerging renewable resources, the use of photovoltaic cells has become a promise for offering clean and plentiful energy. The selection of a best photovoltaic cell for a promoter plays a significant role in aspect of maximizing income, minimizing costs [...] Read more.
As one of the emerging renewable resources, the use of photovoltaic cells has become a promise for offering clean and plentiful energy. The selection of a best photovoltaic cell for a promoter plays a significant role in aspect of maximizing income, minimizing costs and conferring high maturity and reliability, which is a typical multiple attribute decision making (MADM) problem. Although many prominent MADM techniques have been developed, most of them are usually to select the optimal alternative under the hypothesis that the decision maker or expert is completely rational and the decision data are represented by crisp values. However, in the selecting processes of photovoltaic cells the decision maker is usually bounded rational and the ratings of alternatives are usually imprecise and vague. To address these kinds of complex and common issues, in this paper we develop a new interval-valued intuitionistic fuzzy behavioral MADM method. We employ interval-valued intuitionistic fuzzy numbers (IVIFNs) to express the imprecise ratings of alternatives; and we construct LINMAP-based nonlinear programming models to identify the reference points under IVIFNs contexts, which avoid the subjective randomness of selecting the reference points. Finally we develop a prospect theory-based ranking method to identify the optimal alternative, which takes fully into account the decision maker’s behavioral characteristics such as reference dependence, diminishing sensitivity and loss aversion in the decision making process. Full article
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6845 KiB  
Article
Impact of Tidal Level Variations on Wave Energy Absorption at Wave Hub
by Valeria Castellucci, Mikael Eriksson and Rafael Waters
Energies 2016, 9(10), 843; https://doi.org/10.3390/en9100843 - 19 Oct 2016
Cited by 10 | Viewed by 5926
Abstract
The energy absorption of the wave energy converters (WEC) characterized by a limited stroke length —like the point absorbers developed at Uppsala University—depends on the sea level variation at the deployment site. In coastal areas characterized by high tidal ranges, the daily energy [...] Read more.
The energy absorption of the wave energy converters (WEC) characterized by a limited stroke length —like the point absorbers developed at Uppsala University—depends on the sea level variation at the deployment site. In coastal areas characterized by high tidal ranges, the daily energy production of the generators is not optimal. The study presented in this paper quantifies the effects of the changing sea level at the Wave Hub test site, located at the south-west coast of England. This area is strongly affected by tides: the tidal height calculated as the difference between the Mean High Water Spring and the Mean Low Water Spring in 2014 was about 6.6 m. The results are obtained from a hydro-mechanic model that analyzes the behaviour of the point absorber at the Wave Hub, taking into account the sea state occurrence scatter diagram and the tidal time series at the site. It turns out that the impact of the tide decreases the energy absorption by 53%. For this reason, the need for a tidal compensation system to be included in the design of the WEC becomes compelling. The economic advantages are evaluated for different scenarios: the economic analysis proposed within the paper allows an educated guess to be made on the profits. The alternative of extending the stroke length of the WEC is investigated, and the gain in energy absorption is estimated. Full article
(This article belongs to the Special Issue Numerical Modelling of Wave and Tidal Energy)
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3524 KiB  
Article
Comparison of Wind Energy Generation Using the Maximum Entropy Principle and the Weibull Distribution Function
by Muhammad Shoaib, Imran Siddiqui, Shafiqur Rehman, Saif Ur Rehman, Shamim Khan and Aref Lashin
Energies 2016, 9(10), 842; https://doi.org/10.3390/en9100842 - 19 Oct 2016
Cited by 6 | Viewed by 5059
Abstract
Proper knowledge of the wind characteristics of a site is of fundamental importance in estimating wind energy output from a selected wind turbine. The present paper focuses on assessing the suitability and accuracy of the fitted distribution function to the measured wind speed [...] Read more.
Proper knowledge of the wind characteristics of a site is of fundamental importance in estimating wind energy output from a selected wind turbine. The present paper focuses on assessing the suitability and accuracy of the fitted distribution function to the measured wind speed data for Baburband site in Sindh Pakistan. Comparison is made between the wind power densities obtained using the fitted functions based on Maximum Entropy Principle (MEP) and Weibull distribution. In case of MEP-based function a system of (N+1) non-linear equations containing (N+1) Lagrange multipliers is defined as probability density function. The maximum entropy probability density functions is calculated for 3–9 low order moments obtained from measured wind speed data. The annual actual wind power density (PA) is found to be 309.25 W/m2 while the Weibull based wind power density (PW) is 297.25 W/m2. The MEP-based density for orders 5, 7, 8 and 9 (PE) is 309.21 W/m2, whereas for order 6 it is 309.43 W/m2. To validate the MEP-based function, the results are compared with the Weibull function and the measured data. Kolmogorov–Smirnov test is performed between the cdf of the measured wind data and the fitted distribution function (Q95 = 0.01457 > Q = 10−4). The test confirms the suitability of MEP-based function for modeling measured wind speed data and for the estimation of wind energy output from a wind turbine. R2 test is also performed giving analogous behavior of the fitted MEP-based pdf to the actual wind speed data (R2 ~ 0.9). The annual energy extracted using the chosen wind turbine based on Weibull function is PW = 2.54 GWh and that obtained using MEP-based function is PE = 2.57–2.67 GWh depending on the order of moments. Full article
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3693 KiB  
Review
Review on Synthesis, Thermo-Physical Property, and Heat Transfer Mechanism of Nanofluids
by Mahesh Suresh Patil, Jae-Hyeong Seo, Suk-Ju Kang and Moo-Yeon Lee
Energies 2016, 9(10), 840; https://doi.org/10.3390/en9100840 - 19 Oct 2016
Cited by 40 | Viewed by 5281
Abstract
Nanofluids are suspended nano-sized particles in a base fluid. With increasing demand for more high efficiency thermal systems, nanofluids seem to be a promising option for researchers. As a result, numerous investigations have been undertaken to understand the behaviors of nanofluids. Since their [...] Read more.
Nanofluids are suspended nano-sized particles in a base fluid. With increasing demand for more high efficiency thermal systems, nanofluids seem to be a promising option for researchers. As a result, numerous investigations have been undertaken to understand the behaviors of nanofluids. Since their discovery, the thermo-physical properties of nanofluids have been under intense research. Inadequate understanding of the mechanisms involved in the heat transfer of nanofluids has been the major obstacle for the development of sophisticated nanofluids with the desired properties. In this comprehensive review paper, investigations on synthesis, thermo-physical properties, and heat transfer mechanisms of nanofluids have been reviewed and presented. Results show that the thermal conductivity of nanofluids increases with the increase of the operating temperature. This can potentially be used for the efficiency enhancement of thermal systems under higher operating temperatures. In addition, this paper also provides details concerning dependency of the thermo-physical properties as well as synthesis and the heat transfer mechanism of the nanofluids. Full article
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3386 KiB  
Article
Water Storage Instead of Energy Storage for Desalination Powered by Renewable Energy—King Island Case Study
by Aya Tafech, Dia Milani and Ali Abbas
Energies 2016, 9(10), 839; https://doi.org/10.3390/en9100839 - 19 Oct 2016
Cited by 24 | Viewed by 8418
Abstract
In this paper, we scrutinized the energy storage options used in mitigation of the intermittent nature of renewable energy resources for desalination process. In off-grid islands and remote areas, renewable energy is often combined with appropriate energy storage technologies (ESTs) to provide a [...] Read more.
In this paper, we scrutinized the energy storage options used in mitigation of the intermittent nature of renewable energy resources for desalination process. In off-grid islands and remote areas, renewable energy is often combined with appropriate energy storage technologies (ESTs) to provide a consistent and reliable electric power source. We demonstrated that in developing a renewable energy scheme for desalination purposes, product (water) storage is a more reliable and techno-economic solution. For a King Island (Southeast Australia) case-study, electric power production from renewable energy sources was sized under transient conditions to meet the dynamic demand of freshwater throughout the year. Among four proposed scenarios, we found the most economic option by sizing a 13 MW solar photovoltaic (PV) field to instantly run a proportional RO desalination plant and generate immediate freshwater in diurnal times without the need for energy storage. The excess generated water was stored in 4 × 50 ML (mega liter) storage tanks to meet the load in those solar deficit times. It was also demonstrated that integrating well-sized solar PV with wind power production shows more consistent energy/water profiles that harmonize the transient nature of energy sources with the water consumption dynamics, but that would have trivial economic penalties caused by larger desalination and water storage capacities. Full article
(This article belongs to the Special Issue Selected Papers from 2nd Energy Future Conference)
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558 KiB  
Article
Spatial and Temporal Traffic Variation in Core Networks: Impact on Energy Saving and Devices Lifetime
by Filip Idzikowski, Frank Pfeuffer, Axel Werner and Luca Chiaraviglio
Energies 2016, 9(10), 837; https://doi.org/10.3390/en9100837 - 19 Oct 2016
Viewed by 3984
Abstract
We assess the impact of traffic variations on energy consumption and devices lifetime in a core network. Specifically, we first define a model to control the spatial as well as the temporal variations of traffic. We generate different sets of traffic matrices by [...] Read more.
We assess the impact of traffic variations on energy consumption and devices lifetime in a core network. Specifically, we first define a model to control the spatial as well as the temporal variations of traffic. We generate different sets of traffic matrices by adopting our model, which are then used as input to an energy-aware algorithm, with the aim of finding the set of Line Cards (LCs) in Sleep Mode (SM) for each traffic matrix. Given this output, we are able to compute different evaluation metrics, including: the total energy consumption, the normalized lifetime as a consequence of activation/deactivation of network devices, and the total network profitability (i.e., the monetary gain/loss for the operator). Our results show that the temporal variation of traffic affects the LCs energy consumption, but has a limited impact on their lifetime. Moreover, the spatial variation of traffic is no obstacle for energy saving. Eventually, the frequency of the power cycles, introduced by the energy-aware algorithm, is particularly important for the lifetime of LCs. Finally, we show that positive total profitability is achieved in most of the considered cases. Full article
(This article belongs to the Special Issue Energy-Efficient and Sustainable Networking)
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2713 KiB  
Article
Optimal Site Selection of Tidal Power Plants Using a Novel Method: A Case in China
by Yunna Wu, Chuanbo Xu and Hu Xu
Energies 2016, 9(10), 832; https://doi.org/10.3390/en9100832 - 19 Oct 2016
Cited by 13 | Viewed by 9161
Abstract
The site selection plays an important role in the entire life cycle of a tidal power plant (TPP) project. However, some problems decrease the evaluation quality of TPP site selection: (a) suitable and effective methods are scarce since the TPP site selection involves [...] Read more.
The site selection plays an important role in the entire life cycle of a tidal power plant (TPP) project. However, some problems decrease the evaluation quality of TPP site selection: (a) suitable and effective methods are scarce since the TPP site selection involves multiple forms of data; (b) there is no comprehensive evaluation index system due to the unilateralism of existing criteria. In this paper, we firstly propose a novel method based on interval number with probability distribution weighted operation and stochastic dominance degree. It takes all stakeholders’ preferences into consideration and can simultaneously deal with different forms of data in the TPP site selection; then, a comprehensive evaluation index system for TPP site selection is constructed on the basis of academic literature, feasibility research reports and expert opinions in different fields. It takes the factors of construction conditions, existing policies, social impacts as well as ecological and environmental impacts which reflects the inherent characteristics of TPP site selection fully into account. Finally, a Chinese case study is given to illustrate the applicability and effectiveness of the proposed method. Full article
(This article belongs to the Special Issue Numerical Modelling of Wave and Tidal Energy)
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1943 KiB  
Article
The BioSCWG Project: Understanding the Trade-Offs in the Process and Thermal Design of Hydrogen and Synthetic Natural Gas Production
by Mohamed Magdeldin, Thomas Kohl, Cataldo De Blasio, Mika Järvinen, Song Won Park and Reinaldo Giudici
Energies 2016, 9(10), 838; https://doi.org/10.3390/en9100838 - 18 Oct 2016
Cited by 20 | Viewed by 6617
Abstract
This article presents a summary of the main findings from a collaborative research project between Aalto University in Finland and partner universities. A comparative process synthesis, modelling and thermal assessment was conducted for the production of Bio-synthetic natural gas (SNG) and hydrogen from [...] Read more.
This article presents a summary of the main findings from a collaborative research project between Aalto University in Finland and partner universities. A comparative process synthesis, modelling and thermal assessment was conducted for the production of Bio-synthetic natural gas (SNG) and hydrogen from supercritical water refining of a lipid extracted algae feedstock integrated with onsite heat and power generation. The developed reactor models for product gas composition, yield and thermal demand were validated and showed conformity with reported experimental results, and the balance of plant units were designed based on established technologies or state-of-the-art pilot operations. The poly-generative cases illustrated the thermo-chemical constraints and design trade-offs presented by key process parameters such as plant organic throughput, supercritical water refining temperature, nature of desirable coproducts, downstream indirect production and heat recovery scenarios. The evaluated cases favoring hydrogen production at 5 wt. % solid content and 600 °C conversion temperature allowed higher gross syngas and CHP production. However, mainly due to the higher utility demands the net syngas production remained lower compared to the cases favoring BioSNG production. The latter case, at 450 °C reactor temperature, 18 wt. % solid content and presence of downstream indirect production recorded 66.5%, 66.2% and 57.2% energetic, fuel-equivalent and exergetic efficiencies respectively. Full article
(This article belongs to the Collection Bioenergy and Biofuel)
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1985 KiB  
Article
Flexible Yttrium Coordination Geometry Inhibits “Bare-Metal” Guest Interactions in the Metal-Organic Framework Y(btc)
by Josie E. Auckett, Stephen H. Ogilvie, Samuel G. Duyker, Peter D. Southon, Cameron J. Kepert and Vanessa K. Peterson
Energies 2016, 9(10), 836; https://doi.org/10.3390/en9100836 - 18 Oct 2016
Viewed by 5337
Abstract
Y(btc) (btc = 1,3,5-benzenetricarboxylate) is a metal-organic framework that exhibits significant adsorption of industrially-relevant gases such as H2, CH4, and O2. Previous studies have noted a surprising lack of close interactions between the adsorbed guest molecules and [...] Read more.
Y(btc) (btc = 1,3,5-benzenetricarboxylate) is a metal-organic framework that exhibits significant adsorption of industrially-relevant gases such as H2, CH4, and O2. Previous studies have noted a surprising lack of close interactions between the adsorbed guest molecules and Y, despite the apparent availability of a “bare-metal” binding site. We have extended our previous work in a detailed investigation of the adsorption behaviours of CO2, CD4, and O2 in Y(btc) over a range of concentrations using in situ neutron powder diffraction methods. The O–Y–O bond angles enclosing the bare-metal site are found to change considerably depending on the type and quantity of guest molecules present. Multiple binding sites are found for each guest species, and the largest changes in O–Y–O angles are accompanied by changes in the filling sequences of the binding sites, pointing to an important interplay between guest-induced framework distortions and binding site accessibility. These results suggest the potential for coordinatively flexible rare-earth metal centres to promote guest-selective binding in metal-organic frameworks. Full article
(This article belongs to the Special Issue Selected Papers from 2nd Energy Future Conference)
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5950 KiB  
Article
Thermal Analysis of an Industrial Furnace
by Mirko Filipponi, Federico Rossi, Andrea Presciutti, Stefania De Ciantis, Beatrice Castellani and Ambro Carpinelli
Energies 2016, 9(10), 833; https://doi.org/10.3390/en9100833 - 18 Oct 2016
Cited by 20 | Viewed by 6614
Abstract
Industries, which are mainly responsible for high energy consumption, need to invest in research projects in order to develop new managing systems for rational energy use, and to tackle the devastating effects of climate change caused by human behavior. The study described in [...] Read more.
Industries, which are mainly responsible for high energy consumption, need to invest in research projects in order to develop new managing systems for rational energy use, and to tackle the devastating effects of climate change caused by human behavior. The study described in this paper concerns the forging industry, where the production processes generally start with the heating of steel in furnaces, and continue with other processes, such as heat treatments and different forms of machining. One of the most critical operations, in terms of energy loss, is the opening of the furnace doors for insertion and extraction operations. During this time, the temperature of the furnaces decreases by hundreds of degrees in a few minutes. Because the dispersed heat needs to be supplied again through the combustion of fuel, increasing the consumption of energy and the pollutant emissions, the evaluation of the amount of lost energy is crucial for the development of systems which can contain this loss. To perform this study, CFD simulation software was used. Results show that when the door opens, because of temperature and pressure differences between the furnace and the ambient air, turbulence is created. Results also show that the amount of energy lost for an opening of 10 min for radiation, convection and conduction is equal to 5606 MJ where convection is the main contributor, with 5020 MJ. The model created, after being validated, has been applied to perform other simulations, in order to improve the energy performance of the furnace. Results show that reducing the opening time of the door saves energy and limits pollutant emissions. Full article
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2922 KiB  
Article
Smart Grid Cost-Emission Unit Commitment via Co-Evolutionary Agents
by Xiaohua Zhang, Jun Xie, Zhengwei Zhu, Jianfeng Zheng, Hao Qiang and Hailong Rong
Energies 2016, 9(10), 834; https://doi.org/10.3390/en9100834 - 17 Oct 2016
Cited by 2 | Viewed by 4141
Abstract
In this paper, the uncertainty of wind, solar and load; smart charging and discharging of plug-in hybrid electric vehicles (PHEVs) to and from various energy sources; and the coordination of wind, solar power, PHEVs and cost-emission are considered in the smart grid unit [...] Read more.
In this paper, the uncertainty of wind, solar and load; smart charging and discharging of plug-in hybrid electric vehicles (PHEVs) to and from various energy sources; and the coordination of wind, solar power, PHEVs and cost-emission are considered in the smart grid unit commitment (UC). First, a multi-scenario simulation is used in which a set of valid scenarios is considered for the uncertainties of wind and solar energy sources and load. Then the UC problem for the set of scenarios is decomposed into the optimization of interactive agents by multi-agent technology. Agents’ action is represented by a genetic algorithm with adaptive crossover and mutation operators. The adaptive co-evolution of agents is reached by adaptive cooperative multipliers. Finally, simulation is implemented on an example of a power system containing thermal units, a wind farm, solar power plants and PHEVs. The results show the effectiveness of the proposed method. Thermal units, wind, solar power and PHEVs are mutually complementarily by the adaptive cooperative mechanism. The adaptive multipliers’ updating strategy can save more computational time and further improve the efficiency. Full article
(This article belongs to the Special Issue Smart Microgrids: Developing the Intelligent Power Grid of Tomorrow)
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1742 KiB  
Article
The Relationship between Residential Electricity Consumption and Income: A Piecewise Linear Model with Panel Data
by Yanan Liu, Yixuan Gao, Yu Hao and Hua Liao
Energies 2016, 9(10), 831; https://doi.org/10.3390/en9100831 - 17 Oct 2016
Cited by 22 | Viewed by 6245
Abstract
There are many uncertainties and risks in residential electricity consumption associated with economic development. Knowledge of the relationship between residential electricity consumption and its key determinant—income—is important to the sustainable development of the electric power industry. Using panel data from 30 provinces for [...] Read more.
There are many uncertainties and risks in residential electricity consumption associated with economic development. Knowledge of the relationship between residential electricity consumption and its key determinant—income—is important to the sustainable development of the electric power industry. Using panel data from 30 provinces for the 1995–2012 period, this study investigates how residential electricity consumption changes as incomes increase in China. Previous studies typically used linear or quadratic double-logarithmic models imposing ex ante restrictions on the indistinct relationship between residential electricity consumption and income. Contrary to those models, we employed a reduced piecewise linear model that is self-adaptive and highly flexible and circumvents the problem of “prior restrictions”. Robust tests of different segment specifications and regression methods are performed to ensure the validity of the research. The results provide strong evidence that the income elasticity was approximately one, and it remained stable throughout the estimation period. The income threshold at which residential electricity consumption automatically remains stable or slows has not been reached. To ensure the sustainable development of the electric power industry, introducing higher energy efficiency standards for electrical appliances and improving income levels are vital. Government should also emphasize electricity conservation in the industrial sector rather than in residential sector. Full article
(This article belongs to the Special Issue Energy Policy and Climate Change 2016)
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5337 KiB  
Article
Neural Network Ensemble Based Approach for 2D-Interval Prediction of Solar Photovoltaic Power
by Mashud Rana and Irena Koprinska
Energies 2016, 9(10), 829; https://doi.org/10.3390/en9100829 - 17 Oct 2016
Cited by 14 | Viewed by 5583
Abstract
Solar energy generated from PhotoVoltaic (PV) systems is one of the most promising types of renewable energy. However, it is highly variable as it depends on the solar irradiance and other meteorological factors. This variability creates difficulties for the large-scale integration of PV [...] Read more.
Solar energy generated from PhotoVoltaic (PV) systems is one of the most promising types of renewable energy. However, it is highly variable as it depends on the solar irradiance and other meteorological factors. This variability creates difficulties for the large-scale integration of PV power in the electricity grid and requires accurate forecasting of the electricity generated by PV systems. In this paper we consider 2D-interval forecasts, where the goal is to predict summary statistics for the distribution of the PV power values in a future time interval. 2D-interval forecasts have been recently introduced, and they are more suitable than point forecasts for applications where the predicted variable has a high variability. We propose a method called NNE2D that combines variable selection based on mutual information and an ensemble of neural networks, to compute 2D-interval forecasts, where the two interval boundaries are expressed in terms of percentiles. NNE2D was evaluated for univariate prediction of Australian solar PV power data for two years. The results show that it is a promising method, outperforming persistence baselines and other methods used for comparison in terms of accuracy and coverage probability. Full article
(This article belongs to the Special Issue Energy Time Series Forecasting)
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3268 KiB  
Article
Short-Term Load Forecasting Based on Wavelet Transform and Least Squares Support Vector Machine Optimized by Improved Cuckoo Search
by Yi Liang, Dongxiao Niu, Minquan Ye and Wei-Chiang Hong
Energies 2016, 9(10), 827; https://doi.org/10.3390/en9100827 - 17 Oct 2016
Cited by 31 | Viewed by 5092 | Correction
Abstract
Due to the electricity market deregulation and integration of renewable resources, electrical load forecasting is becoming increasingly important for the Chinese government in recent years. The electric load cannot be exactly predicted only by a single model, because the short-term electric load is [...] Read more.
Due to the electricity market deregulation and integration of renewable resources, electrical load forecasting is becoming increasingly important for the Chinese government in recent years. The electric load cannot be exactly predicted only by a single model, because the short-term electric load is disturbed by several external factors, leading to the characteristics of volatility and instability. To end this, this paper proposes a hybrid model based on wavelet transform (WT) and least squares support vector machine (LSSVM), which is optimized by an improved cuckoo search (CS). To improve the accuracy of prediction, the WT is used to eliminate the high frequency components of the previous day’s load data. Additional, the Gauss disturbance is applied to the process of establishing new solutions based on CS to improve the convergence speed and search ability. Finally, the parameters of the LSSVM model are optimized by using the improved cuckoo search. According to the research outcome, the result of the implementation demonstrates that the hybrid model can be used in the short-term forecasting of the power system. Full article
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