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Energies, Volume 11, Issue 1 (January 2018)

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Cover Story (view full-size image) The battery management system (BMS) in electric vehicles is based on state of charge (SOC) [...] Read more.
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Open AccessArticle An Evaluation of Investment in a PV Power Generation Project in the Gobi Desert Using a Real Options Model
Energies 2018, 11(1), 257; https://doi.org/10.3390/en11010257
Received: 14 November 2017 / Revised: 16 January 2018 / Accepted: 18 January 2018 / Published: 21 January 2018
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Abstract
This paper presents a policy benefit model of a photovoltaic (PV) power generation project based on real options analysis (ROA) and the two-factor learning curve model. The main purpose is to examine the investment behavior of developing a PV project in the Gobi
[...] Read more.
This paper presents a policy benefit model of a photovoltaic (PV) power generation project based on real options analysis (ROA) and the two-factor learning curve model. The main purpose is to examine the investment behavior of developing a PV project in the Gobi desert considering multiple uncertain factors. We take the environmental cost of desertification control into account for the first time in the literature. Four other uncertain factors are thermal power cost, PV power generation cost, carbon prices, and government subsidy. A binary tree method is applied to solve the proposed model, and we obtain both unit decision value and optimal investment time. Our baseline scenario illustrates that ROA is more effective than net present value (NPV) analysis when dealing with uncertainty. Our simulation results show that the government could suffer a loss in accordance with the existing subsidy policy when investing in a PV project. Therefore, the subsidy should be gradually reduced. Finally, the influence of the subsidy policy on decision value is discussed, and an appropriate subsidy is determined accordingly. Full article
(This article belongs to the Section Electrical Power and Energy System)
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Open AccessArticle Numerical Study of Bubble Coalescence and Breakup in the Reactor Fuel Channel with a Vaned Grid
Energies 2018, 11(1), 256; https://doi.org/10.3390/en11010256
Received: 20 December 2017 / Revised: 9 January 2018 / Accepted: 12 January 2018 / Published: 21 January 2018
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Abstract
The characteristics of bubbles of different sizes in fuel assembly are vital to two-phase flow resistance and heat transfer capacity. However, due to the swirl flow caused by the mixing vane, bubbles can crowd at the heated surface, which may anticipate the occurrence
[...] Read more.
The characteristics of bubbles of different sizes in fuel assembly are vital to two-phase flow resistance and heat transfer capacity. However, due to the swirl flow caused by the mixing vane, bubbles can crowd at the heated surface, which may anticipate the occurrence of departure from nucleation boiling. In the current work, the adiabatic two-phase flow in a simplified fuel assembly was analyzed by using the Eulerian two-fluid model and the MUSIG (MUltiple SIze Group) model. This computational domain consists of two coolant channels and two sets of vaned spacers, with three sets of periodic boundary conditions at the side faces of the domain. The distributions of vapor phase and bubble diameters were obtained, based on which the effects of mixing vanes on the bubble characteristics were analyzed. Vapor phase crowded at the rod surface in the higher inlet vapor fraction case, but crowded in the channel center in the lower inlet vapor fraction cases. This work can be used as a reference for the design of mixing vanes to avoid the anticipation of departure of nucleation boiling that may be caused by unreasonable design. Full article
(This article belongs to the Section Electrical Power and Energy System)
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Open AccessArticle Maximum Permissible Integration Capacity of Renewable DG Units Based on System Loads
Energies 2018, 11(1), 255; https://doi.org/10.3390/en11010255
Received: 25 November 2017 / Revised: 12 January 2018 / Accepted: 16 January 2018 / Published: 21 January 2018
Cited by 2 | PDF Full-text (3926 KB) | HTML Full-text | XML Full-text
Abstract
Increasing demand for electricity, as well as rising environmental and economic concerns have resulted in renewable energy sources being a center of attraction. Integration of these renewable energy resources into power systems is usually achieved through distributed generation (DG) techniques, and the number
[...] Read more.
Increasing demand for electricity, as well as rising environmental and economic concerns have resulted in renewable energy sources being a center of attraction. Integration of these renewable energy resources into power systems is usually achieved through distributed generation (DG) techniques, and the number of such applications increases daily. As conventional power systems do not have an infrastructure that is compatible with these energy sources and generation systems, such integration applications may cause various problems in power systems. Therefore, planning is an essential part of DG integration, especially for power systems with intermittent renewable energy sources with the objective of minimizing problems and maximizing benefits. In this study, a mathematical model is proposed to calculate the maximum permissible DG integration capacity without causing overvoltage problems in the power systems. In the proposed mathematical model, both the minimum loading condition and maximum generation condition are taken into consideration. In order to prove the effectiveness and the consistency of the proposed mathematical model, it is applied to a test system with different case studies, and the results are compared with the results obtained from other models in the literature. Full article
(This article belongs to the Special Issue Distributed Renewable Generation 2018)
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Open AccessArticle Multi-Time Scale Model Order Reduction and Stability Consistency Certification of Inverter-Interfaced DG System in AC Microgrid
Energies 2018, 11(1), 254; https://doi.org/10.3390/en11010254
Received: 23 November 2017 / Revised: 17 January 2018 / Accepted: 18 January 2018 / Published: 20 January 2018
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Abstract
AC microgrid mainly comprise inverter-interfaced distributed generators (IIDGs), which are nonlinear complex systems with multiple time scales, including frequency control, time delay measurements, and electromagnetic transients. The droop control-based IIDG in an AC microgrid is selected as the research object in this study,
[...] Read more.
AC microgrid mainly comprise inverter-interfaced distributed generators (IIDGs), which are nonlinear complex systems with multiple time scales, including frequency control, time delay measurements, and electromagnetic transients. The droop control-based IIDG in an AC microgrid is selected as the research object in this study, which comprises power droop controller, voltage- and current-loop controllers, and filter and line. The multi-time scale characteristics of the detailed IIDG model are divided based on singular perturbation theory. In addition, the IIDG model order is reduced by neglecting the system fast dynamics. The static and transient stability consistency of the IIDG model order reduction are demonstrated by extracting features of the IIDG small signal model and using the quadratic approximation method of the stability region boundary, respectively. The dynamic response consistencies of the IIDG model order reduction are evaluated using the frequency, damping and amplitude features extracted by the Prony transformation. Results are applicable to provide a simplified model for the dynamic characteristic analysis of IIDG systems in AC microgrid. The accuracy of the proposed method is verified by using the eigenvalue comparison, the transient stability index comparison and the dynamic time-domain simulation. Full article
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Open AccessReview Novel Receiver-Enhanced Solar Vapor Generation: Review and Perspectives
Energies 2018, 11(1), 253; https://doi.org/10.3390/en11010253
Received: 30 November 2017 / Revised: 5 January 2018 / Accepted: 16 January 2018 / Published: 20 January 2018
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Abstract
Efficient solar vapor/steam generation is important for various applications ranging from power generation, cooling, desalination systems to compact and portable devices like drinking water purification and sterilization units. However, conventional solar steam generation techniques usually rely on costly and cumbersome optical concentration systems
[...] Read more.
Efficient solar vapor/steam generation is important for various applications ranging from power generation, cooling, desalination systems to compact and portable devices like drinking water purification and sterilization units. However, conventional solar steam generation techniques usually rely on costly and cumbersome optical concentration systems and have relatively low efficiency due to bulk heating of the entire liquid volume. Recently, by incorporating novel light harvesting receivers, a new class of solar steam generation systems has emerged with high vapor generation efficiency. They are categorized in two research streams: volumetric and floating solar receivers. In this paper, we review the basic principles of these solar receivers, the mechanism involving from light absorption to the vapor generation, and the associated challenges. We also highlight the two routes to produce high temperature steam using optical and thermal concentration. Finally, we propose a scalable approach to efficiently harvest solar energy using a semi-spectrally selective absorber with near-perfect visible light absorption and low thermal emittance. Our proposed approach represents a new development in thermally concentrated solar distillation systems, which is also cost-effective and easy to fabricate for rapid industrial deployment. Full article
(This article belongs to the Special Issue The Future of Solar Thermal Energy)
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Open AccessArticle Drag Reduction by Laminar Flow Control
Energies 2018, 11(1), 252; https://doi.org/10.3390/en11010252
Received: 20 December 2017 / Revised: 13 January 2018 / Accepted: 15 January 2018 / Published: 20 January 2018
Cited by 3 | PDF Full-text (8967 KB) | HTML Full-text | XML Full-text
Abstract
The Energy System Transition in Aviation research project of the Aeronautics Research Center Niedersachsen (NFL) searches for potentially game-changing technologies to reduce the carbon footprint of aviation by promoting and enabling new propulsion and drag reduction technologies. The greatest potential for aerodynamic drag
[...] Read more.
The Energy System Transition in Aviation research project of the Aeronautics Research Center Niedersachsen (NFL) searches for potentially game-changing technologies to reduce the carbon footprint of aviation by promoting and enabling new propulsion and drag reduction technologies. The greatest potential for aerodynamic drag reduction is seen in laminar flow control by boundary layer suction. While most of the research so far has been on partial laminarization by application of Natural Laminar Flow (NLF) and Hybrid Laminar Flow Control (HLFC) to wings, complete laminarization of wings, tails and fuselages promises much higher gains. The potential drag reduction and suction requirements, including the necessary compressor power, are calculated on component level using a flow solver with viscid/inviscid coupling and a 3D Reynolds-Averaged Navier-Stokes (RANS) solver. The effect on total aircraft drag is estimated for a state-of-the-art mid-range aircraft configuration using preliminary aircraft design methods, showing that total cruise drag can be halved compared to today’s turbulent aircraft. Full article
(This article belongs to the Special Issue Towards a Transformation to Sustainable Aviation Systems)
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Open AccessArticle Aspects Referring Wind Energy Integration from the Power System Point of View in the Region of Southeast Europe. Study Case of Romania
Energies 2018, 11(1), 251; https://doi.org/10.3390/en11010251
Received: 22 December 2017 / Revised: 9 January 2018 / Accepted: 18 January 2018 / Published: 20 January 2018
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Abstract
Wind energy integration is a complex target that could refer to different aspects such as: grid capacity; power system; support scheme; environmental; social issues; etc. It is probably the less predictable renewable energy sources (RES) due to its high volatility being difficult to
[...] Read more.
Wind energy integration is a complex target that could refer to different aspects such as: grid capacity; power system; support scheme; environmental; social issues; etc. It is probably the less predictable renewable energy sources (RES) due to its high volatility being difficult to be securely integrated into the power systems. This paper will focus on the wind energy integration from the power system point of view, emphasizing the case of Romania. Before going into the Romanian case, the paper analyzes the potential benefits of the regional approach in terms of power system integration, revealing that it can bring significant advantages by reducing the required power reserves or increasing wind power plants (WPP) generation. Currently, the power system integration is one of the major obstacle to large scale wind energy penetration in the region of Southeast (SE) Europe with high wind energy potential. The results of our research consist in proposing a model for estimating the balancing reserves sharing at regional level, comparing regional to country-by-country approach in terms of the power reserve requirements for balancing the operation of WPP. It definitely reveals that by regional Transmission System Operators (TSO) coordination; less reserves are needed; therefore, the space for RES enlarges. We also propose a model for Romanian power system that is able to calculate the installed power of WPP that could operate without considerable interruptions. Also, the model estimates the additional power reserves required for larger wind energy integration. This perspective can provide interesting insights on what should be foreseen as reasonable behavior of the policy makers and investors. Full article
(This article belongs to the Section Electrical Power and Energy System)
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Open AccessArticle Reducing Energy Demand Using Wheel-Individual Electric Drives to Substitute EPS-Systems
Energies 2018, 11(1), 247; https://doi.org/10.3390/en11010247
Received: 18 December 2017 / Revised: 11 January 2018 / Accepted: 16 January 2018 / Published: 20 January 2018
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Abstract
The energy demand of vehicles is influenced, not only by the drive systems, but also by a number of add-on systems. Electric vehicles must satisfy this energy demand completely from the battery. Hence, the use of power steering systems directly result in a
[...] Read more.
The energy demand of vehicles is influenced, not only by the drive systems, but also by a number of add-on systems. Electric vehicles must satisfy this energy demand completely from the battery. Hence, the use of power steering systems directly result in a range reduction. The “e2-Lenk” joint project funded by the German Federal Ministry of Education and Research (BMBF) involves a novel steering concept for electric vehicles to integrate the function of steering assistance into the drive-train. Specific distribution of driving torque at the steered axle allows the steering wheel torque to be influenced to support the steering force. This provides a potential for complete substitution of conventional power steering systems and reduces the vehicle’s energy demand. This paper shows the potential of wheel-individual drives influencing the driver’s steering torque using a control technique based on classical EPS control plans. Compared to conventional power-assisted steering systems, a reduced energy demand becomes evident over a wide range of operating conditions. Full article
(This article belongs to the Special Issue Methods to Improve Energy Use in Road Vehicles)
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Open AccessArticle Improvement of Shade Resilience in Photovoltaic Modules Using Buck Converters in a Smart Module Architecture
Energies 2018, 11(1), 250; https://doi.org/10.3390/en11010250
Received: 13 December 2017 / Revised: 16 January 2018 / Accepted: 17 January 2018 / Published: 19 January 2018
Cited by 2 | PDF Full-text (7713 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Partial shading has a nonlinear effect on the performance of photovoltaic (PV) modules. Different methods of optimizing energy harvesting under partial shading conditions have been suggested to mitigate this issue. In this paper, a smart PV module architecture is proposed for improvement of
[...] Read more.
Partial shading has a nonlinear effect on the performance of photovoltaic (PV) modules. Different methods of optimizing energy harvesting under partial shading conditions have been suggested to mitigate this issue. In this paper, a smart PV module architecture is proposed for improvement of shade resilience in a PV module consisting of 60 silicon solar cells, which compensates the current drops caused by partial shading. The architecture consists of groups of series-connected solar cells in parallel to a DC-DC buck converter. The number of cell groups is optimized with respect to cell and converter specifications using a least-squares support vector machine method. A generic model is developed to simulate the behavior of the smart architecture under different shading patterns, using high time resolution irradiance data. In this research the shading patterns are a combination of random and pole shadows. To investigate the shade resilience, results for the smart architecture are compared with an ideal module, and also ordinary series and parallel connected architectures. Although the annual yield for the smart architecture is 79.5% of the yield of an ideal module, we show that the smart architecture outperforms a standard series connected module by 47%, and a parallel architecture by 13.4%. Full article
(This article belongs to the Special Issue PV System Design and Performance)
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Open AccessArticle Hot Spot Temperature and Grey Target Theory-Based Dynamic Modelling for Reliability Assessment of Transformer Oil-Paper Insulation Systems: A Practical Case Study
Energies 2018, 11(1), 249; https://doi.org/10.3390/en11010249
Received: 23 December 2017 / Revised: 13 January 2018 / Accepted: 17 January 2018 / Published: 19 January 2018
Cited by 1 | PDF Full-text (5235 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
This paper develops a novel dynamic correction method for the reliability assessment of large oil-immersed power transformers. First, with the transformer oil-paper insulation system (TOPIS) as the target of evaluation and the winding hot spot temperature (HST) as the core point, an HST-based
[...] Read more.
This paper develops a novel dynamic correction method for the reliability assessment of large oil-immersed power transformers. First, with the transformer oil-paper insulation system (TOPIS) as the target of evaluation and the winding hot spot temperature (HST) as the core point, an HST-based static ageing failure model is built according to the Weibull distribution and Arrhenius reaction law, in order to describe the transformer ageing process and calculate the winding HST for obtaining the failure rate and life expectancy of TOPIS. A grey target theory based dynamic correction model is then developed, combined with the data of Dissolved Gas Analysis (DGA) in power transformer oil, in order to dynamically modify the life expectancy calculated by the built static model, such that the corresponding relationship between the state grade and life expectancy correction coefficient of TOPIS can be built. Furthermore, the life expectancy loss recovery factor is introduced to correct the life expectancy of TOPIS again. Lastly, a practical case study of an operating transformer has been undertaken, in which the failure rate curve after introducing dynamic corrections can be obtained for the reliability assessment of this transformer. The curve shows a better ability of tracking the actual reliability level of transformer, thus verifying the validity of the proposed method and providing a new way for transformer reliability assessment. This contribution presents a novel model for the reliability assessment of TOPIS, in which the DGA data, as a source of information for the dynamic correction, is processed based on the grey target theory, thus the internal faults of power transformer can be diagnosed accurately as well as its life expectancy updated in time, ensuring that the dynamic assessment values can commendably track and reflect the actual operation state of the power transformers. Full article
(This article belongs to the Section Electrical Power and Energy System)
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Open AccessArticle CFD-Driven Valve Shape Optimization for Performance Improvement of a Micro Cross-Flow Turbine
Energies 2018, 11(1), 248; https://doi.org/10.3390/en11010248
Received: 13 December 2017 / Revised: 10 January 2018 / Accepted: 16 January 2018 / Published: 19 January 2018
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Abstract
Turbines are critical parts in hydropower facilities, and the cross-flow turbine is one of the widely applied turbine designs in small- and micro-hydro facilities. Cross-flow turbines are relatively simple, flexible and less expensive, compared to other conventional hydro-turbines. However, the power generation efficiency
[...] Read more.
Turbines are critical parts in hydropower facilities, and the cross-flow turbine is one of the widely applied turbine designs in small- and micro-hydro facilities. Cross-flow turbines are relatively simple, flexible and less expensive, compared to other conventional hydro-turbines. However, the power generation efficiency of cross-flow turbines is not yet well optimized compared to conventional hydro-turbines. In this article, a Computational Fluid Dynamics (CFD)-driven design optimization approach is applied to one of the critical parts of the turbine, the valve. The valve controls the fluid flow, as well as determines the velocity and pressure magnitudes of the fluid jet leaving the nozzle region in the turbine. The Non-Uniform Rational B-Spline (NURBS) function is employed to generate construction points for the valve profile curve. Control points from the function that are highly sensitive to the output power are selected as optimization parameters, leading to the generation of construction points. Metamodel-assisted and metaheuristic optimization tools are used in the optimization. Optimized turbine designs from both optimization methods outperformed the original design with regard to performance of the turbine. Moreover, the metamodel-assisted optimization approach reduced the computational cost, compared to its counterpart. Full article
(This article belongs to the Section Energy Sources)
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Open AccessArticle Assessment of Future Whole-System Value of Large-Scale Pumped Storage Plants in Europe
Energies 2018, 11(1), 246; https://doi.org/10.3390/en11010246
Received: 14 November 2017 / Revised: 18 December 2017 / Accepted: 6 January 2018 / Published: 19 January 2018
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Abstract
This paper analyses the impacts and benefits of the pumped storage plant (PSP) and its upgrade to variable speed on generation and transmission capacity requirements, capital costs, system operating costs and carbon emissions in the future European electricity system. The combination of a
[...] Read more.
This paper analyses the impacts and benefits of the pumped storage plant (PSP) and its upgrade to variable speed on generation and transmission capacity requirements, capital costs, system operating costs and carbon emissions in the future European electricity system. The combination of a deterministic system planning tool, Whole-electricity System Investment Model (WeSIM), and a stochastic system operation optimisation tool, Advanced Stochastic Unit Commitment (ASUC), is used to analyse the whole-system value of PSP technology and to quantify the impact of European balancing market integration and other competing flexible technologies on the value of the PSP. Case studies on the Pan-European system demonstrate that PSPs can reduce the total system cost by up to €13 billion per annum by 2050 in a scenario with a high share of renewables. Upgrading the PSP to variable-speed drive enhances its long-term benefits by 10–20%. On the other hand, balancing market integration across Europe may potentially reduce the overall value of the variable-speed PSP, although the effect can vary across different European regions. The results also suggest that large-scale deployment of demand-side response (DSR) leads to a significant reduction in the value of PSPs, while the value of PSPs increases by circa 18% when the total European interconnection capacity is halved. The benefit of PSPs in reducing emissions is relatively negligible by 2030 but constitutes around 6–10% of total annual carbon emissions from the European power sector by 2050. Full article
(This article belongs to the Special Issue Hydropower 2017)
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Open AccessArticle Impact of Optimum Allocation of Renewable Distributed Generations on Distribution Networks Based on Different Optimization Algorithms
Energies 2018, 11(1), 245; https://doi.org/10.3390/en11010245
Received: 24 December 2017 / Revised: 5 January 2018 / Accepted: 12 January 2018 / Published: 19 January 2018
Cited by 3 | PDF Full-text (13088 KB) | HTML Full-text | XML Full-text
Abstract
Integration of Renewable Distributed Generations (RDGs) such as photovoltaic (PV) systems and wind turbines (WTs) in distribution networks can be considered a brilliant and efficient solution to the growing demand for energy. This article introduces new robust and effective techniques like hybrid Particle
[...] Read more.
Integration of Renewable Distributed Generations (RDGs) such as photovoltaic (PV) systems and wind turbines (WTs) in distribution networks can be considered a brilliant and efficient solution to the growing demand for energy. This article introduces new robust and effective techniques like hybrid Particle Swarm Optimization in addition to a Gravitational Search Algorithm (PSOGSA) and Moth-Flame Optimization (MFO) that are proposed to deduce the optimum location with convenient capacity of RDGs units for minimizing system power losses and operating cost while improving voltage profile and voltage stability. This paper describes two stages. First, the Loss Sensitivity Factors (LSFs) are employed to select the most candidate buses for RDGs location. In the second stage, the PSOGSA and MFO are implemented to deduce the optimal location and capacity of RDGs from the elected buses. The proposed schemes have been applied on 33-bus and 69-bus IEEE standard radial distribution systems. To insure the suggested approaches validity, the numerical results have been compared with other techniques like Backtracking Search Optimization Algorithm (BSOA), Genetic Algorithm (GA), Particle Swarm Algorithm (PSO), Novel combined Genetic Algorithm and Particle Swarm Optimization (GA/PSO), Simulation Annealing Algorithm (SA), and Bacterial Foraging Optimization Algorithm (BFOA). The evaluated results have been confirmed the superiority with high performance of the proposed MFO technique to find the optimal solutions of RDGs units’ allocation. In this regard, the MFO is chosen to solve the problems of Egyptian Middle East distribution network as a practical case study with the optimal integration of RDGs. Full article
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Open AccessArticle A Distributed Randomized Gradient-Free Algorithm for the Non-Convex Economic Dispatch Problem
Energies 2018, 11(1), 244; https://doi.org/10.3390/en11010244
Received: 25 November 2017 / Revised: 6 January 2018 / Accepted: 17 January 2018 / Published: 19 January 2018
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Abstract
In this paper, a distributed randomized gradient-free algorithm (DRGF) is employed to solve the complex non-convex economic dispatch problem whose non-convex constraints include valve-point loading effects, prohibited operating zones, and multiple fuel options. The DRGF uses the Gauss approximation, smoothing parameters, and a
[...] Read more.
In this paper, a distributed randomized gradient-free algorithm (DRGF) is employed to solve the complex non-convex economic dispatch problem whose non-convex constraints include valve-point loading effects, prohibited operating zones, and multiple fuel options. The DRGF uses the Gauss approximation, smoothing parameters, and a random sequence to construct distributed randomized gradient-free oracles. By employing a consensus procedure, generation units can gather local information through local communication links and then process the economic dispatch data in a distributed iteration format. Based on the principle of projection optimization, a projection operator is adopted in the DRGF to deal with the discontinuous solution space. The effectiveness of the proposed approach in addressing the non-convex economic dispatch problem is demonstrated by simulations implemented on three standard test systems. Full article
(This article belongs to the Section Electrical Power and Energy System)
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Open AccessArticle Adaptively Constrained Stochastic Model Predictive Control for the Optimal Dispatch of Microgrid
Energies 2018, 11(1), 243; https://doi.org/10.3390/en11010243
Received: 19 December 2017 / Revised: 9 January 2018 / Accepted: 17 January 2018 / Published: 19 January 2018
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Abstract
In this paper, an adaptively constrained stochastic model predictive control (MPC) is proposed to achieve less-conservative coordination between energy storage units and uncertain renewable energy sources (RESs) in a microgrid (MG). Besides the economic objective of MG operation, the limits of state-of-charge (SOC)
[...] Read more.
In this paper, an adaptively constrained stochastic model predictive control (MPC) is proposed to achieve less-conservative coordination between energy storage units and uncertain renewable energy sources (RESs) in a microgrid (MG). Besides the economic objective of MG operation, the limits of state-of-charge (SOC) and discharging/charging power of the energy storage unit are formulated as chance constraints when accommodating uncertainties of RESs, considering mild violations of these constraints are allowed during long-term operation, and a closed-loop online update strategy is performed to adaptively tighten or relax constraints according to the actual deviation probability of violation level from the desired one as well as the current change rate of deviation probability. Numerical studies show that the proposed adaptively constrained stochastic MPC for MG optimal operation is much less conservative compared with the scenario optimization based robust MPC, and also presents a better convergence performance to the desired constraint violation level than other online update strategies. Full article
(This article belongs to the Section Electrical Power and Energy System)
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Open AccessArticle Deep Belief Network Based Hybrid Model for Building Energy Consumption Prediction
Energies 2018, 11(1), 242; https://doi.org/10.3390/en11010242
Received: 15 December 2017 / Revised: 16 January 2018 / Accepted: 16 January 2018 / Published: 19 January 2018
Cited by 6 | PDF Full-text (2475 KB) | HTML Full-text | XML Full-text
Abstract
To enhance the prediction performance for building energy consumption, this paper presents a modified deep belief network (DBN) based hybrid model. The proposed hybrid model combines the outputs from the DBN model with the energy-consuming pattern to yield the final prediction results. The
[...] Read more.
To enhance the prediction performance for building energy consumption, this paper presents a modified deep belief network (DBN) based hybrid model. The proposed hybrid model combines the outputs from the DBN model with the energy-consuming pattern to yield the final prediction results. The energy-consuming pattern in this study represents the periodicity property of building energy consumption and can be extracted from the observed historical energy consumption data. The residual data generated by removing the energy-consuming pattern from the original data are utilized to train the modified DBN model. The training of the modified DBN includes two steps, the first one of which adopts the contrastive divergence (CD) algorithm to optimize the hidden parameters in a pre-train way, while the second one determines the output weighting vector by the least squares method. The proposed hybrid model is applied to two kinds of building energy consumption data sets that have different energy-consuming patterns (daily-periodicity and weekly-periodicity). In order to examine the advantages of the proposed model, four popular artificial intelligence methods—the backward propagation neural network (BPNN), the generalized radial basis function neural network (GRBFNN), the extreme learning machine (ELM), and the support vector regressor (SVR) are chosen as the comparative approaches. Experimental results demonstrate that the proposed DBN based hybrid model has the best performance compared with the comparative techniques. Another thing to be mentioned is that all the predictors constructed by utilizing the energy-consuming patterns perform better than those designed only by the original data. This verifies the usefulness of the incorporation of the energy-consuming patterns. The proposed approach can also be extended and applied to some other similar prediction problems that have periodicity patterns, e.g., the traffic flow forecasting and the electricity consumption prediction. Full article
(This article belongs to the Special Issue Short-Term Load Forecasting by Artificial Intelligent Technologies)
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Open AccessArticle Modeling Interprovincial Cooperative Energy Saving in China: An Electricity Utilization Perspective
Energies 2018, 11(1), 241; https://doi.org/10.3390/en11010241
Received: 7 January 2018 / Revised: 15 January 2018 / Accepted: 17 January 2018 / Published: 19 January 2018
Cited by 3 | PDF Full-text (1014 KB) | HTML Full-text | XML Full-text
Abstract
As the world faces great challenges from climate change and environmental pollution, China urgently requires energy saving, emission reduction, and carbon reduction programmes. However, the non-cooperative energy saving model (NCESM), the simple regulation mode that is China’s main model for energy saving, is
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As the world faces great challenges from climate change and environmental pollution, China urgently requires energy saving, emission reduction, and carbon reduction programmes. However, the non-cooperative energy saving model (NCESM), the simple regulation mode that is China’s main model for energy saving, is not beneficial for optimization of energy and resource distribution, and cannot effectively motivate energy saving at the provincial level. Therefore, we propose an interprovincial cooperative energy saving model (CESM) from the perspective of electricity utilization, with the object of maximizing the benefits from electricity utilization of the cooperation union based on achieving the energy saving goals of the union as a whole. The CESM consists of two parts: (1) an optimization model that calculates the optimal quantities of electricity consumption for each participating province to meet the joint energy saving goal; and (2) a model that distributes the economic benefits of the cooperation among the provinces in the cooperation based on the Shapley value method. We applied the CESM to the case of an interprovincial union of Shanghai, Sichuan, Shanxi, and Gansu in China. The results, based on the data from 2001–2014, show that cooperation can significantly increase the benefits of electricity utilization for each province in the union. The total benefits of the union from utilization of electricity increased 38.38%, or 353.98 billion CNY, while the benefits to Shanghai, Sichuan, Shanxi, and Gansu were 200.28, 58.37, 57.11, and 38.22 billion CNY respectively greater under the CESM than the NCESM. The implementation of the CESM provides the provincial governments not only a flexible and incentive way to achieve short-term goals, but also a feasible and effective path to realize long-term energy saving strategies. To test the impact of different parameter values on the results of the CESM, a sensitivity analysis was conducted. Some policy recommendations are made at the central government level and the provincial government level to promote the implementation of the CESM. Full article
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Open AccessArticle Gas-Lifting Characteristics of Methane-Water Mixture and Its Potential Application for Self-Eruption Production of Marine Natural Gas Hydrates
Energies 2018, 11(1), 240; https://doi.org/10.3390/en11010240
Received: 1 December 2017 / Revised: 8 January 2018 / Accepted: 16 January 2018 / Published: 19 January 2018
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Abstract
A gas-lifting production method was firstly proposed to transport the methane-water mixture from natural gas hydrates deposits through marine vertical pipe in this work. Aiming at UBGH2-6 site, SH7 site and GMGS2-8 site, the gas-lifting performance of methane-water mixture in the vertical pipe
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A gas-lifting production method was firstly proposed to transport the methane-water mixture from natural gas hydrates deposits through marine vertical pipe in this work. Aiming at UBGH2-6 site, SH7 site and GMGS2-8 site, the gas-lifting performance of methane-water mixture in the vertical pipe was investigated by numerical calculation. The potential of Natural gas hydrates (NGH) self-eruption production induced by the gas-lifting process under ideal conditions was also studied based on the energy analysis. The calculation results indicate that the gas-lifting method has great advantage in avoiding the secondary hydrates formation in marine vertical pipe and reducing energy consumption. The gas-lifting process in the vertical pipe is testified to be spontaneous in UBGH2-6 site and SH7 site during the initial 4000 and 1000 days, respectively, which indicates the energy consumption for methane-water mixture transportation is saved. Sufficient heat supply for the hydrate dissociation is crucial for the NGH self-eruption production. Sensitivity analysis indicates that the water-gas ratio has more significant influences on gas-lifting performance in the vertical pipe compared to the flow rate. With the decrease of water-gas ratio, the bottomhole pressure decreases rapidly. Thus, the reduction of water production is effective to improve the gas-lifting performance. Full article
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Open AccessArticle Frequency Regulation of a Hybrid Wind–Hydro Power Plant in an Isolated Power System
Energies 2018, 11(1), 239; https://doi.org/10.3390/en11010239
Received: 13 December 2017 / Revised: 11 January 2018 / Accepted: 16 January 2018 / Published: 19 January 2018
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Abstract
Currently, some small islands with high wind potential are trying to reduce the environmental and economic impact of fossil fuels by using renewable resources. Nevertheless, the characteristics of these renewable resources negatively affect the quality of the electrical energy, causing frequency disturbances, especially
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Currently, some small islands with high wind potential are trying to reduce the environmental and economic impact of fossil fuels by using renewable resources. Nevertheless, the characteristics of these renewable resources negatively affect the quality of the electrical energy, causing frequency disturbances, especially in isolated systems. In this study, the combined contribution to frequency regulation of variable speed wind turbines (VSWT) and a pump storage hydropower plant (PSHP) is analyzed. Different control strategies, using the kinetic energy stored in the VSWT, are studied: inertial, proportional, and their combination. In general, the gains of the VSWT controller for interconnected systems proposed in the literature are not adequate for isolated systems. Therefore, a methodology to adjust the controllers, based on exhaustive searches, is proposed for each of the control strategies. The control strategies and methodology have been applied to a hybrid wind–hydro power plant on El Hierro Island in the Canary archipelago. At present, in this isolated power system, frequency regulation is only provided by the PSHP and diesel generators. The improvements in the quality of frequency regulation, including the VSWT contribution, have been proven based on simulating different events related to wind speed, or variations in the power demand. Full article
(This article belongs to the Special Issue Wind Generators Modelling and Control)
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Open AccessArticle A New PV Array Fault Diagnosis Method Using Fuzzy C-Mean Clustering and Fuzzy Membership Algorithm
Energies 2018, 11(1), 238; https://doi.org/10.3390/en11010238
Received: 1 November 2017 / Revised: 15 January 2018 / Accepted: 16 January 2018 / Published: 19 January 2018
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Abstract
Photovoltaic (PV) power station faults in the natural environment mainly occur in the PV array, and the accurate fault diagnosis is of particular significance for the safe and efficient PV power plant operation. The PV array’s electrical behavior characteristics under fault conditions is
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Photovoltaic (PV) power station faults in the natural environment mainly occur in the PV array, and the accurate fault diagnosis is of particular significance for the safe and efficient PV power plant operation. The PV array’s electrical behavior characteristics under fault conditions is analyzed in this paper, and a novel PV array fault diagnosis method is proposed based on fuzzy C-mean (FCM) and fuzzy membership algorithms. Firstly, clustering analysis of PV array fault samples is conducted using the FCM algorithm, indicating that there is a fixed relationship between the distribution characteristics of cluster centers and the different fault, then the fault samples are classified effectively. The membership degrees of all fault data and cluster centers are then determined by the fuzzy membership algorithm for the final fault diagnosis. Simulation analysis indicated that the diagnostic accuracy of the proposed method was 96%. Field experiments further verified the correctness and effectiveness of the proposed method. In this paper, various types of fault distribution features are effectively identified by the FCM algorithm, whether the PV array operation parameters belong to the fault category is determined by fuzzy membership algorithm, and the advantage of the proposed method is it can classify the fault data from normal operating data without foreknowledge. Full article
(This article belongs to the Special Issue PV System Design and Performance)
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Open AccessFeature PaperArticle Energy-Saving Analysis of Solar Heating System with PCM Storage Tank
Energies 2018, 11(1), 237; https://doi.org/10.3390/en11010237
Received: 18 November 2017 / Revised: 14 January 2018 / Accepted: 15 January 2018 / Published: 19 January 2018
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Abstract
A solar heating system (SHS) with a phase change material (PCM) thermal storage tank is proposed with the view that traditional heat water storage tanks present several problems including large space requirements, significant heat loss and unstable system performance. An entire heating season
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A solar heating system (SHS) with a phase change material (PCM) thermal storage tank is proposed with the view that traditional heat water storage tanks present several problems including large space requirements, significant heat loss and unstable system performance. An entire heating season (November–March) is selected as the research period on the basis of numerical models of the SHS-PCM. In addition, taking a public building in Lhasa as the object, the heating conditions, contribution rate of solar energy, and overall energy-saving capability provided by the heating system are analyzed under different PCM storage tanks and different terminal forms. The results show that an SHS with a PCM tank provides a 34% increase in energy saving capability compared to an ordinary water tank heating system. It is suggested that the design selection parameters of the PCM storage tank should specify a daily heat storage capacity that satisfies 70~80% of the entire heating season. A floor radiant system with supply/return water temperatures of 40/35 °C provides the optimal operation and the largest energy saving capability. Full article
(This article belongs to the Special Issue Solar Technologies for Buildings)
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Open AccessReview The Innovative Concept of Cold District Heating Networks: A Literature Review
Energies 2018, 11(1), 236; https://doi.org/10.3390/en11010236
Received: 22 December 2017 / Revised: 16 January 2018 / Accepted: 16 January 2018 / Published: 19 January 2018
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Abstract
The development of sustainable and innovative solutions for the production and supply of energy at district level is nowadays one of the main technical challenges. In the past, district heating and cooling networks aimed to achieve greater energy efficiency through the centralization of
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The development of sustainable and innovative solutions for the production and supply of energy at district level is nowadays one of the main technical challenges. In the past, district heating and cooling networks aimed to achieve greater energy efficiency through the centralization of the energy production process but with relevant losses related to heat transport. Moving towards a higher share of renewables and lower demand of primary energy requires redesign of the energy district networks. The novel concept of cold district heating networks aims to combine the advantages of a centralized energy distribution system with low heat losses in energy supply. This combined effect is achieved through the centralized supply of water at relatively low temperatures (in the range 10–25 °C), which is then heated up by decentralized heat pumps. Moreover, cold district heating networks are also very suitable for cooling delivery, since cold water supplying can be directly used for cooling purposes (i.e., free cooling) or to feed decentralized chillers with very high energy efficiency ratio. This paper provides a preliminary literature review of existing cold district heating networks and then qualitatively analyses benefits and drawbacks in comparison with the alternatives currently used to produce heat and cold at district level, including the evaluation of major barriers to its further development. Full article
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Open AccessArticle Sensorless Speed Control Based on the Improved Q-MRAS Method for Induction Motor Drives
Energies 2018, 11(1), 235; https://doi.org/10.3390/en11010235
Received: 20 December 2017 / Revised: 9 January 2018 / Accepted: 11 January 2018 / Published: 19 January 2018
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Abstract
For high-power and high-performance speed control system, speed feedback signals are generally required. The employment of sensorless control technology makes the installation of the system easier and lower-cost, while its reliability needs to be improved. The robustness of the improved instantaneous reactive power
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For high-power and high-performance speed control system, speed feedback signals are generally required. The employment of sensorless control technology makes the installation of the system easier and lower-cost, while its reliability needs to be improved. The robustness of the improved instantaneous reactive power based on the quadrature model reference adaptive system (MRAS) with respect to the variation of the motor inductance parameter is improved by selecting the appropriate reference model and adjustable model. The improved instantaneous reactive power (Q) based on model reference adaptive system (Q-MRAS) algorithm is studied by small signal analysis, and the stability of the control system is verified by the Routh Stability Criterion. The simulation models and experimental platform for the proposed control are built in the laboratory. The feasibility and superiority are verified by the corresponding simulation and experimental results. Full article
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Open AccessFeature PaperArticle Linking of Barriers to Energy Efficiency Improvement in Indonesia’s Steel Industry
Energies 2018, 11(1), 234; https://doi.org/10.3390/en11010234
Received: 16 November 2017 / Revised: 21 December 2017 / Accepted: 28 December 2017 / Published: 18 January 2018
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Abstract
Energy use in Indonesia’s steel industry accounts for about 20–35% of total production costs. Consequently, energy end-use efficiency is a crucial measure that is used to reduce energy intensity and decrease production costs. This article aims to investigate the relationships among different barriers
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Energy use in Indonesia’s steel industry accounts for about 20–35% of total production costs. Consequently, energy end-use efficiency is a crucial measure that is used to reduce energy intensity and decrease production costs. This article aims to investigate the relationships among different barriers to energy efficiency improvement (EEI), using a framework with the following six constructs: government policy, the financial–economic factor, the managerial–organizational factor, the technological factor, workforce, and quality and type of feedstock and fuel used. The data were collected from steel firm practitioners in Indonesia, using a questionnaire to test our framework. The results demonstrate that the applied framework was applicable. We find that EEI is moderately influenced by all constructs but that the managerial–organizational factor has the greatest direct effect on improvements and is the most significant factor. Full article
(This article belongs to the Special Issue Sustainable and Renewable Energy Systems)
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Open AccessArticle Data Analysis of Heating Systems for Buildings—A Tool for Energy Planning, Policies and Systems Simulation
Energies 2018, 11(1), 233; https://doi.org/10.3390/en11010233
Received: 6 December 2017 / Revised: 9 January 2018 / Accepted: 16 January 2018 / Published: 18 January 2018
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Abstract
Heating and cooling in buildings is a central aspect for adopting energy efficiency measures and implementing local policies for energy planning. The knowledge of features and performance of those existing systems is fundamental to conceiving realistic energy savings strategies. Thanks to Information and
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Heating and cooling in buildings is a central aspect for adopting energy efficiency measures and implementing local policies for energy planning. The knowledge of features and performance of those existing systems is fundamental to conceiving realistic energy savings strategies. Thanks to Information and Communication Technologies (ICT) development and energy regulations’ progress, the amount of data able to be collected and processed allows detailed analyses on entire regions or even countries. However, big data need to be handled through proper analyses, to identify and highlight the main trends by selecting the most significant information. To do so, careful attention must be paid to data collection and preprocessing, for ensuring the coherence of the associated analyses and the accuracy of results and discussion. This work presents an insightful analysis on building heating systems of the most populated Italian region—Lombardy. From a dataset of almost 2.9 million of heating systems, selected reference values are presented, aiming at describing the features of current heating systems in households, offices and public buildings. Several aspects are considered, including the type of heating systems, their thermal power, fuels, age, nominal and measured efficiency. The results of this work can be a support for local energy planners and policy makers, and for a more accurate simulation of existing energy systems in buildings. Full article
(This article belongs to the Special Issue Energy Production Systems)
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Open AccessArticle An Intelligent Fault Diagnosis Method for Bogie Bearings of Metro Vehicles Based on Weighted Improved D-S Evidence Theory
Energies 2018, 11(1), 232; https://doi.org/10.3390/en11010232
Received: 26 December 2017 / Revised: 14 January 2018 / Accepted: 15 January 2018 / Published: 18 January 2018
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Abstract
Bogie bearings are very important for the safe and normal operation of metro vehicles. The prevailing fault diagnosis methods for bogie bearings generally utilize a single information source, such as vibration, temperature or acoustics. There are some shortcomings in these methods, including low
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Bogie bearings are very important for the safe and normal operation of metro vehicles. The prevailing fault diagnosis methods for bogie bearings generally utilize a single information source, such as vibration, temperature or acoustics. There are some shortcomings in these methods, including low accuracy and poor reliability. To address these shortcomings, this paper proposes an intelligent fault diagnosis method. Based on improved D-S (Dempster-Shafer) evidence theory, this method comprehensively analyzes vibration and temperature signals to diagnose bearing faults. In order to verify the feasibility and effectiveness of the proposed method, this study designed the hardware device and constructed a test platform. Bogie bearings with faults occurring on the outer ring, inner ring and rolling elements were tested on this platform. The diagnosis accuracy rate of the proposed fusion algorithm reached 91%, and the misdiagnosis rate was only 2%. The test results showed that the proposed method can accurately and reliably realize fault diagnosis with a high accuracy rate and a low misdiagnosis rate compared to previous methods. Thus, the proposed fault diagnosis method can accurately and effectively identify the faults of metro vehicle bogie bearings. Full article
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Open AccessEditorial Acknowledgement to Reviewers of Energies in 2017
Energies 2018, 11(1), 231; https://doi.org/10.3390/en11010231
Received: 18 January 2018 / Revised: 18 January 2018 / Accepted: 18 January 2018 / Published: 18 January 2018
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Abstract
Peer review is an essential part in the publication process, ensuring that Energies maintains high quality standards for its published papers [...]
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Open AccessArticle Modelling and Simulation of a Hydrostatic Steering System for Agricultural Tractors
Energies 2018, 11(1), 230; https://doi.org/10.3390/en11010230
Received: 6 December 2017 / Revised: 10 January 2018 / Accepted: 12 January 2018 / Published: 18 January 2018
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Abstract
The steering system of a vehicle impacts on the vehicle performance, safety and on the driver’s comfort. Moreover, in off-road vehicles using hydrostatic steering systems, the energy dissipation also becomes a critical issue. These aspects push and motivate innovation, research and analysis in
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The steering system of a vehicle impacts on the vehicle performance, safety and on the driver’s comfort. Moreover, in off-road vehicles using hydrostatic steering systems, the energy dissipation also becomes a critical issue. These aspects push and motivate innovation, research and analysis in the field of agricultural tractors. This paper proposes the modelling and analysis of a hydrostatic steering system for an agricultural tractor to calculate the performance of the system and determine the influence of its main design parameters. The focus here is on the driver’s steering feel, which can improve the driver’s behavior reducing unnecessary steering corrections during the working conditions. The hydrostatic steering system is quite complex and involves a hydraulic circuit and a mechanical mechanism to transmit the steering to the vehicle tires. The detailed lumped parameters model here proposed allows to simulate the dynamic behavior of the steering system and to both enhance the understanding of the system and to improve the design through parameters sensitivity analysis. Full article
(This article belongs to the Section Energy Fundamentals and Conversion)
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Open AccessArticle A Bi-Level Optimization Approach to Charging Load Regulation of Electric Vehicle Fast Charging Stations Based on a Battery Energy Storage System
Energies 2018, 11(1), 229; https://doi.org/10.3390/en11010229
Received: 20 December 2017 / Revised: 13 January 2018 / Accepted: 15 January 2018 / Published: 18 January 2018
Cited by 3 | PDF Full-text (4094 KB) | HTML Full-text | XML Full-text
Abstract
Fast charging stations enable the high-powered rapid recharging of electric vehicles. However, these stations also face challenges due to power fluctuations, high peak loads, and low load factors, affecting the reliable and economic operation of charging stations and distribution networks. This paper introduces
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Fast charging stations enable the high-powered rapid recharging of electric vehicles. However, these stations also face challenges due to power fluctuations, high peak loads, and low load factors, affecting the reliable and economic operation of charging stations and distribution networks. This paper introduces a battery energy storage system (BESS) for charging load control, which is a more user-friendly approach and is more robust to perturbations. With the goals of peak-shaving, total electricity cost reduction, and minimization of variation in the state-of-charge (SOC) range, a BESS-based bi-level optimization strategy for the charging load regulation of fast charging stations is proposed in this paper. At the first level, a day-ahead optimization strategy generates the optimal planned load curve and the deviation band to be used as a reference for ensuring multiple control objectives through linear programming, and even for avoiding control failure caused by insufficient BESS energy. Based on this day-ahead optimal plan, at a second level, real-time rolling optimization converts the control process to a multistage decision-making problem. The predictive control-based real-time rolling optimization strategy in the proposed model was used to achieve the above control objectives and maintain battery life. Finally, through a horizontal comparison of two control approaches in each case study, and a longitudinal comparison of the control robustness against different degrees of load disturbances in three cases, the results indicated that the proposed control strategy was able to significantly improve the charging load characteristics, even with large disturbances. Meanwhile, the proposed approach ensures the least amount of variation in the range of battery SOC and reduces the total electricity cost, which will be of a considerable benefit to station operators. Full article
(This article belongs to the Special Issue The International Symposium on Electric Vehicles (ISEV2017))
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Open AccessArticle How Do Chinese Residents Expect of Government Subsidies on Solar Photovoltaic Power Generation?—A Case of Wuhan, China
Energies 2018, 11(1), 228; https://doi.org/10.3390/en11010228
Received: 4 December 2017 / Revised: 9 January 2018 / Accepted: 16 January 2018 / Published: 18 January 2018
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Abstract
This paper investigates local residents’ expectations of the Chinese government subsidies on solar photovoltaic (PV) power generation. Residents’ demographics including age, educational attainment, income level, gender, and employment fields are analyzed based on a survey study in Wuhan, China. Results of the regression
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This paper investigates local residents’ expectations of the Chinese government subsidies on solar photovoltaic (PV) power generation. Residents’ demographics including age, educational attainment, income level, gender, and employment fields are analyzed based on a survey study in Wuhan, China. Results of the regression analysis on the influence of demographic variables on residents’ expectations indicate that: (1) residents with different demographics have significantly different expectations of the Chinese government subsidies for adopting PV power generation facilities; (2) income, education attainment, and residents’ employment fields have a significant impact on their expectations of government subsidies. With these findings, this paper concludes with useful policy implications. Full article
(This article belongs to the Special Issue Solar Energy Harvesting, Storage and Utilization)
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