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1.
This article investigates charging strategies for plug‐in hybrid electric vehicles (PHEV) as part of the energy system. The objective was to increase the combined all‐electric mileage (total distance driven using only the traction batteries in each PHEV) when the total charging power at each workplace is subject to severe limitations imposed by the energy system. In order to allocate this power optimally, different input variables, such as state‐of‐charge, battery size, travel distance, and parking time, were considered. The required vehicle mobility was generated using a novel agent‐based model that describes the spatiotemporal movement of individual PHEVs. The results show that, in the case of Helsinki (Finland), smart control strategies could lead to an increase of over 5% in the all‐electric mileage compared to a no‐control strategy. With a high prediction error, or with a particularly small or large battery, the benefits of smart charging fade off. Smart PHEV charging strategies, when applied to the optimal allocation of limited charging power between the cars of a vehicle fleet, seem counterintuitively to provide only a modest increase in the all‐electric mileage. A simple charging strategy based on allocating power to PHEVs equally could thus perform sufficiently well. This finding may be important for the future planning of smart grids as limiting the charging power of larger PHEV fleets will sometimes be necessary as a result of grid restrictions. Copyright © 2013 John Wiley & Sons, Ltd. 相似文献
2.
Superconducting magnetic energy storage (SMES) is known to be an excellent high‐efficient energy storage device. This article is focussed on various potential applications of the SMES technology in electrical power and energy systems. SMES device founds various applications, such as in microgrids, plug‐in hybrid electrical vehicles, renewable energy sources that include wind energy and photovoltaic systems, low‐voltage direct current power system, medium‐voltage direct current and alternating current power systems, fuel cell technologies and battery energy storage systems. An extensive bibliography is presented on these applications of SMES. Also, some conclusive remarks in terms of future perspective are presented. Also, the present ongoing developments and constructions are also discussed. This study provides a basic guideline to investigate further technological development and new applications of SMES, and thus benefits the readers, researchers, engineers and academicians who deal with the research works in the area of SMES. Copyright © 2017 John Wiley & Sons, Ltd. 相似文献
3.
Mass roll‐out of plug‐in hybrid electric vehicles (PHEVs) and significant penetration of renewable energy sources in distribution system play a major role in delivering low carbon environment. However, placing and utilizing these units randomly result in overloading, increased power loss, and reduced voltage profile. This paper responds to these technical challenges by using a strategic placement method for locating the distributed generation (DG) and the charging station (CS) of PHEVs in a multi‐zone distribution system. For simultaneously scheduling of these units in each zone, the smart energy management framework is proposed in this paper. Apart from usual energy management constraints, this paper also incorporates the real‐time constraints involving the capacity of PHEV batteries, the mobility pattern, and the power level of the charging infrastructure. The simulation studies are carried out for each hour of a day. To cope with this time constraint execution, particle swarm optimization algorithm‐based approach is used. The proposed framework is tested in IEEE 33 and IEEE 69 bus radial distribution system. The obtained results imply that the presented energy management framework provides maximum profits for the vehicle owner, and meanwhile it fulfills preferences of the user in each zone simultaneously. 相似文献
4.
In this study we explore the effects of different charging behaviors of PHEVs in the United States on electricity demand profiles and energy use, in terms of time of day and location (at home, the workplace, or public areas). Based on driving behavior statistics on vehicle distance traveled and daily trips (US DOT, 2003) in the US, we develop a simulation algorithm to estimate the PHEV charging profiles of electricity demand with plausible plug-in times and depth of discharge of the PHEVs. 相似文献
5.
Guihua Wang 《Journal of power sources》2011,196(1):530-540
Advanced vehicles and alternative fuels could play an important role in reducing oil use and changing the economy structure. We developed the Costs for Advanced Vehicles and Energy (CAVE) model to investigate a vehicle portfolio scenario in California during 2010-2030. Then we employed a computable general equilibrium model to estimate macroeconomic impacts of the advanced vehicle scenario on the economy of California. Results indicate that, due to slow fleet turnover, conventional vehicles are expected to continue to dominate the on-road fleet and gasoline is the major transportation fuel over the next two decades. However, alternative fuels could play an increasingly important role in gasoline displacement. Advanced vehicle costs are expected to decrease dramatically with production volume and technological progress; e.g., incremental costs for fuel cell vehicles and hydrogen could break even with gasoline savings in 2028. Overall, the vehicle portfolio scenario is estimated to have a slightly negative influence on California's economy, because advanced vehicles are very costly and, therefore, the resulting gasoline savings generally cannot offset the high incremental expenditure on vehicles and alternative fuels. Sensitivity analysis shows that an increase in gasoline price or a drop in alternative fuel prices could offset a portion of the negative impact. 相似文献
6.
Management of plug‐in hybrid electric vehicles (PHEVs) is an important alternative energy solution to accord the prevailing environmental depletion. However, adding PHEVs to the existing distribution network may stimulate issues such as increase in peak load, power loss, and voltage deviation. Addressing the aforementioned issues by incorporating distinct mobility patterns together will develop an attractive energy management. In this paper, suitable location of the charging station is presented for a novel 2‐area distribution system following distinct mobility patterns. A comprehensive study by considering the optimal, midst, and unfit site for placing the charging station is incorporated. For managing the charging sequence of PHEVs, a meta‐heuristic solving tool is developed. The main contribution of this programming model is its ability to schedule the vehicles simultaneously in both the areas. The efficiency of the proposed energy management framework is evaluated on the IEEE 33‐bus and IEEE 69‐bus distribution systems. The test system is subjected to different scenarios for demonstrating the superior performance of the proposed solving tool in satisfying the convenience of vehicle owner along with reducing the peak demand. The results show that charging at low electricity price period and discharging at high electricity price period enables the minimum operational cost. 相似文献
7.
Bernd Propfe Danny Kreyenberg Joerg Wind Stephan Schmid 《International Journal of Hydrogen Energy》2013
There is currently intensive public discussion of fuel cell electric vehicles (FCEV) and other electric powertrains, such as battery electric vehicles (BEV), plug-in hybrid electric vehicles (PHEV) and hybridized combustion engine vehicles (HEV). In this context, the German government has set the target of one million electric vehicles on the road by 2020, and six million by 2030 [1]. The goal of this paper is to identify the possible market share of electric vehicles in the German new car fleet in three scenarios in the timeframe from 2010 to 2030. The VECTOR21 vehicle technology scenario model is used to model the fleet in three scenarios. In the reference scenario with business-as-usual parameters, 189,000 electric vehicles will be sold in Germany by 2020. Scenario two with purchase price incentives from 5000 EUR, high oil prices, and low prices for hydrogen and electricity will result in 727,000 vehicles. In the last scenario with substantial OEM mark-up reductions and external conditions as in the business-as-usual scenario, 3.28 million vehicles will be sold. 相似文献
8.
The battery electric vehicle is evolving and has the potential to replace conventional internal combustion‐based vehicles in the future. Batteries are the major power source of these vehicles. A thermal management system is required for a battery to attain effective operation and long life in all environmental conditions. Although several types of thermal management system are available, there remains a need to address various issues like high power consumption, narrow optimum temperature range and operation in varying climates. Phase change materials can assist in resolving these issues. In this paper, battery thermal management systems for electric and hybrid electric vehicles are reviewed, and challenges and opportunities for battery electric vehicles are discussed. Cooling strategies used in various thermal management systems are explained. Applications of and issues regarding the use of phase change materials in thermal management systems are also reviewed. Potential bottlenecks that need to be addressed in electric vehicle technology are explained, as are important achievement milestones and trends regarding the growth of the electric vehicle industry. It is shown that using graphite can increase thermal conductivity of PCMs by up to 70 W m‐ 1K‐ 1. Some commercially available passive thermal management systems for batteries use wax and graphite, which can increase the driving range of an electric scooter from 30 km to 55 km. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献
9.
The universal adaptive equivalent consumption minimization strategy (A‐ECMS) has the potential of being implemented in real‐time for plug‐in hybrid electric vehicles (PHEVs). However, the imprecise prediction of a long‐term future driving cycle and biggish computation burdens remain the barriers for further real vehicle application. Thus, it is of great significance to develop a real‐time optimal energy management strategy for PHEVs by weakening the influence of future driving cycle to the control accuracy and improving its computation efficiency. In this paper, a novel real‐time energy management strategy for PHEVs based on equivalence factor (EF) dynamic optimization method is proposed. Firstly, a novel proportional plus integral adaption law for calculating the dynamic optimal EF is established for A‐ECMS using only instantaneous information of current vehicle speed and battery state of charge. Second, three key coefficients are obtained and converted into a three‐dimensional look up tables, so as to determine the dynamic optimal EF. Finally, the method of fast searching the optimal engine torque is proposed, which significantly enhances the computational efficiency. Compared with A‐ECMS, the computational time of A‐ECMS2 is decreased near 94.8% and the deviation of fuel consumption is controlled within 4.4%. Both the numerical results and hardware‐in‐loop results prove that the proposed novel energy management strategy A‐ECMS2 has better real‐time performance and less computing burden than the general A‐ECMS. 相似文献
10.
Andrei Marinescu Adam Taylor Siobhn Clarke Ioan Serban Corneliu Marinescu 《国际能源研究杂志》2019,43(8):3853-3868
The integration of intermittent renewable energy sources coupled with the increasing demand of electric vehicles (EVs) poses new challenges to the electrical grid. To address this, many solutions based on demand response have been presented. These solutions are typically tested only in software‐based simulations. In this paper, we present the application in hardware‐in‐the‐loop (HIL) of a recently proposed algorithm for decentralised EV charging, prediction‐based multi‐agent reinforcement learning (P‐MARL), to the problem of optimal EV residential charging under intermittent wind power and variable household baseload demands. P‐MARL is an approach that can address EV charging objectives in a demand response aware manner, to avoid peak power usage while maximising the exploitation of renewable energy sources. We first train and test our algorithm in a residential neighbourhood scenario using GridLAB‐D, a software power network simulator. Once agents learn optimal behaviour for EV charging while avoiding peak power demand in the software simulator, we port our solution to HIL while emulating the same scenario, in order to decrease the effects of agent learning on power networks. Experimental results carried out in a laboratory microgrid show that our approach makes full use of the available wind power, and smooths grid demand while charging EVs for their next day's trip, achieving a peak‐to‐average ration of 1.67, down from 2.24 in the baseline case. We also provide an analysis of the additional demand response effects observed in HIL, such as voltage drops and transients, which can impact the grid and are not observable in the GridLAB‐D software simulation. 相似文献
11.
Mahmoud Abdelhamid Srikanth Pilla Rajendra Singh Imtiaz Haque Zoran Filipi 《国际能源研究杂志》2016,40(11):1489-1508
Environmental concerns along with high energy demand in transportation are leading to major development in sustainable transportation technologies, not the least of which is the utilization of clean energy sources. Solar energy as an auxiliary power source of on‐board fuel has not been extensively investigated. This study focuses on the energy and economic aspects of optimizing and hybridizing, the conventional energy path of plug‐in electric vehicles (EVs) using solar energy by means of on‐board photovoltaic (PV) system as an auxiliary fuel source. This study is novel in that the authors (i) modeled the comprehensive on‐board PV system for plug‐in EV; (ii) optimized various design parameters for optimum well‐to‐tank efficiency (solar energy to battery bank); (iii) estimated hybrid solar plug‐in EVs energy generation and consumption, as well as pure solar PV daily range extender; and (iv) estimated the economic return of investment (ROI) value of adding on‐board PVs for plug‐in EVs under different cost scenarios, driving locations, and vehicle specifications. For this study, two months in two US cities were selected, which represent the extremities in terms of available solar energy; June in Phoenix, Arizona and December in Boston, Massachusetts to represent the driving conditions in all the US states at any time followed by assessment of the results worldwide. The results show that, by adding on‐board PVs to cover less than 50% (around 3.2 m2) of the projected horizontal surface area of a typical passenger EV, the daily driving range could be extended from 3.0 miles to 62.5 miles by solar energy based on vehicle specifications, locations, season, and total time the EV remains at Sun. In addition, the ROI of adding PVs on‐board with EV over its lifetime shows only small negative values (larger than ?45%) when the price of electricity remains below Environmental concerns along with high energy demand in transportation are leading to major development in sustainable transportation technologies, not the least of which is the utilization of clean energy sources. Solar energy as an auxiliary power source of on‐board fuel has not been extensively investigated. This study focuses on the energy and economic aspects of optimizing and hybridizing, the conventional energy path of plug‐in electric vehicles (EVs) using solar energy by means of on‐board photovoltaic (PV) system as an auxiliary fuel source. This study is novel in that the authors (i) modeled the comprehensive on‐board PV system for plug‐in EV; (ii) optimized various design parameters for optimum well‐to‐tank efficiency (solar energy to battery bank); (iii) estimated hybrid solar plug‐in EVs energy generation and consumption, as well as pure solar PV daily range extender; and (iv) estimated the economic return of investment (ROI) value of adding on‐board PVs for plug‐in EVs under different cost scenarios, driving locations, and vehicle specifications. For this study, two months in two US cities were selected, which represent the extremities in terms of available solar energy; June in Phoenix, Arizona and December in Boston, Massachusetts to represent the driving conditions in all the US states at any time followed by assessment of the results worldwide. The results show that, by adding on‐board PVs to cover less than 50% (around 3.2 m2) of the projected horizontal surface area of a typical passenger EV, the daily driving range could be extended from 3.0 miles to 62.5 miles by solar energy based on vehicle specifications, locations, season, and total time the EV remains at Sun. In addition, the ROI of adding PVs on‐board with EV over its lifetime shows only small negative values (larger than ?45%) when the price of electricity remains below $0.18/kWh and the vehicle is driven in low‐solar energy area (e.g. Massachusetts in the US and majority of Europe countries). The ROI is more than 148% if the vehicle is driven in high‐solar energy area (e.g. Arizona in the US, most Africa countries, Middle East, and Mumbai in India), even if the electricity price remains low. For high electricity price regions ($0.35/kWh), the ROI is positive and high under all driving scenarios (above 560%). Also, the reported system has the potential to reduce electricity consumption from grid by around 4.5 to 21.0 MWh per EV lifetime. A sensitivity analysis has been carried out, in order to study the impacts of the car parked in the shade on the results. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献
12.
In order to accommodate additional plug‐in electric vehicle (PEV) charging loads for existing distribution power grids, the vehicle‐to‐grid (V2G) technology has been regarded as a cost‐effective solution. Nevertheless, it can hardly scale up to large PEVs fleet coordination due to the computational complexity issue. In this paper, a centralized V2G scheme with distributed computing capability engaging internet of smart charging points (ISCP) is proposed. Within ISCP, each smart charging point equips a computing unit and does not upload PEV sensitive information to the energy coordinator, to protect PEV users’ privacy. Particularly, the computational complexity can be decreased dramatically by employing distributed computing, viz., by decomposing the overall scheduling problem into many manageable sub‐problems. Moreover, six typical V2G scenarios are analyzed deliberately, and based on that, a load peak‐shaving and valley‐filling scheduling algorithm is built up. The proposed algorithm can be conducted in real‐time to mitigate the uncertainties in arrival time, departure time, and energy demand. Finally, the proposed scheme and its algorithm are verified under the distribution grid of the SUSTech campus (China). Compared with uncoordinated charging, the proposed scheme realizes load peak‐shaving and valley‐filling by 11.98% and 12.68%, respectively. The voltage values are ensured within the limitation range by engaging power flow calculation, in which the minimum voltage values are increasing and the maximum voltage values are decreasing with the expansion of PEV penetration. What is more, the computational complexity of peak‐shaving and valley‐filling strategy is near‐linear, which verifies the proposed scheme can be carried out very efficiently. 相似文献
13.
作为智能电网建设的内容之一,智能自动电压控制(smart AVC)面临着同样的建设需要。电网智能AVC系统(S10)在对电压安全、经济和优质的多目标协调控制下,用于在线电压无功优化分析计算与闭环控制。S10系统已在泸州电网投入使用。该系统通过对电网的数据采集分析,智能生成并执行相应的控制策略,满足泸州地区电压无功在线实时控制的需要。S10系统提高了电压合格率又降低网损,大幅度减少有载调压变压器的分接头调节次数,在电网的无功潮流优化、数据信息配置、故障智能分析等方面均取得了很好的效果。 相似文献
14.
Nadia Adnan Shahrina Md Nordin Imran Rahman Pandian M. Vasant Amir Noor 《国际能源研究杂志》2017,41(3):317-335
Green vehicles, such as electric vehicles (EVs), are getting noteworthy popularity among consumers worldwide. The purpose of this paper is to establish EVs as a feasible long‐term solution for the future of technology in the vehicle industry, which can decrease the current dependency on fossil fuels and also decrease greenhouse gas (GHG) emissions. As a part of long‐term benefits, the adoption of EVs gives environmentally friendly innovation to society. Despite positive environmental implications, the total number of EVs in usage is still inadequate. One of the major causes of this insubstantial adoption of EVs is largely dependent on the perceptions of consumers regarding EVs. However, this particular research study offers an inclusive outline on the existing hurdles for consumer adoption of EVs as well as a framework of the theoretical standpoints that were developed for the adoption behaviour, in addition to considering consumer intentions in the direction of EVs. In this particular study, the researcher found that the literature regarding EV adoption tried to address only the diffusion method of EVs. Whereas this study highlights consumer innovations, which provides a wide insight on consumer emotions to overlook the major aspect in consumer EVs' adoption research. The theme of this particular literature can be implemented in order to better understand the consumers' emotions and behaviour towards the adoption of EVs. The scholars further stated that there is a possible cause for more recent developments within the technological adoption part that can assist to be a standard for upcoming developments. For the last few years, knowledge regarding the problems surrounding the adoption and diffusion of EVs has gained less attention. This study expands this line of research by focusing on making a chance for developing the theoretical frameworks in terms of adding emotions in a psychological perspective where consumer behaviour and ethics are considered. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献
15.
An optimal operation method in smart‐energy houses with photovoltaics (PV) and a storage battery was investigated in a trial production system. In this method, the inverse current of the PV output is not conveyed to the commercial electricity system as operation conditions. Instead, the excess of the consumed PV power is applied to leveling the electricity purchase by appropriately charging and discharging the storage battery. To validate the proposed system, a lithium battery (4 kWh) and PV cell (3 kW) used in average individual houses was installed in a smart‐energy house in a local city (Kitami) in Japan. Another example was introduced into a wider area (Hokkaido, Japan). Accounting for the error between the weather forecast and actual solar radiation, the trial production system reduced the range in the electricity purchase amount by 75.0%, 77.0%, and 73.0% on a representative day in January, April, and July, respectively. The accuracy of the reduction effect in the trial production system, obtained in the proposed optimization analysis, ranged from 1.9% to 7.2%. Moreover, the CO2 emissions were reduced by 1.990 kg‐CO2/(Day‐House) in January, 2.910 kg‐CO2/(Day‐House) in April, and 2.210 kg‐CO2/(Day‐House) in July. 相似文献
16.
A worldwide shift headed for a greener and low emissions will necessitate remarkable advancement in the way in which the energy is being produced and used. The factors such as climate changes induced by pollution, progressively more strict emissions norms for vehicles, depletion of petrol/diesel along with instability in their prices for transportation systems, play a vital role in the improvisation of technology involved in conventional vehicles. The hybrid electric vehicles (HEVs) are on the peak of the list of choices available for clean vehicle technologies. The various architectures of HEV, different methodologies of hybrid vehicle, are focused in this paper. The design criteria and optimization techniques with reference to the driving cycle is also elucidated. The various electric drives used for HEV are discussed in this paper. Also, the different electric propulsion systems are explained. To improve the fuel economy and emission of hybrid power system, control strategies are very significant. Researchers concentrate in optimizing the performance of HEV. 相似文献
17.
Bri‐Mathias S. Hodge Shisheng Huang Aviral Shukla Joseph F. Pekny Venkat Venkatasubramanian Gintaras V. Reklaitis 《风能》2012,15(7):903-914
Renewable energy portfolio standards have created a large increase in the amount of renewable electricity production, and one technology that has benefited greatly from these standards is wind power. The uncertainty inherent in wind electricity production dictates that additional amounts of conventional generation resources be kept in reserve, should wind electricity output suddenly dip. The introduction of plug‐in hybrid electric vehicles into the transportation fleet presents an possible solution to this problem through the concept of vehicle‐to‐grid power. The ability of vehicle‐to‐grid power systems to help solve the variability and uncertainty issuess in systems with large amounts of wind power capacity is examined through a multiparadigm simulation model. The problem is examined from the perspectives of three different stakeholders: policy makers, the electricity system operator and plug‐in hybrid electric vehicle owners. Additionally, a preliminary economic analysis of the technology is performed, and a comparison made with generation technologies that perform similar functions. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
18.
This paper investigates a new operation strategy for photovoltaic (PV) systems, which improves the overall reliability of the system as a result of the improvement in the reliability of the critical components. First, a mathematical model is proposed using the fault tree analysis (FTA) to estimate the reliability of the PV systems in order to find the suitable maintenance strategies. The implementations demonstrate that it is essential to employ smart maintenance plans and monitor the identified most critical components of PV systems. Then, an innovative analytical method based on the Markov process is presented to model smart operation plans in PV systems. The impact of smart operation strategy on the PV systems is then evaluated. The objective of this paper is to develop plans for improving the reliability of PV systems. A series of case studies have been conducted to demonstrate the importance of smart operation strategies for PV systems as well as the applicability and feasibility of the proposed method. 相似文献
19.
储能技术是突破可再生能源大规模开发利用瓶颈的关键技术,是智能电网的必要组成部分.在储能市场商业化雏形阶段,系统性的比较分析各类储能技术的性能特点,为未来市场发展提供筛选技术路线的框架基础至关重要.本文阐述了储能技术在可再生能源发电和智能电网中的作用,对物理储能(抽水蓄能,压缩空气储能,飞轮储能),电化学储能(二次电池,液流电池),其它化学储能(氢能,合成天然气)等储能技术进行了系统的比较与分析,最后提出储能技术的发展趋势. 相似文献
20.
This paper proposes a powertrain controller for a solar photovoltaic battery powered hybrid electric vehicle (HEV). The main objective of the proposed controller is to ensure better battery management, load regulation, and maximum power extraction whenever possible from the photovoltaic panels. The powertrain controller consists of two levels of controllers named lower level controllers and a high-level control algorithm. The lower level controllers are designed to perform individual tasks such as maximum power point tracking, battery charging, and load regulation. The perturb and observe based maximum power point tracking algorithm is used for extracting maximum power from solar photovoltaic panels while the battery charging controller is designed using a PI controller. A high-level control algorithm is then designed to switch between the lower level controllers based on different operating conditions such as high state of charge, low state of charge, maximum battery current, and heavy load by respecting the constraints formulated. The developed algorithm is evaluated using theoretical simulation and experimental studies. The simulation and experimental results are presented to validate the proposed technique. 相似文献