垂直轴风力发电机的设计【含CAD图纸和说明书】
收藏
资源目录
压缩包内文档预览：
编号：166715403
类型：共享资源
大小：1.96MB
格式：ZIP
上传时间：2021-11-21
上传人：机****料
认证信息
个人认证
高**（实名认证）
河南
IP属地：河南
50
积分
- 关 键 词：
-
含CAD图纸和说明书
垂直
风力发电机
设计
CAD
图纸
说明书
- 资源描述：
-
资源目录里展示的全都有预览可以查看的噢，，下载就有,,请放心下载，原稿可自行编辑修改=【QQ：11970985 可咨询交流】====================喜欢就充值下载吧。。。资源目录里展示的全都有，，下载后全都有,,请放心下载，原稿可自行编辑修改=【QQ：197216396 可咨询交流】====================
- 内容简介：
-
毕业设计（论文）外文翻译（原文）Capacity credit of wind power generation problems and solutionsPeople have used wind energy for thousands of years. The earliest known use of wind power is by the Egyptians some 5000 years ago, who used it to sail their boats from shore to shore on the Nile. Around 2000BC the first windmill was built in Babylon. Till now, people have used wind power generation to generate for so many years and the research on this field is keep moving all the time. People have found the huge potential on helping we to solve the energy crisis, so I want to just discuss one easy aspect on the wind power generation about its problems and the solutions.First, I will point out some basic concepts about wind power as the foundation of the further discussion. Wind power is the conversion of wind energy into a useful form of energy, such as using wind turbines to make electricity, windmills for mechanical power, windpumps for water pumping or drainage, or sails to propel ships. The total amount of economically extractable power available from the wind is considerably more than present human power use from all sources. Wind power, as an alternative to fossil fuels, is plentiful, renewable, widely distributed, clean, and produces no greenhouse gas emissions during operation, and the cost per unit of energy produced is similar to the cost for new coal and natural gas installations. A large wind farm may consist of several hundred individual wind turbines which are connected to the electric power transmission network. Offshore wind power can harness the better wind speeds that are available offshore compared to on land, so offshore wind powers contribution in terms of electricity supplied is higher. Small onshore wind facilities are used to provide electricity to isolated locations and utility companies increasingly buy back surplus electricity produced by small domestic wind turbines. The construction of wind farms is not universally welcomed, but any effects on the environment from wind power are generally much less problematic than those of any other power source. A wind farm is a group of wind turbines in the same location used for production of electric power. A large wind farm may consist of several hundred individual wind turbines, and cover an extended area of hundreds of square miles, but the land between the turbines may be used for agricultural or other purposes. A wind farm may also be located offshore.In a wind farm, individual turbines are interconnected with a medium voltage (often 34.5 kV), power collection system and communications network. At a substation, this medium-voltage electric current is increased in voltage with a transformer for connection to the high voltage electric power transmission system.The surplus power produced by domestic micro-generators can, in some jurisdictions, be fed into the network and sold to the utility company, producing a retail credit for the micro-generators owners to offset their energy costs.Electricity generated from wind power can be highly variable at several different timescales: from hour to hour, daily, and seasonally. Annual variation also exists, but is not as significant. Related to variability is the short-term (hourly or daily) predictability of wind plant output. Like other electricity sources, wind energy must be scheduled. Wind power forecasting methods are used, but predictability of wind plant output remains low for short-term operation.Because instantaneous electrical generation and consumption must remain in balance to maintain grid stability, this variability can present substantial challenges to incorporating large amounts of wind power into a grid system. Intermittency and the non-dispatchable nature of wind energy production can raise costs for regulation, incremental operating reserve, and (at high penetration levels) could require an increase in the already existing energy demand management, load shedding, or storage solutions or system interconnection with HVDC cables. At low levels of wind penetration, fluctuations in load and allowance for failure of large generating units require reserve capacity that can also regulate for variability of wind generation. Wind power can be replaced by other power stations during low wind periods. Transmission networks must already cope with outages of generation plant and daily changes in electrical demand. Systems with large wind capacity components may need more spinning reserve. After knowing about some basic aspects, we have a relatively clear concept in many ways, such as wind farms, electricity generation, variability and intermittency. So next, I will discuss the topic of this thesis, Capacity Credit. The capacity credit of wind power in a grid has received quite some attention in the past. In the early days of wind power, the capacity credit, or rather the perceived lack thereof, was a grave concern for the large-scale development of wind power on a nation-wide basis. Therefore, a number of studies were made since the 1970ies, arriving at the conclusion that wind power has a capacity credit and the capacity credit is around the mean wind power output for small penetrations of wind power in the grid, and drops to a value near the minimum wind power generation for larger penetrations. The value of wind energy has traditionally been assessed by a comparison of wind power output characteristics to those of conventional power plants. This reflects the cost-based planning paradigm of the regulated electricity market. The standard of measure of the comparison is the availability of both plant types. Forced outage rates of conventional plants and wind availability captured by the probability distributions of wind speed are aggregated to a cumulative availability function using reliability models. An acceptable loss of load probability determines the maximum load. On this basis capacity credit is calculated as an “equivalent capacity” of wind generators to conventional generators with respect to reliability. As available wind energy varies over time, capacity credit changes as well. Therefore the capacity credit in time of peak demand is generally used for further interpretation. Consequently, a high correlation between wind energy production and electricity demand would result in a high capacity credit assigned to wind generators.An intermittent energy source is any source of energy that is not continuously available due to some factor outside direct control. The intermittent source may be quite predictable, for example, tidal power, but cannot be dispatched to meet the demand of a power system. An example of intermittent sources is the wind.The concept that Capacity Credit of wind power is relativity newly so till now there is not a clear and agreed by all definition. Many researchers concentrate on whether or not wind has any capacity credit without defining what they mean by this and its relevance. Wind does have a capacity credit, using a widely accepted and meaningful definition, equal to about 20% of its rated output (but this figure varies depending on actual circumstances). This means that reserve capacity on a system equal in MW to 20% of added wind could be retired when such wind is added without affecting system security or robustness.UK academic commentator Graham Sinden, of Oxford University, argues that this issue of capacity credit is a red herring in that the value of wind generation is largely due to the value of displaced fuel-not any perceived capacity credit it being well understood by the wind energy proponents that conventional capacity will be retained to fill in during periods of low or no wind. The main value of wind, (in the UK, 5 times the capacity credit value) is its fuel and CO2 savings. Wind does not require any extra back-up, as is often wrongly claimed, since it uses the existing power stations, which are already built, as back-up, and which are started up during low wind periods, just as they are started up now, during the non availability of other conventional plant. More spinning reserve, of existing plant, is required, but this again is already built and has a low cost comparatively. The capacity factor of a power plant is the ratio of the electrical energy produced in a given period of time to the electrical energy that could have been produced at continuous maximum power operation during the same period. For a conventional fossil-fuel power station, the capacity factor is determined by planned maintenance downtime, unplanned equipment failure, and by shutdowns when the stations electricity is not needed. For wind and solar energy, power output is also determined by the availability of wind and sunlight. The maximum power output, or installed capacity, is a rather theoretical value that is rarely reached. It would be clearer to quote the mean power for solar and wind energy, but because peak power is more commonly quoted, its important to know the capacity factor as well, to make sense of the peak numbers.So after comprehending the capacity factor of windpower generation, we know thats the ratio between a wind farms average power output and its maximum or “nameplate” capacity. That ratio is usually between about 20% and 30%. That is, when averaged over a year, a wind farm produces about 20%30% as much energy as it would if it operated continuously at its maximum power output. But with research growing, there is another more advanced key operating parameter for wind power generation, its “capacity credit”. Whereas the capacity factor is a measure of the average output of a wind farm, the capacity credit is a measure of the worst case minimum output that can be relied on as a part of the total system capacity. The capacity credit is the “firm” capacity of a wind farm that can be counted on as a reliable contribution to the sum of all grid capacity. The capacity credit of wind, is estimated by determining the capacity of conventional plants displaced by wind power, whilst maintaining the same degree of system security, in other words an unchanged probability of failure to meet the reliability criteria for the system. Alternatively, it is estimated by determining the additional load that the system can carry when wind power is added, maintaining the same reliability level.For low wind energy penetrations levels, the relative capacity credit of wind power (that is firm capacity as a fraction of total installed wind power capacity) will be equal or close to the average production (load factor) during the period under consideration, which is usually the time of highest demand. For Northern European countries, this is winter time and the load factor is typically 2530 percent onshore and up to 50 per cent offshore. The load factor determining the capacity credit in general is higher than the average yearly load factor. With increasing penetration levels of wind energy in the system, its relative capacity credit reduces. However, this does not mean that less conventional capacity can be replaced, but rather that a new wind plant added to a system with high wind power penetration levels will substitute less than the first wind plants in the system. Put another way, the capacity credit of a wind farm is the amount by which other generating capacity (such as coal, for example) can be removed from the grid without compromising reliability of supply.Wind is unusual, however, in the unpredictability of its output. It doesnt have the fixed periodic variations of tidal or solar. This unpredictability of wind power makes the question of its capacity credit a rather complicated one.What, then, is the capacity credit of wind power? What is that minimum power capacity that a wind farm can reliably provide?Since a wind farms output can drop all the way to zero, it seems at first sight that the capacity credit of wind power must be zero. In fact thats not the case. It would be true if the wind farm operated in isolation, but a wind farm is usually connected to a much larger supply grid. Supply and demand across the grid vary all the time, and energy planners have developed detailed statistical calculations to handle this problem.They plan grid capacity so as to meet a given “loss of load probability”, or LOLP. The LOLP is the probability that generation will be insufficient to meet demand. Energy supply planners must ensure that there is sufficient capacity to keep the loss of load probability below some specified level, but they dont want to spend money needlessly on surplus capacity beyond that. One issue of managing risk is that wind farms can be treated statistically in exactly the same way as conventional power plant. For any type of power plant it is possible to calculate the probability of it not being able to supply the expected load. As wind is variable, the probability that it will not be available at any particular time is higher. Wind power can be factored into the grid reliability statistics in exactly the same way as every other power source. Wind has a lower probability of being available, but that number is simply fed into the calculations. There is nothing qualitatively different about wind. Energy engineers have taken a careful look at the statistics of wind supply, and their conclusion is that wind has a significant capacity credit after all.How can this be? After all, the wind speed can drop all the way to zero. To answer that, we have to look at the supply statistics across the entire electricity grid. For example, when wind power is geographically dispersed, it becomes less likely that the wind will stop blowing at all wind farm sites simultaneously. Thats not to say its impossible, but it is less likely. Also, when wind strength and electricity demand correlate (for example, in regions where the wind is stronger during the winter) there is again a higher likelihood that wind will contribute to that demand.After then, what are the actual numbers for the capacity credit of wind power?The capacity credit of wind depends on the fraction of total grid capacity that is met by wind power. In the jargon, it depends on the “penetration” of wind power on the grid.“Wind energy penetration” is generally defined as the ratio of the total amount of wind energy produced in a year to the total electrical energy produced in a year for a given region, while “wind capacity penetration” is defined as the ratio of installed wind power capacity to peak load for a given region.When the amount of wind capacity is a negligible fraction of the total grid capacity, the capacity credit of the wind farm can be treated as being equal to the average power of the wind farm. That is, the capacity credit is the same as the capacity factor multiplied by the installed capacity. Thats because at very low levels of wind penetration, the grid can deal with fluctuations in wind output as part of its routine capability.As wind capacity increases to about 10% of total grid capacity, the capacity credit falls to about 20% of the installed capacity (peak power) of the wind farm. That is, the capacity credit is now lower than the average power of the wind farm.If still more wind farms are built, so that wind capacity increases to well above 10% of grid capacity, then wind starts to form a very substantial part of total electricity supply. There is now less leeway elsewhere in the system, and the capacity credit falls further still, to about 10% of installed capacity. That is, each 1GW of installed wind capacity must be treated as only 100MW of “firm” capacity. Put another way, each 1GW of installed wind capacity allows 100MW of conventional (gas or coal) capacity to be removed from the grid, although that wind capacity supplies about 300MW of power on average (because it still has a 30% capacity factor).Since we have already known that the capacity credit of wind power generation can be quantificational, we will discuss how to calculate capacity credit of wind power generation.Power systems must have enough generation to meet demand at each moment of the day. In addition, they must also have enough reserve to deal with unexpected contingencies. The increase in the penetration of wind generation in recent years has led to a number of challenges in the calculations required to facilitate wind generation while maintaining the existing level of security of supply. A key calculation in this process is the capacity credit or value of wind generation. Capacity credit/value of wind generation can be broadly dened as the amount of rm conventional generation capacity that can be replaced with wind generation capacity, while maintaining the existing levels of security of supply.Power system reliability consists of system security and adequacy. A power system is adequate if there is a sufficient installed power supply to meet customer needs. A system is secure if it can withstand a loss (or potentially multiple losses) of key power supply components such as generators or transmission links. This paper focuses on the impact that wind generation has on generation adequacy. The analyses for generation adequacy are made several months or years ahead and associated with static conditions of the system. This can be studied by a chronological generation load model that can include transmission and distribution or by probabilistic methods. The estimation of the required production needs includes the system demand and the availability data of production units.Capacity credit is the contribution that a given generator makes to overall system adequacy. Even the availability of conventional generation is not assured at all times because there is always a nonzero risk of mechanical or electrical failure. Because reliability is expensive it is common to adopt a reliability target for the system. The capacity value of any generator is the amount of additional load that can be served at the target reliability level with the addition of the generator in question.Although there are several methods used to calculate wind capacity value, most methods are based on power system reliability analysis methods. The criteria that are used for the adequacy evaluation include the loss of load expectation (LOLE), the loss of load probability (LOLP) and the loss of energy expectation (LOEE), for instance. LOLP is the probability that the load will exceed the available generation at a given time. This criterion gives an idea of the possibility of system malfunction but it lacks information on the importance and duration of the outage. LOLE is the number of hours, usually per year, during which the load will not be met over a dened time period. One key capacity value metric is effective load carrying capability (ELCC). This metric is calculated by calculating a suitable reliability measure such as loss of load probability or loss of load expectation for the year.During the course of system operation through the year, generating units can be in one of several states. Units are scheduled for maintenance at regular intervals, and this is typically scheduled during noncritical system periods. However, it is always possible that any generator could fail unexpectedly at any time of the year. The unexpected nature of these forced outages is the primary concern and focus of reliability analysis.Contingency reserves (sometimes called disturbance re-serves) are provided to ensure against system collapse in the event of a forced outage. System adequacy assessments must take planned outages and forced outages into account, although the different types of outages are treated very differently in the reliability model. Additional considerations include hydro system operation, both run of river and reservoir hydro power (and pumped storage, if available). Other system services may also be quantied in the reliability model.While hourly load and wind generation proles for at least one year are essential prerequisites for wind power capacity credit calculations, a number of studies such as the DENA study have been exposed to a lack of load proles for the power system investigated. As an alternative, several of those studies used a probabilistic representation of wind generation for the capacity credit calculation (also called load duration curve method).The reliable capacity of the system including wind is determined by convolving the wind power probability density function with conventional power plant probabilities. In the studies, all installed wind power has been dened as one wind power unit. In order to determine the power probability function of this aggregated wind power block, it is again assumed that long term statistics on wind power avail ability deliver its probability to be available during hours of signicant system risk (high LOLP or equivalent). Reliability models look for periods of time with signicant risk. The capacity credit is calculated as the difference between the two reliability curves at the target risk level: the power system without and with wind energy.Weather inuences both electricity consumption and wind power generation. Although it may be difficult to directly calculate the statistical correlation between them, there are certainly complex interrelationships between wind and load. Even in cases with wind separated from load centre by relatively large distances, the weather correlation may consist of a complex lag structure that varies based on time and weather conditions. Because of this, it is critically important to use wind and load proles that result from a common weather driver to calculate wind capacity value. In a practical sense this means that at least one year of hourly wind generation and load must be obtained from the same calendar year. Because wind generation proles and energy capture can vary from year to year, it is preferable to assess wind capacity value on multiple years of time synchronized wind and load data. The probabilistic approach immediately converts wind power time series into probability density of power levels, to be combined with the probabilities of conventional power stations availabilities. A main reason to apply this approach can be the lack of appropriate chronological data. However, the probabilistic approach will not be informed by variability of wind generation and is not as accurate as the chronological approach.The probabilistic approach requires:(1) Correct load time series for the period of investigation.(2) Wind power probability density, varying by month or season that can accurately represent the same period as the loads.(3) A complete inventory of conventional generation units capacity and forced outage rates.(4) Target reliability level.If a probabilistic representation of wind generation is used it should be consistent with the load years used in the analysis. An analysis that uses wind and load data from different years will yield invalid results. Many reliability models have the capability to perform Monte Carlo analysis, in which random states of the conventional generation are sampled repeatedly. Even though this is computationally expensive, it can be valuable to more accurately assess the risk of alternative system states. However, the intrinsic Monte Carlo ability that is provided by most, if not all, reliability models is inadequate for wind because of the more complex probabilistic structure of wind power generation.The capacity credit of wind power answers questions like: Can wind substitute for other generations in the system and to what extent? Is the system capable of meeting a higher (peak) demand if wind power is added to the system? This is related to the long term reserve or planning reserve that power systems carry. Wind generation will provide some additional load carrying capability to meet projected increases in system demand. The capacity factor and thus the capacity credit is fundamentally linked with the quality of the wind regime at each of the sites. The contribution can be up to 40% of installed wind power capacity (in situations with low wind penetration and high capacity factor at times of peak load). It can also be as low as 5% in higher wind penetrations, low capacity factor at times of peak load or if regional wind power output proles correlate negatively with the system load profile. Aggregation of larger geographical areas will result in the capacity credit being higher.The wind capacity credit in percent of installed wind capacity is reduced at higher wind penetration, but depends also on the geographical smoothing. In essence, it means that the wind capacity credit of all installed wind in Europe or the US is likely to be higher than those of the individual countries or regions, even if the total penetration level is as in the individual countries or regions. Indeed, this is true only when assuming that the grid is not limiting the use of the wind capacity, i.e. just as available grid capacity is a precondition for allocating capacity credit to other generation.After stating so many aspects about the calculating capacity credit of wind power generation, we need back to the practical problems. Power system has a deep relationship with economy, so I will discuss the capacity credit of wind power generation on the marketing next.The assessment of capacity credits for wind energy and the value interpretation is shown that the electricity market values the contribution to system reliability with market prices in a more precise way. This requires that markets for ancillary services exist and are based on price spike incentives given by the regulator. Price signals sent out by markets to investors and customers enable the electricity system to adjust more effectively to the challenge of high wind power penetration in the near future.The dispatch of the available capacity follows contracts made in competitive spot and forward markets. Although it is expected that only 20 % of energy traded in the market will be traded at Power Exchanges, the liquidity and transparency of these marketplaces lead to prices which can be used as reference prices for the whole market.Figure 1: Determination of the market price of wind energy Figure 1 shows the fixing of the market price for wind energy in the market where all generators bid their marginal cost and an assumed price inelastic total demand curve. Prices are fixed for every single hour of the day ahead and follow the demand and supply situation. Wind energy bids are integrated in the market according to the wind forecast. Since wind energy has a variable cost of zero, it is always “in the market” and receives the respective market price. Thus, a high correlation of wind energy production and demand results in high peak prices paid to wind generators. Here it becomes obvious again those prices are below variable cost of all displaced conventional generators since the marginal cost of the last dispatched generator determines the spot-market price. Reliability issues are crucial when it comes to integration of wind energy. Therefore, this section discusses how reliability is ensured in deregulated markets. Even if capacity investment, dispatch and pricing are determined by market forces, system reliability cannot be provided without regulation. Since every participant is affected by a system blackout caused by unexpected mismatches between supply and demand, system reliability can be considered to be a public good to be provided by an Independent System Operator (ISO). The cost for reliability (supply of reserves) has to be carried by all market participants. In economic theory, the marginal benefit of increased reliability has to be made equal to the incremental cost of supplying reserve. In practice marginal benefit cannot easily be determined and is surely varying among market participants. Therefore, a reliability standard is defined and incentives to keep excess capacity to provide installed and operating reserves at this defined level have to be given by the ISO. The concrete regulatory regime is mostly specified on national or state level and varies widely so only basic principles can be presented here. An ISO can ensure that market forces lead to the optimal reserve level in basically two different ways. The first and more common way is to define a capacity requirement, share it among participants, and penalize whoever falls short of that requirement. The second way is to make the ISO to pay a lot more for energy if remaining capacity falls below a certain level and thus causing a price spike. Both systems ensure that excess capacity is not rewarded when it is worthless (which means that it is abundant in times of total excess capacity), but investments are encouraged when they are necessary for system reliability: At the “correct” level of total installed capacity, peaking units on the margin of the merit order will be able to recover their fixed costs from the incentives given by the ISO either directly through peak prices or through a capacity price that will establish on a market of reserve capacity close to the penalty value. For wind generators, the peak price solution is more attractive since they can make use of price peaks but would have to give up revenue from electricity sales to offer a share of the capacity in the reserves market. In the electricity market where wind energy will be traded in the near future, the value of capacity credit is “assigned” by the market by valuing the contribution to system reliability with market prices: The regulatory regime should be designed in a way that price peaks give incentives for investments. This principle applies not only to the day-ahead energy market but also to ancillary services markets where reserves have to be provided with the appropriate reaction time. A high penetration of wind power in the electricity system will lead to price peaks on energy and ancillary services markets. They, in turn, provide incentives for the use of interruptible loads and will also increase the profitability of different electricity storage systems which make use of price differences. Hence, market forces lead to an adaptation of the system, which is frequently demanded by integrated system studies. Intelligent networks with interconnected decentralized systems that provide the different services will be established and be able run automatically to allow the use of a greater variety of supply and demand options such as electric vehicles and flexible combined heat and power systems Besides certificate support schemes for wind energy which are likely to be established more commonly in the near future, “green electricity” is defined and sold to customers who have a willingness to pay an extra contribution to foster the adaptation of the electricity system towards the use of more sustainable sources. In this framework, any additional demand for certificates caused by “green customers” provides extra income for renewable energy generators. Although in most markets reserve capacity in its various needed forms is available and able to cope with high wind power penetration, market mechanisms have to ensure that reserve allocation (including ancillary services) as well as demand management and investment in storage is encouraged efficiently. The price spike system for reserve markets was reviewed briefly and is appropriate to send the right price signals to market participants. Finally, I will discuss the backup requirements for achieving the better application of wind power in our life. So, what does the capacity credit of a wind farm tell us about the backup capacity that a wind farm requires? Because a wind farm cant always be relied on to deliver its average power, it needs an operating reserve to act as back up. Nowadays that operating reserve is usually gas or coal.On top of that, there is also the question of “spinning reserve”. Some thermal power stations are kept in a “warm” state, with turbines spinning, so they can deliver full power at very short notice. This is the “spinning reserve” on the grid. At the present low level of wind penetration in the UK, no extra “spinning reserve” is needed. Wind power wont create a need for additional spinning reserve until its share of total grid capacity exceeds 20%.Looking further ahead, a more elaborate network of renewable power sources can be set up if we have a large enough grid. Between them the various renewable can provide power reliably, even though each renewable individually has a relatively low probability of being available. And another question is how much backup capacity is needed? The backup requirement is usually seen as the amount of capacity needed to make up the difference between a wind farms average output and its capacity credit:Backup capacity needed =average power capacity credit To illustrate this, here are two examples. The first is for a capacity credit of 20% of “nameplate” installed capacity, as would be the case for low levels of wind penetration. The second example is for a capacity credit of 10% of “nameplate” capacity, the case for a high level of wind penetration. A 30% capacity factor is assumed for both cases:Backup capacity requirement at 20% capacity creditInstalled capacity (peak power)1000MWAverage power at 30% capacity factor= 1000MW 30% = 300MWCapacity credit= 1000MW 20% = 200MWBackup capacity = average power capacity credit= 300MW 200MW =100MWIn this case, the 1000MW of installed capacity generates an average power of 300MW, and requires an additional backup capacity of 100MW.Backup capacity requirement at 10% capacity creditInstalled capacity (peak power)1000MWAverage power at 30% capacity factor= 1000MW 30% = 300MWCapacity credit= 1000MW 10% = 100MWBackup capacity = average power capacity credit= 300MW 100MW =200MWWhen the capacity credit has fallen to 10% of installed capacity, the 1000MW of installed capacity still generates the same 300MW of average wind power, but it now requires 200MW of backup capacity, more than before, because a lower fraction of the installed capacity can be counted on as “firm” capacity. Reviewing all the information above, I have discussed the capacity credit of wind power generation in many aspects, such as history, wind energy, wind farms, electricity generation, economics and backup requirement. From the all above discussion, we can see that the capacity credit of wind power generation is concerned by many researchers and has strong potential on using energy more efficient. We have already solved some problems till now but there are many still not. This thesis is just a very fundamental discuss for reference and hope researchers can make a great breakthrough in the future to make our life better. 毕业设计（论文）外文翻译（原文）风力发电容量信用问题及解决方案人们都使用风能了数千年。已知的最早使用风力发电是由埃及人大约5000年前，他们用该帆船航行从此岸到彼岸尼罗河上。大约公元前2000年第一个风车是建立在巴比伦。直到现在，人们都使用风力发电以来这么多年了，这一领域的研究也随着时间逐步发展。人们已经发现了帮助我们解决能源危机方法，所以我想讨论一个简单的风力发电方面对其问题和解决方案。首先，我要指出的一些基本概念，风力为基础的进一步讨论。风力发电是将风能转换成有用的能源形式，如使用风力涡轮机来发电，风车机械动力，提水或引流，或风帆推动船只。可以从风能中提取的经济力量总额是大大超过目前人类利用来自所有来源。风力，作为一种替代矿物燃料，可再生，是丰富，分布广泛，清洁，不产生温室气体的排放，在操作过程中，和每单位煤和天然气能源生产装置的成本相近。大型风电场，由几百个风力涡轮机连接到电力传输网络的构成的。海上风电可以利用海上比陆地上更好的风速，所以海上风电的贡献方面的电力供应更高。小型陆上风力发电设备，是用来给孤立的地点和公共事业公司提供电力的，用于公司减少那越来越贵的电力资金消费的家用小型风力发电机。建设风力农场并未受到普遍欢迎，但任何对环境的影响，风力一般是少的问题比其他任何电源。 风电场的用于生产电力的风力涡轮机在同一地点。大型风电场，可由几百个人风力涡轮机，并覆盖扩展面积数百平方英里的土地，但之间的涡轮可用于农业或其他用途。风力发电场，也可能位于海洋。 在风力涡轮机，个人是相互关联的一种中压（通常34.5），功率采集系统及通信网络。在变电站，该中压电流增加电压变压器连接到高电压电力传输系统。剩余电力生产的家用微型发电机，在某些司法管辖区，反馈到网络并销往公共事业公司，生产零售信贷的微型发电机主抵消自己的能源成本。风力发电的电力可高度变量在不同的时间：从每小时，每天，和季节性。年际变化也存在，但并不显着。相关的变异是短期（每小时或每天）可预测性的风电场输出。像其他电力来源，风能必须是“定”。风电功率预测方法的使用，但可预测性的风电场输出仍然很低的短线操作。由于瞬时发电和消费必须保持平衡，以维持电网的稳定，这种差异可以提出重大的挑战，把大量的风力发电成一个网格系统。间歇性和自然风能生产可以提高成本管理，增量储备经营，和（在高渗透水平）可能需要增加已经存在的能源需求管理，甩负荷，或存储解决方案或系统互连用直流高压电缆。在低级别的风力渗透，波动负荷和津贴失败大型发电机组，需要储备能力，还可以调节的变异的风力发电。风能可以取代其他发电站在低风时期。传输网络必须应对停电的发电厂和每日变动的需求。系统与大型风力发电能力可能需要更多的旋转备用零件。之后了解一些基本的方面，我们有一个比较清晰的概念在许多方面，如风力发电场，发电，和间歇性，变异。所以下一次，我将讨论本文的主题，容量信用。在过去容量信用风电在一个网格已经收到了很多注意。在早期的风力，容量信用，而知觉缺乏，是一个严重关切的大规模发展风电的一个全国性的基础。因此，一些研究了自1970ies，达成的结论，风力有能力信用能力和信用的平均风功率输出为小穿透风电的电网，和下降到一个值接近最低风力发电的大突破。那些传统的发电厂评估比较风功率输出特性来确定风能价值。这反映了内部规划范式的管制的电力市场。标准措施的比较是提供植物种类。强迫停运率的传统植物和风力可捕获的概率分布的风速汇总累计可用性功能的使用可靠性模型。一个可以接受的损失负荷概率确定最大负荷。在此基础上，计算能力，信用作为一个“当量”的风力发电机常规发电机可靠性方面。作为可用风能随时间变化的能力，信用好。因此，在高峰时间能力的信贷需求通常是用于进一步的解释。因此，高相关性的风力能源生产和电力需求将导致一个高容量的信贷分配到风力发电机。间歇能量来源是任何能量的来源，是不可由于一些因素外直接控制。间歇性的来源可能是可预见的，例如，潮汐能，但不能被派遣到满足电力系统的需求。例间歇性的来源是风。容量的概念，信用是风力相对论到现在也没有一个明确的和大家都同意的定义。许多研究人员集中在是否或没有风有任何“风险”没有界定什么是这个及其相关性。风也有风险，使用广泛接受的和有意义的定义，约等于20%的额定输出（但这一数字取决于实际情况）。这意味着，储备能力在系统中添加等于20%风可以退休时，风是添加不影响系统的安全控制。英国学术评论员辛登，牛津大学，认为这一问题的能力是一个“红鲱鱼”的价值，风力发电的主要原因是价值的流离失所任何知觉能力，信用它被很好地理解了风能的支持者，传统的能力将保留“填补”期间的低或没有风。主要价值风，（在英国，5倍的容量信用值）是它的燃料和二氧化碳储蓄所。风不需要任何额外的备份，因为往往是错误的，因为它使用现有的发电站，其中已经建成，作为后备，并开始在低风，正如他们开始到现在，在不提供其他传统的植物。更多的旋转备用，现有厂房，是必要的，但这又是已经建成，有一个低成本的比较。电厂的能力因素是电能的在给定时间的可以在同一期间最大连续功率运行时产生的电能源生产的比率。对于传统的化石燃料发电站,容量因子是由计划的维护停机时间,意外的设备故障,空间站的电力时关闭不需要的。对风能和太阳能,输出功率也由风和阳光的可用性。最大输出功率、或“装机容量”,是一个相当的理论价值,是很少达到。这将是清晰引用的平均功率为太阳能和风能,但是因为峰值功率是通常引用,重要的是要知道的容量因子,来理解这些峰数字。所以在理解能力要素，风力发电，我们知道这是之间的比例，风电场的输出平均功率和最大或“名牌”的能力。这个比例通常是20%和30%之间。那是，当平均超过一年，风力农场生产约20%30%一样多的能量，因为如果连续运行在最大功率输出。但随着越来越多的研究，还有另一个更先进的关键操作参数的风力发电，其“能力”。而风电场的能力的因素是通过平均输出来衡量的，容量信用是一个衡量的最坏情况最小输出可以依靠的一部分的总系统容量。能力是“公司”的能力，一个风电场，可以算的上是作为一个可靠的贡献的总和所有电网容量。容量信用风，估计是通过确定生产常规的植物流离失所的风功率，同时保持同样程度的系统的安全性，换句话说，一个不变的失效概率满足可靠性标准的系统。另外，据估计确定额外的负载，该系统可以进行风力增加，保持相同的可靠性水平。风电穿透水平低，相对风险风力（即公司能力作为一个部分的总风力发电装机容量）会相等或接近平均生产（因子）在审议期间，通常是时间的最高需求。在北欧国家，这是冬季和负载因子通常是25百分之30陆上和50 %的海洋。加载因子确定能力信用一般高于年平均负荷因子。增加的渗透水平风力能源系统，其相对风险降低。然而，这并不意味着较传统的能力可以被取代，而是一个新的风力发电厂添加到系统的风电穿透功率水平高会比第一次少风电厂在系统。另一方面，一个风电场容量信用量是由其他发电能力（如煤，例如）可从网格不影响供电可靠性。风是不寻常的但是，在其输出的不可预知性。它没有固定周期变化的潮汐或太阳能。风力发电的此不可预测性使其能力的问题一项相当复杂的信贷。什么，然后，是风力发电容量信用？该风力发电场可以可靠地提供的最小电源容量是什么？由于风电场输出可以下降到零，似乎一见钟情风力发电容量信用必须为零。事实上并非如此。如果风电场运营中隔离，但风电场通常连接到多大的供电网，这会是真的。整个网格内的供应和需求各不相同的所有时间，和能源规划开发了详细统计的计算方法，以处理这一问题。他们计划，以满足给定的负荷概率损失，网格能力或概率。概率是概率代将不足以满足需求。能源供应计划人员必须确保有足够的能力来保持负荷概率的损失低于某些指定的水平，但他们不想花费的钱会不必要地之外，产能过剩。风险管理的一个问题是风力发电场可以统计学在常规电厂完全相同的方式处理。对于任何类型的电厂有可能要计算它不能供应的预期的负载的概率。风是变量，它不会提供在任何特定时间的概率较高。风力发电，可以在每个其他电源完全相同的方式纳入电网可靠性统计。风有较低的可能性可用，但这数字只是被送入计算。没有任何关于风质的不同。能源工程师们已经来仔细看看风供应的统计数字，他们得出的结论是风有大容量信用。怎么能这样呢？毕竟，风速可降一路至零。要回答这个问题，我们要看跨整个电网的供应统计数字。例如，地理位置分散风力发电，变成不太可能风将停止所有风力农场站点同时都吹。这并不是说这是不可能的但它是不太可能。此外，当风力强度和电力需求关联 （例如，在冬天更强的风是地区） 又有风将有助于这一需求的几率较高。之后，有什么实际数字的能力信用风力？容量信用风取决于分数电网总容量是由风力。在行话，这取决于“渗透”风电对电网。风电能源渗透通常定义为风能在今年虽然风电容量渗透被定义为给定的区域到峰值负载已安装的风力发电能力的比例为某一区域，一年生产的总电力能源生产总量的比例。当风容量总网格容量可以忽略不计的小部分，风电场的能量信用可以视为相等的平均功率的风电场。也就是说，容量信用是乘以安装容量的能力因素相同。这是能力的因为风渗透的水平非常低，网格可以处理风输出波动作为其日常的一部分。随着风容量增加到电网总容量的 10%左右，容量信用降至约 20%的安装容量 （峰值功率） 的风电场。就是现在的风电场的平均功率较低容量信用。随着风容量增加到电网总容量的 10%左右，容量信用降至约 20%的安装容量 （峰值功率） 的风电场。就是现在的风电场的平均功率较低容量信用。既然我们已经知道，容量信用的风力发电可以定量，我们将讨论如何计算信用风力发电容量。电力系统必须具有足够的代以满足一天每一刻的需求。此外，他们还必须具有足够的储备，以应付意外情况的紧急事件。风力发电在最近几年中的渗透率的增加，导致一些便利风力发电同时维持现有的供应的安全级别所需的计算中的挑战。在此过程中的关键计算是容量信贷或风力发电的价值。风力发电容量信用/值可以大致可以替换风力发电的能力，同时保持供应安全的现有水平的稳固传统的发电容量为 dened。电力系统可靠性包括系统的安全性和足够。电力系统是足够的如果有足够的安装的电源供应，以满足客户的需求。一种系统是安全的如果它能够抵挡发电机或传输链接等关键电源组件的损失 （或多个潜在损失）。本白皮书重点风力发电已对代充分性的影响。几个月或今后几年作出代足够的分析并将其与系统的静态条件相关联。这可以通过一种按时间顺序生成负载模型，其中可以包括输电和配电或概率方法研究。估计所需的生产需要的包括系统需求和生产单位的可用性数据。容量信用是一个给定的生成器使整体系统足够的贡献。甚至传统的发电方式的可用性是不能保证任何时候都因为始终有机械或电气故障为零风险。由于可靠性的开销很普遍采取了系统的可靠性目标。任何发电机容量值是发电机的可以加上的问题送达目标可靠性级别的额外负载量。虽然有几种方法，用来计算风容量值，但大多数方法基于电力系统可靠性分析方法。用于充裕度评估的标准例如包括损失的负载期望 (LOLE)、 负荷概率 （概率） 的损失和能源展望 (LOEE) 的损失。概率是负荷将超过在给定时间，可用代的概率。这一标准是给好的系统发生故障的可能性，但它缺少的重要性和停电持续时间的信息。LOLE 是通常每年，期间负荷将不会实现超过 dened 的时间的小时数。一个关键的能力
- 温馨提示:
1: 本站所有资源如无特殊说明，都需要本地电脑安装OFFICE2007和PDF阅读器。图纸软件为CAD,CAXA,PROE,UG,SolidWorks等.压缩文件请下载最新的WinRAR软件解压。
2: 本站的文档不包含任何第三方提供的附件图纸等，如果需要附件，请联系上传者。文件的所有权益归上传用户所有。
3.本站RAR压缩包中若带图纸，网页内容里面会有图纸预览，若没有图纸预览就没有图纸。
4. 未经权益所有人同意不得将文件中的内容挪作商业或盈利用途。
5. 人人文库网仅提供信息存储空间，仅对用户上传内容的表现方式做保护处理，对用户上传分享的文档内容本身不做任何修改或编辑，并不能对任何下载内容负责。
6. 下载文件中如有侵权或不适当内容，请与我们联系，我们立即纠正。
7. 本站不保证下载资源的准确性、安全性和完整性, 同时也不承担用户因使用这些下载资源对自己和他人造成任何形式的伤害或损失。
人人文库网所有资源均是用户自行上传分享，仅供网友学习交流，未经上传用户书面授权，请勿作他用。
川公网安备: 51019002004831号