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Wind power variability, its cost, and effect on power plant emissions.

機譯：風力發(fā)電的可變性，其成本以及對發(fā)電廠排放的影響。

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The recent growth in wind power is transforming the operation of electricity systems by introducing variability into utilities' generator assets. System operators are not experienced in utilizing significant sources of variable power to meet their loads and have struggled at times to keep their systems stable. As a result, system operators are learning in real-time how to incorporate wind power and its variability. This thesis is meant to help system operators have a better understanding of wind power variability and its implications for their electricity system.;Estimating the Cost of Wind Power Variability. We develop a metric to quantify the variability cost of individual wind plants and show its use in valuing reductions in wind power variability. Our method partitions wind energy into hourly and subhourly components and uses corresponding market prices to determine the cost of variability. The range of variability costs for 20 wind plants in ERCOT was ;Estimating How Wind Power Variability Affects Power Plant Emissions. Renewables portfolio standards (RPS) encourage large scale deployment of wind and solar electric power, whose power output varies rapidly even when several sites are added together. In many locations, natural gas generators are the lowest cost resource available to compensate for this variability, and must ramp up and down quickly to keep the grid stable, affecting their emissions of NOx and CO2. We model a wind or solar photovoltaic plus gas system using measured 1-minute time resolved emissions and heat rate data from two types of natural gas generators, and power data from four wind plants and one solar plant. Over a wide range of renewable penetration, we find CO2 emissions achieve ∼80% of the emissions reductions expected if the power fluctuations caused no additional emissions. Pairing multiple turbines with a wind plant achieves ∼77 to 95% of the emissions reductions expected. Using steam injection, gas generators achieve only 30-50% of expected NOx emissions reductions, and with dry control NO x emissions increase substantially. We quantify the interaction between state RPSs and constraints such as the NOx Clean Air Interstate Rule (CAIR), finding that states with substantial RPSs could see upward pressure on CAIR NOx permit prices, if the gas turbines we modeled are representative of the plants used to mitigate wind and solar power variability.;Characterizing Wind Power Variability. We present the first frequency-dependent analyses of the geographic smoothing of wind power's variability, analyzing the interconnected measured output of 20 wind plants in Texas. Reductions in variability occur at frequencies corresponding to times shorter than ∼24 hours and are quantified by measuring the departure from a Kolmogorov spectrum. At a frequency of 2.8x10-4 Hz (corresponding to 1 hour), an 87% reduction of the variability of a single wind plant is obtained by interconnecting 4 wind plants. Interconnecting the remaining 16 wind plants produces only an additional 8% reduction. We use step-change analyses and correlation coefficients to compare our results with previous studies, finding that wind power ramps up faster than it ramps down for each of the step change intervals analyzed and that correlation between the power output of wind plants 200 km away is half that of co-located wind plants. To examine variability at very low frequencies, we estimate yearly wind energy production in the Great Plains region of the United States from automated wind observations at airports covering 36 years. The estimated wind power has significant inter-annual variability and the severity of wind drought years is estimated to be about half that observed nationally for hydroelectric power.
機譯：通過將可變性引入公用事業(yè)公司的發(fā)電機資產(chǎn)，風能的最新發(fā)展正在改變電力系統(tǒng)的運行。系統(tǒng)操作員在利用大量可變功率源來滿足其負載方面經(jīng)驗不足，并且有時會努力保持系統(tǒng)穩(wěn)定。結(jié)果，系統(tǒng)操作員正在實時學習如何整合風能及其可變性。本文旨在幫助系統(tǒng)運營商更好地了解風能變化及其對電力系統(tǒng)的影響。；估算風能變化的成本。我們開發(fā)了一種度量標準來量化單個風電廠的可變性成本，并顯示其在評估風電可變性的降低中的用途。我們的方法將風能分為每小時和每小時的組成部分，并使用相應的市場價格來確定可變性的成本。 ERCOT中20座風力發(fā)電廠的可變成本范圍是；估計風電變率如何影響發(fā)電廠排放?？稍偕茉赐顿Y組合標準（RPS）鼓勵大規(guī)模部署風能和太陽能，即使將多個地點加在一起，其功率輸出也會迅速變化。在許多地區(qū)，天然氣發(fā)生器是可用于補償這種可變性的成本最低的資源，并且必須迅速上升和下降以保持電網(wǎng)穩(wěn)定，從而影響其NOx和CO2的排放。我們使用來自兩種類型的天然氣發(fā)電機的1分鐘時間分辨的排放量和熱率數(shù)據(jù)以及來自四個風力發(fā)電廠和一個太陽能發(fā)電廠的功率數(shù)據(jù)，對風或太陽能光伏加氣系統(tǒng)進行建模。在廣泛的可再生能源滲透范圍內(nèi)，我們發(fā)現(xiàn)，如果電力波動不會導致其他排放，那么二氧化碳排放量將達到預期減排量的80％。將多臺渦輪機與風力發(fā)電廠配對可以達到預期排放量的約77％至95％。使用蒸汽噴射，氣體發(fā)生器僅能實現(xiàn)NOx排放預期減少量的30％至50％，并且在干式控制下，NOx排放量會大大增加。我們量化了州RPS與約束條件（例如NOx清潔空氣州際規(guī)則（CAIR））之間的相互作用，發(fā)現(xiàn)具有較高RPS的州可能會看到CAIR NOx許可價格上漲的壓力，如果我們建模的燃氣輪機代表了過去減輕風能和太陽能的可變性。我們介紹了風電可變性的地理平滑化的第一個頻率相關(guān)分析，分析了德克薩斯州20座風電廠的互連實測輸出。變異性的降低發(fā)生在對應于小于約24小時的時間的頻率上，并通過測量與Kolmogorov譜的偏離來量化。在2.8x10-4 Hz的頻率（相當于1小時）下，通過將4個風力發(fā)電廠互連，單個風力發(fā)電廠的可變性降低了87％。將其余16座風力發(fā)電廠互連，僅能減少8％的能耗。我們使用階躍變化分析和相關(guān)系數(shù)將我們的結(jié)果與以前的研究進行比較，發(fā)現(xiàn)對于所分析的每個階躍變化間隔，風能的上升速度要快于其下降的速度，并且200 km外的風電廠的功率輸出之間的相關(guān)性為一半位于同一地點的風力發(fā)電廠。為了檢查非常低的頻率下的變異性，我們根據(jù)涵蓋36年的機場的自動風向觀測估計了美國大平原地區(qū)的年風能產(chǎn)量。估計的風能具有明顯的年際變化，估計風旱年的嚴重程度約為全國水力發(fā)電年的一半。

著錄項

  • 作者

    Katzenstein, Warren.;

  • 作者單位

    Carnegie Mellon University.;

  • 授予單位 Carnegie Mellon University.;
  • 學科 Alternative Energy.;Political Science General.;Economics General.
  • 學位 Ph.D.
  • 年度 2010
  • 頁碼 112 p.
  • 總頁數(shù) 112
  • 原文格式 PDF
  • 正文語種 eng
  • 中圖分類
  • 關(guān)鍵詞

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