本文選題：風電注入功率模型 + 電網協(xié)調規(guī)劃��； 參考：《山東大學》2015年碩士論文

【摘要】：風電是潔凈的可再生能源,大力開發(fā)可再生能源是合理調整電源結構的需要,是我國能源發(fā)展戰(zhàn)略的重要組成部分,風能已成為當前利用規(guī)模最大、技術成熟度最高的可再生能源形式之一。風電的隨機性和間歇性,決定了它必須由常規(guī)能源配合來滿足電網連續(xù)供電的要求,應在電網規(guī)劃的總體框架內納入統(tǒng)一規(guī)劃,有序進行。本文從風電注入功率模型、提高風電消納的能力措施與機制以及風電與電網協(xié)調規(guī)劃三個方面開展研究取得了一定的成果。風電功率的預測方法,并對風電出力的多時空尺度波動特性進行了分析和對基于時間序列和神經網絡法的風電功率預測和風電場出力的縱向時刻概率分布特性進行了研究的基礎上,本章提出了一種新的分析風電出力概率分布特征的方法�；趯崪y數(shù)據,對風電場在一年時間內每天的特定時間點處有功出力及有功出力變化率進行統(tǒng)計,得到對應時間點的概率分布結果。并對所提的風電出力的縱向時刻概率分布函數(shù)適用性進行了校驗,效果良好。利用電動汽車的負荷特性及其接入電網技術與風電相協(xié)調來提高風電消納能力的方法和提出了考慮風電場儲能系統(tǒng)適應電網調度決策的儲能容量優(yōu)化計算模型；該模型以適應電網調度運行計劃的風電場輸出功率時段參考值為基礎,同時計及風電場棄風能量與儲能系統(tǒng)損失能量的影響,以儲能投資成本及風電系統(tǒng)運行成本最小為目標函數(shù),建立基于蓄電池儲能系統(tǒng)的儲能容量優(yōu)化決策模型,并應用改進的粒子群算法進行求解。該方法使得經過儲能系統(tǒng)作用輸出的風電功率實現(xiàn)分時段平滑輸出,以此實現(xiàn)儲能系統(tǒng)與現(xiàn)有調度運行方式的有效銜接,同時達到最佳經濟效益�？紤]大規(guī)模風電接入電網的電網規(guī)劃模型及輸電網協(xié)調規(guī)劃算法。并在18節(jié)點系統(tǒng)上進行了仿真,通過算例仿真分析可知該方法考慮了如未來發(fā)電的不確定性,風電出力的波動性以及負荷的不確定性等更多的不確定性的信息,兼顧了規(guī)劃方案的安全性和經濟性。求解時利用遺傳算法搜索,按照給定的N-1靜態(tài)安全過載概率值,所得規(guī)劃方案在未來的不確定性環(huán)境下更具靈活性和適應性�；陲L電注入功率概率模型的電網規(guī)劃軟件應用,該軟件由輸電網規(guī)劃程序和規(guī)劃方案評價程序兩部分構成。采用改進遺傳算法作為核心尋優(yōu)方法實現(xiàn)輸電網的規(guī)劃,采用基于層次分析法約束錐的數(shù)據包絡分析法對規(guī)劃方案進行評價�？梢詫崿F(xiàn)含風電的輸電網規(guī)劃和規(guī)劃方案的評價,操作簡便,實用。
[Abstract]:Wind power is a clean renewable energy, vigorously develop renewable energy is the need to adjust the power supply structure, is an important part of China's energy development strategy, has become the largest wind energy utilization, technology maturity is the highest form of renewable energy. One of the randomness and intermittence of wind power, decided it must be made of conventional energy with the continuous power supply to meet the requirements of the power grid, should be in the general framework of power grid planning in included in the unified planning and orderly. The wind power injection model, improve the wind power utilization capacity measure and mechanism of wind power and power grid planning and coordination of three aspects to carry out research and achieved certain results. The prediction method of wind power the multi time scale and fluctuation characteristics of wind power output are analyzed and based on time series and neural network method to predict wind power and wind power. The longitudinal moment distribution characteristics were studied on the basis of this chapter proposes a new method of analysis of wind power output probability distribution. Based on the measured data, the specific time point for the wind farm in a year's time every day at the active power output and output power of the rate of change of statistics, probability distribution results of the corresponding time the point of wind power output. And the longitudinal moment of the probability distribution function is verified, the effect is good. The load characteristics of electric vehicle and grid connected wind power technology and coordination method to improve the absorptive capacity of wind power and considering wind farm energy storage system to meet the power dispatching decision storage capacity optimization calculation model is used; the model to adapt to the wind power grid dispatching operation period plan reference value basis, considering wind energy and energy storage system. Effects of loss of energy, the storage cost of investment and the minimum wind power system operation cost as objective function, a battery energy storage system energy storage capacity optimization decision model based on the improvement and application of the particle swarm algorithm. This method makes the energy storage system of wind power output time to achieve smooth output. In order to achieve effective convergence of energy storage system and the existing scheduling operation mode, and achieve the best economic benefits. Large scale wind power grid transmission network planning model and coordinated planning algorithm. And the simulation is conducted on a 18 node system, the simulation analysis shows that this method is considered as the future generation of uncertainty. The wind power output fluctuation and load uncertainty and more uncertain information, taking into account the safety and economy of the planning scheme. Using genetic algorithm to solve The search, according to the N-1 static security overload probability values, the planning scheme has more flexibility and adaptability in the future uncertain environment. The application of power network planning software based on the probability model of wind power injection, the software from the planning process and transmission planning scheme on two part program using the improved genetic algorithm as the core. The optimization method of transmission network planning method to evaluate the planning scheme analysis using data envelopment analysis hierarchy process. Based on the constraint cone can realize the evaluation, including wind power transmission network planning and the planning scheme is simple, practical.

【學位授予單位】：山東大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：TM614;TM715

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相關期刊論文 前1條

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本文編號：1762950