發(fā)布時(shí)間：2018-03-24 22:15

  本文選題：微網(wǎng)　切入點(diǎn)：光伏　出處：《華北電力大學(xué)(北京)》2017年碩士論文

【摘要】：微網(wǎng)利用光伏、風(fēng)機(jī)等可再生能源發(fā)電并與儲(chǔ)能系統(tǒng)配合向本地負(fù)荷供電是解決能源危機(jī)和環(huán)境污染問題的方法之一。然而,光伏、風(fēng)機(jī)等電源的出力具有間歇性,且與用戶負(fù)荷需求呈不對(duì)等分布,難以被本地用戶直接利用。因此,通過能量管控實(shí)現(xiàn)能源就地高效利用,避免大量過剩功率入網(wǎng),對(duì)負(fù)荷起到削峰效果是當(dāng)前微網(wǎng)研究重點(diǎn)之一。目前,已有不少微網(wǎng)能量管控策略,然而大部分控制策略依賴于精確的負(fù)荷需求和分布式電源出力預(yù)測(cè)數(shù)據(jù)或通過短時(shí)的預(yù)測(cè)修正來(lái)減小對(duì)預(yù)測(cè)數(shù)據(jù)的依賴,但精準(zhǔn)預(yù)測(cè)和反復(fù)預(yù)測(cè)修正的過程受到現(xiàn)有預(yù)測(cè)技術(shù)和軟件計(jì)算能力的限制。此外,隨著電動(dòng)汽車的快速發(fā)展,其充電隨機(jī)性高、瞬時(shí)充電功率較大且難以精確預(yù)測(cè)的特性會(huì)降低依賴精確預(yù)測(cè)數(shù)據(jù)的能量管控策略的控制效果。針對(duì)上述問題,論文對(duì)包含光伏、風(fēng)機(jī)和微型燃?xì)廨啓C(jī)分布式電源的小區(qū)微網(wǎng)提出了冷/熱電聯(lián)產(chǎn)和儲(chǔ)能系統(tǒng)聯(lián)合運(yùn)行的能量管控策略,實(shí)現(xiàn)了對(duì)各類能源的高效利用和對(duì)用戶冷/熱、電負(fù)荷的分類削減,改善能源供給和負(fù)荷需求分布不對(duì)等的現(xiàn)狀。其中,考慮小區(qū)內(nèi)電動(dòng)汽車充電負(fù)荷不斷增長(zhǎng)的情況,論文對(duì)儲(chǔ)能系統(tǒng)的充放電控制提出了一種基于預(yù)測(cè)數(shù)據(jù)的實(shí)時(shí)修正算法。該算法利用預(yù)測(cè)數(shù)據(jù)但不依賴于預(yù)測(cè)數(shù)據(jù)的精確性,也不需要對(duì)數(shù)據(jù)預(yù)測(cè)部分進(jìn)行反復(fù)計(jì)算修正,直接通過對(duì)儲(chǔ)能系統(tǒng)充放電功率的修正計(jì)算實(shí)現(xiàn)最大程度的沖擊負(fù)荷削減。論文利用實(shí)測(cè)和模擬數(shù)據(jù),對(duì)提出的微型燃?xì)廨啓C(jī)冷/熱電聯(lián)產(chǎn)和儲(chǔ)能系統(tǒng)聯(lián)合運(yùn)行的能量管控策略進(jìn)行編程實(shí)現(xiàn),并與儲(chǔ)能系統(tǒng)充放電控制采用固定閾值算法和自適應(yīng)控算法的控制策略進(jìn)行結(jié)果比較。結(jié)果表明,論文設(shè)計(jì)的能量管控策略較好的實(shí)現(xiàn)了各類能源的本地利用,并在保證運(yùn)行最優(yōu)經(jīng)濟(jì)性的基礎(chǔ)上實(shí)現(xiàn)最大程度的沖擊負(fù)荷削減效果。
[Abstract]:One of the ways to solve the problem of energy crisis and environmental pollution is to use photovoltaic, blower and other renewable energy sources to generate electricity and cooperate with energy storage system to supply local load. However, the output of photovoltaic, blower and other power sources is intermittent. And the distribution is not equal to the demand of user load, so it is difficult to be directly utilized by local users. Therefore, energy can be efficiently utilized in place through energy control, and a large amount of excess power can be avoided. Peak-cutting effect on load is one of the key points in microgrid research. At present, there are many microgrid energy control strategies. However, most control strategies rely on accurate load demand and distributed power generation prediction data or reduce the dependence on prediction data by short-term forecasting correction. But the process of accurate prediction and repeated prediction correction is limited by existing prediction techniques and software computing capabilities. In addition, with the rapid development of electric vehicles, their charging randomness is high. The characteristics of high instantaneous charge power and difficult to predict accurately will reduce the control effect of energy control strategy which depends on accurate predictive data. In this paper, the microgrid of distributed power system of fan and micro gas turbine has put forward the energy control strategy of combined operation of cold / heat power generation and energy storage system, which realizes the efficient utilization of all kinds of energy and the classification and reduction of user's cold / heat and electric load. Improving the unequal distribution of energy supply and load demand. Among them, considering the increasing charge load of electric vehicles in the district, In this paper, a real-time correction algorithm based on predictive data is proposed for charge and discharge control of energy storage system, which utilizes the prediction data but does not depend on the accuracy of the prediction data, nor does it need to calculate and modify the prediction part repeatedly. The maximum impact load reduction is realized by modifying the charge and discharge power of the energy storage system. The proposed energy control strategy for the combined operation of cooling / heat and power generation and energy storage system of micro gas turbine is realized by programming. The results are compared with the control strategies of fixed threshold algorithm and adaptive control algorithm in charge and discharge control of energy storage system. The results show that the energy control strategy designed in this paper can achieve the local utilization of all kinds of energy. The maximum impact load reduction effect is realized on the basis of ensuring the optimal operation economy.
【學(xué)位授予單位】：華北電力大學(xué)(北京)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TM73

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