發(fā)布時間：2018-01-04 21:20

  本文關(guān)鍵詞：能源大數(shù)據(jù)背景下微網(wǎng)風(fēng)險元傳遞模型與優(yōu)化研究　出處：《華北電力大學(xué)(北京)》2017年博士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 微網(wǎng) 能源大數(shù)據(jù) 風(fēng)險管理 雙向型風(fēng)險元傳遞 優(yōu)化

【摘要】：微網(wǎng)是在新能源發(fā)電背景下,在分布式發(fā)電基礎(chǔ)上新興的前沿技術(shù)。微網(wǎng)作為智能電網(wǎng)的有機組成部分,對于企業(yè)節(jié)能降耗、發(fā)電、供電質(zhì)量需求具有重要意義。微網(wǎng)運營相關(guān)技術(shù)研究已受到了世界各國普遍關(guān)注和重視。微網(wǎng)集成了多種能源輸入(太陽能、風(fēng)能、常規(guī)化石燃料、生物質(zhì)能等)、多種特性負(fù)荷、多種能源轉(zhuǎn)換單元(燃料電池、微型燃?xì)廨啓C、內(nèi)燃機,儲能系統(tǒng)等),是化學(xué)、熱力學(xué)、電動力學(xué)等行為相互藕合的非線性復(fù)雜系統(tǒng)。微網(wǎng)中許多類型的分布式發(fā)電電源受制于自然條件,運行不確定性強,具有間歇性、復(fù)雜性、多樣性、不穩(wěn)定性的特點,其電能質(zhì)量特征與傳統(tǒng)電力系統(tǒng)有很大差異。同時,微網(wǎng)中的負(fù)荷受區(qū)域環(huán)境、經(jīng)濟(jì)和政策等社會因素的影響,也給微網(wǎng)帶來更多的不確定性。電的流動性導(dǎo)致了電網(wǎng)中的各單元的緊密聯(lián)系特性,當(dāng)某個單元發(fā)生風(fēng)險時也會影響到其他單元,甚至導(dǎo)致其他單元也發(fā)生風(fēng)險,電網(wǎng)中這種緊密聯(lián)系性也給風(fēng)險可以在其間發(fā)生傳遞提供了可能。隨著能源互聯(lián)網(wǎng)建設(shè)的不斷深入和推進(jìn),電網(wǎng)運行和設(shè)備檢/監(jiān)測產(chǎn)生的數(shù)據(jù)量呈現(xiàn)指數(shù)級增長,逐漸構(gòu)成了當(dāng)今信息學(xué)界所關(guān)注的能源大數(shù)據(jù)。能源大數(shù)據(jù)蘊含著能源互聯(lián)網(wǎng)的大量知識信息,能源大數(shù)據(jù)的有效使用將為微網(wǎng)高效運行提供有力保障。本文站在能源大數(shù)據(jù)背景下,基于風(fēng)險元傳遞理論,先從發(fā)電量和用電量兩個方面研究如何識別微網(wǎng)運營中的風(fēng)險元;再分別研究微網(wǎng)間的雙向型和網(wǎng)絡(luò)型風(fēng)險元傳遞路徑,由簡入繁揭示微網(wǎng)風(fēng)險元傳遞機理;最后給出減少或消彌微網(wǎng)風(fēng)險元傳遞的優(yōu)化方法,為管理者提供較為系統(tǒng)的微網(wǎng)風(fēng)險管理決策依據(jù)。本文主要研究內(nèi)容包括以下幾個方面:(1)能源大數(shù)據(jù)創(chuàng)新微網(wǎng)風(fēng)險管理研究。首先分析風(fēng)力發(fā)電大數(shù)據(jù)、光伏發(fā)電大數(shù)據(jù)和供用電大數(shù)據(jù)等,指出微網(wǎng)運營過程中,微網(wǎng)間存在的風(fēng)險動態(tài)變化現(xiàn)象。然后提出在能源大數(shù)據(jù)背景下,可以創(chuàng)新微網(wǎng)風(fēng)險管理研究,采用風(fēng)險元傳遞理論能夠更好地分析并解釋微網(wǎng)間的風(fēng)險相互影響情況。(2)微網(wǎng)發(fā)電量風(fēng)險元識別研究。受自然環(huán)境條件的限制,微網(wǎng)發(fā)電量不確定性是微網(wǎng)發(fā)生風(fēng)險的主要原因之一,能源大數(shù)據(jù)為微網(wǎng)發(fā)電量風(fēng)險元挖掘提供了新的途徑,在風(fēng)力發(fā)電和光伏發(fā)電功率預(yù)測的基礎(chǔ)上,先對微網(wǎng)潮流進(jìn)行確定性預(yù)測,再將馬爾可夫鏈和拉丁超立方抽樣相結(jié)合,分別對微網(wǎng)潮流的條件聯(lián)合概率分布和非條件聯(lián)合概率分布進(jìn)行預(yù)測。根據(jù)風(fēng)速和光照的演變特性,計算微網(wǎng)潮流的概率分布及置信區(qū)間可以對預(yù)測結(jié)果的不確定性進(jìn)行風(fēng)險元識別。(3)微網(wǎng)用電量風(fēng)險元識別研究。在微網(wǎng)運行中用電量的不確定也是造成微網(wǎng)風(fēng)險的主要因素之一。受飛蛾撲火自然現(xiàn)象的啟發(fā),為提高預(yù)測的精度,將其用于優(yōu)化最小二乘支持向量機算法,提出一個基于最小二乘支持向量機和飛蛾撲火優(yōu)化算法的混合的負(fù)荷預(yù)測模型,以達(dá)到更加精確地預(yù)測用電負(fù)荷、準(zhǔn)確識別微網(wǎng)中用電量風(fēng)險元的效果。(4)微網(wǎng)風(fēng)險元雙向型傳遞模型研究。通過對大數(shù)據(jù)分析發(fā)現(xiàn),風(fēng)險元不只是在微網(wǎng)間單向傳遞,還存在著互相傳遞的情況。以并入大電網(wǎng)的風(fēng)光儲微網(wǎng)的風(fēng)險管理為研究對象,提出雙向風(fēng)險元傳遞模型,給出缺電風(fēng)險值和影響因子計算方法。此傳遞路徑的提出豐富了原風(fēng)險元傳遞理論研究的內(nèi)容,揭示了風(fēng)險元傳遞的又一種客觀現(xiàn)象。(5)微網(wǎng)群網(wǎng)絡(luò)風(fēng)險元傳遞模型研究。與大電網(wǎng)互聯(lián)的多個微網(wǎng),它們之間通過大電網(wǎng)相互聯(lián)系,符合網(wǎng)絡(luò)的特征,每個微網(wǎng)可以看作是網(wǎng)絡(luò)中的節(jié)點,大電網(wǎng)互通關(guān)系是它們的邊�；趶�(fù)雜網(wǎng)絡(luò)理論,構(gòu)建微網(wǎng)群網(wǎng)絡(luò)模型分析其復(fù)雜網(wǎng)絡(luò)特性,并在此基礎(chǔ)上研究微網(wǎng)群網(wǎng)絡(luò)風(fēng)險元傳遞情況。(6)微網(wǎng)結(jié)構(gòu)智能仿生優(yōu)化模型研究。研究風(fēng)險的主要目的是為了規(guī)避風(fēng)險和控制風(fēng)險,微網(wǎng)是一個局部區(qū)域供能系統(tǒng),規(guī)避和控制微網(wǎng)風(fēng)險的主要措施是優(yōu)化微網(wǎng)的結(jié)構(gòu)配置。在考慮能源資源、分布式能源、儲能和負(fù)載的復(fù)雜匹配關(guān)系和分析分布式電源功率外特性的基礎(chǔ)上,建立了供電可靠性、經(jīng)濟(jì)成本和環(huán)境效益的微網(wǎng)容量優(yōu)化配置的目標(biāo)函數(shù),并采用混沌優(yōu)化多目標(biāo)遺傳算法進(jìn)行求解。(7)微網(wǎng)備用容量優(yōu)化模型研究。根據(jù)光伏、風(fēng)力發(fā)電為代表的可再生能源具有間歇性、隨機性及不確定性等特點,提出了用于平滑可再生能源發(fā)電系統(tǒng)功率輸出及微網(wǎng)聯(lián)絡(luò)線功率波動的儲能系統(tǒng)容量優(yōu)化方法。利用離散傅里葉變換對可再生能源輸出功率、微網(wǎng)平滑聯(lián)絡(luò)線功率所需可控功率輸出進(jìn)行頻譜分析,優(yōu)化選取滿足約束的儲能系統(tǒng)所需最優(yōu)容量。本文在能源大數(shù)據(jù)背景下,將風(fēng)險元傳遞理論引入到了微網(wǎng)的風(fēng)險管理中。豐富了風(fēng)險管理的內(nèi)容,能夠為微網(wǎng)運營風(fēng)險管理提供更多的依據(jù),具有較強的理論價值和現(xiàn)實意義。
[Abstract]:The microgrid is in new energy power generation under the background of new technology in distributed generation based on Microgrid. As an organic part of the smart grid, for energy saving, power generation, has important significance to the quality of power supply requirements. The micro research on related technologies of network operation has been widespread concern and attention all over the world. The micro network integration a variety of input energy (solar, wind, biomass and other conventional fossil fuels), a variety of loads, various units of energy conversion (fuel cell, micro gas turbines, internal combustion engines, storage systems, etc.) is a chemical, thermodynamic, nonlinear electrodynamics behavior of coupled complex systems. Many types of micro network. Distributed power supply is subject to natural conditions, with strong uncertainty in operation, intermittent, complexity, diversity, the characteristics of stability, the power quality characteristics are very different from traditional power system At the same time, in the microgrid load by the regional environment, social factors and economic policies, but also to the micro network brings more uncertainty. Liquidity led to a close contact electrical characteristics of each unit in the network, when a unit of risk will affect the other unit, and even lead to other the unit also has the risk, in this connection the grid closely to risk in during possible transfer. With the deepening of the construction of Internet energy and propulsion, power grid operation and equipment inspection / monitoring the amount of data generated exponentially, and gradually formed a large energy data concern in today's information science. Energy big data contains a large amount of information and knowledge of the energy of the Internet, effective use of energy data will provide a strong guarantee for efficient operation of microgrid. The energy station in the context of large data, based on the risk element transmission From the first generation theory, and Research on two aspects: how to identify the power micro grid operation risk; and then studied the microgrid between bidirectional and network type risk element transmission path, from simple to complex reveals the micro network risk element transmission mechanism; finally, to reduce or eliminate the risk element transmission of microgrid optimization method, providing network risk management decision-making system for more micro management. The main contents of this paper include the following aspects: (1) energy data innovation micro network risk management research. First analysis of wind power generation photovoltaic power big data, big data and data for radio and TV University, pointed out that the microgrid operation process, Risk Dynamic Changes of microgrid between and then energy in the background of big data, can innovation micro network risk management research, the risk element theory can better analyze and explain the micro risk network interaction . (2) microgrid power generation risk element recognition research. By the natural environment conditions, micro grid power generation uncertainty is one of the main reasons for the risks of microgrid, energy data for the micro grid power generation risk provides a new way for yuan mining, based on wind power and Guang Fufa power prediction first, deterministic prediction of microgrid trend, then the Markov chain and Latin hypercube sampling combined, respectively, the joint probability distribution of the micro grid current conditions and non conditional joint probability distribution is predicted. According to the evolution characteristics of wind speed and illumination, calculation of micro probability distribution network power flow and the confidence interval can be the risk element recognition result of forecasting uncertainty. (3) research on micro grid electricity risk recognition. One of the main factors of risk uncertainty in microgrid microgrid operation with electricity is caused by natural fire moths. Inspired by the phenomenon, in order to improve the prediction accuracy for the optimization of least squares support vector machine algorithm, put forward a prediction model of least squares support vector machine and Puhuo optimization algorithm mixed load based on, in order to achieve a more accurate prediction of power load, the accurate identification of micro grid power consumption risk element (4). A transmission model of microgrid based on two-way risk element type. Data analysis found that the risk element is not only in the microgrid between one-way transmission, there is mutual transfer. The scenery storage in grid connected microgrid risk management as the research object, put forward the two-way risk element transmission model, given the shortage of risk value the calculation method and influence factors. The proposed transfer path has enriched the original risk element transmission theory, and reveals a kind of objective phenomenon of risk transfer. (5) micro network network risk element transmission Study on the model. And a plurality of micro grid interconnection network, connected by large power grid, accord with the characteristics of the network, each micro network can be viewed as nodes in the network, network communication relationship is their side. Based on complex network theory, constructing micro network network model analysis of the characteristics of the complex network, and then based on the research of micro network network risk element transmission. (6) model of bionic optimization of micro intelligent network structure. The main objective of the study was to avoid the risks and control risks, microgrid is a local energy supply system, avoid and control risk is the main measures of micro grid optimization of microgrid. In consideration of energy resources, distributed energy, energy storage and load matching relation and complex analysis of distributed power characteristics on the basis of the establishment of the power supply reliability, capacity of microgrid economic cost and environmental benefits The objective function of optimization configuration, which is solved by using chaos optimization multi-objective genetic algorithm. (7) micro network reserve capacity optimization model. According to the research on photovoltaic, wind power as the representative of the renewable energy is intermittent, random and uncertain characteristics, for smooth power renewable energy power generation system and Microgrid power output the fluctuation of energy storage capacity optimization method is proposed. The system output power of renewable energy by using discrete Fourier transform, the microgrid smooth tie line power required for control of power output spectrum analysis, optimal selection of meet the constraints of energy storage system for optimal capacity in energy. In this paper, the background of big data, the risk element transfer theory to the risk management of microgrid. Enrich the content of risk management, it can provide more evidences for microgrid operation risk management theory, has strong value and price Real meaning.

【學(xué)位授予單位】：華北電力大學(xué)(北京)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2017
【分類號】：TM727

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