【摘要】：風(fēng)能是可持續(xù)的清潔能源。在化石能源日益枯竭的情況下,風(fēng)電大規(guī)模并網(wǎng)是新能源電力系統(tǒng)的必然趨勢(shì)。但是風(fēng)電存在著間歇性強(qiáng)、波動(dòng)性大、可控性差等不足,大量的風(fēng)電涌入使電網(wǎng)的運(yùn)行特性變得復(fù)雜。這要求電網(wǎng)自動(dòng)發(fā)電控制系統(tǒng)(Automatic Generation Control,AGC)能及時(shí)響應(yīng)能源與負(fù)荷的快速、大范圍波動(dòng)。進(jìn)一步涉及到系統(tǒng)穩(wěn)定運(yùn)行約束、分區(qū)域調(diào)節(jié)并探究區(qū)域控制性能、協(xié)調(diào)快慢機(jī)組以及考慮市場(chǎng)因素的綜合問(wèn)題,應(yīng)當(dāng)尋求新的思路來(lái)發(fā)展和完善現(xiàn)有的AGC方法。本文首先對(duì)AGC的系統(tǒng)構(gòu)成、工作原理及評(píng)價(jià)標(biāo)準(zhǔn)進(jìn)行闡述。在此基礎(chǔ)上,本文提出互聯(lián)電網(wǎng)AGC動(dòng)態(tài)控制策略,著力解決在充分利用風(fēng)能的情況下如何保證電力系統(tǒng)安全、經(jīng)濟(jì)運(yùn)行的問(wèn)題。在控制策略研究中考慮了互聯(lián)電網(wǎng)系統(tǒng)頻率和聯(lián)絡(luò)線功率變化對(duì)AGC控制的影響,利用互聯(lián)電網(wǎng)“互助”的優(yōu)勢(shì)提高系統(tǒng)容納風(fēng)電的能力;控制策略研究中考慮了AGC機(jī)組的動(dòng)態(tài)特性,包括機(jī)組的可調(diào)容量、運(yùn)行狀態(tài)、爬坡能力以及機(jī)組最小持續(xù)爬坡時(shí)間,以充分協(xié)調(diào)利用全網(wǎng)AGC資源來(lái)提高系統(tǒng)抵消風(fēng)電波動(dòng)的能力;控制策略在保證CPS長(zhǎng)期有效的條件下充分利用“CPS標(biāo)準(zhǔn)不要求短期內(nèi)ACE必須過(guò)零”所帶來(lái)的調(diào)節(jié)空間提高系統(tǒng)抵御風(fēng)電擾動(dòng)的能力;控制策略權(quán)衡了動(dòng)態(tài)優(yōu)化過(guò)程中經(jīng)濟(jì)性目標(biāo)和指標(biāo)性目標(biāo)的比重,在消納風(fēng)電過(guò)程中可保證電網(wǎng)運(yùn)行的安全性和經(jīng)濟(jì)性。AGC動(dòng)態(tài)控制策略模型是一個(gè)多約束、大規(guī)模、多時(shí)段的復(fù)雜優(yōu)化問(wèn)題。為此,本文利用粒子群算法(Particle Swarm Optimization,PSO)進(jìn)行求解運(yùn)算,設(shè)計(jì)含多種信息的粒子,采用帶動(dòng)態(tài)慣性權(quán)重的更新速度,制定符合實(shí)際運(yùn)行特性的粒子分解及修改規(guī)則,并詳細(xì)闡述算法步驟。通過(guò)對(duì)某控制區(qū)域仿真實(shí)驗(yàn)表明,在大規(guī)模風(fēng)電并網(wǎng)條件下,本AGC動(dòng)態(tài)控制策略在協(xié)調(diào)全網(wǎng)AGC資源、穩(wěn)定電網(wǎng)頻率、長(zhǎng)期滿足CPS指標(biāo)以及降低調(diào)節(jié)費(fèi)用方面具有顯著優(yōu)勢(shì)。
[Abstract]:Wind energy is a sustainable and clean energy source. Under the condition that fossil energy is exhausted day by day, large-scale wind power grid is the inevitable trend of new energy power system. However, wind power has some disadvantages, such as strong intermittent, large volatility, poor controllability and so on. A large number of wind power influx makes the operation characteristics of power grid complex. This requires the automatic generation control system (Automatic Generation Control,AGC) to respond to the rapid and wide fluctuation of energy and load in time. Furthermore, it is necessary to find a new way to develop and perfect the existing AGC method, which involves the stable operation constraints of the system, regional regulation and exploration of regional control performance, coordination of speed and slow units, and consideration of market factors. This paper first describes the system structure, working principle and evaluation criteria of AGC. On this basis, this paper puts forward the dynamic control strategy of AGC in interconnected power network, and tries to solve the problem of how to ensure the safe and economical operation of power system under the condition of making full use of wind energy. In the study of control strategy, the influence of frequency and tie-line power change on AGC control is taken into account, and the ability of holding wind power is improved by taking advantage of "mutual aid" of interconnected power grid. In the study of control strategy, the dynamic characteristics of the AGC unit are considered, including the adjustable capacity, the running state, the climbing ability and the minimum continuous climbing time of the unit. In order to fully coordinate the use of AGC resources in the whole network to improve the ability of the system to offset wind power fluctuations; Under the condition that CPS is effective for a long time, the control strategy makes full use of the adjustment space brought by "CPS standard does not require that ACE must cross zero in the short term" to improve the system's ability to resist wind power disturbance. The control strategy balances the proportion of the economic target and the target in the process of dynamic optimization. The dynamic control strategy model of AGC can ensure the safety and economy of the power network operation in the process of wind power consumption, which is a multi-constraint and large-scale. Complex optimization problem with multiple time periods. In this paper, the particle swarm optimization (Particle Swarm Optimization,PSO) algorithm is used to solve the problem, and the particle with various information is designed. The particle decomposition and modification rules are formulated by using the renewal speed with dynamic inertial weight. The algorithm steps are described in detail. The simulation results of a control area show that under the condition of large-scale wind power grid connection, the AGC dynamic control strategy has significant advantages in coordinating AGC resources, stabilizing the power network frequency, meeting the CPS index for a long time and reducing the adjustment cost.
【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)】：TP18;TM732

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本文編號(hào)：2220718