本文選題：分布式能源 + 虛擬發(fā)電廠�。� 參考：《上海交通大學(xué)》2014年博士論文

【摘要】：在我國(guó)大力促進(jìn)分布式能源發(fā)展和智能電網(wǎng)信息化、互動(dòng)化建設(shè)的背景下，考慮分布式能源與我國(guó)當(dāng)前電力調(diào)度模式的協(xié)調(diào)，解決分布式能源發(fā)電(用戶)與電網(wǎng)之間的矛盾，使得分布式能源主動(dòng)參與電網(wǎng)調(diào)度是值得研究的問(wèn)題。主要研究?jī)?nèi)容和成果如下： 結(jié)合虛擬發(fā)電廠運(yùn)行特點(diǎn)，提出一種帶優(yōu)先級(jí)的多目標(biāo)優(yōu)化方法，將虛擬發(fā)電廠的技術(shù)層和經(jīng)濟(jì)層兩層管理理念具體化為帶有優(yōu)先級(jí)的目標(biāo)函數(shù)，并采用基于滿意度表示的兩步分解方法求解。建立虛擬發(fā)電廠和配電網(wǎng)的聯(lián)合優(yōu)化控制模型并采用近似動(dòng)態(tài)規(guī)劃方法求解。在與配電網(wǎng)的聯(lián)合優(yōu)化時(shí)虛擬發(fā)電廠的快速控制功能可以改善配電網(wǎng)的運(yùn)行指標(biāo)，如電網(wǎng)的頻率偏差、電壓偏差、功率控制等。 基于充放儲(chǔ)一體化電站的能量特性，研究了多個(gè)充放儲(chǔ)電站入網(wǎng)的電網(wǎng)協(xié)調(diào)調(diào)度。利用電動(dòng)汽車和電池的充放儲(chǔ)過(guò)程的功率轉(zhuǎn)移功能，改進(jìn)SCOPF方法實(shí)現(xiàn)充放儲(chǔ)節(jié)點(diǎn)功率調(diào)度的時(shí)間和空間解耦。首先采用虛擬發(fā)電廠的思想將區(qū)域電網(wǎng)中所有的分布式能源和充放儲(chǔ)電站看作為一個(gè)整體，優(yōu)化得到24個(gè)時(shí)段的調(diào)度結(jié)果，實(shí)現(xiàn)時(shí)間上的解耦；然后考慮電網(wǎng)拓?fù)浣Y(jié)構(gòu)，優(yōu)化充放儲(chǔ)功率實(shí)現(xiàn)空間解耦。 提出一種內(nèi)點(diǎn)法結(jié)合隨機(jī)調(diào)節(jié)因子更新的方法來(lái)求解基于機(jī)會(huì)約束規(guī)劃的隨機(jī)最優(yōu)調(diào)度模型，采用半不變量和Cornish-Fisher級(jí)數(shù)結(jié)合的方法來(lái)計(jì)算機(jī)會(huì)約束的等效條件。引入與機(jī)會(huì)約束概率相關(guān)的調(diào)節(jié)因子，將隨機(jī)最優(yōu)調(diào)度問(wèn)題轉(zhuǎn)化為可采用內(nèi)點(diǎn)法求解的最優(yōu)潮流模型，并提出調(diào)節(jié)因子的迭代更新方法實(shí)現(xiàn)隨機(jī)環(huán)境下的功率解最優(yōu)。最后以IEEE14和IEEE118節(jié)點(diǎn)系統(tǒng)為例驗(yàn)證所提方法并分析了所提方法的精度分析、靈敏度分析和計(jì)算量。 提出一種多優(yōu)化控制中心互動(dòng)協(xié)調(diào)調(diào)度模式并應(yīng)用于含分布式能源控制中心的電網(wǎng)優(yōu)化調(diào)度。以優(yōu)化控制中心為單位來(lái)分析分布式能源控制中心主動(dòng)優(yōu)化的特點(diǎn)。將傳統(tǒng)的電網(wǎng)調(diào)度模型也轉(zhuǎn)化為一個(gè)優(yōu)化控制中心。各優(yōu)化控制中心可按照自己的資源組成特點(diǎn)和多個(gè)優(yōu)化目標(biāo)并行獨(dú)立優(yōu)化以制定出力計(jì)劃�；诨�(dòng)協(xié)調(diào)調(diào)度模式，提出了并行優(yōu)化和優(yōu)先優(yōu)化兩種優(yōu)化方式和正常和異常兩種運(yùn)行情況，并設(shè)計(jì)了兩種優(yōu)化方式和兩種運(yùn)行情況的協(xié)調(diào)優(yōu)化方法。針對(duì)多優(yōu)化控制中心并行優(yōu)化中的沖突問(wèn)題，，采用協(xié)同優(yōu)化來(lái)協(xié)調(diào)優(yōu)化控制中心間的耦合變量不一致，并通過(guò)協(xié)調(diào)滿意度設(shè)定值來(lái)解決多優(yōu)化控制中心并行優(yōu)化的目標(biāo)沖突問(wèn)題。最后采用不同運(yùn)行情況下的算例仿真來(lái)說(shuō)明和驗(yàn)證所提的模型和方法。
[Abstract]:Under the background of promoting the development of distributed energy and the informatization of smart grid in China, considering the coordination of distributed energy and the current power dispatching mode, the contradiction between distributed energy generation (user) and power grid is solved. The active participation of distributed energy in power grid dispatching is a problem worth studying. The main research contents and results are as follows: according to the operation characteristics of virtual power plant, a multi-objective optimization method with priority is proposed. The idea of technology layer and economic layer of virtual power plant is concretely transformed into objective function with priority and solved by two-step decomposition method based on satisfaction representation. The joint optimal control model of virtual power plant and distribution network is established and solved by approximate dynamic programming method. In the joint optimization with distribution network, the fast control function of virtual power plant can improve the operation index of distribution network, such as frequency deviation, voltage deviation, power control and so on. Based on the energy characteristics of integrated charging, discharging and storage power stations, the coordinated dispatching of multiple charging and discharging storage power stations into the network is studied. Using the power transfer function of charging and discharging process of electric vehicle and battery, the SCOPF method is improved to decouple the time and space of charging and discharging node power scheduling. Firstly, all the distributed energy and charging and discharging power stations in the regional power network are considered as a whole by using the idea of virtual power plant, and the scheduling results of 24 periods are optimized to realize the decoupling in time, and then the topology structure of the power network is considered. Spatial decoupling is realized by optimizing charging and storing power. An interior point method combined with stochastic adjustment factor updating method is proposed to solve the stochastic optimal scheduling model based on chance constrained programming. The semi-invariant and Cornish-Fisher series method is used to solve the equivalent condition of computer constraint. The stochastic optimal scheduling problem is transformed into an optimal power flow model which can be solved by the interior point method, and an iterative updating method of the adjustment factor is proposed to realize the optimal power solution in the random environment. Finally, the proposed method is verified by using IEEE 14 and IEEE 118 bus system as an example, and the accuracy analysis, sensitivity analysis and computational complexity of the proposed method are analyzed. An interactive and coordinated scheduling model for multi-optimal control centers is proposed and applied to power grid optimal scheduling with distributed energy control centers. The characteristics of active optimization of distributed energy control center are analyzed in this paper. The traditional power grid dispatching model is also transformed into an optimal control center. Each optimization control center can make a force plan according to its own resource composition characteristics and multiple optimization objectives in parallel and independent optimization. Based on the interactive coordination scheduling mode, two optimization modes, parallel optimization and priority optimization, and two normal and abnormal operation conditions are proposed, and two optimization methods and two coordinated optimization methods are designed. In order to solve the conflict problem in parallel optimization of multi-optimization control centers, the coordinated optimization is used to coordinate the coupling variables between the control centers. The goal conflict problem of parallel optimization of multi-optimization control center is solved by coordinating satisfaction set value. Finally, the proposed model and method are illustrated and verified by the simulation examples under different operation conditions.
【學(xué)位授予單位】：上海交通大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2014
【分類號(hào)】：TM73

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