發(fā)布時間：2018-04-26 01:04

  本文選題：梯級水電站群 + 發(fā)電調(diào)度　； 參考：《華中科技大學(xué)》2014年博士論文

【摘要】：低碳經(jīng)濟(jì)模式下流域梯級水電站群及其互聯(lián)電力系統(tǒng)中交織著各種物質(zhì)流與信息流的映射關(guān)系,其聯(lián)合優(yōu)化運行受降雨、徑流、用電、用水的不確定性以及各類電力能源發(fā)電特性和電網(wǎng)輸電能力等因素影響,是一類大型的、多尺度、強耦合的非線性約束優(yōu)化問題。傳統(tǒng)的流域梯級水電站群聯(lián)合調(diào)度模式由于存在長、中、短期調(diào)度難以銜接、水電站優(yōu)化運行與火電站調(diào)度方式配合不緊、電力電量平衡相對孤立以及以經(jīng)濟(jì)效益為核心而很少考慮機(jī)組污染物排放等問題,已無法適應(yīng)新時期流域梯級水電站群及其互聯(lián)電力系統(tǒng)節(jié)能發(fā)電調(diào)度模式的實際工程需求,迫切需要研究新的理論與方法,以滿足區(qū)域電力系統(tǒng)安全、經(jīng)濟(jì)運行和水電能源資源優(yōu)化配置的需求。本文圍繞流域梯級水電站群及其互聯(lián)電力系統(tǒng)聯(lián)合優(yōu)化運行的若干關(guān)鍵問題,以梯級水電能源安全高效利用為目標(biāo),與系統(tǒng)科學(xué)理論、群體智能優(yōu)化算法以及多目標(biāo)進(jìn)化優(yōu)化技術(shù)相結(jié)合,對流域梯級水電站群及其互聯(lián)電力系統(tǒng)聯(lián)合優(yōu)化運行的理論與方法開展系統(tǒng)、深入的研究,取得了一些具有基礎(chǔ)理論方法和實際工程應(yīng)用價值的研究成果。本文的主要研究內(nèi)容和創(chuàng)新點包括： (1)針對傳統(tǒng)優(yōu)化方法難以解決的“維數(shù)災(zāi)”和容易陷入局部最優(yōu)等問題,提出了一類基于自適應(yīng)混沌人工蜂群算法的水庫群優(yōu)化調(diào)度方法。提出了改進(jìn)的雇傭蜂算子、選擇概率計算方法以及自適應(yīng)改變率參數(shù)方法。該算法引入了基于logistic映射的混沌局部搜索策略,有效的提高了算法效率和尋優(yōu)能力。將自適應(yīng)混沌人工蜂群算法應(yīng)用于標(biāo)準(zhǔn)測試函數(shù)和水電站群聯(lián)合發(fā)電優(yōu)化調(diào)度模型的求解中,結(jié)果表明本文提出的方法相比較傳統(tǒng)方法能更有效的解決流域水電站群及其互聯(lián)電力系統(tǒng)優(yōu)化運行問題。 (2)圍繞流域水電站群及其互聯(lián)電力系統(tǒng)優(yōu)化運行的時空變量多,約束條件復(fù)雜,優(yōu)化目標(biāo)多樣等問題,本研究將人工蜂群算法引入多目標(biāo)進(jìn)化優(yōu)化理論架構(gòu),提出基于Pareto優(yōu)化的自適應(yīng)多目標(biāo)人工蜂群算法。算法采用小生境技術(shù)的外部群體空間保優(yōu)策略,并提出基于逐步優(yōu)化算法的局部搜索策略。將本文提出的自適應(yīng)多目標(biāo)人工蜂群算法進(jìn)行函數(shù)測試,并應(yīng)用于三峽梯級水電站長期發(fā)電優(yōu)化調(diào)度,以及復(fù)雜水火電力系統(tǒng)多目標(biāo)優(yōu)化調(diào)度。結(jié)果表明本文提出的方法能有效解決調(diào)度目標(biāo)沖突問題,一次性獲得滿足約束條件的Pareto優(yōu)化解集。與文獻(xiàn)中列出的方法進(jìn)行比較表明,本文提出的方法能獲得更廣的Pareto優(yōu)化前沿和更好的收斂效果。 (3)針對復(fù)雜水火電能源系統(tǒng)優(yōu)化運行中水力電力聯(lián)系嵌套約束問題,本文提出了一種多尺度循環(huán)修正約束處理方法。該方法將等式約束中的違反量采用多尺度循環(huán)修正方法分配到各個時段對應(yīng)的變量中,有效實現(xiàn)了算法進(jìn)化過程中不可行解向可行解的轉(zhuǎn)化。將本文提出的約束處理方法應(yīng)用于復(fù)雜水火電能源及其互聯(lián)電力系統(tǒng)優(yōu)化運行的模型求解,結(jié)果顯示此方法能有效獲得可行解。 (4)為解決徑流隨機(jī)性對優(yōu)化調(diào)度的影響問題,提出了三峽入庫流量的隨機(jī)徑流模擬方法,并采用機(jī)會約束方法研究長期優(yōu)化調(diào)度建模問題。此外,為解決傳統(tǒng)的流域梯級水電站群聯(lián)合調(diào)度模式存在不同調(diào)度期,優(yōu)化調(diào)度難以銜接的問題,提出了一種變長調(diào)度期嵌套優(yōu)化方法。該方法將長期優(yōu)化調(diào)度結(jié)果作為中期優(yōu)化調(diào)度的輸入條件,采用基于蒙特卡洛的人工蜂群算法進(jìn)行問題的求解。將此方法應(yīng)用于葛洲壩-三峽梯級水電站的中長期嵌套優(yōu)化模型的求解中,結(jié)果表明本文提出的方法能獲得在不同置信度下的精細(xì)化年內(nèi)長期優(yōu)化調(diào)度結(jié)果并有效描述約束違反風(fēng)險與優(yōu)化效益的對應(yīng)關(guān)系,為指導(dǎo)實際生產(chǎn)運行提出了有意義的理論指導(dǎo)。
[Abstract]:In the low carbon economy model, the cascade hydropower stations and their interconnected power systems are interwoven with the mapped relationship between the material flow and the information flow. The combined optimization of the cascade hydropower stations is influenced by the factors such as rainfall, runoff, power consumption, water use uncertainty, power generation characteristics and power transmission capacity of various kinds of power. It is a large, multi scale and strong coupling. The combined scheduling model of the traditional cascade hydropower stations is difficult to link up because of the long, medium and short term scheduling. The optimal operation of the hydropower station is not fit with the dispatching mode of the thermal power station, the power and electricity balance is relatively isolated and the economic benefit is the core, and the pollutant emission is seldom considered. It is unable to adapt to the actual engineering requirements of the cascade hydropower stations and the energy saving power generation dispatching mode of the interconnected power systems in the new period. The new theories and methods are urgently needed to meet the needs of the regional power system security, the economic operation and the optimal allocation of the hydropower resources. The key problems of the system combined optimization operation are aimed at the efficient utilization of the cascade hydropower energy security and the system science theory, the swarm intelligence optimization algorithm and the multi-objective evolutionary optimization technology to carry out a systematic and in-depth study on the theory and method of the combined optimization operation of the cascade hydropower stations and their interconnected power systems in the basin. Some research results with basic theoretical methods and practical engineering applications have been obtained. The main contents and innovations of this paper include:
(1) aiming at the problem of "dimension disaster" which is difficult to solve in the traditional optimization method and easy to fall into the local optimal problem, a class of optimal scheduling method of reservoir group based on adaptive chaotic artificial bee colony algorithm is proposed. The improved employment bee operator, the selection probability calculation method and the self adaptable change rate parameter method are proposed. The algorithm is introduced based on L. The chaotic local search strategy of ogistic maps effectively improves the efficiency and optimization of the algorithm. The adaptive chaotic artificial bee colony algorithm is applied to the solution of the standard test function and the optimal scheduling model of the joint power generation of hydropower stations. The results show that the method proposed in this paper can be more effective in solving the hydropower station. The problem of optimal operation of groups and their interconnected power systems.
(2) in this study, the artificial bee colony algorithm is introduced into the multi-objective evolutionary optimization theory framework, and the adaptive multi target artificial bee colony algorithm based on Pareto optimization is proposed. The algorithm adopts the exterior of the niche technology. A local search strategy for group space optimization is proposed and a local search strategy based on progressive optimization algorithm is proposed. The adaptive multi-objective artificial bee colony algorithm proposed in this paper is used to perform function testing, and is applied to the optimization and scheduling of long-term power generation in the Three Gorges cascade hydropower stations, as well as the multi target optimal scheduling of complex water and fire power systems. The results show that the proposed method can be used in this paper. In order to solve the problem of scheduling target conflict effectively, the Pareto optimal solution set to satisfy the constraint conditions is obtained at one time. The comparison with the methods listed in the literature shows that the proposed method can obtain a wider range of Pareto optimization frontiers and better convergence effect.
(3) in this paper, a multi scale cyclic modified constraint processing method is proposed to solve the nested constraint problem in the optimization operation of the complex hydroelectric energy system. This method assigns the violation of the equality constraint to the corresponding variables in each period by using the multiscale cyclic correction method, and effectively implements the algorithm evolution process. The constraint processing method proposed in this paper is applied to the model solution of the optimal operation of complex hydro electric energy and interconnected power system. The results show that this method can effectively obtain a feasible solution.
(4) in order to solve the problem of the effect of runoff randomness on optimal scheduling, a stochastic runoff simulation method of the Three Gorges reservoir flow is proposed, and the opportunity constraint method is used to study the long-term optimal scheduling modeling. In addition, in order to solve the problem of different scheduling period for the traditional cascade hydropower station group joint scheduling model, the problem of optimal scheduling is difficult to link up. A nested optimization method of variable length scheduling period is proposed. This method uses the long-term optimal scheduling results as the input condition of the mid-term optimization scheduling, and uses the Monte Carlo based artificial bee colony algorithm to solve the problem. This method is applied to the solution of the middle and long term nested optimization model of the Gezhouba Dam Three Gorges cascade hydropower station. The method proposed in this paper can obtain the long-term optimal scheduling results under different confidence, and effectively describe the corresponding relationship between the risk of constraint violation and the optimization benefit, and put forward meaningful theoretical guidance for guiding the actual production operation.

【學(xué)位授予單位】：華中科技大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2014
【分類號】：TV737;TM732;TP18

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本文編號：1803772