本文選題：水火電系統(tǒng)　切入點(diǎn)：節(jié)能環(huán)保　出處：《華中科技大學(xué)》2014年碩士論文

【摘要】：水火電系統(tǒng)短期優(yōu)化調(diào)度在電力系統(tǒng)運(yùn)行中具有可觀的經(jīng)濟(jì)效益，它一直是國(guó)內(nèi)外學(xué)者的研究熱點(diǎn)。對(duì)于電力系統(tǒng)調(diào)度問(wèn)題，傳統(tǒng)調(diào)度模型僅追求系統(tǒng)經(jīng)濟(jì)效益最大化，使水電廠盡可能多發(fā)電，以火電廠耗煤最小為目標(biāo)。隨著現(xiàn)代化社會(huì)的建設(shè)，能源短缺和環(huán)境惡化問(wèn)題日漸嚴(yán)重，節(jié)能環(huán)保是實(shí)施可持續(xù)發(fā)展戰(zhàn)略的必然選擇，將減少火電廠廢氣排放作為調(diào)度問(wèn)題的優(yōu)化目標(biāo)具有重要意義。許多學(xué)者成功應(yīng)用智能優(yōu)化算法求解水火電短期優(yōu)化調(diào)度問(wèn)題，然而大多數(shù)智能算法都有早熟收斂的缺點(diǎn)，并且對(duì)于問(wèn)題復(fù)雜約束條件的處理方法也較少。本文對(duì)引力搜索算法進(jìn)行改進(jìn)，提高其搜索性能，并提出多目標(biāo)的引力搜索算法，用于解決綜合考慮經(jīng)濟(jì)效益和環(huán)境保護(hù)的水火電系統(tǒng)短期優(yōu)化調(diào)度問(wèn)題。本文的主要研究工作如下： 1)針對(duì)引力搜索算法容易陷入局部最優(yōu)的缺陷，本文提出一種改進(jìn)的引力搜索算法(IGSA)。首先在速度更新過(guò)程引入個(gè)體記憶和群體信息，，提出改進(jìn)的速度和位置更新公式。然后在算法進(jìn)化過(guò)程中引入混沌變異操作，使算法從局部最優(yōu)解附近轉(zhuǎn)到全局范圍內(nèi)搜索最優(yōu)解，增強(qiáng)其全局尋優(yōu)性能。并采用基于選擇操作的種群進(jìn)化規(guī)則，保證種群總是向最優(yōu)解方向進(jìn)化。為了處理多目標(biāo)優(yōu)化問(wèn)題，本文將非支配排序和聚集距離引人引力搜索算法中，提出帶混沌變異的非支配排序引力搜索算法(NSGSA-CM)。通過(guò)基準(zhǔn)問(wèn)題測(cè)試表明，NSGSA-CM算法有較好的搜索性能，適用于解決高維多目標(biāo)優(yōu)化問(wèn)題。 2)本文在節(jié)能環(huán)保的重要背景下，建立了綜合考慮經(jīng)濟(jì)效益和環(huán)境保護(hù)的水火電系統(tǒng)短期優(yōu)化調(diào)度模型。該模型追求電力系統(tǒng)運(yùn)行時(shí)燃料消耗最小和污染氣體排放最少，是一個(gè)雙目標(biāo)優(yōu)化問(wèn)題。并通過(guò)引入基于時(shí)段的可變權(quán)重，將該問(wèn)題轉(zhuǎn)化為單目標(biāo)優(yōu)化問(wèn)題，使其可以用改進(jìn)的引力搜索優(yōu)化算法求解。 3)在處理問(wèn)題眾多約束條件時(shí)，本文采用一系列啟發(fā)式策略使個(gè)體滿足約束。對(duì)于動(dòng)態(tài)水量平衡約束，首先將違反約束水量平均分成若干份，然后將其調(diào)整到隨機(jī)選出的時(shí)段對(duì)應(yīng)的下泄流量中，直到所有水量調(diào)整完從而滿足約束。在處理水庫(kù)庫(kù)容約束時(shí)，基于超過(guò)庫(kù)容限制的水量，在可行域內(nèi)同對(duì)當(dāng)前時(shí)段和后一時(shí)段的下泄流量做出等量調(diào)整，在保持水庫(kù)動(dòng)態(tài)水量平衡的情況下使庫(kù)容約束得到滿足。采用基于火電廠優(yōu)先級(jí)的規(guī)則調(diào)整各火電廠每時(shí)段的出力，以滿足系統(tǒng)負(fù)荷平衡約束。 4)為了驗(yàn)證IGSA和NSGSA-CM算法求解水火電短期優(yōu)化調(diào)度問(wèn)題的有效性，本文選取了兩個(gè)實(shí)例進(jìn)行仿真計(jì)算。實(shí)例結(jié)果表明，與文獻(xiàn)中的結(jié)果相比，IGSA和NSGSA-CM算法有更好的全局優(yōu)化性能，在滿足所有約束的情況下獲得了較小的燃煤成本與污染氣體排放�？芍�，文中的算法與約束處理策略解決水火電系統(tǒng)短期調(diào)度問(wèn)題是可行和有效的。
[Abstract]:Short-term optimal dispatching of hydro-thermal power system has considerable economic benefits in the operation of power system. It has always been a hot research topic of scholars at home and abroad. For the power system scheduling problem, the traditional dispatching model only pursues the maximization of system economic benefits. With the construction of modern society, the problems of energy shortage and environmental deterioration are becoming more and more serious. Energy saving and environmental protection is the inevitable choice to implement the strategy of sustainable development. It is of great significance to reduce exhaust gas emissions from thermal power plants as the optimization objective of scheduling problems. Many scholars have successfully applied intelligent optimization algorithms to solve short-term optimal scheduling problems for hydro-thermal power plants. However, most intelligent algorithms have the disadvantage of premature convergence. In this paper, the gravity search algorithm is improved to improve its search performance, and a multi-objective gravity search algorithm is proposed. The main work of this paper is as follows: (1) to solve the short-term optimal scheduling problem of hydro-thermal power system considering economic benefits and environmental protection comprehensively. 1) aiming at the defect that gravity search algorithm is easy to fall into local optimum, an improved gravity search algorithm is proposed in this paper. Firstly, individual memory and group information are introduced into the speed update process. An improved speed and position updating formula is proposed, and then chaotic mutation operation is introduced in the evolution of the algorithm, which makes the algorithm move from the local optimal solution to the global optimal solution, and search for the optimal solution in the global range. The global optimization performance is enhanced, and the population evolution rule based on the selection operation is adopted to ensure that the population always evolves towards the optimal solution. In order to deal with the multi-objective optimization problem, the undominated ordering and aggregation distance are introduced into the gravitational search algorithm in this paper. An undominated sorting gravitational search algorithm with chaotic mutation is proposed. The benchmark test shows that the NSGSA-CM algorithm has good search performance and is suitable for solving high dimensional multiobjective optimization problems. 2) under the important background of energy saving and environmental protection, this paper establishes a short-term optimal dispatching model of hydro-thermal power system considering economic benefits and environmental protection. The model pursues the minimum fuel consumption and the least emission of polluting gas when the power system is running. By introducing variable weight based on time interval, the problem is transformed into a single objective optimization problem, which can be solved by an improved gravitational search optimization algorithm. 3) in dealing with many constraints, a series of heuristic strategies are used to make individuals satisfy the constraints. For dynamic water balance constraints, first of all, the amount of water in violation of constraints is divided into several parts. It is then adjusted to the lower discharge corresponding to the randomly selected time period until all the water is adjusted to meet the constraints. In dealing with the reservoir capacity constraints, based on the amount of water exceeding the reservoir capacity limit, In the feasible region, the same amount of downward discharge is adjusted for the current period and the later period, Under the condition of keeping the dynamic water balance of the reservoir, the reservoir capacity constraints are satisfied, and the output force of each period of time is adjusted based on the priority rule of the thermal power plant to satisfy the system load balance constraint. 4) in order to verify the effectiveness of IGSA and NSGSA-CM algorithms in solving hydro-thermal power short-term optimal scheduling problem, two examples are selected for simulation. The results show that the algorithm has better global optimization performance than the results in literature. The low cost of coal combustion and the emission of polluting gas are obtained under all constraints. It can be seen that the algorithm and constraint treatment strategy in this paper is feasible and effective to solve the short-term scheduling problem of hydro-thermal power system.
【學(xué)位授予單位】：華中科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TM73

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