电力系统非平滑和多目标经济调度优化方法研究

发布时间：2018-01-10 20:17

本文关键词：电力系统非平滑和多目标经济调度优化方法研究　出处：《浙江大学》2014年博士论文　论文类型：学位论文

【摘要】：考虑机组阀点效应、禁运区和多燃料的经济调度模型是对电力系统经济调度问题更精确的描述,但该模型非凸、不连续、不可微和具有大量局部最优解的特性使其求解更加困难,目前多采用进化算法进行求解,然而进化算法耗时较长,精度不能得到保证,尤其在大规模电力系统中实用性较差。为此本文通过对模型最优解进行分析,提出新的快速有效的求解方法。在提高发电调度的经济性的同时还须降低其污染物排放,故本文还提出了一种新的多目标优化算法用于求解电力系统多目标调度问题。本文主要内容及创新点如下：提出考虑机组阀点效应的电力系统经济调度问题的局部最优解的必要条件,得到问题的两类局部最优解。第一类局部最优解中至多只有一台机组不处于奇异点位置,其中奇异点位置包括机组阀点和出力上下限。分析表明可舍弃第二类局部最优解,这使问题更易求解,从而只需从第一类局部最优解中寻找问题的近似全局最优解。提出一种分维最速下降法(Dimensional steepest decline method, DSD)用于快速有效求解非平滑经济调度问题,其计算量随机组数量的增加呈2阶增长。算例结果表明,DSD可有效求解考虑机组阀点效应、禁运区和多燃料以及网损的经济调度问题。与选取的最好的几个进化算法相比,DSD在精度和计算量方面的优势突出,尤其是在大规模电力系统中其优势更加突出。算例结果还表明在经济调度中考虑机组阀点效应可带来约2%到9%的经济效益。提出考虑机组禁运区的电力系统经济调度问题的最优解的必要条件,提出一种快速λ迭代法求解此问题。3个算例系统的结果表明该方法精度高,计算量非常小,与现有最好的方法相比其优势突出,尤其是在含有大量机组的、更多机组含有禁运区的大规模电力系统中该方法在精度和计算量上的优势均更加突出。基于多目标KKT条件,提出了多目标混合λ迭代法和牛顿法(Multi-objective λ-iteration and Newton method, MOλIN)用于求解环境经济调度问题。该方法无需人为设置权系数或罚系数等参数。MOλIN中选定一台机组称为固定出力机组,固定出力机组的不同出力对应不同的帕累托最优解,所有帕累托最优解构成问题的解集,对于固定出力机组的选取进行优化以提高求解效率。提出一种预判断机制,可减小MOXIN的计算量。指出了问题的帕累托最优解中各机组出力具有等差比微增率的特性。在2个系统的分析结果表明MOXIN可有效求解环境经济调度问题,与多目标粒子群优化算法相比,可得到精度更高、分布更均匀的帕累托前沿,耗时更短。
[Abstract]:Considering the valve point effect of the unit, the economic dispatch model with embargoed area and multi-fuel is a more accurate description of the economic dispatch problem of power system, but the model is non-convex and discontinuous. The non-differentiable and local optimal solutions make it more difficult to solve. At present, evolutionary algorithms are often used to solve them. However, evolutionary algorithms take a long time and the accuracy can not be guaranteed. Especially in large-scale power system, the practicability is poor, so this paper analyzes the optimal solution of the model. A new fast and effective solution method is proposed. It is necessary to reduce the pollutant emission while improving the economy of power generation scheduling. Therefore, a new multi-objective optimization algorithm is proposed to solve the power system multi-objective scheduling problem. The main contents and innovations of this paper are as follows:. A necessary condition for the local optimal solution of economic dispatch problem of power system considering the effect of unit valve point is presented. Two kinds of local optimal solutions of the problem are obtained. In the first kind of local optimal solutions, at most, only one unit is not in the singularity position. The singular point position includes the unit valve point and the upper and lower limit of the output force. The analysis shows that the local optimal solution of the second kind can be abandoned, which makes the problem easier to solve. Thus, we only need to find the approximate global optimal solution of the problem from the first kind of local optimal solution. A fractal dimension steepest descent method is presented. Dimensional steepest decline method. DSD) is used to solve the non-smooth economic scheduling problem quickly and effectively, and the increase of the number of random groups is of the second order. The numerical results show that DSD can effectively solve the valve point effect of the unit. Economic scheduling problems in embargoed zones and multi-fuel and network losses. Compared with the best evolutionary algorithms selected, DSD is superior in accuracy and computational complexity. Especially in large-scale power system, its advantages are more prominent. The numerical results also show that considering the valve point effect in economic dispatch can bring economic benefit of about 2% to 9%. The power system considering the unit embargoed area is put forward. Necessary conditions for optimal solution of economic scheduling problems. A fast 位 iteration method is proposed to solve this problem. The results of three numerical examples show that the method has high accuracy and low computational cost, and it has more advantages than the best one, especially in the case of large number of units. In the large scale power system with more units containing embargoed area, the advantages of this method in accuracy and computational complexity are more prominent. The method is based on the multi-objective KKT condition. The multiobjective mixed 位 iteration method and Newton method are proposed for multi-object 位 -iteration and Newton method. MO 位 IN) is used to solve the environmental and economic scheduling problem. In this method, it is not necessary to choose a unit in the parameters such as weight coefficient or penalty coefficient, such as artificial weight coefficient or penalty coefficient, which is called fixed output unit. The Pareto optimal solution is corresponding to the different output force of the fixed output unit, and all Pareto optimal solutions constitute the solution set of the problem. In order to improve the efficiency of solving the problem, a prejudgment mechanism is proposed to optimize the selection of fixed output units. The calculation cost of MOXIN can be reduced. It is pointed out that in the Pareto optimal solution of the problem, the output force of each unit has the characteristic of equal difference ratio slight increase rate. The analysis results of two systems show that MOXIN can effectively solve the environmental and economic adjustment. The degree problem. Compared with the multi-objective particle swarm optimization algorithm, the Pareto front with higher precision and more uniform distribution can be obtained, and the time is shorter.
【学位授予单位】：浙江大学
【学位级别】：博士
【学位授予年份】：2014
【分类号】：TM73

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