摘要
利用负荷曲线的单调性及广义粒子群算法动态划分出负荷的子时间段落,并运用能量轨迹的方法融合子段落,求取特征断面,从而较为细致地描述了系统负荷曲线攀峰降谷的过程,更能表征出系统的实际负荷水平。建立了兼顾节能环保的多目标日发电计划模型,结合最优潮流并引入基于满意度和贴近度将多目标转化为单目标优化模型求解,并可根据决策者的主观愿望对目标满意度进行调整,制定出以经济成本低并兼顾污染气体排放量少为目标的日发电计划。IEEE30机算例证实了方法的可行性。
This paper divides the sub-processes of load curve dynamically with the monotonicity of load curve and the extended PSO algorithm and gets the characteristics section. It fuses the sub-processes with the energy trajectory methods in order to describe the climbing peak and descending valley of the load curve closely, and characterizes the actual load curve. The multi-objective daily generation scheduling model is built based on energy conservation and envirotunental protection. The goal satisfaction degree and goal close degree are introduced to transform multi-objective into the single-objective decision-making model. The optimal power flow is used to Solve the problem. Decision-maker can make interactive solution via adjusting goal satisfaction degree and close degree, so as to receive satisfactory results balancing each aspect and make the daily generation scheduling based on the goal of low-economic cost and low-polluted gas discharge. The example oflEEE 30-bus system shows the efficiency of the proposed method.
出处
《电力系统保护与控制》
EI
CSCD
北大核心
2011年第18期44-48,55,共6页
Power System Protection and Control
基金
高等学校博士学科点专项科研基金(20060213042)
哈尔滨工业大学科研创新基金资助(HIT.NSRIF.2008.54))
关键词
广义粒子群算法
能量轨迹融合方法
节能减排
多目标决策
最优潮流
extended PSO
energy trajectory method
energy-saving reduction
multi-objective decision-making
optimal power flow
