考虑风电随机模糊不确定性的电力系统多目标优化调度计划研究
提出了一种考虑风电随机模糊多重不确定性的电力系统多目标调度计划新模型和相应的算法。首先，依据风电并网后的电力系统不确定环境实际提出以随机模糊变量描述风电功率，以区间形式表述负荷预测的不确定性。其次，以燃煤机组的购电费用和污染气体排放量最小为目标函数，构建考虑风电和负荷预测值不确定性的电力系统随机模糊多目标交易计划模型。然后，提出利用负荷的不等式区间约束将遗传算法的初始寻优种群模糊化，提出采用概率密度分布描述解的随机模糊分布特征，从而可获得兼顾多重不确定特征多目标交易计划解集。最后，以含10台燃煤机组和一个大型等值风电场的某省级系统为例进行模型和算法的求解验证，结果表明了提出模型和算法的合理性和...
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| Published in | 电力系统保护与控制 Vol. 41; no. 1; pp. 150 - 156 |
|---|---|
| Main Author | |
| Format | Journal Article |
| Language | Chinese |
| Published |
智能电网运行与控制湖南省重点实验室长沙理工大学,湖南 长沙 410004%甘肃省电力公司天水供电公司,甘肃 天水 741000%国网信息通信有限公司,北京 100761
2013
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1674-3415 |
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| Abstract | 提出了一种考虑风电随机模糊多重不确定性的电力系统多目标调度计划新模型和相应的算法。首先，依据风电并网后的电力系统不确定环境实际提出以随机模糊变量描述风电功率，以区间形式表述负荷预测的不确定性。其次，以燃煤机组的购电费用和污染气体排放量最小为目标函数，构建考虑风电和负荷预测值不确定性的电力系统随机模糊多目标交易计划模型。然后，提出利用负荷的不等式区间约束将遗传算法的初始寻优种群模糊化，提出采用概率密度分布描述解的随机模糊分布特征，从而可获得兼顾多重不确定特征多目标交易计划解集。最后，以含10台燃煤机组和一个大型等值风电场的某省级系统为例进行模型和算法的求解验证，结果表明了提出模型和算法的合理性和有效性。 |
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| AbstractList | TM614%TM73; 提出了一种考虑风电随机模糊多重不确定性的电力系统多目标调度计划新模型和相应的算法.首先,依据风电并网后的电力系统不确定环境实际提出以随机模糊变量描述风电功率,以区间形式表述负荷预测的不确定性.其次,以燃煤机组的购电费用和污染气体排放量最小为目标函数,构建考虑风电和负荷预测值不确定性的电力系统随机模糊多目标交易计划模型.然后,提出利用负荷的不等式区间约束将遗传算法的初始寻优种群模糊化,提出采用概率密度分布描述解的随机模糊分布特征,从而可获得兼顾多重不确定特征多目标交易计划解集.最后,以含10台燃煤机组和一个大型等值风电场的某省级系统为例进行模型和算法的求解验证,结果表明了提出模型和算法的合理性和有效性. 提出了一种考虑风电随机模糊多重不确定性的电力系统多目标调度计划新模型和相应的算法。首先，依据风电并网后的电力系统不确定环境实际提出以随机模糊变量描述风电功率，以区间形式表述负荷预测的不确定性。其次，以燃煤机组的购电费用和污染气体排放量最小为目标函数，构建考虑风电和负荷预测值不确定性的电力系统随机模糊多目标交易计划模型。然后，提出利用负荷的不等式区间约束将遗传算法的初始寻优种群模糊化，提出采用概率密度分布描述解的随机模糊分布特征，从而可获得兼顾多重不确定特征多目标交易计划解集。最后，以含10台燃煤机组和一个大型等值风电场的某省级系统为例进行模型和算法的求解验证，结果表明了提出模型和算法的合理性和有效性。 |
| Abstract_FL | This paper presents a novel dispatch planning of the power system considering the stochastic and fuzzy characteristics and multiple uncertainties of large-scale wind power. Firstly, based on the actual uncertainty of power system integrating wind power, wind speed is modeled as random fuzzy variable, and the fluctuation of the load forecast uncertainty is expressed by the interval. Secondly, considering the multi-attribute uncertainty of wind power and load, a novel multi-objective unit commitment model which minimizes both the power purchase cost and emission of atmospheric pollutants of thermal generators is proposed. Then the initial optimization populations of genetic algorithm are fuzzed by inequality interval constraint of load. The probability density distribution is used to describe the stochastic and fuzzy characteristics of the solution. Therefore, the solution set of multi-objective considering multiple uncertain characteristics can be achieved. Finally, the proposed generation dispatch method is tested on a provincial grid containing ten thermal generators and a large wind farm. The results show the effectiveness of the proposed model and the approach. This work is supported by National Natural Science Foundation of China (No. 51277015). |
| Author | 马瑞 康仁 姜飞 熊龙珠 李凌霄 徐慧明 |
| AuthorAffiliation | 智能电网运行与控制湖南省重点实验室长沙理工大学,湖南长沙410004 甘肃省电力公司天水供电公司,甘肃天水741000 国网信息通信有限公司,北京100761 |
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| Keywords | wind power probability density distribution 概率密度分布 改进遗传算法 improved genetic algorithm 风力发电 多目标优化 multi-objective optimization 随机模糊变量 random fuzzy variable |
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| Notes | wind power; random fuzzy variable; multi-objective optimization; improved genetic algorithm; probability densitydistribution 41-1401/TM This paper presents a novel dispatch planning of the power system considering the stochastic and fuzzy characteristics and multiple uncertainties of large-scale wind power. Firstly, based on the actual uncertainty of power system integrating wind power, wind speed is modeled as random fuzzy variable, and the fluctuation of the load forecast uncertainty is expressed by the interval. Secondly, considering the multi-attribute uncertainty of wind power and load, a novel multi-objective unit commitment model which minimizes both the power purchase cost and emission of atmospheric pollutants of thermal generators is proposed. Then the initial optimization populations of genetic algorithm are fuzzed by inequality interval constraint of load. The probability density distribution is used to describe the stochastic and fuzzy characteristics of the solution. Therefore, the solution set of |
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| Publisher | 智能电网运行与控制湖南省重点实验室长沙理工大学,湖南 长沙 410004%甘肃省电力公司天水供电公司,甘肃 天水 741000%国网信息通信有限公司,北京 100761 |
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| Snippet | 提出了一种考虑风电随机模糊多重不确定性的电力系统多目标调度计划新模型和相应的算法。首先，依据风电并网后的电力系统不确定环境实际提出以随机模糊变量描述风电功率，以... TM614%TM73; 提出了一种考虑风电随机模糊多重不确定性的电力系统多目标调度计划新模型和相应的算法.首先,依据风电并网后的电力系统不确定环境实际提出以随机模糊变量描述... |
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| SubjectTerms | 多目标优化 改进遗传算法 概率密度分布 随机模糊变量 风力发电 |
| Title | 考虑风电随机模糊不确定性的电力系统多目标优化调度计划研究 |
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