SIA OpenIR  > 工业控制网络与系统研究室
基于光伏预测的微电网能源随机优化调度
Alternative TitleEnergy stochastic optimization scheduling for micro-grid based on photovoltaic forecasting
李鹏梅; 臧传治; 李鹤鹏; 李忠文; 杨建宏
Department工业控制网络与系统研究室
Source Publication传感器与微系统
ISSN1000-9787
2015
Volume34Issue:2Pages:61-64
Indexed ByCSCD
CSCD IDCSCD:5333027
Contribution Rank1
Funding Organization国家自然科学基金资助项目(61100159) ; 中国科学院知识创新工程重要方向性项目(KGCX2-EW-104)
Keyword微电网 不确定性 随机规划 粒子群优化算法 能源优化调度
Abstract

可再生能源的间歇性和负荷的随机性对微电网能源管理系统(EMS)产生了巨大的挑战。在随机环境下的能源优化调度问题在微电网的研究中具有重要意义。以微电网中光伏发电系统的功率预测为基础,将光伏预测误差当做随机变量,建立了一种基于期望模型的能源随机优化调度模型。用Monte Carlo模拟方法生成了光伏发电预测误差的情景集,应用粒子群优化算法来解决随机优化调度模型。通过与确定性模型产生的调度方案相对比,证明了随机优化调度模型更加有效。

Other Abstract

Intermittent and stochastic loads of renewable energy generate great challenges to micro-grid energy management systems ( EMS). Issue of energy optimal scheduling in research of micro-grid under stochastic environment has important meaning. An energy stochastic optimization scheduling model based on expectation model is set up by considering uncertainties associated with photovoltaic forecasting. A scenarios of photovoltaic forecasting error is generated Monte Carlo model approach is employed to characterize the random nature of uncertainty according to probability density function. Then, particle swarm optimization algorithm is applied to solve stochastic optimization scheduling model. Through comparing with scheduling scheme generated by deterministic model, the effectiveness of proposed stochastic optimization scheduling model is verified. 

Language中文
Citation statistics
Cited Times:3[CSCD]   [CSCD Record]
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/15651
Collection工业控制网络与系统研究室
Affiliation1.中国科学院沈阳自动化研究所中国科学院网络化控制系统重点实验室
2.中国科学院大学
3.内蒙古上都发电有限责任公司
Recommended Citation
GB/T 7714
李鹏梅,臧传治,李鹤鹏,等. 基于光伏预测的微电网能源随机优化调度[J]. 传感器与微系统,2015,34(2):61-64.
APA 李鹏梅,臧传治,李鹤鹏,李忠文,&杨建宏.(2015).基于光伏预测的微电网能源随机优化调度.传感器与微系统,34(2),61-64.
MLA 李鹏梅,et al."基于光伏预测的微电网能源随机优化调度".传感器与微系统 34.2(2015):61-64.
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