文章摘要
甘伟,郭剑波,艾小猛,等.应用于风电场出力平滑的多尺度多指标储能配置[J].电力系统自动化. DOI: 10.7500/AEPS20180815002.
GAN Wei,GUO Jianbo,AI Xiaomeng, et al.Multi-scale Multi-index Sizing of Energy Storage Applied to Fluctuation Mitigation of Wind Farm[J].Automation of Electric Power Systems. DOI: 10.7500/AEPS20180815002.
应用于风电场出力平滑的多尺度多指标储能配置
Multi-scale Multi-index Sizing of Energy Storage Applied to Fluctuation Mitigation of Wind Farm
DOI:10.7500/AEPS20180815002
关键词: 风电并网  储能配置  出力平滑  多时间尺度  混整线性规划
KeyWords: wind power integration  energy storage sizing  fluctuation mitigation  multi-time scale  mixed integer linear programming  
上网日期:2019-03-13
基金项目:国家自然科学基金项目;国家电网公司科技项目
作者单位E-mail
甘伟 华中科技大学 weigan@hust.edu.cn 
郭剑波 新能源与储能运行控制国家重点实验室(中国电力科学研究院有限公司) guojianbo@epri.sgcc.com.cn 
艾小猛 华中科技大学 xiaomengai1986@foxmail.com 
姚 伟 华中科技大学 w.yao@hust.edu.cn 
杨 波 中国电力科学研究院(南京) yangbo@epri.sgcc.com.cn 
姚良忠 中国电力科学研究院 yaoliangzhong@epri.sgcc.com.cn 
文劲宇 华中科技大学 jinyu.wen@hust.edu.cn 
摘要:
      风电场出力具有较强的波动性与不确定性,往往需配置储能以平滑其出力波动、满足风电并网导则要求。针对这一问题,本文提出了应用于风电场出力平滑的多尺度多指标储能配置模型。首先提出分段线性化的风电出力波动越限惩罚评价方法,并基于此构建了以考虑越限惩罚、储能成本以及限电损失的总运行成本最小为目标的多指标储能配置模型。该模型同时兼顾风电并网1min与10min的多时间尺度波动越限要求。为精确求解该模型,采用大M法将原有非线性模型转换成混合整数线性规划模型,通过调用Gurobi求解器求解。最后,基于一周的实际风电场数据,仿真验证了所提方法的有效性。
Abstract:
      Due to the high volatility and uncertainty of wind power, the integartion of the energy storage system (ESS) at the wind farms is required to mitigate the wind power fluctuations, so that the requirements of wind power inter-gration can be satisfied. To solve this problem, a multi-scale and multi-index ESS sizing model applied to wind power fluctuation mitigation is proposed. Firstly, a piecewise linearized penalty costs evaluation method for wind power fluctuations is proposed. Secondly, a multi-index ESS sizing model is proposed. It minimizes the sum of penalty costs, ESS investment and wind curtailment costs. Also, the fluctuation limits of 1min time-scale and 10min time-scale are considered in the model. Thirdly, the large M method is introduced to solve the model ac-curately. The original nonlinear model is transformed into a mixed integer linear programming model, which is solved by Gurobi. Finally, the effectiveness of the proposed model is validated based on one-week""s actual wind farm data.
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