应用于风电场出力平滑的多尺度多指标储能配置

GAN Wei

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应用于风电场出力平滑的多尺度多指标储能配置

更新时间：2025-08-13

- 应用于风电场出力平滑的多尺度多指标储能配置
- Automation of Electric Power Systems Vol. 43, Issue 9, Pages: 92-98(2019)
- 作者机构：
  
  强电磁工程与新技术国家重点实验室(华中科技大学电气与电子工程学院),湖北省,武汉市,430074
- 作者简介：
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- Published：2019
- 稿件说明：
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GAN Wei. [J]. Automation of electric power systems, 2019, 43(9): 92-98.
DOI：

GAN Wei. [J]. Automation of electric power systems, 2019, 43(9): 92-98. DOI：

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，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1 min与10 min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 integration of the energy storage system(ESS)in wind farms is required to mitigate the wind power fluctuations so that the requirements of wind power integration can be satisfied. To solve this problem

a multi-scale multi-index ESS sizing model applied to wind power fluctuation mitigation is proposed

which considers the penalty costs. Firstly

a piecewise linearized evaluation method for wind power fluctuations is proposed

which considers the penalty costs. 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 1 min time-scale and 10 min time-scale are considered in the model. Thirdly

the large M method is introduced to solve the model accurately. 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 actual wind farm data.

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