| 引用本文: | 张新松,袁越,茅靖峰,顾菊平,曹阳,华亮,郭晓丽.基于蒙特卡洛模拟的电池储能系统容量优化配置[J].电力自动化设备,2017,37(4): |
| ZHANG Xinsong,YUAN Yue,MAO Jingfeng,GU Juping,CAO Yang,HUA Liang,GUO Xiaoli.BESS capacity optimization based on Monte Carlo simulation[J].Electric Power Automation Equipment,2017,37(4): |
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| 摘要: |
| 电池储能系统(BESS)可使风电场具备一定的发电计划跟踪能力，有必要研究风电场中的BESS容量优化问题。根据BESS技术特性与风功率波动特性制定发电计划，BESS分两部分运行，分别处于充、放电状态，交替平抑风功率与发电计划间的正、负偏差。一旦任一部分BESS到达满充或满放状态，则同时切换两部分BESS的工作状态。采用蒙特卡洛模拟技术对风-储混合电站一年内的运行状况进行模拟，并计算发电计划跟踪概率与BESS运行利润。在确保风-储混合电站按期望置信度跟踪发电计划的基础上，依据利润最大化的原则对BESS容量进行优化。基于某风电场历史数据的仿真实验证明了所提模型及算法的有效性。 |
| 关键词: 风电 发电计划 电池储能系统 蒙特卡洛模拟 运行利润 发电计划跟踪概率 |
| DOI：10.16081/j.issn.1006-6047.2017.04.012 |
| 分类号:TM73 |
| 基金项目:国家自然科学基金资助项目(51407097,61673226)；江苏省六大人才高峰资助计划(2015-ZNDW-009)；江苏省自然科学基金资助项目(BK20141238) |
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| BESS capacity optimization based on Monte Carlo simulation |
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ZHANG Xinsong1, YUAN Yue2, MAO Jingfeng1, GU Juping1, CAO Yang2, HUA Liang1, GUO Xiaoli1
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1.School of Electrical Engineering, Nantong University, Nantong 226019, China;2.College of Energy and Electrical Engineering, Hohai University, Nanjing 210098, China
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| Abstract: |
| Since the wind farm equipped with BESS(Battery Energy Storage System) has certain ability to follow the generation schedule, it is necessary to research the BESS capacity optimization of wind farm. The generation schedule is determined according to the technical characteristic of BESS together with the fluctuation characteristic of wind power. The BESS is divided into two parts operating in the charging and discharging modes respectively to alternatively compensate the positive and negative deviations between generation schedule and wind power. Once any part arrives at the corresponding fully-charged or fully-discharged condition, the operating mode of each part is switched simultaneously. The yearly operation of a hybrid wind-BESS station is simulated by Monte Carlo simulation and the generation schedule following probability and operational profit of BESS are calculated. While it is guaranteed that the hybrid wind-BESS station follows the generation schedule at the expected confidence level, the BESS capacity is optimized for the maximum profit. The simulative experiment based on the historical data of a wind farm verifies the effectiveness of the proposed model and algorithm. |
| Key words: wind power generation schedule battery energy storage system Monte Carlo simulation operational profit generation schedule following probability |
