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计及需求侧资源的大规模风电消纳随机机组组合模型

刘小聪 王蓓蓓 李扬 王珂

中国电机工程学报Issue(14):3714-3723,10.
中国电机工程学报Issue(14):3714-3723,10.DOI:10.13334/j.0258-8013.pcsee.2015.14.028

计及需求侧资源的大规模风电消纳随机机组组合模型

Stochastic Unit Commitment Model for High Wind Power Integration Considering Demand Side Resources

刘小聪 1王蓓蓓 1李扬 1王珂2

作者信息

  • 1. 江苏省智能电网技术与装备重点实验室 东南大学,江苏省南京市 210096
  • 2. 中国电力科学研究院,江苏省南京市 210003
  • 折叠

摘要

Abstract

The growing scale of wind power had brought new challenges on power system operation. This paper focused on a two-stage stochastic unit commitment model for high wind power penetration. The model flexibly combined day-ahead price-based demand response and intra-day incentive-based demand response participating power balance based on the features of two-stage stochastic programming. It explored the complementary relationship between price-based and incentive-based demand response programs on response characteristics. The day-ahead price-based demand response was associated with first-stage decision and it could guide users to follow the change of wind power output to integrate the part of wind power with higher probability; while the intra-day incentive-based demand response was associated with second-stage decision to compensate the deviation among multiple scenarios and it could also reduce the uncertainty of price-based demand response to some extent. Case study indicates that the model in this paper can maximum the effectiveness of demand response on flexibility at minimum cost and increase the levels of wind power integration.

关键词

能源互联网/需求响应/随机规划/风电消纳/机组组合

Key words

energy internet/demand response/stochastic programming/wind power integration/unit commitment

分类

信息技术与安全科学

引用本文复制引用

刘小聪,王蓓蓓,李扬,王珂..计及需求侧资源的大规模风电消纳随机机组组合模型[J].中国电机工程学报,2015,(14):3714-3723,10.

基金项目

国家自然科学基金项目(51277028,71471036);国家电网公司科学技术项目(DZ71-14-042)。 National Natural Science Foundation of China (51277028,71471036) (51277028,71471036)

Key Technology Project of State Grid Corporation of China (DZ71-14-042) (DZ71-14-042)

中国电机工程学报

OA北大核心CSCDCSTPCD

0258-8013

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