基于改进细菌群体趋药性算法的风-蓄-火联合调度

doi:10.11930/j.issn.1004-9649.2014.11.95.5

中国电力 ›› 2014, Vol. 47 ›› Issue (11): 95-100.DOI: 10.11930/j.issn.1004-9649.2014.11.95.5

基于改进细菌群体趋药性算法的风-蓄-火联合调度

韩花荣, 张晶, 徐婧劼, 范镇南

国网四川省电力公司技能培训中心,四川成都 610000

收稿日期:2014-06-14 出版日期:2014-11-18 发布日期:2015-12-08
作者简介:韩花荣（1981—）,女,山西寿阳人,讲师,从事电力系统及其自动化研究。E-mail: 1810699707@qq.com
基金资助:
中央高校基本科研业务费资助项目（CDJXS11151152）

Research on Joint Dispatch of Wind-Storage-Thermal System Based on Improved Bacterial Colony Chemotaxis Algorithm

HAN Hua-rong, ZHANG Jing, XU Jing-jie, FAN Zhen-nan

Skill Training Center, State Grid Electric Power Company Sichuan Province, Chengdu 610000, China

Received:2014-06-14 Online:2014-11-18 Published:2015-12-08
Supported by:
This work is supported by Fundamental Research Funds for the Central Universites (CDJXS11151152)

摘要/Abstract

摘要： 具有随机性与波动性的风电直接接入电网后,给电网的调度运行带来很大的风险。针对风电出力的随机性,结合抽水蓄能电站削峰填谷特点,利用风电场景模拟风电出力波动,编制日前发电计划,引入时前调度模型修正各机组出力,建立了含风-蓄-火联合系统的优化调度模型,并利用改进的细菌群体趋药性算法求解该模型。用IEEE-10机组标准算例进行仿真,仿真结果验证了所建调度优化模型的合理性及算法的有效性,模型可供制定含风电和抽水蓄能的电力系统发电调度方案时参考。

关键词: 随机性, 波动性, 风电出力, 抽水蓄能, 削峰填谷, 日前发电计划, 时前调度, 细菌群体趋药算法

Abstract: Wind power has the characteristics of randomness and volatility. When integrated to the grid, the wind power brings a high risk to the dispatcher. With consideration of the randomness of wind power output and the peak load shifting characteristics of pumped storage power station, a day-ahead generation plan can be made by simulating the wind power fluctuations scene. The hour-ahead scheduling model can be introduced to amend each unit output so as to establish optimal scheduling model of the wind-storage-fire joint system. Meanwhile, the improved bacterial colony chemotaxis algorithm is then introduced to solve the model. Finally, IEEE-10 crew Benchmarks simulation is applied for the analysis. The simulation results demonstrate the effectiveness and rationality of the optimal scheduling models, and can provide a theoretical reference for scheduling the dispatching scheme of the power system containing wind power and pumped storage.

Key words: randomness, volatility, wind power output, pumped storage station, cut a peak to fill valley, day-ahead generation plan, hour-ahead dispatch, bacterial colony chemotaxis algorithm

中图分类号:

TM732

韩花荣, 张晶, 徐婧劼, 范镇南. 基于改进细菌群体趋药性算法的风-蓄-火联合调度[J]. 中国电力, 2014, 47(11): 95-100.

HAN Hua-rong, ZHANG Jing, XU Jing-jie, FAN Zhen-nan. Research on Joint Dispatch of Wind-Storage-Thermal System Based on Improved Bacterial Colony Chemotaxis Algorithm[J]. Electric Power, 2014, 47(11): 95-100.

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https://www.electricpower.com.cn/CN/Y2014/V47/I11/95

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基于改进细菌群体趋药性算法的风-蓄-火联合调度

Research on Joint Dispatch of Wind-Storage-Thermal System Based on Improved Bacterial Colony Chemotaxis Algorithm

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模态框（Modal）标题

基于改进细菌群体趋药性算法的风-蓄-火联合调度

Research on Joint Dispatch of Wind-Storage-Thermal System Based on Improved Bacterial Colony Chemotaxis Algorithm

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