| 引用本文: | 孙东磊,韩学山,李文博.风储共存于配网的动态优化潮流分析[J].电力自动化设备,2015,35(8): |
| SUN Donglei,HAN Xueshan,LI Wenbo.Analysis of dynamic optimal power flow for distribution network with wind power and energy storage[J].Electric Power Automation Equipment,2015,35(8): |
|
| 摘要: |
| 为适应未来电网发展，在日前时间级，建立以向输电网购电量最小为目标的风储共存配网动态优化潮流的数学模型。该模型在配网原有条件的基础上，考虑了普通异步风电系统、双馈感应风电系统和蓄电池储能系统的特性和限制条件。基于GAMS平台，通过调用CONOPT求解器对该模型进行求解。以12节点风储共存的配网为例，对多种方式进行机制分析发现，普通异步风电系统、双馈感应风电系统和蓄电池储能系统共存于配网中运行时，可解决有功、无功和电压间存在相互牵制的矛盾，考虑风储运行特性的动态优化可更有效地接纳风电，使资源得到有效配置。 |
| 关键词: 配电 风电 储能 动态优化潮流 四象限调节特性 模型 |
| DOI： |
| 分类号: |
| 基金项目:国家自然科学基金资助项目（51177091，51477091）；国家重点基础研究发展计划（973计划）项目（2013CB228205） |
|
| Analysis of dynamic optimal power flow for distribution network with wind power and energy storage |
|
SUN Donglei1, HAN Xueshan1, LI Wenbo2
|
|
1.Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education，Shandong University，Ji’nan 250061，China;2.Electric Power Institute of State Grid Shandong Electric Power Company，Ji’nan 250002，China
|
| Abstract: |
| To adapt to the development of future power system，a mathematical model of day-ahead dynamic optimal power flow is built for the distribution network with wind power and energy storage，which takes the minimum electricity purchase from transmission system as its objective and considers the characteristics and limitation conditions of common asynchronous wind power system，double-fed induction wind power system and battery storage system besides the basic operation limits of distribution network. Based on the GAMS platform，the CONOPT solver is adopted to solve the model. Taking a 12-bus distribution network with wind power and energy storage as an example，the mechanism analysis on several patterns shows that，with the dynamic optimization considering the operating characteristics of distribution network with wind power and energy storage，the resources are effectively allocated，the diversion among active power，reactive power and voltage avoided and the wind power more effectively accommodated. |
| Key words: voltage sag monitoring optimization fuzzy control fuzzy threshold observation index BPSO algorithm models |
