Optimization of regional spinning reserve capacity based on improved genetic algorithm

LI Hui1; LI Ning1; LIANG Wen-ju2

English Version Reader LoginJournal Login

您当前的位置：

首页 >

文章列表页 >

Optimization of regional spinning reserve capacity based on improved genetic algorithm

更新时间：2025-11-18

- Optimization of regional spinning reserve capacity based on improved genetic algorithm
- Vol. 29, Issue 3, Pages: 1-4(2009)
- 作者机构：
  
  1. 湖南省电力公司调度通信局
  2. 湖南大学电气与信息工程学院
- 作者简介：
- 基金信息：
- DOI：
  CLC： TM73
- Published：2009
- 稿件说明：
移动端阅览
[1]李辉,李宁,梁文举.基于改进遗传算法的区域旋转备用容量的优化[J].湖南电力,2009,29(03):1-4.

LI Hui1, LI Ning1, LIANG Wen-ju2. Optimization of regional spinning reserve capacity based on improved genetic algorithm[J]. 2009, 29(3): 1-4.
[1]李辉,李宁,梁文举.基于改进遗传算法的区域旋转备用容量的优化[J].湖南电力,2009,29(03):1-4. DOI：

LI Hui1, LI Ning1, LIANG Wen-ju2. Optimization of regional spinning reserve capacity based on improved genetic algorithm[J]. 2009, 29(3): 1-4. DOI：

摘要

在改进遗传算法的基础上

提出了区域购买旋转备用成本最小的数学模型和求解方法。模型按照备用交易"协调运作"、备用价格按区域统一边际价格结算并计及了联络线传输容量上下限、备用机组提供容量上下限、旋转备用爬坡率等约束条件。算例表明本算法能更加有效地达到或接近全局最优解

区域备用容量在优化后降低了获取的备用容量

充分体现了区域间的备用支持

优化了各地的电力资源。

Abstract

Based on improved genetic algorithm

the mathematical model and solution for minimum cost of spinning reserve in regions were presented.Restriction conditions

such as reserve deal coordination

reserve price settled according to regional uniform margin price and considering the upper and lower limits of transmission capacity of contact lines

the maximum and minimum capacity of reserve units

and spinning reserve climbing rate

et al

were considered in the mode.The calculation indicated that this algorithm can be more efficient in achieving or approaching the global optimization

The genetic algorithm method takes advantage of reserve supports between the regions

decreases total reserve procurement

and optimizes the power resources.

关键词

Keywords

references

Views

182

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Frame design of aerial work platform in substation based on genetic algorithm

Analysis of Influence of Spinning Reserve on Hunan Power Grid Voltage Stability

Optimization of Wind and Light Power Generation Prediction Model Based on RNA-CS Hybrid Algorithm

Short Term Power Forecasting Method of Improved BP Neural Network Based on Characteristic Analysis

Short-Term Load Forecasting Method Based on QPSO-ELM Combined with GA Theory

Related Author

TAN Qing-ke

WANG Bo-zhong

HE Quan

LI Fucai

XIANG Meng

HU Zhen

ZHONG Wei

CHEN Daojun

Related Institution

State Grid Hunan Electric Power Corporation Maintenance Company

State Grid Hunan Electric Power Company Limited

State Grid Hunan Electric Power Company Limited Research Institute

Hunan University of Technology

China Energy Engineering Group Hunan Electric Power Design Institute Co.,Ltd.

AI问答

⁰