基于遗传算法发电规划的BOT电厂成本效益分析

被引：5

作者：

邢卫国

吴复立

机构：

[1] 香港大学电机与电子工程学系!香港

来源：

电力系统自动化 | 2000年 / 02期

关键词：

BOT电厂; 成本效益分析; 发电扩展规划; 遗传算法;

D O I：

暂无

中图分类号：

TM71 [理论与分析];

学科分类号：

080802 ;

摘要：

分析了电力市场发展中 BOT( build operate transfer)形式私有发电厂对系统规划和运行的影响 ,并且基于发电扩展规划 ,提出了 BOT电厂的成本效益分析模型。为了较好地处理 BOT电厂的附加约束 ,而且更有效地求解发电规划问题 ,提出了一个基于遗传算法的发电规划方法。通过对一个实际系统的测试表明 ,所提出的方法可行、有效。

引用

页码：56 / 60

页数：5

共 12 条

[1]

The BOT Option: Conflicts and Compromises. David A K,Fernando P N. Energy Policy . 1995

[2]

Genetic Algorithms+Data Structures=Evolution Programs. Michalewicz Z. . 1996

[3]

Risk Modelling in Energy Contracts Between Host Utilities and BOT Plant Investors. David A K. IEEE Transactions on Energy Conversion . 1996

[4]

Integrating Expert Systems with Dynamic Programming in Generation Expansion Planning. David A K,Zhao R D. IEEE Transactions on Power Systems . 1989

[5]

A Hybrid GeneticAlgorithm / Dynam ic Program ming Approach toOptim al L ong- Term Generation Expansion Planning. Park Y M,Park J B,Won J R. Electrical Power and Energy Systems . 1 998

[6]

Planning for New ElectricGeneration Technologies—— A Stochastic DynamicProgramming Approach. Dapkus W D,Nowe T R. IEEE Trans on PowerApparatus and Systems . 1 984

[7]

Flexible Generation Mix Under Multiobjectives and Uncertainties. Tanabe R,Yasuda K,Yokoyama R,et al. IEEE Transactions on Power Systems . 1993

[8]

Stochastic Generation Expansion Planning by Means of Stochastic Dynamic Programming. Mo B,Hegge J,Wangensteen I. IEEE Transactions on Power Systems . 1991

[9]

Integrating Non-Utility Generation into the NEPOOL Resource Planning Process. Bentley B W. IEEE Transactions on Power Systems . 1988

[10]

Private Investm ent in Power and Deviationsfrom the L east Cost Expansion Plan. David A K. IEEProceedings—— Generation,Transm ission andDistribution . 1 995

← 1 2 →