| 摘要: |
| 【目的】针对传统优化算法的不足，将微分进化算法应用到水电站水库优化调度问题中，建立新的优化算法模型。【方法】建立基于微分进化算法的水电站水库优化调度模型，并给出具体求解步骤。为验证算法的有效性，将其应用于具体水电站水库的优化调度计算中，最后将该方法与遗传算法的计算结果进行了对比。【结果】实例计算结果表明，与遗传算法相比，微分进化算法收敛速度快，可调参数少，计算精度高，稳定性好，且该算法简单、容易实现，具有较强的全局搜索能力。【结论】微分进化算法在解决水电站水库优化调度问题时具有很强的适用性，为求解水电站水库优化调度问题提供了新思路。 |
| 关键词: 水电站水库 优化调度 微分进化算法 |
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| 基金项目:国家自然科学基金项目(51109175，51079120)；公益性行业科研专项(201001011) |
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| Application of differential evolution algorithm in optimal-operation of hydropower station |
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| Abstract: |
| 【Objective】In view of the disadvantages of the traditional optimization algorithm,differential evolution algorithm was used in the optimal operation problem of hydropower station to establish a new optimization model.【Method】We established an optimal operation model of hydropower station based on differential evolution algorithm,and worked out the specific steps of that problem.In order to validate the efficiency of the algorithm,differential evolution algorithm was used in specific calculation of optimal operation,and finally the calculation results of DE and GA were contrasted.【Result】Example calculations show that this algorithm has fast convergence,small number of tuning parameters,high calculation accuracy,good stability,simple and is easy to be implemented with strong global search capability.【Conclusion】Differential evolution algorithm has a strong suitability in the optimal operation field of hydropower station,and it will be a new method to solve the problem of hydropower station optimal operation. |
| Key words: hydropower station reservoir optimal operation differential evolution algorithm |
