摘要
中长期水资源优化调度问题是一类具有非线性、多阶段、高维度和多重约束特性的复杂优化问题。针对经典智能算法在求解此类问题时容易陷入局部最优或者收敛效率较低等问题,应用混沌搜索策略增强算法的探索能力,同时改进传统算法的变异方式,向精英个体学习以提升收敛速度,提出自适应混沌精英变异差分进化(ACEDE)算法。将所提出的算法应用于珠江三角洲水资源配置工程中长期调度进行实例研究,并与经典智能算法进行对比分析。结果表明:①ACEDE算法在全局探索能力、收敛精度与速度上实现了全面提升,并且表现出良好的适应性。相较于传统差分进化(DE)算法,2030年水平年6月份和2040年水平年6月份调度中ACEDE算法所计算的电费成本分别节省了74.23万元和23.55万元,降低了6.68%和1.52%。②在珠江三角洲水资源配置工程中长期调度中,充分利用调蓄水库库容满足高分水量需求,同时放缓月末补水充库过程,能够有效控制泵站的平稳运行,达到降低电费成本的目的。
The medium-and long-term optimal scheduling of water resources is a complex optimization problem characterized by non-linearity,multi-stage high dimensionality,and multi-constraints.To address the local optimization and low convergence efficiency of classical intelligent algorithms,this paper introduce a novel algorithm named the Adaptive Chaotic Elite Mutation Differential Evolution(ACEDE)algorithm.The algorithm leverages a chaotic search strategy to enhance the algorithm’s exploration capabilities while revising the traditional mutation approach to learn from elite individuals,thereby accelerating convergence.The proposed algorithm is applied to the medium-and long-term scheduling of the Pearl River Delta Water Resources Allocation Project(PRD WRAP)as a case study and is compared with classical intelligent algorithms.Results indicate that:1)The ACEDE algorithm improves significantly in global exploration capabilities and convergence accuracy and speed,demonstrating good adaptability.For the June 2030 and June 2040 level year dispatches,respectively,the ACEDE algorithm,saves¥742300 and¥235500 in electricity costs compared to the traditional DE algorithm,reducing the cost of electricity by 6.68%and 1.52%.2)For the medium-and long-term optimal scheduling of PRD WRAP,fully utilizing the reservoir storage capacity to meet high water demand while slowing down the replenishment at the end of month could effectively control the smooth operation of the pumping station and minimize electricity costs.
作者
何耀耀
胡千帝
张召
HE Yao-yao;HU Qian-di;ZHANG Zhao(School of Management,Hefei University of Technology,Hefei 230009,China;College of Water Resourcesand Hydropower,China Institute of Water Resources and Hydropower,Beijing 100038,China)
出处
《长江科学院院报》
CSCD
北大核心
2024年第10期14-22,共9页
Journal of Changjiang River Scientific Research Institute
基金
国家自然科学基金项目(52209046)。
关键词
水资源优化调度
差分进化算法
混沌映射
精英变异
珠江三角洲水资源配置工程
optimization of water resources dispatching
differential evolution algorithm
chaotic mapping
elite mutation
Pearl River Delta Water Resources Allocation Project