水利水电技术（中英文）

【目的】针对我国西北干旱地区水资源时空分布不均、利用效率偏低，且传统水库调度算法易陷入局部最优、收敛性能不足的问题，研发适配干旱区复杂水文场景的水库水量联合调度模型与高效求解算法，提升区域水资源配置效率。【方法】以总缺水量最小、总弃水量最小为双目标，构建干旱区水库水量联合优化调度模型；针对传统粒子群算法（PSO）及常规多子群协同粒子群算法（MSC-PSO）的缺陷，提出改进的多子群协同粒子群算法（IMSC-PSO），通过设计基于适应度的动态边界子群划分机制、优化层次化自适应惯性权重策略、构建含跨群学习因子的差异化更新学习机制提升算法求解性能；以典型西北干旱区新疆鄯善县的二塘沟、坎尔其、柯柯亚三座水库为研究对象，设置丰、平、枯、特枯四种典型来水情景，开展模拟计算与实例验证，并与常规调度、传统PSO算法及MSC-PSO算法的调度效果对比分析。【结果】IMSC-PSO算法下优化调度方案的总缺水量较常规调度在四种来水条件下分别降低43.6%～77.68%，总弃水量平均降低55.85%；【结论】IMSC-PSO算法通过干旱区各水库水量协同调控实现了区域月度供水稳定最大化，单库合理波动服从整体最优目标，有效提升了关键用水期的供水保障能力，为西北干旱地区水库水量联合调度及水资源可持续利用提供了科学的模型与算法支撑。

[Objective] Aiming at the problems of uneven temporal and spatial distribution of water resources， low utilization efficiency in arid areas of Northwest China， as well as the defects of traditional reservoir operation algorithms such as easy trapping in local optimum and poor convergence performance， this study develops a joint water regulation model of reservoirs and an efficient solving algorithm adapted to complex hydrological scenarios in arid areas， so as to improve the allocation efficiency of regional water resources.[Methods] Taking the minimum total water shortage and the minimum total water abandonment as the dual objectives， a joint optimal water operation model for reservoirs in arid areas is constructed. In view of the shortcomings of the traditional Particle Swarm Optimization (PSO) and conventional Multi-Subgroup Cooperative Particle Swarm Optimization (MSC-PSO)， an Improved Multi-Subgroup Cooperative Particle Swarm Optimization (IMSC-PSO) is proposed. The algorithm performance is improved by designing a fitness-based dynamic boundary subgroup division mechanism， optimizing the hierarchical adaptive inertia weight strategy， and establishing a differentiated renewal learning mechanism with cross-subgroup learning factors. Taking three reservoirs including Ertanggou， Kanerqi and Kekeya in Shanshan County of Xinjiang， a typical arid area in Northwest China， as the research objects， four typical inflow scenarios (wet year， normal year， dry year and extra-dry year) are set up for simulation calculation and example verification. The operation results are compared with those of conventional operation， traditional PSO and MSC-PSO algorithms.[Results] Compared with the conventional operation scheme under the four inflow scenarios， the optimal operation scheme based on the IMSC-PSO algorithm reduces the total water shortage by 43.6%～77.68% and the average total water abandonment by 55.85%.[Conclusion] The IMSC-PSO algorithm realizes the maximum stability of regional monthly water supply through the collaborative water regulation of reservoirs in arid areas. The reasonable fluctuation of single reservoir conforms to the overall optimization goal， which effectively improves the water supply guarantee capacity in critical water use periods. It provides scientific model and algorithm support for joint reservoir water regulation and sustainable utilization of water resources in arid areas of Northwest China.