为解决传统模型过于简化以致调度计划存在电量不可交付、产生系统频率偏差的问题,提出一种考虑电量可实现性和启停功率轨迹的火电机组组合混合整数线性规划（mixed-integer linear programming,MILP）模型,该模型引入一类0-1变量表示燃...为解决传统模型过于简化以致调度计划存在电量不可交付、产生系统频率偏差的问题,提出一种考虑电量可实现性和启停功率轨迹的火电机组组合混合整数线性规划（mixed-integer linear programming,MILP）模型,该模型引入一类0-1变量表示燃煤机组的运行状态,便于在其加热、升负荷、调度和降负荷4个阶段的逻辑判断和发电量计算;根据燃气燃油机组启停迅速的特点,对其运行状态重新建模;并支持冷、温、热等多种启动类型和1 h、15 min等多种调度时段长度。10～1 000机24时段系统的计算结果表明：所提模型更符合实际运行情况,可很好地解决电量不可交付问题,且具有较高的求解效率。展开更多
在乡村振兴进程中,农业发展的关键在于合理规划农作物种植策略。本论文研究了乡村农作物种植策略优化问题,旨在通过构建混合线性规划模型,预测未来七年(2024~2030)的最佳种植方案,以最大化收益。论文考虑了农作物销售量、产量、成本、...在乡村振兴进程中,农业发展的关键在于合理规划农作物种植策略。本论文研究了乡村农作物种植策略优化问题,旨在通过构建混合线性规划模型,预测未来七年(2024~2030)的最佳种植方案,以最大化收益。论文考虑了农作物销售量、产量、成本、价格的波动性以及作物间的可替代性和互补性,并使用了鲁棒优化方法处理不确定性。最终得出兼顾多种条件的最优策略,为农业实践提供科学支撑。In the process of rural revitalization, the key to agricultural development lies in the rational planning of crop planting strategies. This paper studies the optimization problem of rural crop planting strategies, aiming to predict the best planting plan for the next seven years (2024~2030) by constructing a hybrid linear programming model to maximize profits. The paper considers the volatility of crop sales volume, yield, cost, price, and the substitutability and complementarity between crops and uses robust optimization methods to deal with uncertainty. Finally, the optimal strategy considering multiple conditions is obtained, providing scientific support for agricultural practice.展开更多
文摘在乡村振兴进程中,农业发展的关键在于合理规划农作物种植策略。本论文研究了乡村农作物种植策略优化问题,旨在通过构建混合线性规划模型,预测未来七年(2024~2030)的最佳种植方案,以最大化收益。论文考虑了农作物销售量、产量、成本、价格的波动性以及作物间的可替代性和互补性,并使用了鲁棒优化方法处理不确定性。最终得出兼顾多种条件的最优策略,为农业实践提供科学支撑。In the process of rural revitalization, the key to agricultural development lies in the rational planning of crop planting strategies. This paper studies the optimization problem of rural crop planting strategies, aiming to predict the best planting plan for the next seven years (2024~2030) by constructing a hybrid linear programming model to maximize profits. The paper considers the volatility of crop sales volume, yield, cost, price, and the substitutability and complementarity between crops and uses robust optimization methods to deal with uncertainty. Finally, the optimal strategy considering multiple conditions is obtained, providing scientific support for agricultural practice.
