改进的二次插值优化器用于随机的短期热水计划,并集成太阳能光伏和风力发电
Noor Habib Khan1, Yong Wang2, Raheela Jamal1
1College of Mechanical and Electrical Engineering, Qingdao Binhai University, Shandong Sheng, 266540, China.
Scientific reports
|April 2, 2025
概括
这项研究增强了二次插值优化 (QIO) 算法,以提高其在复杂问题上的性能. 增强的IQIO有效地解决了短期的热水计划,通过整合可再生能源来降低成本和排放.
科学领域:
- 计算智能是一种计算智能.
- 优化算法 优化算法
- 能源系统工程 能源系统工程
背景情况:
- 四位数插值优化 (QIO) 是一种具有双重探索机制的元启发算法.
- 传统的QIO面临着高度非线性和多维问题的局限性,包括停滞和过早的融合.
- 解决这些局限性对于在复杂的优化任务中有效应用至关重要.
研究的目的:
- 通过引入新的策略来增强二次插值优化 (QIO) 算法.
- 改善QIO的复杂优化问题的勘探和开发能力.
- 应用增强的QIO (IQIO) 来解决可再生能源整合的短期水热计划 (STHS) 问题.
主要方法:
- 提出了三个增强策略:韦布尔飞行运动,混乱突变和PDO机制,以改进QIO成为IQIO.
- 将改进的IQIO应用于短期热水计划 (STHS) 问题,并纳入系统不确定性和可再生能源单位 (光伏,风能).
- 使用加权总和方法处理依赖约束,并使用CEC 2022测试套件验证性能.
主要成果:
- 增强的IQIO在基准测试功能上显示出与原始QIO相比的显著改进.
- 对STHS的应用导致大幅降低:燃料成本高达23.73%,排放量高达45.50%.
- IQIO有效地管理了系统限制,包括水排放,水库储存和电力平衡.
结论:
- 提议的改进显著增强了QIO的勘探和开发能力,克服了原始算法的局限性.
- IQIO是一个强大的,有效的优化工具,用于复杂的STHS问题,特别是可再生能源的整合.
- 该研究强调了IQIO通过降低运营成本和环境影响来实现可持续能源管理的潜力.
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