修改了哈里斯·霍克斯对混合可再生能源系统的3E可行性评估的优化
Asmita Ajay Rathod1, Balaji S2
1School of Electrical Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India.
Scientific reports
|August 29, 2024
概括
这项研究使用修改后的哈里斯·霍克斯优化 (mHHO) 算法对农村电力优化了混合可再生能源系统 (HRES). 采用mHHO方法实现了成本效益高的能源解决方案,同时最大限度地减少了对环境的影响,并提高了人类发展指数.
科学领域:
- 可再生能源系统工程可再生能源系统工程
- 优化算法 优化算法
- 可持续能源解决方案 可持续能源解决方案
背景情况:
- 不断增长的能源需求需要可持续和经济可行的解决方案.
- 脱离电网的混合可再生能源系统 (HRES) 提供了巨大的潜力.
- 优化HRES组件尺寸对于成本和可靠性评估至关重要.
研究的目的:
- 呈现HRES的最佳尺寸,以实现经济高效的农村电力供应.
- 为了对光伏-风电-电池-DG系统进行3E分析 (能源,经济,环境二氧化碳排放).
- 评估修改后的哈里斯·霍克斯优化 (mHHO) 算法的性能,用于HRES设计.
主要方法:
- 开发一个光伏-风电-电池-DG系统模型.
- 应用一种新的修改后的哈里斯·霍克斯优化 (mHHO) 算法,使用九个不同的运算符进行同时优化.
- 技术 (LPS,RF,PVF,WF) 和社会 (HDI) 参数的评估,以及CEC 2019测试套件的验证.
主要成果:
- mHHO算法以0.14130美元/kWh的优化能源成本 (COE),1,649,900美元的净当前成本 (NPC) 和116,090美元/年的年度系统成本 (ASC) 实现了优化.
- 与其他元启发算法相比,观察到COE减少了0.49%.
- 设计的HRES显示出高度依赖可再生能源 (0.03%的柴油使用),并保持了高的人类发展指数.
结论:
- 对于3E分析和HRES设计,mHHO算法是有效的,显示出优异的融合和高质量的结果.
- 提出的方法实现了最佳的经济效率,同时最大限度地减少了对环境的影响.
- 该研究成功地证明了农村电气化的可持续和高性能HRES解决方案.
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