基于柴油发动机的独立动力系统的技术,经济和环境评估,使用优化算法进行储能或不储能:中国的一个案例研究
1College of Information Science and Technology, Henan University of Technology, Zhengzhou, 450000, Henan, China. yxvlbsigc60@gmail.com.
Environmental science and pollution research international
|December 22, 2023
概括
这项研究优化了用于偏远岛屿的混合太阳能和柴油动力系统,使用修改的群体智能算法. 该研究通过平衡技术,经济和环境因素,确保了具有成本效益,可靠和低排放的能源解决方案.
科学领域:
- 可再生能源系统可再生能源系统
- 人工智能在能源中的作用
- 动力系统优化 动力系统优化
背景情况:
- 独立的电力系统需要严格的技术,经济和环境 (TEE) 评估,尤其是在不确定性的情况下.
- 结合光伏 (PV) 和柴油发电机 (DG) 与电池存储 (BS) 的混合能源系统对于远程微电网至关重要.
- 优化光伏,GD和BS组件的尺寸对于经济可行性,可靠性和效率至关重要.
研究的目的:
- 在中国偏远的岛屿上,对具有/没有BS的独立光伏-电流混合系统进行 TEE 评估.
- 确定最佳的系统组件尺寸,以实现经济,可靠和高效的微电网运行.
- 尽量降低独立太阳能发电系统的成本,同时考虑负载不确定性和二氧化碳排放.
主要方法:
- 一个经过修改的群集智能算法被开发并用于优化.
- 该算法与标准的群体智能和模拟火方法进行了比较.
- 对燃料成本和二氧化碳罚款成本进行了敏感性分析.
主要成果:
- 与其他方法相比,修改后的群集智能算法在TEE方面表现出优越的性能.
- 模拟结果证实了算法在降低运营成本和功率损失方面的有效性.
- 该研究得出了相关性,以轻松计算可靠性,低碳影响和成本效益.
结论:
- 拟议的修改群集智能算法为优化混合可再生能源系统提供了一个有希望的方法.
- 优化的系统为远程独立电力系统提供可靠,低碳和成本有效的能源解决方案.
- 这些系统的能源成本从0.2845美元到0.6492美元/千瓦时不等.
相关概念视频
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01:28Load-frequency control
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01:30Control of Power Flow
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01:21Generator Voltage Control
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