一个多时间尺度的滚动优化框架,用于低碳运行的CCHP微电网与需求响应集成需求响应
Jue Wang1,2, Zhiwei Cheng3, Dejun Lu4
1Institute of Intelligent Manufacturing, Nanjing Tech University, Nanjing, China.
PloS one
|July 28, 2025
概括
这项研究引入了一种新的优化框架,用于组合冷却,供暖和电力 (CCHP) 微电网,提高能源效率和节省成本. 该框架有效地管理了可持续能源系统的需求响应和碳交易.
科学领域:
- 能源系统工程 能源系统工程
- 人工智能在能源中的作用
- 可持续发展的能源发展
背景情况:
- 微电网对于低碳社会至关重要,但设备响应率,负载预测错误和多能源设备复杂性阻碍了最佳运行.
- 碳交易和需求响应 (DR) 的整合为增强微电网性能和可持续性提供了机会.
- 微电网运行的挑战包括管理各种设备响应时间和复杂的能源相互依存.
研究的目的:
- 为混合冷却,供暖和电力 (CCHP) 微电网系统提出一个强大的优化框架.
- 为应对包括响应率差异,负载预测不准确性和复杂设备合在内的运营挑战.
- 尽量减少运营成本,同时整合需求响应和碳交易机制.
主要方法:
- 一个双层滚动优化框架与多个时间尺度调度被开发用于CCHP微电网.
- 使用CNN-ATT-BiLSTM模型预测风能和光伏发电,与CNN,BiLSTM和CNN-LSTM进行比较.
- 建立了一个多时间尺度优化模型,目标函数是运营成本最小化.
主要成果:
- 与基线模型相比,CNN-ATT-BiLSTM模型在预测可再生能源发电方面表现优越.
- 拟议的优化框架成功地协调了多时间分辨率,以满足冷却,加热和电力需求.
- 对四个运行场景的比较分析突出了整合DR和碳交易的成本效益.
结论:
- 开发的框架有效地减轻了CCHP微电网的随机供需波动.
- 该研究验证了通过协调的多时间调度,同时满足各种能源需求.
- 需求响应和碳交易的整合大大提高了微电网的经济和可持续运行.
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