基于负载预测对企业的变压器过载和新能源规划的识别
1School of Finance and Information, Ningbo University of Finance and Economics, Ningbo, China.
PloS one
|October 2, 2024
概括
这项研究优化了面临变压器过载的企业的新能源系统. 它提出了一个负载预测和光伏 (PV) 和储能系统的最佳配置模型,以减少电力成本和排放.
科学领域:
- 电气工程 电气工程
- 能源系统 能源系统
- 运营研究 运营研究
背景情况:
- 变压器过载是许多企业面临的重大运营挑战.
- 整合新的能源系统,包括光伏发电和储能,为变压器过载,成本降低和低碳排放减少提供了解决方案.
- 投资回报率低,目前阻碍企业采用新能源系统.
研究的目的:
- 为潜在的客户开发光伏和储能系统的最佳配置模型,以应对变压器过载的情况.
- 建立负载预测模型,以确定有新能源安装需求的潜在客户.
- 确定最佳的光伏装机容量和储能充/放电策略,以降低电力成本并确保运营能力.
主要方法:
- 为潜在客户开发负载预测模型.
- 基于非线性编程的光伏和储能系统的最佳配置模型.
- 一个建筑材料生产工厂的案例研究分析.
主要成果:
- 通过负载预测识别潜在客户.
- 确定最佳的光伏和储能能力和运营策略.
- 通过案例研究来证明降低成本和提高效率.
结论:
- 建议的优化策略有效地解决了企业的变压器过载问题.
- 光伏和储能系统的最佳配置带来了显著的经济效益和减排.
- 开发的模型为在工业环境中实施新能源解决方案提供了实际框架.
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