| 赵本源,赵建立,张沛超,姚 刚,杜 江.模型和数据驱动结合的暖通空调需求响应成本分析[J].电力需求侧管理,2024,26(2):27-33 |
| 模型和数据驱动结合的暖通空调需求响应成本分析 |
| Demand response cost assessment of HVAC based on model and data driven |
| 投稿时间：2023-11-27 修订日期：2023-12-19 |
| DOI：10. 3969 / j. issn. 1009-1831. 2024. 02. 005 |
| 中文关键词: 暖通空调 需求响应成本 人工神经网络 工作效率 |
| 英文关键词: HVAC demand response cost ANN efficiency |
| 基金项目:国网上海市电力公司科技项目（52090D200002） |
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| 中文摘要: |
| 为实现楼宇暖通空调与电网友好互动,提出了模型与数据驱动相结合的需求响应成本分析。首先,利用人工神经网络的拟合能力,从物理模型中自动学习并构建动态模型。然后,考虑温度变化对楼宇人员工作效率的影响,建立暖通空调设定温度的优化模型并基于粒子群优化算法进行求解。最后,将用户因偏离最优设定温度而产生的额外成本定义为响应成本,据此提出暖通空调的需求响应成本分析方法。仿真结果表明,通过设定暖通空调的最优温度,可显著降低用户的总成本；响应成本曲线可反映用户的工作效率损失因素,从而帮助用户在需求响应中理性确定投标价格。 |
| 英文摘要: |
| To realize friendly interaction between building heating, ventilation and air conditioning（HVAC）and the power grid, a demand response cost assessment method combining model and data driven is proposed. Firstly, the fitting ability of artificial neural network（ANN） is used to automatically learn from the physical model and build a dynamic model of HVAC. Then, considering the impact of temperature changes on the personnel efficiency of building, an optimization model of the HVAC setting temperature is established and solved based on particle swarm optimization（PSO）algorithm. Finally, additional cost incurred by users due to deviation from the optimal set temperature is defined as response cost, and demand response cost assessment for HVAC is proposed accordingly. Simulation results show that by setting optimal temperature of HVAC, total cost of users can be significantly reduced. The response cost curve can reflect users’productivity loss factors, thereby helping users determine the bid price rationally in demand response. |
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