| 摘要: |
| 光伏空调和蓄冰空调同属于绿色空调，两者均能起到缓解电网压力、节约空调运行费用的作用。本文将光伏空调与蓄冰空调结合，提出了一种含有充供（充冷同时供冷）工作模式的光伏蓄冰空调系统，构建了光伏蓄冰空调系统运行调度的非线性优化模型，并基于动态规划方法对优化问题进行了全局最优求解；根据光伏发电与建筑冷负荷的预测数据，进行了不同建筑冷负荷下的光伏蓄冰空调预测控制案例分析。结果表明：在考虑光伏发电预测的情况下，光伏蓄冰空调系统的预测控制可将夜间的蓄冰能耗转移到日间，有效降低了系统的运行费用，并提高了系统的太阳能保证率、光伏消纳率和平均能效；当光伏售电价格降低时，预测控制下的光伏蓄冰空调系统可更充分利用光伏电能，系统的运行费用得到了更大幅度的降低。 |
| 关键词: 太阳能光伏 冰蓄冷 动态规划 预测控制 运行费用 |
| DOI： |
| 投稿时间：2019-09-11 修订日期：2020-01-11
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| 基金项目:空调设备及系统运行节能国家重点实验室开放基金项目（ACSKL2018KT03）资助。 |
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| Predictive Control of Photovoltaic Ice Storage Air-conditioning System Based on Dynamic Programming |
| Zhao Baiyang,Zhang Xuefen,Li Yong,Wang Ruzhu,Dong Mingzhu,Zhao Zhigang |
| (Institute of Refrigeration and Cryogenics, Shanghai Jiao Tong University;State Key Laboratory of Air-Conditioning Equipment and System Energy Conservation;Gree Electric Appliances, Inc. of Zhuhai) |
| Abstract: |
| Solar photovoltaic and ice storage air-conditioning are both green air-conditioning technologies that can relieve the power supply pressure on power grids and reduce the operation cost of air-conditioning system. This study combines these two technologies and proposes a photovoltaic ice storage air-conditioning (PSAC) system that has a charging-and-chiller-cooling mode. A nonlinear optimization model for the PSAC system operation is developed and solved by the dynamic programming method to achieve global optimal results. According to the photovoltaic generation and building cooling load predictions, several case studies have been conducted for PSAC predictive control with different building cooling loads. The results show that when the photovoltaic generation prediction is considered, the cooling load for forming ice at night is shifted to the daytime, resulting in a reduction of the system operation cost and improvements in the solar fraction, self-consumption ratio, and average COP. When the selling price of photovoltaic electricity decreases, the PSAC is able to utilize the photovoltaic electricity in a better manner and the system operation cost can be reduced further under the predictive control. |
| Key words: solar photovoltaic ice storage dynamic programming predictive control operation cost |
