| 基于队列分析的改进空调负荷控制策略及其评估 |
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| 引用本文： | 朱兰,黄超,唐陇军,刘伸,王吉. 基于队列分析的改进空调负荷控制策略及其评估[J]. 现代电力, 2019, 36(2): 56-65 |
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| 作者姓名： | 朱兰 黄超 唐陇军 刘伸 王吉 |
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| 作者单位： | 1.上海电力学院电气工程学院,上海 200090; |
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| 基金项目： | 国家青年自然基金(51407113);上海绿色能源并网工程技术研究中心资助项目(13DZ2251900)“电气工程”上海市II类高原学科;电力传输与功率变换控制教育部重点实验室开放课题资助(2016AA10) |
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| 摘 要： | 空调负荷作为电网中的重要负荷,占据了负荷高峰需求中的较大比重。由于具有能够将电能转化为热(冷)能储存在室内的特性,空调负荷在电网中的需求响应能力得到了发挥。通过分析传统空调控制策略的状态队列变化,考虑用户舒适性,计算了极限停机时间,在此基础上提出了一种对空调负荷按组进行控制的策略,降低了控制中心在空调数量较多的情况下处理温度设定数据的压力。在处理"二次峰荷"时,基于分时段改变温度区间长度的方式,进一步降低了负荷恢复时的波动峰值。最后,提出了空调控制评估指标和方法,算例仿真验证了本文改进策略具有较好的削峰能力、较小的反弹负荷波动和较少的温度设定值计算。
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| 关 键 词： | 需求响应 空调负荷 状态队列 控制策略 极限停机时间 |
| 收稿时间： | 2018-04-14 |
Improved Air-conditioning Load Control Strategy and Evaluation Based on State-queue Analysis |
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| ZHU Lan,HUANG Chao,TANG Longjun,LIU Shen,WANG Ji. Improved Air-conditioning Load Control Strategy and Evaluation Based on State-queue Analysis[J]. Modern Electric Power, 2019, 36(2): 56-65 |
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| Authors: | ZHU Lan HUANG Chao TANG Longjun LIU Shen WANG Ji |
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| Affiliation: | 1.School of Electric Power Engineering, Shanghai University of Electric Power, Shanghai 200090, China;2.Key Laboratory of Control of Power Transmission and Conversion(SJTU), Ministry of Education, Shanghai 200240, China;3.East Electric Power Dispatch and Control Sub-center, State Grid Corporation of China, Shanghai 200000, China |
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| Abstract: | Air-conditioning load, as an important load in power grid, occupies a large proportion of load peak demand. With the capability to convert electrical energy into thermal (cold) energy stored indoors, the demand response potential of air-conditioning load in power grid has been explored. By analyzing the state-queue change of the traditional air-conditioning control strategy and considering consumers comfort, the limit downtime is calculated. On the basis of this, a strategy to control air-conditioning load by group is proposed, which reduces temperature setting workload of the control center in the case of massive air conditioners. In dealing with the “recovery peak”, the fluctuating peak value of load recovery is further reduced by changing the temperature interval length in different time intervals. Finally, the evaluation Indicators and method of air-conditioning control are put forward. The simulation results show that the improved method has better peaking curtailment performance, less fluctuation of rebound load and less computation cost of temperature set value. |
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| Keywords: | demand response air-conditioning load state queue control strategy limit downtime |
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