Air Conditioning Load Optimization Dispatching Model Considering Users' Comfort Compensation

被引：2
|
作者：
Zhang Y. [1 ]
Hao J. [1 ]
机构：
[1] School of Electric Power, Guangdong Key Laboratory of Green Energy Technology, South China University of Technology, Guangzhou, 510640, Guangdong
来源：
Huanan Ligong Daxue Xuebao/Journal of South China University of Technology (Natural Science) | 2019年 / 47卷 / 03期
基金：
中国国家自然科学基金;
关键词：
Air conditioning load; Demand response; Load aggregator; Renewable energy;
D O I：
10.12141/j.issn.1000-565X.180496
中图分类号：
学科分类号：
摘要：
Through the dispatching of demand side response resources, the adverse effects of distributed power output fluctuation on grid operation can be alleviated, and the consumption of renewable energy can be promoted. Firstly, based on the operation framework of the load aggregator, the cost and benefit of the load aggregator were analyzed. In the component of the load aggregator cost, the demand response compensation strategy based on users' comfort was proposed. Secondly, the temperature variation model of air conditioning load was established. Finally, the air conditioning load optimization dispatching model was proposed. The objective function of the model is the maximum total revenue of the air conditioning load aggregator, taking into account the air conditioning temperature, wind power fluctuation and aggregator revenue constraints. The simulation results show that the proposed model has good economic benefits and improves the smoothing effect on distributed wind power fluctuations. © 2019, Editorial Department, Journal of South China University of Technology. All right reserved.
引用
收藏
页码：1 / 8
页数：7
相关论文
共 23 条
  • [1] Shu Y., Zhang Z., Guo J., Et al., Study on key factors and solution of renewable energy accommodation, Proceedings of the CSEE, 37, 1, pp. 1-9, (2017)
  • [2] Pang P., Electric power demand response mechanism and support technology under electric power market reform, Guangdong Power, 29, 1, pp. 70-78, (2016)
  • [3] Chen X., Yang Y., Zhang Y., Et al., Influence of illumination probability of photovoltaic system on voltage of power distribution networks, Journal of South China University of Technology(Natural Science Edition), 43, 4, pp. 112-118, (2015)
  • [4] Zhang X., Zhou F., Smart grid leads the journey to innovative smart home and energy consumption patterns, Power System Protection and Control, 42, 5, pp. 59-67, (2014)
  • [5] Chen H., Huang S., Fan Z., Et al., Demand response of multi-microgrid based on game theory, Southern Power System Technology, 11, 2, pp. 34-40, (2017)
  • [6] Zhang K., Song Y., Yan Z., Energy storage capacity optimization for load aggregators considering probablity of demand response resources's breach, Automation of Electric Power Systems, 39, 17, pp. 127-133, (2015)
  • [7] Mohsenian-Rad A.H., Wong V.W.S., Jatskevich J., Et al., Autonomous demand-side management based on game-theoretic energy consumption scheduling for the future smart grid, IEEE Transactions on Smart Grid, 1, 3, pp. 320-331, (2010)
  • [8] Wang Q., Lei C., Li Y., Et al., Areactive power optimization model of high voltage distribution network considering DLC cycle control of air-conditioning loads, Proceedings of the CSEE, 38, 6, pp. 1684-1694, (2018)
  • [9] Wang Y., Tong Y., Huang M., Et al., Research on virtual energy storage model of air conditioning loads based on demand response, Power System Technology, 41, 2, pp. 394-401, (2017)
  • [10] Gao C., Li Q., Li Y., Bi-level optimal dispatch and control strategy for air-conditioning load based on direct load control, Proceedings of the CSEE, 34, 10, pp. 1546-1555, (2014)
123