Integrated Intelligent Energy ›› 2024, Vol. 46 ›› Issue (1): 28-37.doi: 10.3969/j.issn.2097-0706.2024.01.004

• Decision Support System based on Intelligent Algorithms • Previous Articles     Next Articles

Research on control strategy for virtual power plants in response to thermostatically controlled loads

TIAN Zeyu(), SHA Zhaoyang, ZHAO Quanbin, YAN Hui, CHONG Daotong*()   

  1. State Key Laboratory of Multiphase Flow in Power Engineering,Xi'an Jiaotong University,Xi'an 710049,China
  • Received:2023-05-11 Revised:2023-07-15 Published:2024-01-25
  • Supported by:
    National Key R&D Program of China(2022YFB4202403);Innovation Capacity Support Program of Shaanxi Province(2023-LL-QY-29)

Abstract:

Thermostatically controlled load(TCL) is of frequent and drastic fluctuations and high- proportion peak load,which threats the safe operation of the power grid. To alleviate the fluctuation, a power system has to raise its load over the peak load regulation constraint of 90% maximum load. To study the over-limit process of a virtual power plant(VPP)system, two control strategies are proposed to reduce the total amount of over-limit electricity and gain profits from the process. Two types of variation laws of the power demand varying with TCLs are selected to study the effectiveness of the strategies. The results show that the peak value of the power demand varying with TCLs has a great impact on the strategies. Under the safe mode,the proportion of over-limit electricity is inversely proportional to the power demand peak value,while is proportional to the average value. Under the profiting mode,since the peak value and average value of power affects the charging and discharge processes,the profit decreases with the increase of power demand,ranging from 36 200 to 32 500 yuan.

Key words: virtual power plant, thermostatically controlled load, coordinated control strategy, price differential revenue, APROS, electric vehicle, stored energy, peak regulation

CLC Number: