Continuously adjusting the power of units with changes in power load not only fails to fundamentally solve the problem of power load, but also brings negative impacts on the safe operation of the power grid and units. Therefore, this article explored the economic benefits of the power load management system and provided factors such as government resources, customer market resources, and power enterprise resources that affect the power load management system. This article analyzed the load characteristics of the M region power grid and compared the proportion of power load of regional air conditioning at different times in summer. The air conditioning power response resources in the M area were evaluated, and the commercial relationships between power grid companies, power generation companies, and power users were explored. In summer, the power load in M area was 634.9 KW at 28 ℃ and 836.6 KW at 29 ℃. This article has provided a new approach to intelligent electricity consumption and response to power load resources.

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Business Model for Developing Power Load Resources

  • Yafang Zhu,
  • Yaru Han,
  • Sijie Cai

摘要

Continuously adjusting the power of units with changes in power load not only fails to fundamentally solve the problem of power load, but also brings negative impacts on the safe operation of the power grid and units. Therefore, this article explored the economic benefits of the power load management system and provided factors such as government resources, customer market resources, and power enterprise resources that affect the power load management system. This article analyzed the load characteristics of the M region power grid and compared the proportion of power load of regional air conditioning at different times in summer. The air conditioning power response resources in the M area were evaluated, and the commercial relationships between power grid companies, power generation companies, and power users were explored. In summer, the power load in M area was 634.9 KW at 28 ℃ and 836.6 KW at 29 ℃. This article has provided a new approach to intelligent electricity consumption and response to power load resources.