Research on demand response strategy of power distribution and sale companies under the background of incremental power distribution business reform
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Research on demand response strategy of power distribution and sale companies under the background of incremental power distribution business reform
Vol. 22, Issue 4, (2020)
作者机构:
1. 中电联 工业领域电力需求侧管理促进中心,北京,100055
2. 华北电力大学 电气与电子工程学院,北京,102206
作者简介:
基金信息:
DOI:
CLC:
Published:2020
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郄双源, 杨 迪, 王 鹏, et al. Research on demand response strategy of power distribution and sale companies under the background of incremental power distribution business reform[J]. 2020, 22(4).
DOI:
郄双源, 杨 迪, 王 鹏, et al. Research on demand response strategy of power distribution and sale companies under the background of incremental power distribution business reform[J]. 2020, 22(4).DOI:
Research on demand response strategy of power distribution and sale companies under the background of incremental power distribution business reform
With the continuous advancement of incremental power distribution business reform
a large number of park pilots are entering the stage of implementation and grid-connected operation. From two aspects
strategic recommendations for power distribution companies to fully mobilize demandside response resources are provided. Firstly
in order to absorb local distributed energy inside
time-of-use price signals are used to guide users to adjust production plans. Based on the net load curve of the park pilots and seasonal production characteristics of industrial users
the peak-to-valley time and implementation cycle are arranged. Then conduct separate research and simulation operations for industrial users who intend to implement time-of-use electricity prices
and customize personalized time-of-use retail power packages for them.Secondly
in order to avoid price risks in a certain period of time in the future power spot market outside
a peak-cutting bidding model suitable for industrial and commercial users of park pilots is established. And a credit assessment link is added
and peak-cut com-pensation fees are paid based on the user’s performance credit coefficient and real-time response. In the end
an example is used to verify the feasibility of the proposed method model
and it can effectively guide users to cut peaks and fill valleys while saving corporate electricity expenses.