Abstract

In order to build a low-carbon power system, a large number of new energy generators are integrated into the system. The carbon emissions at the source side have been significantly reduced. However, the output of wind power and photovoltaic power are intermittent and volatile. The power consumption behavior of users in different time periods has an important impact on the proportion of power generation at the source side. Thus, an effective carbon measurement considering the differentiated consumption behavior on the load side is expected. Then the low carbon interaction between source and load side and the carbon emission reduction on the source side can be further realized. In this paper, we propose a calculation method of dynamic carbon emission factors for different load regions in a province based on time division. Taking the 220 kV sub-network as the unit spatial scale, the carbon emission factor for power consumption in each time period is calculated. Then the fuzzy C-means clustering method is applied to divide the time periods of carbon emission factors according to the two categories of power consumption. Furthermore, the carbon emission reduction model is established to provide a feasible scheme for users to regulate the power consumption for carbon benefits. Numerical results based on the province A are obtained to validate the effectiveness of the proposed method.

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