Abstract
As the power industry is the largest source of carbon emissions, it is necessary to study the low-carbon planning of power supply expansion. This paper proposes a two-stage power expansion planning model considering carbon emission control, which evaluates two policies that directly and indirectly affect carbon emissions, namely the carbon tax policy and the renewable portfolio standard policy (RPS) is expected to reduce CO2 emissions. Considering the risks brought by the uncertainty of wind power output and load demand to power planning, a two-stage power expansion planning model based on robust optimization is established. Finally, the feasibility of the model proposed in this paper is verified by example analysis. The results show that the carbon tax policy can reduce carbon emissions, and the implementation of RPS can increase the proportion of new energy and be more resistant to uncertain fluctuation risks, which can be used in actual planning, providing support for formulating relevant low-carbon policies.
| Original language | English |
|---|---|
| Title of host publication | EI2 2022 - 6th IEEE Conference on Energy Internet and Energy System Integration |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 824-829 |
| Number of pages | 6 |
| ISBN (Electronic) | 9798350347159 |
| DOIs | |
| State | Published - 2022 |
| Event | 6th IEEE Conference on Energy Internet and Energy System Integration, EI2 2022 - Chengdu, China Duration: 11 Nov 2022 → 13 Nov 2022 |
Publication series
| Name | EI2 2022 - 6th IEEE Conference on Energy Internet and Energy System Integration |
|---|
Conference
| Conference | 6th IEEE Conference on Energy Internet and Energy System Integration, EI2 2022 |
|---|---|
| Country/Territory | China |
| City | Chengdu |
| Period | 11/11/22 → 13/11/22 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- carbon emissions
- low carbon policies
- power generation planning
- robust optimization
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