Abstract
Through the market-oriented reform and operation in the recent 30 years, the organizational structure of power systems in the U.S. has formed a relatively stable situation, where various levels of power companies can supervise and restrict each other to create a set of perfect management, plan and approval mechanisms. In this paper, by use of the time series data of electricity price, renewable energy proportion and CO2 emission at each state from 1990 to 2014, we analyze these data from 50 states based on the approach of network science. Firstly, we perform the time series visualization according to the vision graph method. Subsequently, the correlation among these 50 states is calculated regarding the related indicators, and henceforth the relationship network between them is constructed. Finally, the community detection is used to cluster the specific policies carried out at various states. After the detailed analyses, it is indicated that all these 50 states can be divided into four categories as far as the policy of electric reform and power market is concerned. The current results provide some clues to deeply understand the electricity marketing reform in the U.S., and also offer some valuable hints for other countries to optimize the operation or reform of power systems.
| Original language | English |
|---|---|
| Article number | 125434 |
| Journal | Applied Mathematics and Computation |
| Volume | 385 |
| DOIs | |
| State | Published - 15 Nov 2020 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- Community structure
- Complex network
- Multi-dimensional analysis
- Power systems
- Visibility graph
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