Paper Info
Title
Multi-Time Scale Trading Simulation of Source Grid Load Storage Based on Continuous Trading Mechanism for China
Abstract
The proportion of new energy in power systems is increasing yearly. How to deal with the adverse impact of new energy output uncertainty on its participation in trading from the mechanism level is an urgent problem in China that must be solved. A source grid load storage (SGLS) continuous trading mechanism and a multi-time scale trading simulation method are proposed which meet the needs of Chinese new energy consumption and satisfies the trading needs of Chinese power market players. Firstly, the connection mechanism of mid-long term, day-ahead, and intra-day SGLS interactive trading is established, and the meaning and ways of continuous development are defined. Secondly, the clearing model of SGLS trading based on the continuous trading mechanism is established to provide mathematical models and strategic methods for various resources to participate in SGLS trading. Then, the multi-time scale trading simulation of SGLS based on the continuous trading mechanism is carried out to obtain the trading strategies of different trading subjects. The example results show that compared with the trading mechanism based on deviation assessment, the one-day trading cost is reduced by 4.20% and the consumption rate of new energy is increased by 6.53%. It can be seen that the mid-long term-day-ahead-day SGLS interactive trading connection mechanism has advantages in reducing trading costs and improving the consumption rate of new energy. It can flexibly deal with the trading scenario of domestic new energy consumption and new energy reverse peak shaving, which has an effect on the adverse impact of trading and operation deviation caused by source load uncertainty on trading.
Year
DOI
Venue
2022
10.3390/s22062363
SENSORS
Keywords
DocType
Volume
source grid load storage, continuous trading mechanism, multi-time scale, trading simulation, interactive trading
Journal
22
Issue
ISSN
Citations 
6
1424-8220
0
PageRank 
References 
Authors
0.34
0
6
Name
Order
Citations
PageRank
Xun Dou100.68
Song Li2117.33
Shengnan Zhang300.34
Lulu Ding400.34
Ping Shao500.34
Xiaojun Cao600.34