Research on Collaborative optimization Decision Method of Source-Grid-Load-Storage

Author(s):  
Xiaorui Guo ◽  
Ke Wang ◽  
Liwen Wang ◽  
Shaofei Shen ◽  
Chen Zhang
2013 ◽  
Vol 709 ◽  
pp. 417-420
Author(s):  
Yue Xiang ◽  
Jun Yong Liu ◽  
You Bo Liu

Collaborative optimization and control of integrated distribution system/ microgrid with high penetration of distributed energy have been introduced in this paper. Along with the development of the smart grid, source-grid-load coordination framework, unit flexibility and load feasibility, muti-energy combination microgrid optimization, control strategies are introduced, and related methodologies and approaches are concluded, as well as the further research.


AIAA Journal ◽  
2000 ◽  
Vol 38 ◽  
pp. 1931-1938 ◽  
Author(s):  
I. P. Sobieski ◽  
I. M. Kroo

2021 ◽  
Vol 13 (6) ◽  
pp. 3400
Author(s):  
Jia Ning ◽  
Sipeng Hao ◽  
Aidong Zeng ◽  
Bin Chen ◽  
Yi Tang

The high penetration of renewable energy brings great challenges to power system operation and scheduling. In this paper, a multi-timescale coordinated method for source-grid-load is proposed. First, the multi-timescale characteristics of wind forecasting power and demand response (DR) resources are described, and the coordinated framework of source-grid-load is presented under multi-timescale. Next, economic scheduling models of source-grid-load based on multi-timescale DR under network constraints are established in the process of day-ahead scheduling, intraday scheduling, and real-time scheduling. The loads are classified into three types in terms of different timescale. The security constraints of grid side and time-varying DR potential are considered. Three-stage stochastic programming is employed to schedule resources of source side and load side in day-ahead, intraday, and real-time markets. The simulations are performed in a modified Institute of Electrical and Electronics Engineers (IEEE) 24-node system, which shows a notable reduction in total cost of source-grid-load scheduling and an increase in wind accommodation, and their results are proposed and discussed against under merely two timescales, which demonstrates the superiority of the proposed multi-timescale models in terms of cost and demand response quantity reduction.


2021 ◽  
Vol 556 ◽  
pp. 209-222
Author(s):  
Hua Li ◽  
Runmin Cong ◽  
Sam Kwong ◽  
Chuanbo Chen ◽  
Qianqian Xu ◽  
...  

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