Approximate dynamic programming-based decentralised robust optimisation approach for multi-area economic dispatch considering wind power uncertainty

This study presents a fully decentralised robust optimisation (RO) approach for multi-area economic dispatch (MA-ED) in the presence of wind power uncertainty. Unlike traditional algorithms, the authors formulate this MA-ED problem as dynamic programming problem, and decompose the centralised robust...

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Veröffentlicht in:IET renewable power generation Jg. 14; H. 13; S. 2376 - 2385
Hauptverfasser: Zhu, Jianquan, Wang, Chenxi, Guo, Ye, Luo, Tianyun, Mo, Xiemin, Xia, Yunrui
Format: Journal Article
Sprache:Englisch
Veröffentlicht: The Institution of Engineering and Technology 05.10.2020
Schlagworte:
approximate dynamic programming algorithm
approximate dynamic programming‐based
centralised robust MA‐ED problem
decentralised control
decision making
dispatch independence
dispatches
dynamic programming
dynamic programming problem
fully decentralised decision‐making
fully decentralised robust optimisation
multiarea economic dispatch
neighbouring areas
optimisation
power generation dispatch
power generation economics
Research Article
robust optimisation approach
wind power uncertainty
wind power uncertainty
neighbouring areas
fully decentralised robust optimisation
centralised robust MA-ED problem
dynamic programming problem
dynamic programming
decentralised control
approximate dynamic programming-based
power generation dispatch
power generation economics
optimisation
robust optimisation approach
dispatches
fully decentralised decision-making
approximate dynamic programming algorithm
multiarea economic dispatch
decision making
dispatch independence
ISSN:1752-1416, 1752-1424
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Beschreibung
Zusammenfassung:This study presents a fully decentralised robust optimisation (RO) approach for multi-area economic dispatch (MA-ED) in the presence of wind power uncertainty. Unlike traditional algorithms, the authors formulate this MA-ED problem as dynamic programming problem, and decompose the centralised robust MA-ED problem into a series of sub-problems based on approximate dynamic programming algorithm. The value functions are proposed for each area to iteratively estimate the impacts of its dispatches on the dispatches of other areas which make decisions subsequently. The proposed algorithm does not require a central operator but only needs to exchange a small amount of information among neighbouring areas to achieve fully decentralised decision-making. It is practical in cases where the centralised operator cannot be implemented considering the dispatch independence and the detailed data of one area is unavailable considering the privacy. Additionally, the accuracy, adaptability and computational efficiency of the proposed algorithm are illustrated using numerical simulations on two test systems and an actual power system.
ISSN:1752-1416
1752-1424
DOI:10.1049/iet-rpg.2019.0794