Open AccessDistributed accelerated descent algorithm for energy resource coordination in multi‐agent integrated energy systems
Author(s) -
Kou Yu,
Wang Yinghui,
Bie Zhaohong,
Wang Xu,
Ding Tao
Publication year - 2021
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/gtd2.12142
Subject(s) - initialization , computer science , robustness (evolution) , distributed algorithm , algorithm , mathematical optimization , convergence (economics) , distributed computing , process (computing) , energy (signal processing) , regular polygon , mathematics , statistics , biochemistry , chemistry , geometry , economics , gene , programming language , economic growth , operating system
Composed of multiple integrated energy systems (IESs) belonging to different stakeholders, multi‐agent IESs (MA‐IESs) are widely concerned because of data privacy protect. As the basis of planning design and reliability evaluation for MA‐IESs, distributed energy resource coordination (DERC) problem is studied in this paper. First, a DERC model for MA‐IESs is established, which considers energy conversion process specifically. Meanwhile, a novel distributed accelerated descent (DAD) algorithm is proposed to realize fully distributed solving. Different from most of the existing researches that investigate the DERC with box constraints, the presented algorithm is able to solve the DERC with general convex constraints. Moreover, the backward operators in the method improve the convergence rate to the best of distributed first‐order optimization algorithm with fixed step size, O ( 1 / T ) . Furthermore, the presented approach is initialization robustness when the load fluctuations suddenly happened in MA‐IESs. The convergence property, computing, and communication complexity are strictly proved. Finally, the effectiveness of DERC model and DAD algorithm are demonstrated by some modified case studies.