Open AccessDynamic battery loss evaluation and its application for optimal online wind‐storage integrated scheduling
Author(s) -
Zhou Yun,
Su Hao,
Gui Qiang,
Gan Lei,
Feng Donghan,
Yan Zheng,
Fan Yue
Publication year - 2020
Publication title -
iet renewable power generation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.005
H-Index - 76
eISSN - 1752-1424
pISSN - 1752-1416
DOI - 10.1049/iet-rpg.2020.0344
Subject(s) - adaptability , state of charge , scheduling (production processes) , economic dispatch , mathematical optimization , reliability engineering , computer science , piecewise , electricity , capacity loss , wind power , battery (electricity) , engineering , electric power system , power (physics) , electrical engineering , mathematics , ecology , mathematical analysis , physics , quantum mechanics , biology
The life loss of batteries caused by the daily operation implies a reduction in capital value, which is essential for the economic performance of storage‐containing systems. Most of current studies rarely considered it or simplified it to be proportional of throughput electricity, due to its multi‐factor dependence and complexity to be incorporated into dispatch models. This study presents a dynamic loss evaluation model for batteries that considers the cumulative effect of state of charge (SOC) changes. First, based on the results of battery aging test, the loss coefficient subject to SOC is derived. The general formulation of analytical battery life loss is further presented by integrating the damage effect during the change in SOC. Finally, by means of self‐optimal piecewise linearisation, the resultant life loss term is embedded in the online wind‐storage integrated scheduling. Case studies demonstrate the desirable computational complexity of the proposed evaluation method and the adaptability in general economic dispatch.