Open AccessPortfolio management for a wind‐storage system based on distributionally robust optimisation considering a flexible ramping product
Author(s) -
Huang Chenyang,
Ma Hongyan,
Yan Zheng,
Chen Sijie,
Li Mingjie
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.2019.0964
Subject(s) - wind power , portfolio , profit (economics) , computer science , mathematical optimization , energy storage , renewable energy , robust optimization , operations research , reliability engineering , power (physics) , business , engineering , economics , microeconomics , finance , electrical engineering , mathematics , physics , quantum mechanics
A wind‐storage system (WSS) can use the synergy between wind farms and battery storages to mitigate the uncertainty of wind. With the flexible ramping capability of battery storages, a WSS can diversify its portfolio by selling energy, committing regulation services and offering flexible ramping products in a power market. The portfolio management problem of a WSS is studied here. The uncertainties of market prices and wind power are considered. In order to maximise the expected profit in the worst case, a distributionally robust optimisation model is proposed. The model is then reformulated as a solvable semidefinite optimisation problem. Real market data are used in the simulation, which validates the proposed method.