Open AccessProvision of flexible ramping product by battery energy storage in day‐ahead energy and reserve markets
Author(s) -
Hu Jiahua,
Sarker Mushfiqur R.,
Wang Jianhui,
Wen Fushuan,
Liu Weijia
Publication year - 2018
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/iet-gtd.2017.1522
Subject(s) - news aggregator , environmental economics , renewable energy , energy storage , computer science , profit (economics) , electricity , electricity market , demand response , risk analysis (engineering) , electric power system , reliability engineering , operations research , business , economics , power (physics) , microeconomics , engineering , electrical engineering , physics , quantum mechanics , operating system
The variability and uncertainty of renewable energy resources introduce significant challenges to power system operation. One particular example is the occurrence of ramp capability shortage in real‐time dispatch, which can cause power balance violations and price spikes. To meet the increasing need for ramp capability, some independent system operators in the USA have led initiatives to promote the implementation of flexible ramping product (FRP). More potential FRP providers, apart from conventional generators, are being explored, among which battery energy storage (BES) appears to be a feasible option owing to its good controllability and fast responsive characteristics. This study proposes an optimisation model for a BES aggregator to optimally provide FRP in day‐ahead energy and reserve markets, aiming to maximise its monetary benefits. The basic concept of FRP is first introduced, including comparisons with traditional ancillary services, pricing mechanisms, and the extensions of market models to integrate FRP. The modes and strategies for BES aggregators to participate in the electricity markets are then addressed. Case studies indicate that an aggregator can gain more profit by optimally allocating its resources among various products than only providing energy and reserves. A sensitivity analysis on several key factors is also conducted.