Open AccessOptimal energy management of compressed air energy storage in day‐ahead and real‐time energy markets
Author(s) -
Nojavan Sayyad,
AkbariDibavar Alireza,
Zare Kazem
Publication year - 2019
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.2018.7022
Subject(s) - energy (signal processing) , compressed air energy storage , energy storage , computer science , energy management , compressed air , environmental science , real time computing , engineering , mathematics , mechanical engineering , thermodynamics , physics , statistics , power (physics)
A hybrid stochastic‐robust optimisation framework for compressed air energy storage (CAES) independent owners is proposed to provide optimal bids and offers in both day‐ahead (DA) and real‐time (RT) energy arbitrage markets. The RT energy market has an excellent opportunity for energy arbitrage, but there are few works which consider this trading. To deal with uncertain characteristics of market prices in the presented study, for DA market stochastic programming (SP) is proposed; however, for RT stage the uncertainty and volatility of electricity price are managed by robust optimisation approach (ROA), and the CAES owner will be safe against undesired price fluctuations. At first, the optimal scheduling of CAES is investigated in the DA market considering price scenarios. After the DA market realisation, additional bids and offers at RT stage will be determined. The proposed optimisation is modelled mathematically as mixed integer linear programming (MIP) and handled by GAMS optimisation software. Using ROA, participation in the RT market can increase the profit of the CAES units. The gained profit in RT market is directly related to robustness level and is selected by decision maker.