Open AccessMethod for planning a wind–solar–battery hybrid power plant with optimal generation‐demand matching
Author(s) -
Khalid Muhammad,
AlMuhaini Mohammed,
Aguilera Ricardo P.,
Savkin Andrey V.
Publication year - 2018
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.2018.5216
Subject(s) - renewable energy , wind power , stand alone power system , energy storage , grid parity , distributed generation , solar power , automotive engineering , photovoltaic system , hybrid power , intermittent energy source , grid energy storage , computer science , pumped storage hydroelectricity , solar energy , engineering , electrical engineering , power (physics) , quantum mechanics , physics
This study aims to propose a methodology for a hybrid wind–solar power plant with the optimal contribution of renewable energy resources supported by battery energy storage technology. The motivating factor behind the hybrid solar–wind power system design is the fact that both solar and wind power exhibit complementary power profiles. Advantageous combination of wind and solar with optimal ratio will lead to clear benefits for hybrid wind–solar power plants such as smoothing of intermittent power, higher reliability, and availability. However, the potential challenges for its integration into electricity grids cannot be neglected. A potential solution is to utilise one of the energy storage technologies, though all of them are still very expensive for such applications, especially at large scale. Therefore, optimal capacity calculations for energy storage system are also vital to realise full benefits. Currently, battery energy storage technology is considered as one of the most promising choices for renewable power applications. This research targets at battery storage technology and proposes a generic methodology for optimal capacity calculations for the proposed hybrid wind–solar power system.