Open AccessStorage allocation and investment optimisation for transmission‐constrained networks considering losses and high renewable penetration
Author(s) -
Yacar Dean,
TejadaArango Diego A.,
Wogrin Sonja
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.2018.5472
Subject(s) - renewable energy , energy storage , computer science , automotive engineering , environmental science , electrical engineering , engineering , power (physics) , physics , quantum mechanics
This study investigates the effects of transmission losses, constraints and increased renewable energy penetration on planning energy storage allocation and investment. By modifying a DC optimal power flow model using a linearised approximation for ohmic losses, the authors were able to understand which network characteristic or inhibitor drives the most change in expanding utility‐scale storage. Four different storage technologies were explored: compressed air energy storage, pumped hydro storage, lithium‐ion battery and fly wheel. Each had different charging, capacity and cost characteristics. The results of the storage allocation trials revealed that network congestion was a more influential network inhibitor than were line losses. Losses only had substantial effects on a free‐flowing network but produced marginal changes in allocation in congested ones. The conclusion of the investment trials revealed two things: (i) storage investment is not significantly affected by transmission constraints so long as renewable generation stays constant and relatively low; (ii) more flexible technologies like flywheels are favoured at lower volumes of renewable penetration for their load balancing capabilities while cheaper technologies are best as the volume of renewable power generated increases.