Storage allocation and investment optimisation for transmission-constrained networks considering losses and high renewable penetration

• Published in: IET renewable power generation 2018-12, Vol.12 (16), p.1949-1956
• Main Authors: Yacar, Dean, Tejada-Arango, Diego A, Wogrin, Sonja
• Format: Article
• Language: English
• Subjects: capacity; compressed air energy storage; congested ones; cost characteristics; DC optimal power flow model; different storage technologies; energy storage allocation planning; fly wheel; flywheels; high renewable penetration; influential network inhibitor; inhibitor drives; investment optimisation; investment trials; line losses; linearised approximation; lithium‐ion battery; load flow; marginal changes; network characteristic; network congestion; ohmic losses; optimisation; power transmission economics; pumped hydro storage; renewable energy penetration; renewable energy sources; renewable power generation; Research Article; secondary cells; storage allocation trials; storage investment; substantial effects; transmission constraints; transmission losses; transmission‐constrained networks; utility‐scale storage
• ISSN: 1752-1416; 1752-1424; 1752-1424
• DOI: 10.1049/iet-rpg.2018.5472

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.