English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Battery Energy Storage Systems (BESS) can mitigate effects of intermittentenergy production from renewable energy sources and play a critical role inpeak shaving and demand charge management. To optimally size the BESS from aneconomic perspective, the trade-off between BESS investment costs, lifetime,and revenue from utility bill savings along with microgrid ancillary servicesmust be taken into account. The optimal size of a BESS is solved via astochastic optimization problem considering wholesale market pricing. Astochastic model is used to schedule arbitrage services for energy storagebased on the forecasted energy market pricing while accounting for BESS costtrends, the variability of renewable energy resources, and demand prediction.The uniqueness of the approach proposed in this paper lies in the convexoptimization programming framework that computes a globally optimal solution tothe financial trade-off solution. The approach is illustrated by application tovarious realistic case studies based on pricing and demand data from theCalifornia Independent System Operator (CAISO). The case study results giveinsight in optimal BESS sizing from a cost perspective, based on both yearlyscheduling and daily BESS operation.

Market-Driven Energy Storage Planning for Microgrids with Renewable Energy Systems Using Stochastic Programming