|کد مقاله||کد نشریه||سال انتشار||مقاله انگلیسی||ترجمه فارسی||نسخه تمام متن|
|5000956||1368405||2017||8 صفحه PDF||سفارش دهید||دانلود کنید|
- A complete MILP model for BESS considering the effect on cycle-life degradation and variable efficiency based on its operations.
- A data-driven method to transform variable C-rate degradation and efficiencies into economic proxies that can be included into the optimization framework.
- Application of a BESS exploiting energy arbitrage under local retail electricity tariffs while considering tradeoff between potential revenue and degradation.
The utilization of grid-scale energy storage is growing exponentially due its decreasing costs and added flexibility to providing numerous services. Among the currently available storage systems, batteries based on lithium-ion chemistries are poised to provide a significant share of such flexibility due to their high power and energy density, and relatively low cost per unit energy. However, research on such systems has been segregated into focus on its chemical properties, and focus on the grid integration separately. This paper proposes a data-driven framework to characterize battery energy storage systems embedded into a decision-making optimization model. The model embeds two mechanisms, variable C-rates and variable efficiencies, so that batteries may be scheduled at high-power (high C-rate) operations to capture additional grid revenues, only if economical against the cost of degradation effects. The framework is applied to stationary battery energy storage systems in retail markets in order to explore the improved energy arbitrage benefits.
Journal: Electric Power Systems Research - Volume 152, November 2017, Pages 342-349