Capacity Planning for Forming Sustainable and Cost-Effective Nanogrids

Abstract

This paper proposes a new strategy for nanogrid capacity planning as a bilevel programming mathematical model with look-ahead logic. The first program, the Planner, is a linear program that solves for the optimal size of the Nano-grid comprising a PV solar system and a battery energy storage system. The second program, the Operator, is a mixed integer linear program that uses resultant sizes from the Planner and other data and then solves for the optimal asset dispatch on an hourly basis throughout the whole horizon. 24-hours is used as the main optimization window, to be consistent with real case operations of day-ahead scheduling but longer windows were also tested with the Lookahead (LA) logic. A sensitivity to LA logic was applied for an analysis conducted on cost-effectiveness, system sustainability, and local energy sufficiency. It was shown that implementing two days of LA logic reduces the import cost by 44%. Nano-grid was considered in this study to test the capacity planning strategy, but the methodology is also applicable to larger schemes.