The rising significance of renewable energy increases the importance of representing time-
varying input data in energy system optimization studies. Time-series aggregation, which …

To account for volatile renewable energy supply, energy systems optimization problems
require high temporal resolution. Many models use time-series clustering to find …

Shares of renewable energy are rapidly increasing in many countries due to emissions
policies and declining prices. Investment planning for future renewable deployment often …

Abstract Generation Capacity Expansion Planning (GCEP) requires high temporal resolution
to account for the volatility of renewable energy supply. Because the GCEP optimization …

When considering the design of electricity-intensive industrial processes, a challenge is that
future electricity prices are highly uncertain. Design decisions made before construction can …

To reduce computational complexity, macro-energy system models commonly implement
reduced time-series data. For renewable energy systems dependent on seasonal storage …

This paper investigates the role of a transmission system operator within a carbon footprint
reduction strategy incorporating carbon taxes and renewable energy generation subsidies …

Summary CapacityExpansion is a Julia (Bezanson, Edelman, Karpinski, & Shah, 2017)
implementation of a scale-independent capacity expansion modelling framework. It provides …

The electricity sector will play an important role in the transition to a more sustainable energy
system. In order to reduce the sector's carbon dioxide emissions, renewable energy is …

Energy and media supply systems and related infrastructure at industrial sites have grown
historically and is largely dependent on the use of fossil fuels. High fuel prices and the …