EMPIRE is a comprehensive power system model including generation, storage, and transmission capacity expansion. It is designed to determine optimal capacity investments under operational uncertainty, while also incorporating long- and short-term dynamics.To achieve these objectives, EMPIRE is a stochastic linear program endogenously considering uncertainty on an hourly operational resolution of (1) nationally aggregated load and (2) availability of variable renewable supply. The model considers net transfer capacity (NTC) of power exchange between countries, up-ramping constraints for generators and investment and operation of storage technologies.

EMPIRE has three key advantages in contrast to other power sector models. The first is the special handling of challenges given by the variability of renewable technologies, in particular with wind and solar power, which highly impacts the supply and demand balance. Another major contribution of EMPIRE is that it simultaneously incorporates short- and long-term dynamics, in conjunction with short-term uncertainty. Dynamics refer to multiple investment periods coexisting with multiple sequential operational decision periods, while uncertainty is enhanced through multiple input scenarios that captures different operating conditions. Lastly, EMPIRE uses representative time periods (days or weeks) with an houlry resolution within each investment period to preserve computational tractability.
 

The team at NTNU started developing EMPIRE in 2010. The development started as part of Christian Skar's doctoral degree, and it has been developed and expanded by several researchers since then. The current research team is continuously improving it to maintain topicality, applicability and efficiency. Therefore, EMPIRE contains recent research results, up-to-date data and a clean code basis.

The core of EMPIRE is to generating optimal long-term investment decisions in the European power system towards 2050 with short-term operations. Therefore, the main results include estimation of generation-, storage- and transmission-capacity in Europe, from the start to end year, which are currently 2010 to 2050.

EMPIRE can be flexibly adjusted to to optimize given different developments, e.g. allowing investments in CCS and demand responde. Currently, the team is working on including developments of electric vehicle charging and allowing integrated energy operation between the power system and the heat system for buildings.

The results blow show the generation capacity expansion in Europe from 2010-2050 assuming no CCS technology allowed and an increasing carbon price according to the EU Reference Scenario 2016. The figure shows the total cumulative installed capacity (left) and expected annual generation (right) for all of Europe.

Furthermore, the long-term study is directly linked to short-term operation (hourly dispatch) of generators, storages and transmission lines under uncertainty. It applies the multi-horizon concept in the stochastic composition which is key in creating a computationally tractable problem. Short-term operations are done for representative hours (one week) in several seasons.

Therefore, you can also analyze short term operations of different technologies in different representative hours and countries. The figure below shows hourly operation of France for a winter week in 2040. The black line represents inelastic demand, the yellow line represents net charging of storage technologies while the red line represents net transmission exchange out from France. In this example, France mostly exports surplus energy produced by wind power plants, while storages are used for short term load balancing between days.

EMPIRE model is open access and available for anyone interesting in analysing the transformation of the energy system.
The current version of EMPIRE is downloadable in the link below. We also provide a documentation guide that details how to install the model and different specifications on its usage. In order to download the data files and the documentation you need to install git lfs. See here for more information: https://git-lfs.github.com/
You can download the EMPIRE model at our git here.

• Crespo del Granado, P. C., Skar, C., Doukas, H., & Trachanas, G. P. (2019). Investments in the EU Power System: A Stress Test Analysis on the Effectiveness of Decarbonisation Policies. In Understanding Risks and Uncertainties in Energy and Climate Policy (pp. 97-122). Springer, Cham.
• Skar, C., Egging, R., & Tomasgard, A. (2016). The role of transmission and energy storage for integrating large shares of renewables in Europe. In IAEE Energy Forum (Vol. 1).
• Skar, C., Doorman, G. L., Pérez-Valdés, G. A., & Tomasgard, A. (2016). A multi-horizon stochastic programming model for the European power system. Subimtted to an international peer reviewed journal, In review.
• Skar, C., Doorman, G., & Tomasgard, A. (2014, May). The future European power system under a climate policy regime. In Energy Conference (ENERGYCON), 2014 IEEE International (pp. 318-325). IEEE.