Energy Scenario Exploration with Modeling to Generate Alternatives (MGA)

TL;DR

This paper integrates the modeling to generate alternatives (MGA) technique into an open-source energy modeling framework to systematically explore diverse energy system configurations under uncertainty.

Contribution

It introduces MGA into Temoa, enabling systematic exploration of near-optimal energy system alternatives within an open-source modeling environment.

Findings

Demonstrates MGA integration in Temoa for energy system analysis

Explores alternative energy futures for U.S. electric and transport sectors

Emphasizes methodological approach over specific results

Abstract

Energy system optimization models (ESOMs) should be used in an interactive way to uncover knife-edge solutions, explore alternative system configurations, and suggest different ways to achieve policy objectives under conditions of deep uncertainty. In this paper, we do so by employing an existing optimization technique called modeling to generate alternatives (MGA), which involves a change in the model structure in order to systematically explore the near-optimal decision space. The MGA capability is incorporated into Tools for Energy Model Optimization and Analysis (Temoa), an open source framework that also includes a technology rich, bottom up ESOM. In this analysis, Temoa is used to explore alternative energy futures in a simplified single region energy system that represents the U.S. electric sector and a portion of the light duty transport sector. Given the dataset limitations, we place greater emphasis on the methodological approach rather than specific results.