Back-End Design and Development of an Energy Systems Analysis Tool

Abstract

Abstract Low-carbon transformation of the energy system requires a combination of technology and policy options to ensure reliable, affordable, and clean energy. An assessment of plausible transition pathways can be guided with a set of tools that cover multi-sector dynamics of transitions and consider economy-wide and sectoral life-cycle analysis of numerous options. Sustainable Energy Systems Analysis Modeling Environment (SESAME) is a comprehensive system-level and pathway-level analysis model. Pathway-level analysis includes two main analysis types: life cycle assessment (LCA) and techno-economic assessment (TEA). The framework allows users to assess the sensitivity of key technological, operational, and geographical parameters associated with various energy pathways as measured by the emissions and costs. In this paper, we present the back-end design and implementation of the SESAME web application. The key contribution of web-based framework is that it supports easy integration of new LCA and/or TEA models and data sources in the backend so they can be made easily available to users for analysis via the front-end web interface. We achieve this by creating a Python-based library of classes and functions that model a higher-level code-based representation of LCA and TEA pathways. The tool is designed to capture the inherent modularity of SESAME, which makes it easier to add either new pathways or new data models and sources for existing pathways.