The Python package pyam for analysis, validation & visualization of integrated-assessment and energy-systems scenarios

This presentation was given as part of the ECEMP conference (https://www.energymodellingplatform.eu/conferences/ecemp-2022/) on October 6th 2022

The MESSAGEix Integrated Assessment Model and the ix modeling platform (ixmp)

The MESSAGE Integrated Assessment Model (IAM) developed by IIASA has been a central tool of energy-environment-economy systems analysis in the global scientific and policy arena. It played a major role in the Assessment Reports of the Intergovernmental Panel on Climate Change (IPCC); it provided marker scenarios of the Representative Concentration Pathways (RCPs) and the Shared Socio-Economic Pathways (SSPs); and it underpinned the analysis of the Global Energy Assessment (GEA). Alas, to provide relevant analysis for current and future challenges, numerical models of human and earth systems need to support higher spatial and temporal resolution, facilitate integration of data sources and methodologies across disciplines, and become open and transparent regarding the underlying data, methods, and the scientific workflow. In this manuscript, we present the building blocks of a new framework for an integrated assessment modeling platform; the \ecosystem" comprises: i) an open-source GAMS implementation of the MESSAGE energy++ system model integrated with the MACRO economic model; ii) a Java/database backend for version-controlled data management, iii) interfaces for the scientific programming languages Python & R for efficient input data and results processing workflows; and iv) a web-browser-based user interface for model/scenario management and intuitive \drag-and-drop" visualization of results. The framework aims to facilitate the highest level of openness for scientific analysis, bridging the need for transparency with efficient data processing and powerful numerical solvers. The platform is geared towards easy integration of data sources and models across disciplines, spatial scales and temporal disaggregation levels. All tools apply best-practice in collaborative software development, and comprehensive documentation of all building blocks and scripts is generated directly from the GAMS equations and the Java/Python/R source code

North American natural gas and energy markets in transition: insights from global models

This modeling comparison exercise looks at the global consequences of increased shale gas production in the U.S. and increased gas demand from Asia. We find that differences in models' theoretical construct and assumptions can lead to divergences in their predictions about the consequences of U.S. shale gas boom. In general, models find that U.S. High Shale Gas scenario leads to increased U.S. production, lower global gas prices, and lower gas production in non-U.S. regions. Gas demand in Asia alone has little effects on U.S. production; but together with the shale gas boom, the U.S. can have a large export advantage. Overall, models find U.S. exports level range from 0.06 to 13.7 trillion cubic feet (TCF) in 2040. The comparison of supply, demand, and price changes in response to shocks reveals important differences among models. First is how the demand shocks were implemented and how the model responds to shocks: static and elastic within each time period vs. endogenous to the long-term gross domestic product (GDP) growth. Second is how the supply response is expressed through fuel/technology substitutions, particularly the flexibility of cross-fuel substitution in the power sector. Identifying these differences is important in understanding the model's insights and policy recommendations

Assessing global climate change mitigation scenarios from a power system perspective using a novel multi-model framework

There is a debate within the scientific and policy making community as to the suitability of global integrated assessment models (IAMs) for long-term planning exercises of the global power system. This study informs this debate and proposes a methodological framework for soft-linking of global IAMs with detailed global power system models. With the proposed open-source framework, the scenario results from IAMs can be fed into a power system model to assess given scenarios with enhanced spatial, technological, and temporal resolution. Results from these simulations can be redirected to the IAM through iterative bi-directional soft-linking. A proof of concept application of the proposed framework is presented by linking global IAM MESSAGEix-GLOBIOM with global power system model PLEXOS-World. Among others, the results highlight that the assumption of unconstrained electricity flows inside large regional copperplates causes an overestimation of variable renewables integration potential within MESSAGEix-GLOBIOM. We propose areas for informed improvements in MESSAGEix-GLOBIOM

Local Consequences of Global Uncertainty: Capacity Development and LNG Trade Under Shale Gas and Demand Uncertainty and Disruption Risk

Recent supply security concerns in Europe have revived interest into the natural gas market. Here, we investigate investment behavior and trade in an imperfect market structure under uncertainty in both supply and demand. We focus on three uncertain events: i) transit of Russian gas via Ukraine that may be disrupted from 2020 on; ii) natural gas intensity of electricity generation in OECD countries that may lead to higher or lower natural gas demand after 2025; and iii) availability of shale gas around the globe after 2030. We illustrate how timing of investments is affected by inter-temporal hedging behavior of market agents, such as when LNG capacity provides ex-ante flexibility (e.g., in Ukraine to hedge for a possible Russian supply disruption) or an expost fallback option if domestic or nearby pipeline supply sources are low (e.g., uncertain shale gas resources in China). Moreover, we find that investment in LNG capacities is more determined by demand side pull (due to higher needs in electric power generation) than by supply side push (higher shale gas supplies needing an outlet)

Decarbonization pathways and energy investment needs for developing Asia in line with 'well below' 2 °C

Exploring potential future pathways for developing Asia’s energy consumption, CO2 emissions and infrastructure investment needs is essential to understanding how the countries of this rapidly growing region may contribute to the global climate targets set out in the 2015 Paris Agreement. To this end, this study employs the state-of-the-art global integrated assessment model MESSAGEix-GLOBIOM to investigate mid-century decarbonization strategies for developing Asia to 2050. Our results indicate that a radical change in the energy portfolio is required to reach the target of ‘well below’ 2°C. Specifically, our scenarios point to a rapid reduction of fossil fuel utilization, enhancement of low-carbon energy supply, and boosting of energy efficiency efforts. Such a transformation leads to a deep cut in CO2 emissions by 78% and 93% by 2050 in scenarios consistent with the 2°C and 1.5°C targets, respectively. Electricity generation and final energy consumption become dominated by low-carbon energy by 2050 in these scenarios. In terms of investment needs beyond a baseline scenario, the 2°C and 1.5°C pathways imply that the scale of low-carbon investment may need to double and triple, respectively. These increases would be partially offset by disinvestment in coal, oil and natural gas extraction and conversion infrastructure. Decarbonizing the energy system also impacts the capital needed for making progress on other sustainable development goals (SDGs), such as air pollution, clean water and food security