How can Mexico achieve its climate targets and work toward the Paris Agreement goals? This working paper addresses this question by identifying and evaluating the key climate and energy policy options available to Mexico to support the implementation of its INDC. The analysis shows that Mexico can meet its unconditional and conditional targets while at the same time saving money and lives.
Energy Modeling: System Dynamics Studies
In October 2015, Energy Innovation launched Energy Policy Solutions, an assessment of climate and energy policies to help meet decarbonization goals. We created a computer model, the Energy Policy Simulator, to quantitatively measure the cost and emissions impacts of more than 50 policies across all economic sectors. This page summarizes key findings from our model analysis, including recommended policy packages for meeting the U.S. 2025 emissions target and the Clean Power Plan target.
Discover the most effective policies to decarbonize America’s economy at the lowest cost. The Energy Policy Simulator was designed to empower decision makers to find the best course toward a low-carbon U.S. economy. The Energy Policy Simulator works in real-time to measure the cost and emissions impacts of more than 50 climate and energy policies.
Energy Innovation identified a cost-effective package of six policies that the U.S. could use to meet the Clean Power Plan at a national average scale. This scenario actually exceeds the emissions goals in later years, as policies designed to meet earlier targets continue to reap benefits in later years, and saves the U.S. more than $40 billion between 2016 and 2030.
A Model of Energy Policy Impacts on Pollutant Emissions, Costs, and Social Benefits Developed for China’s Central Government
This paper describes Energy Innovation’s Energy Policy Simulator, a system dynamics model that assists in selecting policies that will allow China to achieve its emissions reduction goals. The model’s results find that China can peak its carbon emissions before its target year of 2030, and this is done most cost-effectively via a package of policies supporting a diverse set of technologies.
This study uses a causal loops diagram and system dynamics model to evaluate three renewable energy policies for Finland to determine the country’s future level of dependency on imported energy sources. It’s objective is to address the research gaps that exist in modeling energy security, and demonstrate the role of energy diversification for a country that is currently import-dependent for its energy supply.
This study uses a system dynamics model to measure the impact of industrial structure upgrades to reduce carbon dioxide emissions while maintaining GDP growth. The model uses input-output data tables to calculate the industrial influence coefficients (IIC) and the industrial carbon emission coefficients (ICEC) for all of China’s industrial sectors. These coefficients are used to determine which Chinese industries are the highest emitters in order to develop effective emissions reduction strategies.
Exploring the options for carbon dioxide mitigation in Turkish electric power industry: System dynamics approach
This study uses a system dynamics approach to model various mitigation options that Turkey could implement to reduce emissions in its electric power sector. The model’s mitigation strategy inputs are focused mainly on supply-side solutions. The model simulates policy options such as feed-in tariffs, renewable energy investment subsidies, and a carbon tax to determine their impact in terms of emissions reduction and energy costs.
A system dynamics model for analyzing energy consumption and CO2 emission in Iranian cement industry under various production and export scenarios
This paper uses a system dynamics model to analyze energy consumption and carbon dioxide emissions in the Iranian cement industry. It estimates new energy prices and energy demand in the cement industry for the next 20 years. The study emphasizes three corrective policies in its model; production of blended cement, production using waste materials as alternative fuel, and use of waste heat recovery for electricity generation.
System dynamics modeling for urban energy consumption and CO2 emissions: A case study of Beijing, China
The study examines the relationship between energy demand and the economic and social environment to help predict municipal energy demand and carbon emissions in a rapidly expanding urban region, using Beijing as a case study. It uses a system dynamics model to demonstrate Beijing’s energy consumption and carbon dioxide emissions trends between 2005 and 2030. The study estimates that total energy demand in Beijing will more than double by 2030, compared to 2005 levels. China’s transition from coal to natural gas will play a large role in keeping emissions low while energy demand continues to rise.