Hybrid Energy-economy Model Research Articles

Abundant low-cost natural gas and deep GHG emissions reductions for the United States

This paper analyzes the implications of the natural gas revolution on the US’ ability to achieve deep GHG emissions reductions of 80% below 2005 levels by 2050. It uses a hybrid energy-economy model to test how prevailing low US natural gas prices influence the magnitude of the required carbon price needed to achieve this target. While the paper finds in general that lower gas prices resulting from plentiful gas necessitate a higher carbon price to achieve this target, informing firms and consumers in advance about the magnitude of the future carbon price can lower the necessary level.

A hybrid energy-economy model for global integrated assessment of climate change, carbon mitigation and energy transformation

• This paper introduces the design of a hybrid energy-economy model, GTEM-C. • The model offers a unified tool to analyse the energy-carbon-environment nexus. • Results are presented on global energy transformation due to carbon mitigation. • Electrification with renewable energies can contain the spiking of carbon prices. This paper introduces the design of the CSIRO variant of the Global Trade and Environment model (GTEM-C). GTEM-C is a hybrid model that combines the top-down macroeconomic representation of a computable general equilibrium model with the bottom-up engineering details of energy production. The model features detailed accounting for global energy flows that are embedded in traded energy goods, and it offers a unified framework to analyse the energy-carbon-environment nexus. As an illustrative example, we present simulation results on global energy transformation under the Intergovernmental Panel on Climate Change’s representative carbon pathways 4.5 and 8.5. By testing the model’s sensitivity to the relevant parameter, we find that the pace of electrification will significantly contain the spiking of carbon prices because electricity can be produced from carbon-free or less carbon-intensive technologies. The decoupling of energy use and carbon footprint, due to the uptake of clean electricity technologies, such as nuclear, wind, solar, and carbon capture and storage, allows the world to maintain high level of energy consumption, which is essential to economic growth.

Remind-D: A Hybrid Energy-Economy Model of Germany

This paper presents a detailed documentation of the hybrid energy-economy model REMIND-D. REMIND-D is a Ramsey-type growth model for Germany that integrates a detailed bottom-up energy system module, coupled by a hard link. The model provides a quantitative framework for analyzing long-term domestic CO2 emission reduction scenarios. Due to its hybrid nature, REMIND-D facilitates an integrated analysis of the interplay between technological mitigation options in the different sectors of the energy system as well as overall macroeconomic dynamics. REMIND-D is an intertemporal optimization model, featuring optimal annual mitigation effort and technology deployment as a model output. In order to provide transparency on model assumptions, this paper gives an overview of the model structure, the input data used to calibrate REMIND-D to the Federal Republic of Germany, as well as the techno-economic parameters of the technologies considered in the energy system module.

Energy efficiency and the cost of GHG abatement: A comparison of bottom-up and hybrid models for the US

A highly influential report by the McKinsey consulting firm suggests that a large potential for profitable energy efficiency exists in the US, and that substantial greenhouse gas emissions reductions can therefore be achieved at a low cost. This result is consistent with other studies conducted using a bottom-up methodology that dates back to the work of Lovins beginning in the 1970s. Research over the past two decades, however, has identified shortcomings with the conventional bottom-up approach, and this has led to the development of new analytical frameworks that are referred to as hybrid energy–economy models. Using the CIMS hybrid model, we conducted simulations for comparison with the McKinsey results. These exercises suggest a more modest potential to reduce greenhouse gas emissions at a given marginal cost, as well as a smaller contribution from energy efficiency relative to other abatement opportunities such as fuel switching and carbon capture and storage. Hybrid models incorporate parameters reflecting risk and quality into their estimates of technology costs, and our analysis suggests that these play a significant role in explaining differences in the results.

Comparing and Combining Energy Saving Policies: Will Proposed Residential Sector Policies Meet French Official Targets?

This paper assesses the impact of French policies for residential space-heating energy consumption, both enacted (tax credits for the purchase of energy efficient durables, soft loans for retrofitting actions, stringent building codes) and anticipated (carbon tax, retrofitting obligation). It uses a hybrid energy-economy model incorporating specific features of energy conservation, notably the rebound effect and some barriers to energy efficiency such as split incentives and imperfect information. Forward-looking simulations show that (i) stand-alone policies improve the energy efficiency of the building stock but, with the exception of carbon tax, generate a rebound effect ; (ii) interactions among instruments are roughly additive ; (iii) a combination of all policies fails to meet Government conservation targets.

Statistical Simulation to Estimate Uncertain Behavioral Parameters of Hybrid Energy-Economy Models

In energy-economy modeling, new hybrid models attempt to combine the technological explicitness of bottom-up models with the macroeconomic feedbacks and statistically estimated behavioral parameters of top-down models. However, statistical estimation of behavioral parameters (portraying firm and household technology choices) with such models is challenged by the number of uncertain variables and the lack of historical data on technologies in terms of capital costs, operating costs, and market shares. Multiple combinations of parameter values might equally explain past technology choices. This paper reports on the application of a Bayesian statistical simulation approach for estimating the most likely values for these key behavioral parameters in order to best explain past technology choices and then simulate policies to influence future technology choices. The method included (1) data collection of key technology market shares, capital costs, and operating costs over the past; (2) backcasting a hybrid energy-economy model over a historical time period; and (3) the application of Markov chain Monte Carlo statistical simulation using the Metropolis–Hastings algorithm as a tool for estimating distributions for key parameters in the model. The results provide a means of indicating the uncertainty bounds around key behavioral parameters when generating forecasts of the effect of certain policies. However, the results also indicate that this approach may have limited applicability, given that future available technologies may differ substantially from past technologies and that it is difficult to separate the effects of parameter uncertainty from model structure uncertainty.

Modeling Efficiency Standards and a Carbon Tax: Simulations for the U.S. using a Hybrid Approach

Analysts using a bottom-up approach have argued that a large potential exists for improving energy efficiency profitably or at a low cost, while top-down modelers tend to find that it is more expensive to meet energy conservation and greenhouse gas (GHG) reduction goals. Hybrid energy-economy models have been developed that combine characteristics of these divergent approaches in order to help resolve disputes about costs, and test a range of policy approaches. Ideally, such models are technologically explicit, take into account the behavior of businesses and consumers, and incorporate macroeconomic feedbacks. In this study, we use a hybrid model to simulate the impact of end-use energy efficiency standards and an economy-wide carbon tax on GHG emissions and energy consumption in the U.S. to the year 2050. Our results indicate that policies must target abatement opportunities beyond end-use energy efficiency in order to achieve deep GHG emissions reductions in a cost-effective manner. doi: 10.5547/ISSN0195-6574-EJ-Vol32-SI1-4

Comparing and Combining Energy Saving Policies: Will Proposed Residential Sector Policies Meet French Official Targets?

This paper assesses the impact of French policies for residential space-heating energy consumption, both enacted (tax credits for the purchase of energy efficient durables, soft loans for retrofitting actions, stringent building codes) and anticipated (carbon tax, retrofitting obligation). It uses a hybrid energy-economy model incorporating specific features of energy conservation, notably the rebound effect and some “barriers” to energy efficiency such as split incentives and imperfect information. Forward-looking simulations show that (i) stand-alone policies improve the energy efficiency of the building stock but, with the exception of carbon tax, generate a rebound effect; (ii) interactions among instruments are roughly additive; (iii) a combination of all policies fails to meet Government conservation targets. doi: 10.5547/ISSN0195-6574-EJ-Vol32-SI1-12

Hybrid modeling of industrial energy consumption and greenhouse gas emissions with an application to Canada

In this paper, we explore the implications for Canada's industrial sector of an economy-wide, compulsory greenhouse gas reduction policy, such as a tax or emissions cap and tradable permits system. The model used in the analysis is CIMS, a hybrid energy-economy model that combines characteristics of the contrasting top-down and bottom-up approaches in order to generate useful information for policy makers. CIMS is technologically explicit, behaviorally realistic, and has the ability to model equilibrium feedbacks. However, each of these strengths is linked to challenges when it comes to forecasting the impact of greenhouse gas policy. We explore the strengths and weaknesses of CIMS, and provide results from simulating the response of the Canadian industrial sector to GHG charges implemented throughout the economy, starting in the year 2006 and extending to the year 2030.

The application of a hybrid energy-economy model to a key developing country – China

Energy security, local air pollution and GHG emissions are three key challenges facing China's decision-makers. In this study, we first applied CIMS, a hybrid (bottom-up/top-down) energy-economy model, to test how different policy packages could be designed to alleviate China's energy and environment challenges. Secondly, we compared the marginal abatement cost curve of this study with those of other analysts, and found that modeling methodology differences had significant impacts on cost estimates of GHG emission abatement. Finally, we derived the long-run autonomous energy efficiency indices (AEEIs) and elasticity of substitution (ESUB) values for China, and found that the aggregate Chinese AEEIs are somewhere between top-down and bottom-up estimates in the literature. Moreover, because the simulated ESUBs and AEEIs differ from one sector to another, this suggests that aggregated models with economy-wide values for these parameters may be unhelpful to policy-makers seeking to explore the effects of structural evolution on energy demand and emissions.

05/01915 Improving behavioural realism in hybrid energy-economymodels using discrete choice studies of personal transportation decisions: Horne, M. et al. Energy Economics, 2005, 27, (1), 59–77

05/01915 Improving behavioural realism in hybrid energy-economymodels using discrete choice studies of personal transportation decisions: Horne, M. et al. Energy Economics, 2005, 27, (1), 59–77

Improving behavioral realism in hybrid energy-economy models using discrete choice studies of personal transportation decisions

Hybrid energy-economy models combine top-down and bottom-up approaches to explore behaviorally realistic responses to technology-focused policies. This research uses empirically derived discrete choice models to inform key behavioral parameters in CIMS, a hybrid model. The discrete choice models are estimated for vehicle and commuting decisions from a survey of 1150 Canadians. With the choice models integrated into CIMS, we simulate carbon taxes, gasoline vehicle disincentives, and single occupancy vehicle disincentives to show how different policy levers can motivate technological change. We also use the empirical basis for the choice models to portray uncertainty in technological change, costs, and emissions.