Amit Kanudia

Robust responses to climate change via stochastic MARKAL: The case of Quebec

Future patterns of climate change and economic growth are critical parameters in long-term energy planning. This paper describes a multi-stage stochastic programming approach to formulate a flexible energy plan. The plan incorporates multiple future scenarios and provides for mid-course corrections depending upon the actual realizations of future uncertainties. Results are derived from the stochastic version of Extended MARKAL (MARKet ALlocation) model for Quebec, developed for this purpose. The analysis indicates significant savings of overall system cost in using a hedging strategy over any of the perfect foresight ones. With a 50% probability of implementing stringent carbon mitigation measures after 15 years, the emission trajectory takes the middle path till this uncertainty is resolved. Prior to resolution, electricity supply follows the middle path, natural gas and renewable energy tend to follow the low mitigation trajectory, and oil supply approaches the high mitigation trajectory. A set of specialized hedging technologies has been identified, which emerges more competitive in the hedging strategy than in any of the perfect foresight ones. The paper concludes that such treatment of future uncertainties can give insights that are beyond the scope of an analysis based on deterministic scenarios.

Minimax regret strategies for greenhouse gas abatement: methodology and application

Classical stochastic programming has already been used with large-scale LP models for long-term analysis of energy-environment systems. We propose a Minimax Regret formulation suitable for large-scale linear programming models. It has been experimentally verified that the minimax regret strategy depends only on the extremal scenarios and not on the intermediate ones, thus making the approach computationally efficient. Key results of minimax regret and minimum expected value strategies for Greenhouse Gas abatement in the Province of Quebec, are compared.

Advanced bottom-up modelling for national and regional energy planning in response to climate change

This paper describes an advanced bottom-up approach for modelling the energy-environment sector to study greenhouse gas abatement. Three new features are described that give significant new capabilities to this class of models. These are endogenisation of end-use demands, which allows computation of partial equilibria in energy markets; modelling future uncertainties using multi-stage stochastic programming; and combining several bottom-up models as a multi-region model to explore issues of cooperation and burden-sharing. Each of these new features is illustrated by results taken from large-scale extended MARKAL models of Quebec and Ontario. The focus of the paper is on the nature of issues that can be addressed by this methodology, rather than on specific conclusions drawn from the discussed examples. We believe that a very promising avenue of research lies in exploring the role of multiple advanced bottom-up models in the integrated assessment of climate change.

Worldwide impacts of climate change on energy for heating and cooling

The energy sector is not only a major contributor to greenhouse gases, it is also vulnerable to climate change and will have to adapt to future climate conditions. The objective of this study is to analyze the impacts of changes in future temperatures on the heating and cooling services of buildings and the resulting energy and macro-economic effects at global and regional levels. For this purpose, the techno-economic TIAM-WORLD (TIMES Integrated Assessment Model) and the general equilibrium GEMINI-E3 (General Equilibrium Model of International-National Interactions between Economy, Energy and Environment) models are coupled with a climate model, PLASIM-ENTS (Planet-Simulator- Efficient Numerical Terrestrial Scheme). The key results are as follows. At the global level, the climate feedback induced by adaptation of the energy system to heating and cooling is found to be insignificant, partly because heating and cooling-induced changes compensate and partly because they represent a limited share of total final energy consumption. However, significant changes are observed at regional levels, more particularly in terms of additional power capacity required to satisfy additional cooling services, resulting in increases in electricity prices. In terms of macro-economic impacts, welfare gains and losses are associated more with changes in energy exports and imports than with changes in energy consumption for heating and cooling. The rebound effect appears to be non-negligible. To conclude, the coupling of models of different nature was successful and showed that the energy and economic impacts of climate change on heating and cooling remain small at the global level, but changes in energy needs will be visible at more local scale.

The World-Markal Model and Its Application to Cost-Effectiveness, Permit Sharing, and Cost-Benefit Analyses

In this article, we present the new multiregional global MARKAL-TIMES1 model and on several recent applications to global energy-environment issues. The development of the model was motivated by the need to analyze international energy and environmental issues such as climate change, using a detailed, technology rich modeling framework. We then present three different types of application. First, the model is applied to conduct the cost-effectiveness analysis of Greenhouse Gas (GHG) emission abatement, whereby constraints on CO2 emissions are added to the base case formulation. The model then computes the cost-efficient response of the energy system to these emission targets. Second, we address the issue of “who pays”’ for emission reductions (whereas the cost-effictiveness analysis addressed the “who acts” issue). More precisely, we use the model to devise and evaluate certain allocation rules for attributing initial emission rights to regions in a cap-and-trade system. Third, we use World MARKAL in a cost-benefit mode, i.e. we augment the model with damage costs resulting from climate change, and run the integrated model without any pre-set targets on emissions or concentration. We then analyse cooperative and non-cooperative decisions by regions when confronted to the threat of damages. This last application makes systematic use of game theoretic concepts.

Energy Security: A Robust Optimization Approach to Design a Robust European Energy Supply via TIAM-WORLD

Energy supply routes to a given region are subject to random events, resulting in partial or total closure of a route (corridor). For instance, a pipeline may be subject to technical problems that reduce its capacity. Or, oil supply by tanker may be reduced for political reasons or because of equipment mishaps at the point of origin or again, by a conscious decision by the supplier in order to obtain economic benefits. The purpose of this article is to formulate a simplified version of the above issue that mainly addresses long-term uncertainties. The formulation is done via a version of the TIAM-WORLD Integrated Model, modified to implement the approach of robust optimization. In our case, the approach can be interpreted as a revival of chance-constrained programming under the name of distributionally robust, or ambiguous, chance-constrained programming. We apply the approach to improve the security of supply to the European Energy system. The resulting formulation provides several interesting features regarding the security of EU energy supply and has also the advantage to be numerically tractable.

Modeling Uncertainty in a Large scale integrated Energy-Climate Model

The well-known method of stochastic programming in extensive form is used on the large scale, partial equilibrium, technology rich global 15-region TIMES Integrated Assessment Model (ETSAP-TIAM), to assess climate policies in a very uncertain world. The main uncertainties considered are those of the Climate Sensitivity parameter, and of the rate of economic development. In this research, we argue that the stochastic programming approach is well adapted to the treatment of major uncertainties, in spite of the limitation inherent to this technique due to increased model size when many outcomes are modeled. The main advantage of the approach is to obtain a single hedging strategy while uncertainty prevails, contrary to classical scenario analysis. Furthermore, the hedging strategy has the very desirable property of attenuating the (in)famous ’razor edge‘ effect of Linear Programming, and thus to propose a more robust mix of technologies to attain the desired climate target. Although the examples treated use the classical expected cost criterion, the paper also presents, and argues in favor of, altering this criterion to introduce risk considerations, by means of a linearized semi-variance term, or by using the Savage criterion. Risk considerations are arguably even more important in situations where the random events are of a ’one-shot‘ nature and involve large costs or payoffs, as is the case in the modeling of global climate strategies. The article presents methodological details of the modeling approach, and uses realistic instances of the ETSAP-TIAM model to illustrate the technique and to analyze the resulting hedging strategies. The instances modeled and analyzed assume several alternative global temperature targets ranging from less than 2°C to 3°C. The 2.5°C target is analyzed in some more details.

Effectiveness and efficiency of climate change mitigation in a technologically uncertain World

Following a multi-scenario framework based on the technology assumptions proposed by the 27th Energy Modeling Forum (EMF-27), our analysis focuses on analyzing the impacts of key technology assumptions on climate policies, including the interdependencies of different technological options. Each scenario may be considered as either a possible state of nature upon which one has no influence, each scenario thus dictating the availability (or non availability) of some subset of the technology groups, or as an opportunity for society, by its own actions and policies, to influence the availability of said technology group. The main insights obtained from the assessment show the prominent role of bioenergy as a means to abate greenhouse gas emissions, irrespective of other technological developments, while the role of the other technologies (wind and solar, carbon capture and sequestration, nuclear) are more dependent of one another. It appears that CCS may play a sort of “backstop” role: it compensates for a lower contribution of solar and wind, or of nuclear. This means that an increased social acceptability of one (or all) of these three sets of technology should be at the heart of future climate policies. The costs caused by the adaptation of electricity networks to accommodate a high fraction of intermittent sources would deserve more attention in future research.

Using Advanced Technology-Rich Models for Regional And Global Economic Analysis of GHG Mitigation

This article presents the case for a detailed regional analysis of the economic impacts of GHG control, via a set of inter-connected, long term, technology rich, integrated equilibrium models of the energy systems of the countries constituting a region of interest. The potential extension to global analysis is also examined. The article applies the proposed methodology to the region composed of Canada and the United States of America.

Modelling EU-GCC energy systems and trade corridors: Long term sustainable, clean and secure scenarios

Purpose – This article is based on the REACCESS research project, sponsored by the European Commission, with the objectives of evaluating the technical, economic, and environmental aspects of present and future energy corridors between the European countries (EU27) and their main energy suppliers. GCC countries have an important role to play given their role in EU energy supply and in greenhouse gas emissions. The paper aims to discuss these issues.Design/methodology/approach – A single energy model was built by hard‐linking the TIMES integrated assessment model (TIAM‐World), the Pan European TIMES model (PET), and the RECOR model (REaccess CORridors), including more than 1,000 possible energy corridors supplying the European countries. Another major methodology advance was to create a hybrid objective function, combining the usual cost objective and a metric representing the supply risk incurred by EU27. The risk component was constructed via a novel approach that aggregates the elemental risk parameters...