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.     

Assessing a Transition to 100% Renewable Power Generation in a Non-interconnected Area: A Case Study for La Réunion Island

Environmental Modeling & Assessment - In this paper, we present a comprehensive, multi-timescale approach to evaluate energy transition policies aiming at fully renewable generation in power...     

An Oligopoly Game of CDR Strategy Deployment in a Steady-State Net-Zero Emission Climate Regime

In this paper, we propose a simple oligopoly game model to represent the interactions between coalitions of countries in deploying carbon dioxide removal (CDR) strategies in a steady-state net-zero emission climate regime that could take place by the end of the twenty-first century. The emission quotas and CDR activities obtained in the solution of this steady-state model could then be used as a target for end-of-period conditions in a dynamic integrated assessment analysis studying the transition to 2100. More precisely, we analyze a steady-state situation where m coalitions exist and behave as m players in a game of supplying emission rights on an international emission trading system. The quotas supplied by a coalition must correspond to the amount of CO₂ captured through CDR activities in the corresponding world region. We use an extension of the computable general equilibrium model GEMINI-E3 to calibrate the payoff functions and compute an equilibrium solution in the noncooperative game.

     

Extraction of Co,Ni, Cu,Zn and Cd ions using 2-aminophenylaminopropylpolysiloxane

Insoluble porous solid functionalized ligand system bearing 2-aminophenylaminopropyl chelating ligand of the general formula P–(CH₂)₃NH–(C₆H₄)–NH₂ was prepared via the sol–gel process, where P represents [Si–O] _n polysiloxane network. First, the 2-aminophenylaminopropylsilane agent was prepared by substitution reaction between 3-chloropropyltrimethoxysilane and 1,2-phenylenediamine, followed by hydrolytic polycondensation between 2-aminophenylaminopropylsilane agent and tetraethylorthosilicate(TEOS). The immobilized 2-aminophenylaminopropylpolysiloxane P–(CH₂)₃NH–(C₆H₄)–NH₂(P–AphA) was characterized by ¹³C NMR, XPS, and FTIR. The results showed that 1,2-phenylenediamine groups were introduced onto polysiloxane network. The functionalized ligand system exhibits 90–100% metal uptake capacity for all metal ions except Cd²⁺. The elemental analysis data and the metal uptake capacities of the immobilized ligand system suggest that over than 90% ligand sites were involved in coordination with metal ions except that of cadmium forming 1:1 metal to ligand ratio complexes.     

Combining Stochastic Optimization and Monte Carlo Simulation to Deal with Uncertainties in Climate Policy Assessment

In this paper, we explore the impact of several sources of uncertainties on the assessment of energy and climate policies when one uses in a harmonized way stochastic programming in a large-scale bottom-up (BU) model and Monte Carlo simulation in a large-scale top-down (TD) model. The BU model we use is the TIMES Integrated Assessment Model, which is run in a stochastic programming version to provide a hedging emission policy to cope with the uncertainty characterizing climate sensitivity. The TD model we use is the computable general equilibrium model GEMINI-E3. Through Monte Carlo simulations of randomly generated uncertain parameter values, one provides a stochastic micro- and macro-economic analysis. Through statistical analysis of the simulation results, we analyse the impact of the uncertainties on the policy assessment.     

Meta-Modeling to Assess the Possible Future of Paris Agreement

In the meta-modeling approach, one builds a numerically tractable dynamic optimization or game model in which the parameters are identified through statistical emulation of a detailed large scale numerical simulation model. In this paper, we show how this approach can be used to assess the economic impacts of possible climate policies compatible with the Paris Agreement. One indicates why it is appropriate to assume that an international carbon market, with emission rights given to different groups of countries will exist. One discusses the approach to evaluate correctly abatement costs and welfare losses incurred by different groups of countries when implementing climate policies. Finally, using a recently proposed meta-model of game with a coupled constraint on a cumulative CO₂ emissions budget, we assess several new scenarios for possible fair burden sharing in climate policies compatible with the Paris Agreement.