Modeling uncertainty processes for multi-stage optimization of strategic energy planning: An auto-regressive and Markov chain formulation

This paper deals with the modeling of stochastic processes in long-term multistage energy planning problems when little information is available on the degree of uncertainty of such processes. Starting from simple estimates of variation intervals for uncertain parameters, such as energy demands and costs, we model the temporal correlation of these parameters through autoregressive (AR) … Read more

Reaching Paris Agreement Goal through CDR/DAC Development: a Compact OR Model

A compact operations research (OR) model is proposed to analyse the prospects of meeting the Paris Agreement targets when direct air capture technologies can be used or not. The main features of the model are (i) the representation of the economy and energy use with a nested constant elasticity of substitution production function; (ii) the … Read more

Assessment of Climate Agreements over the Long Term with Strategic Carbon Dioxyde Removal Activity

In this paper we extend a game theoretic meta-model used to assess the future of Paris agreement to the time horizon 2100 and we include in the strategic decisions of the negotiating coalitions the use of Carbon Dioxyde Removal (CDR) technologies. The meta-game model is calibrated through statistical emulation of GEMINI-E3, a world computable general … Read more

Decision support for strategic energy planning: a complete robust optimization framework

This paper presents a complete robust optimization framework to deal with a large range of uncertainties in optimization-based energy models. Robust formulations are proposed to address specific features of long- term energy models – such as multiplied uncertain parameters in the objective and many uncertainties in the constraints. Then, we introduce an original approach to … Read more

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 … Read more

NeatWork, a tool for the design of gravity-driven water distribution systems for poor rural communities

NeatWork is an advanced optimization and simulation tool for the design of purely gravity-driven water distribution systems aiming at delivering clean water to poor rural communities. The exclusion of any adjustable devices, such as pumps and valves, for controlling pressures and flows is motivated by two main reasons: firstly, the system should be as simple … Read more

Energy Technology Environment Model with Smart Grid and Robust Nodal Electricity Prices

This paper deals with the modeling of power flow in a transmission grid within the multi-sectoral multi-energy long-term regional energy model ETEM-SG. This extension of the model allows a better representation of demand response for flexible loads triggered by nodal marginal cost pricing. To keep the global model in the realm of linear program- ming … Read more

Energy Security: a robust optimization approach to design a robust European energy supply via TIAM

Energy supply routes to a given TIAM region (say E.U.) are subject to randomness, 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 … Read more

Robust capacity expansion solutions for telecommunication networks with uncertain demands

We consider the capacity planning of telecommunication networks with linear investment costs and uncertain future traffic demands. Transmission capacities must be large enough to meet, with a high quality of service, the range of possible demands, after adequate routings of messages on the created network. We use the robust optimization methodology to balance the need … Read more

Test instances for the traffic assignment problem

This short note on the Traffic Assignment Problem (TAP) provides the relevant information on test problems previously used in the literature to facilitate benchmarking Citation Technical report, Ordecsys, 2008. Article Download View Test instances for the traffic assignment problem