A strategic decision support system framework for energy-efficient technology investments

Cano, E.L., Moguerza, J.M., Ermolieva, T., & Yermoliev, Y. (2017). A strategic decision support system framework for energy-efficient technology investments. TOP 25 (2) 249-270. 10.1007/s11750-016-0429-9.

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Abstract

Energy systems optimization under uncertainty is increasing in its importance due to on-going global de-regulation of the energy sector and the setting of environmental and efficiency targets which generate new multi-agent risks requiring a model-based stakeholders dialogue and new systemic regulations. This paper develops an integrated framework for decision support systems (DSS) for the optimal planning and operation of a building infrastructure under appearing systemic de-regulations and risks. The DSS relies on a new two-stage, dynamic stochastic optimization model with moving random time horizons bounded by stopping time moments. This allows to model impacts of potential extreme events and structural changes emerging from a stakeholders dialogue, which may occur at any moment of the decision making process. The stopping time moments induce endogenous risk aversion in strategic decisions in a form of dynamic VaR-type systemic risk measures dependent on the system’s structure. The DSS implementation via an algebraic modeling language (AML) provides an environment that enforces the necessary stakeholders dialogue for robust planning and operation of a building infrastructure. Such a framework allows the representation and solution of building infrastructure systems optimization problems, to be implemented at the building level to confront rising systemic economic and environmental global changes.

Item Type:	Article
Uncontrolled Keywords:	Decision support systems; dynamic stochastic programming; uncertainty modelling; strategic and operational planning
Research Programs:	Advanced Systems Analysis (ASA) Ecosystems Services and Management (ESM)
Depositing User:	Romeo Molina
Date Deposited:	22 Jul 2016 07:31
Last Modified:	27 Aug 2021 17:41
URI:	https://pure.iiasa.ac.at/13386

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