Systems of energy, food and water (production and/or distribution), have strong interlinkages between them. These interlinkages represent the synergies and trade‑offs arising from an increasingly interconnected and complex world. In order to try to understand and analyze, not just the local behavior of one of these macro-systems, but the dependence between them, it is necessary to use advanced modeling and optimization methods.
Javalera-Rincón has designed an architecture and a methodology to deal with the interaction between systems (or sub-systems) in a distributed control architecture for large-scale systems. This approach combines ideas from distributed artificial intelligence and reinforcement learning in order to provide a controller interaction based on negotiation, cooperation and learning techniques. The aim of this methodology is to provide a general structure to perform optimal control in networked distributed environments, where multiple dependencies between subsystems are found.
Her work at IIASA focuses on the implementation of this architecture to schedule the sustainable development of energy and agricultural industries where there is competition for land and water resources. The models can include stochastic parameters and can be extended to other groups of systems.
Funding: The Mexican National Council for Science and Technology (CONACYT)
Program: Advanced Systems Analysis and Ecosystems Services and Management Program
Dates: May 2017 - April 2019
Last edited: 04 February 2020
International Institute for Applied Systems Analysis (IIASA)
Schlossplatz 1, A-2361 Laxenburg, Austria
Phone: (+43 2236) 807 0 Fax:(+43 2236) 71 313