Integration of predictive and prescriptive approaches in stochastic optimization
The use of data science tools for decision making in organizations has grown significantly in recent years. The usual practice is to first use the data to create a forecast model for uncertain elements, such as demand, and then use this model as input in an optimization scheme that chooses the best course of action from a set of alternatives. The objective of this project…
Configurable Testbed for Low Carbon Power System Dynamics with High Penetration of Power Electronics.
The project consists of a real-time simulator distributed in 4 different geographical locations, which will be coordinated through the internet. The reason for considering distant geographic locations is to model the remote communication of distant elements through conventional communication channels. This interaction seeks to test the feasibility that the distribution infrastructure can respond to control commands given from the electrical system operator for various purposes….
Distributionally Robust Models for Multi-Stage Stochastic Optimization Problems
This research project aims to develop new models, theory, and algorithms for dynamic optimization model problems that incorporate robustness for the underlying probability distributions. We focus our work on the important classes of multistage stochastic problems, in which information is revealed period by period and decisions are made accordingly, using information from previous stages.
REMIND: Renewable Energies for Water Treatment and REuse in Mining Industries
The overall aim of REMIND is to develop an innovative framework of interplay between Renewable Energy Sources (RES) and innovative Water Treatment Technologies in the logic of a sustainable growth for mining industries. The novel paradigms explored are expected to drastically reduce the environmental impact due to extensive water and energy consumption, and to release of untreated wastewater during the production cycle of copper and…
Evaluation of the Distributed Generation Industry as an Engine of Employment and Efficient and Sustainable Economic Development in Chile Post COVID-19
The study aims to explore the potential of distributed generation, providing technical and economic background that allows the Ministry of Energy to evaluate the implementation of a plan to promote the industry of distributed energy resources as a vehicle for job creation and efficient and sustainable energy development. At the same time, establish criteria and methodologies to incorporate the development of distributed energy resources in…
Adapting to the uncertainties and risks of climate change: Advanced methods and models for energy systems and markets
The aim of the project is to develop new mathematical models and computational methods that help the private and public sector to adapt energy systems and markets to high uncertainties and risks derived from climate change. To achieve this goal, the research addresses three research objectives: (1) Model and classify the different types of uncertainties and risks associated with climate change; (2) Develop energy planning…
