The decarbonization and energy transition agenda has prompted a global shift in the generation matrix, leading to a vast integration of renewable resources. New climate patterns and their linkage to […]
[LAMPS DataHub] - In this application, we provide monitoring indices for the Brazilian power system. The first index showcases the wind and solar power generation performance in percentage values of […]
The R&D project carried out with Energisa aims to create a new multimodel automation framework for the simulation (probabilistic forecasting) of time series with optimal selection of explanatory variables. The […]
The objective of the project was to develop a methodology for estimating and forecasting the forward curve of electricity, materialized in a web tool prototype that enables the realization of […]
Updated forecasts for the number of reported cases and deaths due to COVID-19 in Brasil - COVID19analytics.com.br This is an initiative of Prof. Alexandre Street (Electrical Engineering department at PUC-Rio), Davi […]
Energy Analytics - Monitoring and Forecasting Power System Indices [Click here to access the application] - monitoring indices for electricity consumption reduction in Brasil after COVID19. In this app we […]
R&D project between Energisa and LAMPS-PUC-Rio The main goal is to develop a computational tool capable of accounting for the uncertainty due to contingencies and climate variability in the optimal […]
This project is supported by the Chilean government, under the CONICYT PCI/REDES 150008 - 2015 call. The aim of the project is to support international-network cooperation projects between research centers. In […]
Sponsor: FGV. 2017. Development of a Stochastic Dual Dynamic Programming Dispatch Tool for simulating the dispatch of gas-to-wire thermal generation power plants.
Young Talents Attraction Program - Level A Granted: David Pozo Coordinator: Alexandre Street Sponsor: CAPES-CNPq-MCTI SUMMARY Decision-making under uncertainty plays a key role in the operation and planning of restructured power systems. […]
Sponsor: FAPERJ. 2014
Sponsor: Energisa group. Goal: To define the optimal amount of power flow contract that should be contracted for the next 4 years with the transmission system by a distribution company.
It concerns the development of analytic tools applied to Energy. Most of the energy-related activities require decision making under uncertainty. These types of models need to explicitly or implicitly represent the […]
It concerns the study and development of mathematical optimization models and solution methodologies based on stochastic or robust optimization applied to power system planning and operation problems. Transmission and generation expansion […]
It concerns the analysis and optimization of hydro-thermal system operation planning and its resulting policies.
Portfolio optimization models, Asset Liability Management (ALM) models, computational finance, risk analysis and associated aspects of optimization under uncertainty (robust and stochastic optimization) and risk measure.
Tópicos de pesquisa: Modelo interno, capital mínimo requerido, Solvência II, otimização robusta
Research topics: Asset Liability Management (ALM) models, computational finance, risk analysis, and theoretical aspects of optimization under uncertainty such as stochastic dynamic programming models and robust optimization models.
Sponsor: ENEVA. 2012. We present a new methodology to support an energy trading company (ETC) to devise contracting strategies under an optimal risk-averse renewable portfolio. The uncertainty in the generation […]
Sponsor: UTE Norte Fluminense (EDF). 2011 Goal: a renewable generation simulation tool capable to produce a Monte Carlo Simulation of a set of renewable units conditioned (paired) to the scenarios […]
Research topics: Asset and liability management, multistage stochastic programming, risk management, time series simulation models.
The ALM system developed in this project envisions finding the optimal investment portfolio for the public pension fund of Angola while keeping a low insolvency risk.