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Welcome to the ORCS Lab
Welcome to the Laboratory of Operational Research and Complex Systems. Feel free to explore the website and get to know our projects and the people behind the algorithms.
ORCS Lab - Optimisation, Data Science and Complex Systems
Research in the ORCS Lab focuses mainly on the development and application of optimisation methods to complex systems; on data science and statistical modeling; and on the applications of computational intelligence to large-scale power and energy systems.

Latest News

We're very proud to inform that the work

Multiobjective Planning of Power Distribution Networks with Facility Location for Distributed Generation

by Cristiane Taroco, Ricardo Takahashi, and Eduardo G. Carrano has been accepted for publication in the Electric Power Systems Research (IF: 1.809). This paper reports some results of Cristiane's Ph.D. work under Prof. Carrano's supervision. You can read the abstract by clicking the "Read More" button below.


Abstract: A multiobjective algorithm dedicated to simultaneously plan power distribution network and facility location, with focus on substation and distributed generation placement, is proposed in this work. This tool can perform the following operations: to plan the network topology, to assign the conductor capacities and types, to locate new generation units, and to analyze the robustness of the final network in order to help on decision making. In the design procedure, the minimization of both the monetary cost and the fault cost of the network for the “most likely” peak-load scenario are considered, for a future time horizon. The optimization of those different objective functions is performed in a multiobjective setting, leading to the determination of a Pareto-optimal solution set that describes the trade-offs involved in designer choices. The optimization algorithm is composed by a multiobjective genetic algorithm, deterministic local search operators, a procedure to locate new generation units, and a Monte Carlo simulator for evaluating system robustness. Uncertainties are considered in the load growth, energy price, and power supplied by the distributed generation units. The proposed tool allows scenario analyzes that go far beyond the simple cost per kilowatt or the availability rate figures.