| Grant number: | 12/05520-0 |
| Support Opportunities: | Scholarships in Brazil - Post-Doctoral |
| Start date: | August 01, 2012 |
| End date: | July 31, 2016 |
| Field of knowledge: | Engineering - Electrical Engineering - Power Systems |
| Principal Investigator: | Nelson Kagan |
| Grantee: | Juan Carlos Cebrian Amasifen |
| Host Institution: | Escola Politécnica (EP). Universidade de São Paulo (USP). São Paulo , SP, Brazil |
| Associated scholarship(s): | 14/06568-1 - Minimization of financial losses related to sensitive process interruptions by optimal allocation of automatic switches in radial distribution systems, BE.EP.PD 12/18134-0 - Evaluation of power quality costs in sensitive processes and their impact on distribution network expansion planning, BE.EP.PD |
Abstract Power distribution companies nowadays face new challenges in modern societies. Amongst them, a major challenge concerns electricity customers who demand a high quality of service and high reliability in their supply of energy. In such a context, the concept of smart grids is a viable answer to such challenges. The new technologies associated with smart grids aim at improving the performance of power systems, by preventively identifying failures in the system as well as restoring the service in an automated way when facing contingencies, thus improving the operational efficiency of distribution companies. In such a new scenario, this project aims at broaden the classical concepts of multi-stage expansion planning in a way to consider relevant aspects related to smart grids, more specifically related to distributed generation and self healing. These two aspects will be dealt with under normal and emergency operating conditions in order to maintain the power quality criteria for the multiple planning stages. As for the evaluation of power quality, the methodology will take into account long and short duration interruption costs as well as cost related to voltage sags and swells, which are provoked by short circuits throughout the power networks. In order to minimize the proposed objective function, an efficient evolutionary algorithm (EA) will be devised so that different possible alternatives are exploited regardless the network size. Such algorithm will allow for comparative tests in real networks to existing results available in the technical literature. | |
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