Olivier Mickaël Ranarison
i-tantana.mg
University of Antananarivo
Skills
Software Development
Electrical Engineering
Artificial Intelligence
Robotics and Electronics
Work
Optimal power flow using Modified Driving-Training Based Optimization algorithm
International Journal of Advances in Engineering and Management
feb. 2025 | Journal article
DOI : 10.35629/5252-0702846860
Part of ISSN : 2395-5252
CONTRIBUTORS: O. M. Ranarison O. M. Ranarison; E. Randriamora E. Randriamora; H. Andriatsihoarana H. Andriatsihoarana
ABSTRACT: The control and study of electric
power system require solution of Optimal Power
Flow (OPF) problem which is considered one of the
most difficult optimization problems. The objective
of OPF is finding the most secure operating point or
the best control variables while considering equality
and inequality constraints of the system, and
optimizing certain objective functions. In this paper,
five objective functions are considered:
minimization of total generation fuel cost, voltage
profile improvement, voltage stability enhancement,
minimization of active power transmission losses
and reactive power losses minimization. Modified
Driving-Training Based Optimization (MDTBO)
algorithm is used to solve the OPF problem.
Driving-Training-Based Optimization (DTBO) is a
human-based metaheuristic algorithm based on the
simulation of driving training process. With
MDTBO, a new method for choosing the number of
driving learners and instructors is introduced. To
evaluate the proposed method, the standard IEEE
30-bus network is used and results is compared to
another metaheuristic algorithm such as Teaching
Learning Based Optimization (TLBO) and Particle
Swarm Optimization (PSO) algorithm. The results
show that the proposed approach is competitive with
other algorithms.
KEYWORDS: Optimal Power Flow (OPF),
generation cost, voltage stability, voltage profile,
active power transmission losses, reactive power
losses,
Teaching-Learning Based Optimization
(TLBO), Particle Swarm Optimization (PSO),
Modified Driving-Training Based Optimization
(MDTBO).
Calcul numérique de la répartition des puissances - cas des réseaux maillés
Ecole Supérieure Polytechnique d'Antananarivo
juillet. 2022 | Research paper
Download : PDF
CONTRIBUTORS: Olivier Mickaël Ranarison; Jaomiary Antonio
ABSTRACT: All studies in electrical energy network
have the main objective of ensuring the stability of the
network. This is the case of the numerical calculation of load flow, which consists in dertemining
the voltage drops by calculating bus voltages and powers, and also the losses and the limits of
the network from the powers and currents transited in branches. Various electrical simulation
software already exists, but this work aims to implement a more flexible tool with an exploitable
source code in order to be able to customize the program for particular networks. The application
with mesh networks showed that the numerical resolution method of Newton-Raphson, although
it is more complicated in terms of calculation, converges faster than that of Gauss-Seidel.
KEYWORDS: electrical network, mesh network, load flow, stability, Newton-Raphson,
Gauss-Seidel
University
University of Antananarivo
Ecole Doctorale en Sciences et Techniques de l'Ingénierie et de l'Innovation (ED-STII)
2023 to present
Ph.D - Electrical Engineering
University of Antananarivo
Ecole Supérieure Polytechnique d'Antananarivo (ESPA)
2020 to 2022
Master à visée de recherche - Ingénierie des Systèmes Electriques et Développement Durable
University of Antananarivo
Institut d'Enseignement Supérieure d'Antsirabe Vakinankaratra (IES-AV)
2014 to 2019
Diplôme d'Ingénieur - Automatisme Electronique et Informatique Industrielle