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Dive into the research topics where Pavlos S. Georgilakis is active.

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Featured researches published by Pavlos S. Georgilakis.


IEEE Transactions on Power Systems | 2013

Optimal Distributed Generation Placement in Power Distribution Networks: Models, Methods, and Future Research

Pavlos S. Georgilakis; Nikos D. Hatziargyriou

The integration of distributed generation (DG) units in power distribution networks has become increasingly important in recent years. The aim of the optimal DG placement (ODGP) is to provide the best locations and sizes of DGs to optimize electrical distribution network operation and planning taking into account DG capacity constraints. Several models and methods have been suggested for the solution of the ODGP problem. This paper presents an overview of the state of the art models and methods applied to the ODGP problem, analyzing and classifying current and future research trends in this field.


IEEE Transactions on Power Systems | 2012

Taxonomy of PMU Placement Methodologies

Nikolaos M. Manousakis; George N. Korres; Pavlos S. Georgilakis

Utilization of phasor measurement units (PMUs) in the monitoring, protection and control of power systems has become increasingly important in recent years. The aim of the optimal PMU placement (OPP) problem is to provide the minimal PMU installations to ensure full observability of the power system. Several methods, based on mathematical and heuristic algorithms, have been suggested for the OPP problem. This paper presents a thorough description of the state of the art of the optimization methods applied to the OPP problem, analyzing and classifying current and future research trends in this field.


IEEE Transactions on Power Systems | 2013

Transmission Expansion Planning of Systems With Increasing Wind Power Integration

G. A. Orfanos; Pavlos S. Georgilakis; Nikos D. Hatziargyriou

This paper proposes an efficient approach for probabilistic transmission expansion planning (TEP) that considers load and wind power generation uncertainties. The Benders decomposition algorithm in conjunction with Monte Carlo simulation is used to tackle the proposed probabilistic TEP. An upper bound on total load shedding is introduced in order to obtain network solutions that have an acceptable probability of load curtailment. The proposed approach is applied on Garver six-bus test system and on IEEE 24-bus reliability test system. The effect of contingency analysis, load and mainly wind production uncertainties on network expansion configurations and costs is investigated. It is shown that the method presented can be used effectively to study the effect of increasing wind power integration on TEP of systems with high wind generation uncertainties.


IEEE Transactions on Sustainable Energy | 2012

Hybrid Simulated Annealing–Tabu Search Method for Optimal Sizing of Autonomous Power Systems With Renewables

Yiannis A. Katsigiannis; Pavlos S. Georgilakis; Emmanuel S. Karapidakis

Small autonomous power systems (SAPS) that include renewable energy sources are a promising option for isolated power generation at remote locations. The optimal sizing problem of SAPS is a challenging combinatorial optimization problem, and its solution may prove a very time-consuming process. This paper initially investigates the performance of two popular metaheuristic methods, namely, simulated annealing (SA) and tabu search (TS), for the solution of SAPS optimal sizing problem. Moreover, this paper proposes a hybrid SA-TS method that combines the advantages of each one of the above-mentioned metaheuristic methods. The proposed method has been successfully applied to design an SAPS in Chania region, Greece. In the study, the objective function is the minimization of SAPS cost of energy (€/kWh), and the design variables are: 1) wind turbines size, 2) photovoltaics size, 3) diesel generator size, 4) biodiesel generator size, 5) fuel cells size, 6) batteries size, 7) converter size, and 8) dispatch strategy. The performance of the proposed hybrid optimization methodology is studied for a large number of alternative scenarios via sensitivity analysis, and the conclusion is that the proposed hybrid SA-TS improves the obtained solutions, in terms of quality and convergence, compared to the solutions provided by individual SA or individual TS methods.


IEEE Computer Applications in Power | 1999

AI helps reduce transformer iron losses

Pavlos S. Georgilakis; N.D. Hatziargyriou; Dimitris G. Paparigas

Methods for iron loss reduction during manufacturing of wound-core distribution transformers are presented. More specifically, measurements taken at the first stages of core construction are effectively used, in order to minimize iron losses of transformer (final product). To optimally exploit the measurements (feedback), artificial intelligence methods are applied. It is shown that intelligent systems are able to learn and interpret several variations of the same conditions, thus helping in predicting iron losses with increased accuracy.


systems man and cybernetics | 2001

A novel iron loss reduction technique for distribution transformers based on a combined genetic algorithm - neural network approach

Pavlos S. Georgilakis; Nikolaos D. Doulamis; Anastasios D. Doulamis; Nikos D. Hatziargyriou; Stefanos D. Kollias

The paper presents an effective method to reduce the iron losses of wound core distribution transformers based on a combined neural network/genetic algorithm approach. The originality of the work presented is that it tackles the iron loss reduction problem during the transformer production phase, while previous works concentrated on the design phase. More specifically, neural networks effectively use measurements taken at the first stages of core construction in order to predict the iron losses of the assembled transformers, while genetic algorithms are used to improve the grouping process of the individual cores by reducing iron losses of assembled transformers. The proposed method has been tested on a transformer manufacturing industry. The results demonstrate the feasibility and practicality of this approach. Significant reduction of transformer iron losses is observed in comparison to the current practice leading to important economic savings for the transformer manufacturer.


Electric Power Components and Systems | 2009

A Review of Transformer Losses

J. C. Olivares-Galvan; Pavlos S. Georgilakis; Rodrigo Ocon-Valdez

Abstract This article presents an extensive survey of current research on the transformer loss problem, particularly from the view of practical engineering applications. It reveals that the transformer loss problem remains an active research area. This article classified the transformer loss problem into three main groups: (a) tank losses due to high-current bushings, (b) losses in transformer core joints, and (c) stray losses in the transformer tank. It is based on over 50 published works, which are all systematically classified. The methods, the size of transformers, and other relevant aspects in the different works are discussed and presented.


Journal of Intelligent and Robotic Systems | 2006

A Systematic Stochastic Petri Net Based Methodology for Transformer Fault Diagnosis and Repair Actions

Pavlos S. Georgilakis; John A. Katsigiannis; Kimon P. Valavanis; Athanasios T. Souflaris

Transformer fault diagnosis and repair is a complex task that includes many possible types of faults and demands special trained personnel. Moreover, the minimization of the time needed for transformer fault diagnosis and repair is an important task for electric utilities, especially in cases where the continuity of supply is crucial. In this paper, Stochastic Petri Nets are used for the simulation of the fault diagnosis process of oil-immersed transformers and the definition of the actions followed to repair the transformer. Transformer fault detection is realized using an integrated safety detector, in case of sealed type transformer that is completely filled with oil, while a Buchholz relay and an oil thermometer are used, in case of transformer with conservator tank. Simulation results for the most common types of transformer faults (overloading, oil leakage, short-circuit and insulation failure) are presented. The proposed Stochastic Petri Net based methodology provides a systematical determination of the sequence of fault diagnosis and repair actions and aims at identifying the transformer fault and estimating the duration for transformer repair.


international conference on intelligent system applications to power systems | 2011

Optimal placement of phasor measurement units: A literature review

Nikolaos M. Manousakis; George N. Korres; Pavlos S. Georgilakis

The increasing availability of phasor measurement units (PMUs) at substations enables the synchronized measurements to various applications, such as the monitoring of system state under normal operations or the protection and control of power systems during abnormal operation. The objective of the optimal PMU placement (OPP) problem is to determine a minimal set of PMUs such that the whole system is observable. To solve the OPP problem, mathematical programming, heuristic, and meta-heuristic optimization techniques, have been proposed. This paper provides a comprehensive literature review on the OPP problem and the solution methodologies. Due to the vast number of publications in this field, the most representative papers are reviewed.


IEEE Transactions on Magnetics | 2008

A Parallel Mixed Integer Programming-Finite Element Method Technique for Global Design Optimization of Power Transformers

Eleftherios I. Amoiralis; Marina A. Tsili; Pavlos S. Georgilakis; Antonios G. Kladas; Athanassios T. Souflaris

Transformer design optimization is determined by minimizing the transformer cost taking into consideration constraints imposed both by international specifications and customer needs. The main purpose of this work is the development and validation of an optimization technique based on a parallel mixed integer nonlinear programming methodology in conjunction with the finite element method, in order to reach a global optimum design of wound core power transformers. The proposed optimization methodology has been implemented into software able to provide a global feasible solution for every given set of initial values for the design variables, rendering it suitable for application in the industrial transformer design environment.

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Dive into the Pavlos S. Georgilakis's collaboration.

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Nikos D. Hatziargyriou

National Technical University of Athens

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Marina A. Tsili

National Technical University of Athens

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J. C. Olivares-Galvan

Universidad Autónoma Metropolitana

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Antonios G. Kladas

National Technical University of Athens

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Yiannis A. Katsigiannis

Technological Educational Institute of Crete

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Rafael Escarela-Perez

Universidad Autónoma Metropolitana

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N.D. Hatziargyriou

National Technical University of Athens

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G. A. Orfanos

National Technical University of Athens

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