A
Anastasios G. Bakirtzis
Researcher at Aristotle University of Thessaloniki
Publications - 207
Citations - 10720
Anastasios G. Bakirtzis is an academic researcher from Aristotle University of Thessaloniki. The author has contributed to research in topics: Electric power system & Electricity market. The author has an hindex of 49, co-authored 200 publications receiving 9591 citations. Previous affiliations of Anastasios G. Bakirtzis include National Technical University of Athens & University of Liège.
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A genetic algorithm solution to the unit commitment problem
TL;DR: This paper presents a genetic algorithm (GA) solution to the unit commitment problem using the varying quality function technique and adding problem specific operators, satisfactory solutions to theunit commitment problem were obtained.
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Optimal power flow by enhanced genetic algorithm
TL;DR: A number of functional operating constraints, such as branch flow limits, load bus voltage magnitude limits, and generator reactive capabilities, are included as penalties in the GA fitness function (FF).
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A solution to the unit-commitment problem using integer-coded genetic algorithm
TL;DR: A new solution to the thermal unit-commitment (UC) problem based on an integer-coded genetic algorithm (GA) that achieves significant chromosome size reduction compared to the usual binary coding.
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Optimal Bidding Strategy for Electric Vehicle Aggregators in Electricity Markets
TL;DR: The optimal bidding strategy of an electric vehicle (EV) aggregator participating in day-ahead energy and regulation markets using stochastic optimization is determined and a new battery model is proposed for better approximation of the battery charging characteristic.
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Smart Household Operation Considering Bi-Directional EV and ESS Utilization by Real-Time Pricing-Based DR
Ozan Erdinc,Nikolaos G. Paterakis,Tiago D. P. Mendes,Anastasios G. Bakirtzis,Joao P. S. Catalao +4 more
TL;DR: A collaborative evaluation of dynamic-pricing and peak power limiting-based DR strategies with a bi-directional utilization possibility for EV and energy storage system (ESS) is realized and a mixed-integer linear programming (MILP) framework-based modeling of a home energy management (HEM) structure is provided.