Abstract
This paper represents a new methodology to improve the performance of population-based optimization algorithms designed for corrective and preventive control actions enhancing power system dynamic security. Unlike many adaptive approaches employing the parameters such as population size, crossover or mutation rates, the proposed method for the performance improvement is based on the reduction of the search space size. In the method, optimization algorithms run consecutively, while the size of the search space is reduced according to the objective function values attained during the optimization process. In this study, generation rescheduling combined with load curtailment is applied as a preventive control action, whereas load shedding is selected as a corrective control. Each of these control actions is determined through the formulation of a security constrained optimization problem and its solution via population-based optimization algorithms. The proposed methodology is successfully applied to differential evolution, particle swarm optimization, artificial bee colony optimization, and big bang big crunch optimization methods for solving the optimization problems in a 16-generator-68-bus system and the Turkish Transmission System with 750 generators and 2600 buses. It is demonstrated that the proposed method provides better solutions with lesser computational complexity than the ones obtained by using fixed search space sizes.
Original language | English |
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Pages (from-to) | 90-100 |
Number of pages | 11 |
Journal | Electric Power Components and Systems |
Volume | 47 |
Issue number | 1-2 |
DOIs | |
Publication status | Published - 20 Jan 2019 |
Bibliographical note
Publisher Copyright:© 2019, © 2019 Taylor & Francis Group, LLC.
Funding
This work is supported by The Scientific and Technical Research Council of Turkey (TUBITAK) project no. 114E157. The authors thank TUBITAK for supporting the project and to the Turkish Electricity Transmission Company TEIAS for providing the model of Turkish power system This work is supported by The Scientific and Technical Research Council of Turkey (TUBITAK) project no. 114E157. The authors thank TUBITAK for supporting the project and to the Turkish Electricity Transmission Company TEIAS for providing the model of Turkish power system.
Funders | Funder number |
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Scientific and Technical Research Council of Turkey | |
TUBITAK | 114E157 |
Turkish Electricity Transmission Company TEIAS | |
Türkiye Bilimsel ve Teknolojik Araştirma Kurumu |
Keywords
- corrective control
- generation rescheduling
- heuristic optimization
- load shedding
- power system security
- preventive control