Optimal Bus Layout in Transmission System by Using Meta-heuristic Approaches

Dogan E., YÖRÜKEREN N.

ELECTRIC POWER COMPONENTS AND SYSTEMS, cilt.48, sa.12-13, ss.1390-1400, 2020 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 48 Sayı: 12-13
  • Basım Tarihi: 2020
  • Doi Numarası: 10.1080/15325008.2020.1854385
  • Dergi Adı: ELECTRIC POWER COMPONENTS AND SYSTEMS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aerospace Database, Business Source Elite, Business Source Premier, Communication Abstracts, Compendex, Environment Index, INSPEC, Metadex, DIALNET, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.1390-1400
  • Anahtar Kelimeler: network topology optimization, network reconfiguration, bus splitting, multi-objective optimization, congestion management, N-1 contingency analysis, short-circuit current limitation, meta-heuristic optimization algorithms, genetic algorithm, binary particle swarm optimization
  • Kocaeli Üniversitesi Adresli: Evet

Özet

Transmission system expansion leads to excessive short-circuit currents that exceed the capacity of circuit breakers. To avoid over short-circuit current; transmission system operators make various alterations in the transmission system by changing the topology of the system. The feeders can be distributed to different buses in substations through disconnecting coupling circuit breaker between buses. Having been interchanged, the transmission system may face up a lot of problems even in single outage. Therefore, the optimal positions of feeders in substations are important in order to maintain system security. However, this optimization problem has non-convex properties due to AC load flow equations and it has a multi-objective structure to provide the limitation of short-circuit current and security of N-1 contingency. The constraints are the short-circuit current, voltage and transmission line limits in the single contingency. In this paper, the Genetic Algorithm and Binary Particle Swarm Optimization methods were utilized to find a near-optimal bus layout. Algorithms coding was made with Python programming language and PSS/E program was used to obtain power flow and short-circuit data. The results of applying the methods to the IEEE 14-bus test system demonstrated the effectiveness of the methods to take overloads away and restrict short-circuit current and hold voltage in its limit.