Title :
The use of BFA simulation to evaluate reliability of composite system: Case study: Calculation of Muarakarang-Gandul 1 composite system (Islanding system which part of Jawa-Bali-Madura grid in Indonesia)
Author :
Nugraha, Herry ; Arifianto, Yudi ; Sinisuka, N.I. ; Darwis, Sutawanir
Author_Institution :
INDONESIA & Sch. of Electr. Eng. & Inf., Inst. Teknol. Bandung, Bandung, Indonesia
Abstract :
Optimization of Bacteria Foraging Algorithm (BFA) has been widely implemented in power engineering. This algorithm is emulated from escherichia coli bacteria´s ability in finding nutrients in the human body. This research focuses on the implementation of BFA to calculate reliability indices of power system such as Loss of Load Probability (LOLP), Loss of Load Expectation (LOLE) and Expected Energy Not Supplied (EENS). The positions of each bacterium describe the status of the generation system and the resulting fitness value is its probability. The generation system states were visited included a failure state (state which causes load curtailment or loss of load), furthermore some generation systems are configured by block of units which are identically. It is opportunity in this research to improve BFA calculation methodology by considering probability of a system state with identical combinations. New approach of reliability calculation of composite system will be proposed. When the high probability failure states are obtained, the reliability indices can be calculated accurately. To simulate the methodology, case study of BFA and Genetic Algorithms (GA) calculation of Muarakarang-Gandul 1 Composite System (islanding system which part of Jawa-Bali-Madura grid in Indonesia) will be applied.
Keywords :
genetic algorithms; power generation reliability; power grids; probability; thermal power stations; BFA; EENS; Indonesia; Jawa-Bali-Madura grid; LOLE; LOLP; Muarakarang-Gandul 1 composite system; bacteria foraging algorithm; escherichia coli; expected energy not supplied; genetic algorithms; loss of load expectation; loss of load probability; power system reliability; probability failure states; Genetic algorithms; Interconnected systems; Microorganisms; Power generation; Power system reliability; Probability; Reliability; BFA; EENS; LOLE; bacteria foraging algorithm; generation system; power system; reliability;
Conference_Titel :
Probabilistic Methods Applied to Power Systems (PMAPS), 2014 International Conference on
Conference_Location :
Durham
DOI :
10.1109/PMAPS.2014.6960640