Abstract
Nuclear Facility (NF), during shutdown and startup, are in the essential need for reliable electric power that should be delivered by electric power grid to NF. Safe operation of NF needs a limited variation in both frequency and voltage.The reduction of power losses, improving voltage profile, and frequency in electric grid connected with NF can be achieved by optimally distributed generators (DGs) placement. This paper presents a mathematical model for multible types of DGs placement in electric grid feeding NF. Also, it proposes artificial intelligence solution methodology for active and reactive power DGs placement problem. The trained Adaptive Neuro-Fuzzy Inference System (ANFIS) with Cat Swarm Optimization algorithm (CSO) is used for optimal solution. The optimization technique is tested and validated by using different sizes of electric grid. Test results showed a more reliable and efficient approach compared with other approachs.
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Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
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Research funding: None declared.
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Conflict of interest statement: The authors declare no conflicts of interest regarding this article.
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Articles in the same Issue
- Frontmatter
- Application of the COCOSYS code in the safety evaluation of Czech nuclear power plants
- Improving of electric network feeding nuclear facility based on multiple types DGs placement
- Design and evaluation of ecological interface for Feedwater Deaerating Tank and Gas Stripper System based on cognitive work analysis
- Evaluation of different integrated burnable absorber materials in fuel assemblies of Bushehr WWER-1000 nuclear reactor
- Effective physical protection system design and implementation at a radiological facility: an integrated and risk management approach
- Determination of limiter design and material composition of MT-II spherical tokamak
- Dynamics effects of tritium reduction on the energy gain of D-T fuel pellet using double cone ignition
- Design of an unattended ore grading measurement system in a uranium mine
- Prediction of heat transfer characteristics in a microchannel with vortex generators by machine learning
- Prediction of nanofluid flows’ optimum velocity in finned tube-in-tube heat exchangers using artificial neural network
- Investigating the in-core 60Co production assembly for open pool type reactor
- Calendar of events
Articles in the same Issue
- Frontmatter
- Application of the COCOSYS code in the safety evaluation of Czech nuclear power plants
- Improving of electric network feeding nuclear facility based on multiple types DGs placement
- Design and evaluation of ecological interface for Feedwater Deaerating Tank and Gas Stripper System based on cognitive work analysis
- Evaluation of different integrated burnable absorber materials in fuel assemblies of Bushehr WWER-1000 nuclear reactor
- Effective physical protection system design and implementation at a radiological facility: an integrated and risk management approach
- Determination of limiter design and material composition of MT-II spherical tokamak
- Dynamics effects of tritium reduction on the energy gain of D-T fuel pellet using double cone ignition
- Design of an unattended ore grading measurement system in a uranium mine
- Prediction of heat transfer characteristics in a microchannel with vortex generators by machine learning
- Prediction of nanofluid flows’ optimum velocity in finned tube-in-tube heat exchangers using artificial neural network
- Investigating the in-core 60Co production assembly for open pool type reactor
- Calendar of events