NEW SWARM INTELLIGENCE BASED OPTIMIZATION ALGORITHMS FOR THE OPTIMIZATION OF MICROGRIDS

Öz The need for new energy sources has increased due to reasons such as the development of technology, the increase in electricity demand, the decrease of fossil resources, and environmental pollution. Renewable energy sources are self-renewing, friendly, and clean energy sources. Microgrids are small power energy networks consisting of renewable and non-renewable energy sources, batteries, inverters, and loads. They can be operated connected to the network and independently from the network. Metaheuristic methods are algorithms that can achieve optimum results in the search space. In this study, optimization of a microgrid composed of a wind turbine, solar panel, diesel generator, inverter, and loads has been investigated with multi-objective hybrid metaheuristic algorithms. Optimization is aimed at reducing emissions, increasing reliability, and optimizing energy resources.  Swallow Swarm Optimization (SSO) and Hybrid Particle Swallow Swarm Optimization (HPSSO) with different iterations and populations are compared for the first time.

Kaynakça

References

[1] Wang, Z., et al., Intelligent Multi-Agent Control for Integrated Building and Micro-Grid Systems. In Innovative Smart Grid Technologies (ISGT), 2011 IEEE PES, 2011, pp.1-7.[2] Aziza, M., & Walling, F., Multi-objective Particle Swarm Optimization of Hybrid Micro-Grid System: A Case Study in Sweden, Energy, 2017, Vol.123, pp. 108-118.[3] Fossati, J. P., et al., A Method for Optimal Sizing Energy Storage Systems for Microgrids. Renewable Energy, 2015, Vol.77, pp.539-549.[4] Bevrani, H., et al., Intelligent Frequency Control in an AC Microgrid: Online PSO-Based Fuzzy Tuning Approach. IEEE Transactions on Smart Grid, 2012, Vol. 3(4), 1935-1944.[5] Chen, Y. K., et al., Design and İmplementation of Energy Management System with Fuzzy Control for DC Microgrid Systems. IEEE Transactions on Power Electronics, 2013, Vol. 28(4), 1563-1570.[6] Seung, C., et al., Agent based Particle Swarm Optimization for Load Frequency Control of Distribution Grid, In Universities Power Engineering Conference (UPEC), 2012 47th International, 2012, pp. 1-6.[7] Eilaghi, S. F., et al., Optimal Voltage Unbalance Compensation in a Microgrid Using PSO Algorithm. In Power India International Conference (PIICON), 2016 IEEE 7th, 2016, pp.1-6[8] Yazdani, M., & Jolai, F., Lion Optimization Algorithm (LOA): A Nature-inspired Metaheuristic algorithm. Journal of Computational Design and Engineering, 2016, Vol. 3(1): pp.24-36.[9] Gandomi, A. H., et al., Mixed Variable Structural Optimization Using Firefly Algorithm, Computers & Structures, 2011, Vol. 89(23-24), pp. 2325-2336.[10] Gandomi, A. H., & Alavi, A. H., Krill Herd: A New Bio-inspired Optimization Algorithm. Communications in Nonlinear Science and Numerical Simulation, 2012, Vol. 17(12), pp. 4831-4845.[11] Revathi, K., & Krishnamoorthy, N., The Performance Analysis of Swallow Swarm Optimization Algorithm, 2015 2nd International Conference on IEEE, 2015, pp. 558-562.[12] Bouzidi, S., & Riffi, M. E., Discrete Swallow Swarm Optimization Algorithm for Travelling Salesman Problem, In Proceedings of the 2017 International Conference on Smart Digital Environment, 2017, pp. 80-84.[13] Neshat, M., et al., Swallow Swarm Optimization Algorithm: A New Method to Optimization, Neural Computing and Applications, 2013, Vol. 23(2), pp.429-454.[14] Kaveh, A., et al., Hybrid PSO and SSO Algorithm for Truss Layout and Size Optimization Considering Dynamic Constraints, Structural Engineering and Mechanics, 2015, Vol. 54(3), pp. 453-474.[15] Sam C., & Ali, A., A., 2015. Identification of Crack in a Cantilever Beam using Improved PSO Algorithm, International Journal for Innovative Research in Science & Technology, 2015, Vol.1(11), pp. 454- 461.

Kaynak Göster

Bibtex @araştırma makalesi { ejt464197, journal = {European Journal of Technique (EJT)}, issn = {2536-5010}, eissn = {2536-5134}, address = {INESEG Yayıncılık Dicle Üniversitesi Teknokent, Sur/Diyarbakır}, publisher = {Hibetullah KILIÇ}, year = {2018}, volume = {8}, pages = {196 - 208}, doi = {10.36222/ejt.464197}, title = {NEW SWARM INTELLIGENCE BASED OPTIMIZATION ALGORITHMS FOR THE OPTIMIZATION OF MICROGRIDS}, key = {cite}, author = {Tanyıldızı Ağır, Tuba and Tanyıldızı Ağır, Tuba} }
APA Tanyıldızı Ağır, T , Tanyıldızı Ağır, T . (2018). NEW SWARM INTELLIGENCE BASED OPTIMIZATION ALGORITHMS FOR THE OPTIMIZATION OF MICROGRIDS . European Journal of Technique (EJT) , 8 (2) , 196-208 . DOI: 10.36222/ejt.464197
MLA Tanyıldızı Ağır, T , Tanyıldızı Ağır, T . "NEW SWARM INTELLIGENCE BASED OPTIMIZATION ALGORITHMS FOR THE OPTIMIZATION OF MICROGRIDS" . European Journal of Technique (EJT) 8 (2018 ): 196-208 <https://dergipark.org.tr/tr/pub/ejt/issue/41882/464197>
Chicago Tanyıldızı Ağır, T , Tanyıldızı Ağır, T . "NEW SWARM INTELLIGENCE BASED OPTIMIZATION ALGORITHMS FOR THE OPTIMIZATION OF MICROGRIDS". European Journal of Technique (EJT) 8 (2018 ): 196-208
RIS TY - JOUR T1 - NEW SWARM INTELLIGENCE BASED OPTIMIZATION ALGORITHMS FOR THE OPTIMIZATION OF MICROGRIDS AU - Tuba Tanyıldızı Ağır , Tuba Tanyıldızı Ağır Y1 - 2018 PY - 2018 N1 - doi: 10.36222/ejt.464197 DO - 10.36222/ejt.464197 T2 - European Journal of Technique (EJT) JF - Journal JO - JOR SP - 196 EP - 208 VL - 8 IS - 2 SN - 2536-5010-2536-5134 M3 - doi: 10.36222/ejt.464197 UR - https://doi.org/10.36222/ejt.464197 Y2 - 2018 ER -
EndNote %0 European Journal of Technique NEW SWARM INTELLIGENCE BASED OPTIMIZATION ALGORITHMS FOR THE OPTIMIZATION OF MICROGRIDS %A Tuba Tanyıldızı Ağır , Tuba Tanyıldızı Ağır %T NEW SWARM INTELLIGENCE BASED OPTIMIZATION ALGORITHMS FOR THE OPTIMIZATION OF MICROGRIDS %D 2018 %J European Journal of Technique (EJT) %P 2536-5010-2536-5134 %V 8 %N 2 %R doi: 10.36222/ejt.464197 %U 10.36222/ejt.464197
ISNAD Tanyıldızı Ağır, Tuba , Tanyıldızı Ağır, Tuba . "NEW SWARM INTELLIGENCE BASED OPTIMIZATION ALGORITHMS FOR THE OPTIMIZATION OF MICROGRIDS". European Journal of Technique (EJT) 8 / 2 (Aralık 2018): 196-208 . https://doi.org/10.36222/ejt.464197
AMA Tanyıldızı Ağır T , Tanyıldızı Ağır T . NEW SWARM INTELLIGENCE BASED OPTIMIZATION ALGORITHMS FOR THE OPTIMIZATION OF MICROGRIDS. EJT. 2018; 8(2): 196-208.
Vancouver Tanyıldızı Ağır T , Tanyıldızı Ağır T . NEW SWARM INTELLIGENCE BASED OPTIMIZATION ALGORITHMS FOR THE OPTIMIZATION OF MICROGRIDS. European Journal of Technique (EJT). 2018; 8(2): 196-208.
IEEE T. Tanyıldızı Ağır ve T. Tanyıldızı Ağır , "NEW SWARM INTELLIGENCE BASED OPTIMIZATION ALGORITHMS FOR THE OPTIMIZATION OF MICROGRIDS", European Journal of Technique (EJT), c. 8, sayı. 2, ss. 196-208, Ara. 2018, doi:10.36222/ejt.464197