Research Article
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Year 2022, Volume: 8 Issue: 2, 345 - 360, 01.09.2022

Abstract

References

  • 1. Singh, N., Kumar, Y., Multiobjective Economic Load Dispatch Problem Solved by New PSO. Hindawi Publ. Corp 2015:1–7, 2015.
  • 2. Niknam, T, Rasoul, N.M., Jabbari, M., Malekpour, A.R., A modified shuffle frog leaping algorithm for multi-objective optimal power flow. Energy 36(11): 6420-6432, 2011.https://doi.org/10.1016/j.energy.2011.09.027.
  • 3. Gupta, A., Swarnkar, K.K., Wadhwani, K., Combined economic emission dispatch problem using particle swarm optimization. International Journal of Computer Applications 49(6):1-6, 2012.
  • 4. Adaryani, M.R., Karami, A., Artificial bee colony algorithm for solving multi-objective optimal power flow problem. International Journal of Electrical Power & Energy Systems 53:219-230, 2013.
  • 5. Roselyn, J.P., Devaraj, D., Dash, S.S., Economic emission OPF using hybrid GA-Particle swarm optimization. In International Conference on Swarm, Evolutionary, and Memetic Computing, 167-175, 2011.
  • 6. Daryani, N., Hagh, M.T., Teimourzadeh, S., Adaptive group search optimization algorithm for multi-objective optimal power flow problem. Applied soft computing 38:1012-1024, 2016.
  • 7. Mohamed, A.A.A., Mohamed, Y.S., El-Gaafary, A.A., Hemeida, A.M., Optimal power flow using moth swarm algorithm. Electric Power Systems Research 142:190-206, 2017.
  • 8. Akdag, O., Ates, A., Yeroglu, C., Modification of Harris hawks optimization algorithm with random distribution functions for optimum power flow problem. Neural Computing and Applications, 21-27, 2020.
  • 9. Hashim, F.A., Hussain, K., Houssein, E.H., Mabrouk, M.S., Al-Atabany, W. Archimedes optimization algorithm: a new metaheuristic algorithm for solving optimization problems. Applied Intelligence, 1-21, 2020.
  • 10. PowerFactory (2020), User Manual 2020. https://www.digsilent.de/en/downloads.html/.
  • 11. Pulluri, H., Naresh, R., Sharma, V., An enhanced self-adaptive differential evolution based solution methodology for multiobjective optimal power flow. Applied Soft Computing 54: 229-245, 2017.
  • 12. Kumar, A.R., Premalatha, L., Optimal power flow for a deregulated power system using adaptive real coded biogeography-based optimization. International Journal of Electrical Power & Energy Systems 73: 393-399, 2015.
  • 13. Chaib, A.E., Bouchekara, H.R.E.H., Mehasni. R., Abido, M.A., Optimal power flow with emission and non-smooth cost functions using backtracking search optimization algorithm. International Journal of Electrical Power & Energy Systems 81:64-77, 2016. 14. Daryani, N., Hagh, M.T., Teimourzadeh, S., Adaptive group search optimization algorithm for multi-objective optimal power flow problem. Applied soft computing 38:1012-1024, 2016.
  • 15. Niknam, T., Narimani, M.R., Aghaei, J., Azizipanah-Abarghooee, R., Improved particle swarm optimisation for multi-objective optimal power flow considering the cost, loss, emission and voltage stability index. IET generation, transmission & distribution 6(6): 515-527, 2012.
  • 16. Raviprabakaran, V., Subramanian, R.C., Enhanced ant colony optimization to solve the optimal power flow with ecological emission. International Journal of System Assurance Engineering and Management 9(1):58-65, 2018.
  • 17. Ghasemi, M., Ghavidel, S., Akbari, E., Vahed, A.A., Solving non-linear, non-smooth and non-convex optimal power flow problems using chaotic invasive weed optimization algorithms based on chaos. Energy 73: 340-353, 2014.
  • 18. Pasvanoğlu, S., Chandrasekharam, D., Hydrogeochemical and isotopic study of thermal and mineralized waters from the Nevşehir (Kozakli) area, Central Turkey. Journal of Volcanology and Geothermal Research, 202(3-4), 241–250, 2011. https://doi.org/10.1016/j.jvolgeores.2011.03.003.
  • 19. Galip, A., Geothermal Resources of Yozgat Province and Their Characteristics. Cumhuriyet University Faculty of Science Science Journal (CSJ), Vol. 37, 100-112, 2016.
  • 20. TEİAŞ. 2020-2021. Turkish electricity transmission corporation (TEIAS) - Turkey Electricity Generation Capacity (2002–2021). Ankara; 2021.
  • 21. Özer, R., Kozaklı (Nevşehir) Sahası Jeotermal Enerji Kapasitesinin Belirlenmesi. Aksaray Universitesi, Fen Bilimleri Enstitüsü, MSC Thesis, 66s., Aksaray, 2015.
  • 22. MTA, Evaluation Report on Geothermal Energy Opportunities of Kozaklı (Nevşehir) Area, MTA Yayınları, Ankara, 1999.
  • 23. Muffler, L.P.J., ve Cataldi, R., Methods for Regional Assessment of Geothermal Resources, Geothermics, 7, No.2-4, 53-89, 1978.
  • 24. Ren é van Dorp, J., Kotz, S., A novel extension of the triangular distribution and its parameter estimation. Journal of the Royal Statistical Society: Series D (The Statistician), 51(1), 63-79, 2002.
  • 25. EUROPA, https://ec.europa.eu/clima/sites/default/files/f-gas/legislation/docs/c_2017_5230_en.pdf (2017). Yayın tarihi Temmuz 7, 2017. Erişim tarihi Kasım 11, 2020.
  • 26. Yang, C., Seo, S., Takata, N., Thu, K., Miyazaki, T., The life cycle climate performance evaluation of low-GWP refrigerants for domestic heat pumps. International Journal of Refrigeration, 121, 33-42, 2021.
  • 27. Özer, R., Kozaklı (Nevşehir) Sahası Jeotermal Enerji Kapasitesinin Belirlenmesi. Aksaray Universitesi, Fen Bilimleri Enstitüsü, MSC Thesis, 66s., Aksaray, 2015.
  • 28. Ahmet, T.E.K.E., ve Yıldırım, E,. Dağıtık üretimde güneş enerjisi uygulamalarının kısa devre koruması üzerindeki etkileri ve dağıtık üretimde kısa devre koruması için yeni teknikler. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 34(4), 2141-2158, 2019.
  • 29. Akdağ, O., Yeroglu, C., An evaluation of an offshore energy installation for the Black Sea region of Turkey and the effects on a regional decrease in greenhouse gas emissions. Greenhouse Gases: Science and Technology, 2020.

Dağıtık üretim sistemi içeren güç sistemlerinde AOA algoritması ile zehirli ve sera gaz emisyonlarının azaltımı: Nevşehir-Kozaklı vaka çalışması

Year 2022, Volume: 8 Issue: 2, 345 - 360, 01.09.2022

Abstract

Bu makale, Dağıtık Üretim Sistemi (DUS) içeren güç sistemlerinde zehirli/sera gaz emisyonunu en aza indirmeyi yansıtan amaç fonksiyonuyla, Optimum Güç Akışı (OGA) sorununu çözmek için Arşimet Optimizasyon Algoritmasını (AOA) sunmaktadır. Bu çalışmada AOA, IEEE 30-bara ve 13-bara örnek Nevşehir dağıtım sisteminde test edilmiştir. Öncelikle önerilen AOA’nın etkinliği IEEE 30-bara test sisteminde denenmiş ve simülasyon sonuçları son yıllarda literatürde yayınlanan farklı tekniklerle karşılaştırılmıştır. Bu çalışmada modellenen 13-bara test sistemine Organik Rank Çevrimli (ORÇ) jeotermal santral, DUS olarak entegre edilmiştir. Bu bağlamda, Türkiye’de önemli orta derecede jeotermal kaynak potansiyeline sahip ve herhangi bir jeotermal enerji santrali bulunmayan Nevsehir ilinde, bir ORÇ jeotermal santralinin kurulum aşamaları analiz edilmiştir. Öncelikle, Nevşehir ilinde bulunan jeotermal kaynaklar incelenerek, ORÇ santrali kurulucak saha belirlenmiştir. Daha sonra bu sahadaki jeotermal kaynağın (sıcaklık, vb.) özelliğine göre bu sahanın üretilebilir ısı ve elektrik potansiyeli Monte Carlo simülasyonu ile belirlenerek, bu çalışmada hesaplanan görünür kapasite ile karşılaştırılmıştır. Daha sonra bu karşılaştırma sonucu ilgili sahada 2,351 MW’lık bir ORÇ santral kurulabileceği ön görülmüştür. Devamında ORÇ santral ile bölgesel dağıtım şebekesinin sanal modelli DigSilent yazılımı kullanılarak modellenmiştir. Bu sanal modelde ORÇ’nin devreye girmesiyle Newton Raphson ve AOA yöntemlerine göre yük akış analizi yapılarak, sera gazı emisyonlarının azaltım miktarı yorumlanmıştır.

References

  • 1. Singh, N., Kumar, Y., Multiobjective Economic Load Dispatch Problem Solved by New PSO. Hindawi Publ. Corp 2015:1–7, 2015.
  • 2. Niknam, T, Rasoul, N.M., Jabbari, M., Malekpour, A.R., A modified shuffle frog leaping algorithm for multi-objective optimal power flow. Energy 36(11): 6420-6432, 2011.https://doi.org/10.1016/j.energy.2011.09.027.
  • 3. Gupta, A., Swarnkar, K.K., Wadhwani, K., Combined economic emission dispatch problem using particle swarm optimization. International Journal of Computer Applications 49(6):1-6, 2012.
  • 4. Adaryani, M.R., Karami, A., Artificial bee colony algorithm for solving multi-objective optimal power flow problem. International Journal of Electrical Power & Energy Systems 53:219-230, 2013.
  • 5. Roselyn, J.P., Devaraj, D., Dash, S.S., Economic emission OPF using hybrid GA-Particle swarm optimization. In International Conference on Swarm, Evolutionary, and Memetic Computing, 167-175, 2011.
  • 6. Daryani, N., Hagh, M.T., Teimourzadeh, S., Adaptive group search optimization algorithm for multi-objective optimal power flow problem. Applied soft computing 38:1012-1024, 2016.
  • 7. Mohamed, A.A.A., Mohamed, Y.S., El-Gaafary, A.A., Hemeida, A.M., Optimal power flow using moth swarm algorithm. Electric Power Systems Research 142:190-206, 2017.
  • 8. Akdag, O., Ates, A., Yeroglu, C., Modification of Harris hawks optimization algorithm with random distribution functions for optimum power flow problem. Neural Computing and Applications, 21-27, 2020.
  • 9. Hashim, F.A., Hussain, K., Houssein, E.H., Mabrouk, M.S., Al-Atabany, W. Archimedes optimization algorithm: a new metaheuristic algorithm for solving optimization problems. Applied Intelligence, 1-21, 2020.
  • 10. PowerFactory (2020), User Manual 2020. https://www.digsilent.de/en/downloads.html/.
  • 11. Pulluri, H., Naresh, R., Sharma, V., An enhanced self-adaptive differential evolution based solution methodology for multiobjective optimal power flow. Applied Soft Computing 54: 229-245, 2017.
  • 12. Kumar, A.R., Premalatha, L., Optimal power flow for a deregulated power system using adaptive real coded biogeography-based optimization. International Journal of Electrical Power & Energy Systems 73: 393-399, 2015.
  • 13. Chaib, A.E., Bouchekara, H.R.E.H., Mehasni. R., Abido, M.A., Optimal power flow with emission and non-smooth cost functions using backtracking search optimization algorithm. International Journal of Electrical Power & Energy Systems 81:64-77, 2016. 14. Daryani, N., Hagh, M.T., Teimourzadeh, S., Adaptive group search optimization algorithm for multi-objective optimal power flow problem. Applied soft computing 38:1012-1024, 2016.
  • 15. Niknam, T., Narimani, M.R., Aghaei, J., Azizipanah-Abarghooee, R., Improved particle swarm optimisation for multi-objective optimal power flow considering the cost, loss, emission and voltage stability index. IET generation, transmission & distribution 6(6): 515-527, 2012.
  • 16. Raviprabakaran, V., Subramanian, R.C., Enhanced ant colony optimization to solve the optimal power flow with ecological emission. International Journal of System Assurance Engineering and Management 9(1):58-65, 2018.
  • 17. Ghasemi, M., Ghavidel, S., Akbari, E., Vahed, A.A., Solving non-linear, non-smooth and non-convex optimal power flow problems using chaotic invasive weed optimization algorithms based on chaos. Energy 73: 340-353, 2014.
  • 18. Pasvanoğlu, S., Chandrasekharam, D., Hydrogeochemical and isotopic study of thermal and mineralized waters from the Nevşehir (Kozakli) area, Central Turkey. Journal of Volcanology and Geothermal Research, 202(3-4), 241–250, 2011. https://doi.org/10.1016/j.jvolgeores.2011.03.003.
  • 19. Galip, A., Geothermal Resources of Yozgat Province and Their Characteristics. Cumhuriyet University Faculty of Science Science Journal (CSJ), Vol. 37, 100-112, 2016.
  • 20. TEİAŞ. 2020-2021. Turkish electricity transmission corporation (TEIAS) - Turkey Electricity Generation Capacity (2002–2021). Ankara; 2021.
  • 21. Özer, R., Kozaklı (Nevşehir) Sahası Jeotermal Enerji Kapasitesinin Belirlenmesi. Aksaray Universitesi, Fen Bilimleri Enstitüsü, MSC Thesis, 66s., Aksaray, 2015.
  • 22. MTA, Evaluation Report on Geothermal Energy Opportunities of Kozaklı (Nevşehir) Area, MTA Yayınları, Ankara, 1999.
  • 23. Muffler, L.P.J., ve Cataldi, R., Methods for Regional Assessment of Geothermal Resources, Geothermics, 7, No.2-4, 53-89, 1978.
  • 24. Ren é van Dorp, J., Kotz, S., A novel extension of the triangular distribution and its parameter estimation. Journal of the Royal Statistical Society: Series D (The Statistician), 51(1), 63-79, 2002.
  • 25. EUROPA, https://ec.europa.eu/clima/sites/default/files/f-gas/legislation/docs/c_2017_5230_en.pdf (2017). Yayın tarihi Temmuz 7, 2017. Erişim tarihi Kasım 11, 2020.
  • 26. Yang, C., Seo, S., Takata, N., Thu, K., Miyazaki, T., The life cycle climate performance evaluation of low-GWP refrigerants for domestic heat pumps. International Journal of Refrigeration, 121, 33-42, 2021.
  • 27. Özer, R., Kozaklı (Nevşehir) Sahası Jeotermal Enerji Kapasitesinin Belirlenmesi. Aksaray Universitesi, Fen Bilimleri Enstitüsü, MSC Thesis, 66s., Aksaray, 2015.
  • 28. Ahmet, T.E.K.E., ve Yıldırım, E,. Dağıtık üretimde güneş enerjisi uygulamalarının kısa devre koruması üzerindeki etkileri ve dağıtık üretimde kısa devre koruması için yeni teknikler. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 34(4), 2141-2158, 2019.
  • 29. Akdağ, O., Yeroglu, C., An evaluation of an offshore energy installation for the Black Sea region of Turkey and the effects on a regional decrease in greenhouse gas emissions. Greenhouse Gases: Science and Technology, 2020.
There are 28 citations in total.

Details

Primary Language Turkish
Subjects Electrical Engineering
Journal Section Research Articles
Authors

Ozan Akdağ 0000-0001-8163-8898

Publication Date September 1, 2022
Submission Date December 15, 2021
Acceptance Date July 22, 2022
Published in Issue Year 2022 Volume: 8 Issue: 2

Cite

IEEE O. Akdağ, “Dağıtık üretim sistemi içeren güç sistemlerinde AOA algoritması ile zehirli ve sera gaz emisyonlarının azaltımı: Nevşehir-Kozaklı vaka çalışması”, GJES, vol. 8, no. 2, pp. 345–360, 2022.

Gazi Journal of Engineering Sciences (GJES) publishes open access articles under a Creative Commons Attribution 4.0 International License (CC BY). 1366_2000-copia-2.jpg