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Abstract

An essential task of the interconnected power system is about how to optimize power plants during operation time which is known as economic dispatch. In this study, the Fruit Fly Optimization method is proposed to solve problems of dynamic economic dispatch in an electrical power system. To measure the performance of the method, a simulation was conducted for two different electric systems of the existing Sulselbar 150 kV thermal power plant system in Indonesia with two objective functions, namely fuel costs and active power transmission losses, aswell as the 30-bus IEEE standard system with five objective functions namely fuel costs, transmission losses (active and reactive power), a reactive power reserve margin, and an emission index by considering a power generation limit and ramp rates as the constraints. Under tested cases, the simulation results have shown that the Fruit Fly Optimization method can solve the problems of dynamic economic dispatch better than other existing optimization methods. It is indicated by all values of the objective functions that are lowest for the Fruit Fly Optimization method. Moreover, the obtained computational time is sufficiently fast to get the best solution.
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Bibliography

[1] Mei J., Zhao J., An Enhanced Quantum-Behaved Particle SwarmOptimization for Security Constrained Economic Dispatch, Proc. Int. Symp. Distrib. Comput. Appl. Bus. Eng. Sci., no. 1, pp. 221–224 (2018).
[2] Ieng S., Akil Y.S., Gunadin I.C., Hydrothermal Economic Dispatch Using Hybrid Big Bang-Big Crunch (HBB-BC) Algorithm, Journal of Phys. Conf. Ser., vol. 1198, no. 5, pp. 7–13 (2019).
[3] Jiang X., Zhou J.,Wang H., Zhang Y., Dynamic Environmental Economic Dispatch Using Multiobjective Differential Evolution Algorithm with Expanded Double Selection and Adaptive Random Restart, Electr. Power Energy Syst., vol. 49, no. 1, pp. 399–407 (2013).
[4] Saravanan R., Subramanian S., Dharmalingam V., Ganesan S., Economic Dispatch with Integrated Wind-Thermal Using Particle Swarm Optimization, Int. Journal of Adv. Res. Innov., vol. 5, no. 1, pp. 100–103 (2017).
[5] Tyagi N., Dubey H.M., Pandit M., Economic Load Dispatch of Wind-Solar-Thermal System Using Backtracking Search Algorithm, Int. Journal of Eng. Sci. Technol., vol. 8, no. 4, pp. 16–217 (2016).
[6] Zakaria Z., Rahman T.K.A., Hassan E.E., Economic Load Dispatch via an Improved Bacterial Foraging Optimization, Int. Power Eng. Optim. Conf., pp. 380–385 (2014).
[7] Farook S., Manjusha M., Optimization of Multi-Objective Dynamic Economic Dispatch Problem Using Knee Point Driven Evolutionary Algorithm, Int. Electr. Eng. Journal, vol. 7, no. 10, pp. 2396–2402 (2017).
[8] Gamayanti N., Alkaff A., Karim A., Optimization of Dynamic Economic Dispatch Using Artificial Bee Colony Algorithms, Java J. Electr. Electron. Eng., vol. 13, no. 1, pp. 23–28 (2015).
[9] Nema P., Gajbhiye S., Application of Artificial Intelligence Technique to Economic Load Dispatch of Thermal Power Generation Unit, Int. Journal of Energy Power Eng., vol. 3, no. 5, pp. 15–20 (2014).
[10] Elsakaan A.A., El-sehiemy R.A., Kaddah S.S., Elsaid M.I., An Enhanced Moth-Flame Optimizer for Solving Nonsmooth Economic Dispatch Problems with Emissions, Energy, pp. 1–24 (2018).
[11] Singh H.P., BrarY.S.,Kothari D.P., Reactive Power Based Fair Calculation Approach for Multiobjective Load Dispatch Problem, Arch. Electr. Eng., vol. 68, no. 4, pp. 719–735 (2019).
[12] Nwulu N., Emission Constrained Bid Based Dynamic Economic Dispatch Using Quadratic Programming, Int. Conf. Energy, Commun. Data Anal. Soft Comput. ICECDS, pp. 213–216 (2018).
[13] Sadoudi S., Boudour M., Kouba N.E.Y., Gravitational Search Algorithm for Solving Equal Combined Dynamic Economic-Emission Dispatch Problems in Presence of Renewable Energy Sources, Proc. Int. Conf. Appl. Smart Syst. ICASS, no. November, pp. 1–5 (2019).
[14] Chen G., Li C., Dong Z., Parallel and Distributed Computation for Dynamical Economic Dispatch, IEEE Trans. Smart Grid, vol. 8, no. 2, pp. 1026–1027 (2017).
[15] Kaushal R.K., Thakur T., Multiobjective Electrical Power Dispatch of Thermal Units with Convex and Non-Convex Fuel Cost Functions for 24 Hours Load Demands, Int. Journal of Eng. Adv. Technol., vol. 9, no. 3, pp. 1534–1542 (2020).
[16] Zheng X., Wang L., Wang S., An Enhanced Non-Dominated Sorting Based Fruit Fly Optimization Algorithm for Solving Environmental Economic Dispatch Problem, Proceeding Congr. Evol. Comput., pp. 626–633 (2014).
[17] Liang J., Zhang H., Wang K., Jia R., Economic Dispatch of Power System Based on Improved Fruit Fly Optimization Algorithm, Proceeding Int. Conf. Ind. Electron. Appl., pp. 1360–1366 (2019).
[18] Geruna H.A. et al., Fruit Fly Optimization (FFO) for Solving Economic Dispatch Problem in Power System, Proceeding Int. Conf. Syst. Eng. Technol., pp. 2–3 (2017).
[19] Guang C., Xiaolong X., Mengzhou Z., Optimal Sitting and Parameter Selection for Fault Current Limiters Considering Optimal Economic Dispatch of Generators, IEEE Conf. Ind. Electron. Appl., pp. 2084–2088 (2018).
[20] El-Ela A.A.A., El-Sehiemy R.A., Rizk-Allah R.M., Fatah D.A., Solving Multiobjective Economical Power Dispatch Problem Using MO-FOA, Proceeding Int. Middle East Power Syst. Conf., no. 1, pp. 19–24 (2018).
[21] Bharathkumar S., ArulVineeth A.D., Ashokkumar K.,Vijayanand Kadirvel, Multi Objective Economic Load Dispatch Using Hybrid Fuzzy, Bacterial Foraging-Nelder Mead Algorithm, Int. Journal of Electr. Eng. Technol., vol. 4, no. 3, pp. 43–52 (2013).
[22] Vahid Sarfi, Hanif Livani, Logan Yliniemi, A New Multi Objective Economic Emission Dispatch in Microgrids, IEEE (2017).
[23] Dash S.K., Mohanty S., Multi-Objective Economic Emission Load Dispatch with Nonlinear Fuel Cost and Noninferior Emission Level Functions for IEEE-118 Bus System, 2nd Int. Conf. Electron. Commun. Syst. ICECS 2015, pp. 1371–1376 (2015).
[24] PanW.T., ANew Fruit Fly Optimization Algorithm: Taking the Financial Distress Model as an Example, Knowledge-Based Syst., vol. 26, pp. 69–74 (2012).
[25] Soliman S.A.-H., Mantawy A.-A.H., Modern Optimization Techniques with Applications in Electric Power Systems, Springer (2010).
[26] Haripuddin Arsyad, Suyuti Ansar, Sri Mawar Said, Yusri Syam Akil, Dynamic Economic Dispatch for 150 kV Sulselbar Power Generation Systems Using Artificial Bee Colony Algorithm, Proc. Int. Conf. Inf. Commun. Technol., pp. 817–822 (2019).
[27] Rasyid R.A., Optimization of 150 kV Sulselbar Power Generation System with Integration SidrapWind Power Plant, Hasanuddin University (2018).
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Authors and Affiliations

Haripuddin Arsyad
1 2
Ansar Suyuti
1
Sri Mawar Said
1
Yusri Syam Akil
1

  1. Electrical Engineering Department, Hasanuddin University, Gowa, Indonesia
  2. Electrical Engineering Department, Makassar State University, Makassar, Indonesia
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Abstract

Lightning is one of the causes of transmission disorders and natural phenomena that cannot be avoided. The South Sulawesi region is located close to the equator and has a high lightning density. This condition results in lightning susceptibility of disturbances to electrical system lines, especially in high-voltage airlines and substations. An Adaptive Neuro-Fuzzy Inference System (ANFIS) will show the Root Mean Square Error (RMSE) based on the membership function type. This journal is to predict the value of the transmission tower lightning density using the ANFIS method. The value of the lightning strike density index can later be determined based on ANFIS predictions. Analysis of the value calculation system of structural lightning strikes in the South Sulawesi region of the Sungguminasa-Tallasa route can be categorized as three characteristics lightning density (Nd). The calculation system results for the value of structural lightning struck in the South Sulawesi region and validated between manual calculations and ANFIS with an average percentage of 0.0554%.
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Bibliography

[1] Utomo B.T., Nappu M.B., Said S.M., Arief A., The Placement of the Transmission Lightning Arrester (TLA) at 150 kV Network using Fuzzy Logic, in 2018 10th International Conference on Information Technology and Electrical Engineering (ICITEE), pp. 347–352 (2018).
[2] Rawi I.M., Kadir M.Z.A.A., Azis N., Lightning study and experience on the first 500kV transmission line arrester in Malaysia, in 2014 International Conference on Lightning Protection (ICLP), pp. 1106–1109 (2014), DOI: 10.1109/ICLP.2014.6973289.
[3] Gassing, Analisis Sistem Proteksi Petir (Lighting Performance) Pada Sutt 150 kV Sistem Sulawesi Selatan, vol. 6, pp. 978–979 (2012).
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[5] Lembang N., Manjang S., Kitta I., Efek Penurunan Tahanan Pembumian Tower 150 kV terhadap Sistem Penyaluran Petir, J. Penelit. Enj., vol. 21, no. 2, pp. 7–15 (2017).
[6] Islam M.Z., Rashed M.R., Yusuf M.S.U., ATP-EMTP modeling and performance test of different type lightning arrester on 132kv overhead transmission tower, in 2017 3rd International Conference on Electrical Information and Communication Technology (EICT), pp. 1–6 (2017).
[7] Houari K., Hartani T., Remini B., Lefkir A., Abda L., Heddam S., A hybrid model for modelling the salinity of the Tafna River in Algeria, J. Water L. Dev., vol. 40, no. 1, pp. 127–135 (2019).
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[12] Ishii M. et al., Multistory transmission tower model for lightning surge analysis, IEEE Trans. Power Deliv., vol. 6, no. 3, pp. 1327–1335 (1991).
[13] Ito T., Ueda T., Watanabe H., Funabashi T., Ametani A., Lightning flashovers on 77-kV systems: observed voltage bias effects and analysis, IEEE Trans. Power Deliv., vol. 18, no. 2, pp. 545–550 (2003).
[14] Correia M.T., Festas J., Milheiras H., FelizardoN., Fernadez M., Sousa J., Methodologies for evaluating the lightning performance of transmission lines, ICOLIM (1998).
[15] Oktaviani W.A., Hati I.P., Efektifitas Perlindungan Kawat Tanah Jaringan SUTM 20 kV Gardu Induk Boom Baru Palembang, PROtek J. Ilm. Tek. Elektro, vol. 6, no. 2, pp. 90–95 (2019).
[16] Nugroho A., Syakur A., Penentuan Lokasi Pemasangan Lightning Masts Pada Menara Transmisi Untuk Mengurangi Kegagalan Perlindungan Akibat Sambaran Petir, Transmisi, vol. 7, no. 1, pp. 31–36 (2005).
[17] Simon R., Geetha A., Comparison on the performance of Induction motor control using fuzzy and ANFIS controllers, in 2013 IEEE International Conference ON Emerging Trends in Computing, Communication and Nanotechnology (ICECCN), pp. 491–495 (2013).
[18] Lincy L.M., Senthil K.R., Comparison Analysis of Fuzzy Logic and ANFIS Controller for Mitigation of Harmonics, Proc. 4th Int. Conf. Electr. Energy Syst. ICEES 2018, pp. 578–583 (2018).
[19] Rahman M.M.A., Rahim A., Performance evaluation of ANN and ANFIS based wind speed sensorless MPPT controller, in 2016 5th International Conference on Informatics, Electronics and Vision (ICIEV), pp. 542–546 (2016).
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[21] Aniserowicz K., Analytical calculations of surges caused by direct lightning strike to underground intrusion detection system, Bull. Polish Acad. Sci. Tech. Sci., vol. 67, no. 2 (2019).
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Authors and Affiliations

Sri Mawar Said
1
Muhammad Bachtiar Nappu
1
Andarini Asri
2
Bayu Tri Utomo
1

  1. Hasanuddin University, Indonesia
  2. Ujung Pandang State Polytechnic, Indonesia

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