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Design of a Novel Barrier-Well Asymmetric Spacer Layer Tunnel Diodes for Implantable Rectenna Circuits 2 2 This work presents an analysis and design of the two barrier-quantum well asymmetric spacer tunnel layer (QW-ASPAT) diodes for implantable rectenna circuits application. The RF and DC characteristic of a 10×10μm2 QW-ASPAT devices based on GaAs and In0.53Ga0.47As platform was simulated and extracted by using SILVACO atlas software. The highest extracted curvature coefficient, kv value of the both QW-ASPAT devices at zero bias was about 33V-1 compared with the standard structure GaAs/InGaAs was about 13V-1. The effects of changing in the thickness of the thin AlAs-barrier, the well width, and the spacer layer are fully investigated on the non-linear relationship between current and voltage of these diodes. A CV simulation was carried out, and it was found that the addition of the quantum-well layer between spacers and barrier reduced the junction capacitance of the QW-ASPAT device when compared with standard devices. The cut-off frequency of the proposed QW-GaAs and QW-InGaAs devices are 26GHz and 46GHz respectively. Finally, we conclude that the QW-ASPAT device is the best structure and can be used for microwave rectifiers in the miniaturized integrated rectenna systems. 1 11 2022/12/08 1401/9/17 2024/08/22 1403/6/1 Shamil H. Hussein Shamil H. Hussein Department of Electrical Engineering, University of Mosul, Mosul, Iraq Iraq shamil_alnajjar84@uomosul.edu.iq Khalid K. Mohammed Khalid K. Mohammed Department of Electrical Engineering, University of Mosul, Mosul, Iraq Iraq khalid.khaleel@uomosul.edu.iq QW-ASPAT Diodes SILVACO Atlas and Implantable Rectenna Circuits. [1] T. Shimaoka, S. Koizumi, JH, and Kaneko, “Recent progress in diamond radiation detectors,” Functional Diamond, vol. 1, no. 1, pp. 205–220, 2022.##[2] J. Wang, M. Naftaly, and E. Wasige, “An Overview of Terahertz Imaging with Resonant Tunneling Diodes,” Applied Sciences, vol. 12, no. 8, p. 3822, 2022.##[3] M. J. Akura, “Simulation of semiconductor devices: the Potential Well Barrier and Planar-doped Potential-Well Barrier diodes,” 2020.##[4] I. I. Izhnin et al., “Single-photon avalanche diode detectors based on group IV materials,” Applied Nanoscience, pp. 1–11, 2021.##[5] K. Z. Ariffin et al., “Asymmetric spacer layer tunnel diode (ASPAT), quantum structure design linked to current-voltage characteristics: A physical simulation study,” presented at the 2017 10th UK-Europe-China Workshop on Millimetre Waves and Terahertz Technologies (UCMMT), 2017, pp. 1–4.##[6] K. N. Z. Ariffin, Physical Modelling of Tunnel Diodes for Terahertz Frequency Applications. The University of Manchester (United Kingdom), 2019.##[7] A. J. Hadfield, “Heterostructure Tunnel Diodes for Terahertz and mm-Wave applications,” 2021.##[8] O. S. H. Abdulwahid, Advanced Quantum Mechanical Tunnelling Based Devices and Avalanche Breakdown Photodiodes for Radio Frequency and Optical Detection Systems. The University of Manchester (United Kingdom), 2019.##[9] A. Hadfield, A. Salhi, J. Sexton, and M. Missous, “Experimentally Validated Physical Modelling of Asymmetric Spacer Layer Tunnel Diodes for THz Applications,” presented at the 2019 12th UK-Europe-China Workshop on Millimeter Waves and Terahertz Technologies (UCMMT), 2019, pp. 1–3.##[10] A. S. Hajo, O. Yilmazoglu, F. Küppers, and T. Kusserow, “Integration and characterisation of Schottky diodes with a pre-amplifier for THz applications,” presented at the 2020 45th International Conference on Infrared, Millimeter, and Terahertz Waves (IRMMW-THz), 2020, pp. 1–2.##[11] F. Rothmayr et al., “Mid-infrared GaSb-based resonant tunneling diode photodetectors for gas sensing applications,” Applied Physics Letters, vol. 112, no. 16, p. 161107, 2018.##[12] A. Hadfield, A. Salhi, J. Sexton, and M. Missous, “Novel barrier-well heterostructure diodes for microwave and mm-wave applications,” Solid-State Electronics, vol. 178, p. 107963, 2021.##[13] O. Abdulwahid, S. G. Muttlak, J. Sexton, M. Missous, and M. Kelly, “24ghz zero-bias asymmetrical spacer layer tunnel diode detectors,” presented at the 2019 12th UK-Europe-China Workshop on Millimeter Waves and Terahertz Technologies (UCMMT), 2019, pp. 1–3.##[14] N. Tuomisto, A. Zugarramurdi, and M. J. Puska, “Modeling of electron tunneling through a tilted potential barrier,” Journal of Applied Physics, vol. 121, no. 13, p. 134304, 2017.##[15] A. Salhi, J. Sexton, S. Muttlak, O. Abdulwahid, A. Hadfield, and M. Missous, “InGaAs/AlAs/GaAs metamorphic asymmetric spacer layer tunnel (mASPAT) diodes for microwaves and millimeter-waves detection,” Journal of Applied Physics, vol. 127, no. 19, p. 194505, 2020.##[16] A. A. ISMAEL, A. T. YOUNIS, E. A. ABDO, and S. H. HUSSEIN, “IMPROVEMENT OF NON-LINEAR POWER AMPLIFIER PERFORMANCE USING DOHERTY TECHNIQUE,” Journal of Engineering Science and Technology, vol. 16, no. 6, pp. 4481–4493, 2021.##[17] M. Kumar, “Social, economic, and environmental impacts of renewable energy resources,” Wind Solar Hybrid Renewable Energy System, vol. 1, 2020.##[18] M. M. H. Shuvo, T. Titirsha, N. Amin, and S. K. Islam, “Energy Harvesting in Implantable and Wearable Medical Devices for Enduring Precision Healthcare,” Energies, vol. 15, no. 20, p. 7495, 2022.##[19] S. G. Muttlak, M. Sadeghi, K. Ian, and M. Missous, “Low-Cost Compact Integrated Rectenna for Implantable Medical Receivers,” IEEE Sensors Journal, vol. 22, no. 17, pp. 16938–16944, 2022.##[20] S. G. Muttlak, M. Sadeghi, K. Ian, and M. Missous, “Miniaturized Folded Antenna with Improved Matching Characteristic for mm-wave Detections,” presented at the 2021 14th UK-Europe-China Workshop on Millimetre-Waves and Terahertz Technologies (UCMMT), 2021, pp. 1–3.##[21] Das, Rupam, and Hyoungsuk Yoo. "A multiband antenna associating wireless monitoring and nonleaky wireless power transfer system for biomedical implants." IEEE Transactions on Microwave Theory and Techniques 65.7 (2017): 2485-2495.##[22] Radiom, Soheil, et al. "Far-Field On-Chip Antennas Monolithically Integrated in a Wireless-Powered 5.8-GHz Downlink/UWB Uplink RFID Tag in 0.18-µm Standard CMOS." IEEE Journal of Solid-State Circuits 45.9 (2010): 1746-1758.##[23] Muttlak, Saad G., et al. "Low-Cost Compact Integrated Rectenna for Implantable Medal Receivers." IEEE SENSORS JOURNAL 22.17 (2022): 16938-16944.##[24] Walsh, Christopher, et al. "Miniature Integrated 2.4 GHz Rectennas Using Novel Tunnel Diodes." Sensors 23.14 (2023): 6409.## ##

Design and Implementation of a 31-level Inverter Based on FPGA for Sustainable Energy Applications 2 2 Artificial intelligence-based optimization algorithm was used to compute the switching angle values. In order to run the inverter with the lowest possible Total Harmonic Distortion (THD) value, it is suggested in this study to use an algorithm such as the Practical Swarm Algorithm (PSA).  The multilevel inverter and optimization algorithm were created and simulated in this study using a MATLAB software. A frequency spectrum analysis was also conducted and found to be consistent with the theoretical analysis of the system. To provide practical results, the FPGA generates PWM signals that are appropriate for the inverter switches. On the Spartan-3E Starter set, the suggested control schemes were developed and put it into practice. Xilinx-ISE 12.1i design software and VHDL hardware description language were used to create the FPGA software. The suggested approaches have a number of benefits over conventional digital PWM techniques, including straightforward hardware implementation, minimum scaling of digital circuits, easy digital design, reconfigurable, and flexibility in adaptability. The outcomes of the experiment and the simulation agreed rather well. 12 24 2022/12/082023/12/15 1402/9/24 2024/08/222024/09/05 1403/6/15 Ali Riyadh ALI Ali Riyadh ALI the Department of Electrical Engineering, University of Mosul Iraq alipower76@gmail.com Rakan Khalil Antar Rakan Khalil Antar Northern Technical University Iraq rakan.antar@ntu.edu.iq Abdulghani Abdulrazzaq Abdulghafoor Abdulghani Abdulrazzaq Abdulghafoor University of Mosul Iraq drabdulghani18@uomosul.edu.iq FPGA Selective harmonic elimination (SHE) Harmonics Particle Swarm Optimization (PSO). [1] El-Hosainy A., Hamed H. A., Azazi H.Z. and El-Kholy EE., “A review of multilevel inverter topologies, control techniques, and applications,” 2017 Nineteenth International Middle East Power Systems Conference (MEPCON), Dec. 2017, doi: 10.1109/mepcon.2017.8301344.##[2] Ali A.R., Abdulghafoor A.A. and Antar R. K., “Design a 25-level inverter topology with less switching devices fed by PV systems,” International Journal of Power Electronics and Drive Systems (IJPEDS), Vol. 14, No. 3, pp. 1816, Sep. 2023, doi: 10.11591/ijpeds.v14.i3.pp1816-1824##[3] Mittal N., Singh B., Singh S.P., Dixit R. and Komar D., “Multi-level inverter: a literature survey on topologies and control strategies”, ICPCES, 2nd International Conference on Power, Control and Embedded Systems, 2012. ##[4] Carrasco J.M., Franquelo L.G., Bialasiewicz J.T., Galvan E., Portillo Guisado R.C., Prats M.A.M., Leon J.A. and Moreno-Alfonso N., “Powerelectronic systems for the grid integration of renewable energy sources: A survey,” IEEE Trans. Ind. Electron., Vol. 53, No. 4, pp. 1002–1016, January 2006.##[5] Franquelo L., Rodriguez J., Leon J., Kouro S., Portillo R. and Prats M., “The age of multilevel converters arrives,” IEEE Industrial Electronics Magazine, Vol. 2, No. 2, pp. 28–39, Jun. 2008, doi: 10.1109/mie.2008.923519.##[6] Rodriguez J., Jih-Sheng L. and Peng F.Z., “Multilevel inverters: a survey of topologies, controls, and applications,” IEEE Transactions on Industrial Electronics, Vol. 49, No. 4, pp. 724–738, Aug. 2002, doi: 10.1109/tie.2002.801052.##[7] Aghdam M.G.H., Fathi S.S. and Ghasemi A., “The analysis of conduction and switching losses in threephase OHSW multilevel inverter using switching functions”, IEE PEDS 2005, Vol. 1, pp. 209-218, 2005.##[8] Kumar J., “THD analysis for different levels of cascaded multilevel inverters for industrial applications,” International Journal of Emerging Technology and Advanced Engineering (IJETAE), Vol. 2, Issue 10, pp.237-244, October 2012.##[9] Gobinath K, Mahendran S and Gnanambal I, “New cascaded h-bridge multilevel inverter with improved efficiency”, International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering (IJAREEIE), Vol. 2, Issue 4, pp.1263-1271, April 2013.##[10] Memon M.A., Mekhilef S. and Mubin M., “Selective harmonic elimination in multilevel inverter using hybrid APSO algorithm,” IET Power Electron., Vol. 11, No. 10, pp. 1673–1680, 2018, doi: 10.1049/iet-pel.2017.0486##[11] Patil S.D. and Kadwane S.G., “Hybrid optimization algorithm applied for selective harmonic elimination in multilevel inverter with reduced switch topology,” Microsyst. Technol., Vol. 24, No. 8, pp. 3409–3415, 2018, doi: 10.1007/s00542-018-3720-x.##[12] Ganesan K., Barathi K., Chandrasekar P. and Balaji D., “Selective Harmonic Elimination of Cascaded Multilevel Inverter Using BAT Algorithm,” Procedia Technology, Vol. 21, pp. 651–657, 2015, doi: 10.1016/j.protcy.2015.10.078.##[13] Halligudi R. B., “Simulation and Analysis of Reduced Switch Multilevel Inverters for High Power Applications,” Bioscience Biotechnology Research Communications, Vol. 13, No. 13, pp. 131–136, Dec. 2020, doi: 10.21786/bbrc/13.13/18.##[14] Marín-Reyes M., Aguayo-Alquicira J. and De León-Aldaco S.E., “Calculation of Optimal Switching Angles for a Multilevel Inverter Using NR, PSO, and GA- a Comparison,” European Journal of Electrical Engineering, Vol. 22, No. 4–5, pp. 349–355, Oct. 2020, doi: 10.18280/ejee.224-506.##[15] Urgun S. and Yigit H., “Selective Harmonic Eliminated Pulse Width Modulation (SHE-PWM) Method using Genetic Algorithm in Single-Phase Multilevel Inverters,” International Journal on Electrical Engineering and Informatics, Vol. 13, No.1, pp. 191–202, Mar. 2021, doi: 10.15676/ijeei.2021.13.1.11.##[16] Shahbaz R., Ahmed T., Elavarasan R.M., Raju K., Waqas M. and Subramaniam U., “Selective Harmonics Elimination in Multilevel Inverter Using Bio-Inspired Intelligent Algorithms,” 2021 31st Australasian Universities Power Engineering Conference (AUPEC), Sep. 2021, doi: 10.1109/aupec52110.2021.9597805.##[17] Prabaharan N. and Palanisamy K., “A comprehensive review on reduced switch multilevel inverter topologies, modulation techniques and applications,” Renewable and Sustainable Energy Reviews, Vol. 76, pp. 1248–1282, Sep. 2017, doi: 10.1016/j.rser.2017.03.121.##[18] Saifizi M., Kasdi N.S., Rahim H.A., Mashagba H.A., Mustafa W.A., Aihsan M.Z. Syahmi M.M.S., “Selective Harmonic Elimination of Five Level Cascaded H-Bridge Inverter Using the Newton-Raphson Technique,” Journal of Physics: Conference Series, Vol. 1962, No. 1, pp. 012023, Jul. 2021, doi: 10.1088/1742-6596/1962/1/012023.##[19] Yaqoob M.T., Shahid Z., Rahmat M.K., Alam M.M. and Su’ud M.M, “Selective Harmonic Elimination in Cascaded H-Bridge Multilevel Inverters using Particle Swarm Optimization: A review,” 2019 13th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics (MACS), Dec. 2019, doi: 10.1109/macs48846.2019.9024783.##[20] Rao K.V. and Rao G. J., “THD Minimization in Cascaded H-Bridge Inverter using Optimal Selective Harmonic Elimination,” International Journal of Recent Technology and Engineering (IJRTE), Vol.10, No. 2, pp. 170–174, Jul. 2021, doi: 10.35940/ijrte.b5984.0710221.##[21] Mohammed L., “High performance of multilevel inverter reduced switches for a photovoltaic system,” PRZEGLĄD ELEKTROTECHNICZNY, Vol.1, No.8, pp. 16–20, Aug. 2022, doi: 10.15199/48.2022.08.3.##[22] Vijaya A. N, Hema L.J, Devadasu G. and Kumar C, “Generation of Optimal Switching Angle for Nine Level Cascaded H Bridge MLI Using Most Valuable Player Algorithm,” Turkish Journal of Computer and Mathematics Education (TURCOMAT), Vol.12, No.6, pp. 1919–1927, Apr. 2021, doi: 10.17762/turcomat.v12i6.4442.##[23] Espinosa C.A.L., Portocarrero I. and Izquierdoet M., “Minimization of THD and Angle Calculation for Multilevel Inverters,” International Journal of Engineering & Technology (IJET-IJENS), Vol. 12 No.05, October 2012.##[24] Krikor K.S., Alnaimi K.I. and Mohammed J.A., “Optimum Design of Single-Phase Cascade Multilevel Inverter Using OHESW Technique,” Eng. & Tech., Vol.26, No.12, 2008.##[25] Ghasemi N., Zare F., Langton C., Ghosh A., “A New Unequal DC link Voltage Configuration for a Single Phase Multilevel Converter to Reduce Low Order Harmonics,” Conference Paper • October 2011.##[26] Jeevabharathi T. and Padmathilagam V., “Harmonic elimination of Cascaded Multilevel Inverters Using Particle Swarm Optimization,” 2012 International Conference on Computing, Electronics and Electrical Technologies (ICCEET), Mar. 2012, doi: 10.1109/icceet.2012.6203775.##[27] Hagh M.T., Taghizadeh H. and Razi K., “Harmonic Minimization in Multilevel Inverters Using Modified Species-Based Particle Swarm Optimization,” IEEE Transactions on Power Electronics, Vol. 24, No.10, pp. 2259–2267, Oct. 2009, doi: 10.1109/tpel.2009.2022166.##[28] Prashanth N., Kumar B., Yadagiri J., Dasgupta A., “Harmonic minimization in multilevel inverters by using PSO”, ACEEE Int. J. on Control System and Instrumentation, Vol. 02, No. 03, October 2011.##[29] Alishah R.S., Hosseini S.H., Babaei E., and Sabahi M., "Optimal Design of New Cascaded Switch-Ladder Multilevel Inverter Structure", IEEE Transactions on Industrial Electronics, Vol. 64, No. 3, pp. 2072–2080, Mar. 2017, doi: 10.1109/tie.2016.2627019.##[30] Ajami A., Oskuee M.R.J., Khosroshahi M.T. and Mokhberdoran A., "Cascade‐multi‐cell multilevel converter with reduced number of switches", IET Power Electronics, Vol. 7, No. 3, pp. 552–558, Mar. 2014, doi: 10.1049/iet-pel.2013.0261.##[31] Prasad D., Dhanamjayulu C., Padmanaban S., Holm-Nielsen J.B., Blaabjerg F. and Khasim S.R., "Design and Implementation of 31 Level Asymmetrical Inverter with Reduced Components", IEEE Access, Vol. 9, pp. 10.1109/access.2021.3055368.##[32] Thakre K., Mohanty K. B., Chatterjee A. and Kommukuri V.S., "A modified circuit for symmetric and asymmetric multilevel inverter with reduced components count", International Transactions on Electrical Energy Systems, Vol. 29, No. 6, Mar. 2019, doi: 10.1002/2050-7038.12011.## ##

Multivariable Prediction Control for Direct Vector Control of a DFIG-based Wind Turbine using a Fuzzy Space Vector Modulation Converter 2 2 In this research paper, a multivariable prediction control method based on direct vector control is applied to command the active power and reactive power of a doubly-fed induction generator used into a wind turbine system. To obtain high energy performance, the space vector modulation inverter based on fuzzy logic technique (fuzzy space vector modulation) is used to reduce stator currents harmonics and active power and reactive power ripples. Also the direct vector control model of the doubly-fed induction generator is required to ensure a decoupled control. Then its classic proportional integral regulators are replaced by the multivariable prediction controller in order to adjust the active and reactive power. So, in this work, we implement a new method of control for the doubly-fed induction generator energy. This method is carried out for the first time by combining the MPC strategy with artificial intelligence represented by Fuzzy SVM-based converter in order to overcome the drawbacks of other controllers used in renewable energies. The given simulation results using Matlab software show a good performance of the used strategy, particularly with regard to the quality of the energy supplied. 25 37 2022/12/082023/12/152024/01/20 1402/10/30 2024/08/222024/09/052024/09/16 1403/6/26 azzedine khati azzedine khati Mechanical Engineering Department, Faculty of Technology, Hassiba Benbouali University, Chlef, AlgeriaLaboratoire Génie Électrique Et Energies Renouvelables (LGEER) Algerie a.khati@univ-chlef.dz Doubly-fed induction generator (DFIG) fuzzy logic multivariable prediction control (MPC) space vector modulation (SVM) direct vector control (DVC) artificial intelligent (AI). [1] L.Saihi, B. Berbaoui and H. Glaoui,”Robust Control H∞ Fuzzy of a Doubly Fed Induction Generator Integrated to Wind Power System,” Majlesi Journal Of Electrical Engineering, Vol. 14, No. 1, pp.59-69, March 2021. ##[2] H. Benbouhenni, Z. Boudjema and A. Belaidi,”Direct Vector Control of a DFIG Supplied by an Intelligent SVM Inverter for Wind Turbine System,” Iranian Journal of Electrical and Electronic Engineering, Vol. 15, No. 1, pp.45-55, March 2019. ## [3] Z. Boudjema, R. Taleb, Y. Djeriri and A.Yahdou,”A novel direct torque control using second order continuous sliding mode of a doubly fed induction generator for a wind energy conversion system,” Turkish Journal of Electrical Engineering & Computer Sciences, Vol. 25, No. 2, pp.965-975, 2017.## [4] H. Benbouhenni, Z. Boudjema and A. Belaidi,”Indirect Vector Control of a DFIG Supplied by a Two-Level FSVM Inverter for Wind Turbine System,” Majlesi Journal of Electrical Engineering, Vol. 13, No. 1, pp.45-54, March 2019.##[5] S.Labdai, N. Bounar, A. Boulkroune, B. Hemici and L. Nezli,”Artificial neural network-based adaptive control for a DFIG-based WECS,” ISA Transactions, Vol.128, pp.171-180, September 2022.##[6] S. Abazari and S. Farajzadeh Dehkordi,”Sliding-Mode Control for a DFIG-Based Wind-Power Generation System with Series Grid-Side Converter under Unbalanced Grid Voltage Conditions,” Scientia Iranica, Vol. 25, No. 3, pp.1507-1522, 2018.##[7] A. Berkani, K. Negadi, T. Allaoui, F. Marignetti “Sliding mode control of wind energy conversion system using dual star synchronous machine and three level converter,” TECNICA ITALIANA-Italian Journal of Engineering Science, Vol. 63, No. 2-4, pp. 243-250, 2019.##[8] L. Djilali, E. Sanchez; M. Belkheiri,”Neural sliding mode field oriented control for DFIG based wind turbine,” in IEEE International Conference on Systems, man and Cybernetics (SMC), Banff, Canada, October 2017##[9] B. Bossoufi, M. Karim, A. Lagrioui, M. Taoussi and M L ElHafyani,”Backstepping control of DFIG generators for wide-range variable-speed wind turbines,” Int. J. Automation and Control, Vol. 8, No. 2, pp 122-140, 2014.##[10] M. El-Azzaoui, H. Mahmoudi and K. Boudaria,“Backstepping control of wind and photovoltaic hybrid renewable energy system,” Internationale Journal of Power Electronics and Drive Systems, Vol. 7, No. 3, pp. 677–686, 2016.##[11] H. Benbouhenni, Z. Boudjema and A. Belaidi,”Neuro-Second Order Sliding Mode Control of a DFIG Supplied by a Two-Level NSVM Inverter for Wind Turbine System,” Iranian Journal of Electrical and Electronic Engineering, Vol. 14, No. 4, pp. 362-373, December 2018.##[12] V. Meenakshi, G. D. Anbarasi and J. S. Paramasivam,“Space vector modulation technique applied to doubly fed induction generator,” Indian Journal of Science and Technology, Vol. 8, pp 1–8, 2015.##[13] M. Gaballah, M. El-Bardini, S. Sharaf and M. Mabrouk, “Implementation of space vector PWM for driving two level voltage source inverters,” Journal of Engineering Sciences, Vol. 39, No. 4, pp. 871–884, 2011.##[14] A. Khati, A. Kansab, R. Taleb and H. Khouidmi,“Current predictive controller for high frequency resonant inverter in induction heating,” International Journal of Electrical and Computer Engineering, Vol. 10, No. 1, pp. 255-264, February 2020.## [15] H. Khouidmi, A. Massoum, “Predictive Control Based Speed, Torque and Flux Prediction of a Double Stator Induction Motor” Majlesi Journal of Electrical Engineering. Vol. 13, No. 1, pp. 65-77, March 2019.## [16] J. Lyu, W. Hu, F. Wu, K. Yao, J. Wu, “A new DPWM Method to Suppress the Low Frequency Oscillation Of The Neutral-Point Voltage For NPC Three-Level Inverters,” Journal of Power Electronics, Vol. 15, No.5, pp. 1207-1216, 2015.##[17] S. Massoum, A. Meroufel, A. Massoum, P. Wira, “A Direct Power Control of the Doubly-Fed Induction Generator based on the SVM Strategy,” Elektrotehniski Vestnik, Vol. 45, No. 5, pp. 235-240, 2017##[18] M. Gaballah and M. El-Bardini,”Low cost digital signal generation for driving space vector PWM inverter;” Ain Shams Engineering Journal, Vol. 4, pp. 763–774, 2013.##[19]Y. Guo, H. Long, “Self Organizing Fuzzy Sliding Mode Controller for The Position Control of A Permanent Magnet Synchronous Motor Drive, ” Ain Shams Engineering Journal, Vol. 2, pp. 109-118, 2011.##[20] H. Benbouhenni, “36 Sectors DTC based on fuzzy logic of sensorless induction motor drives,” Research & Reviews: Journal of Engineering and Technology. Vol. 7, No. 1, pp. 24–32, 2018.##[21] A. Berkani, MH. Ghazwani, K. Negadi, L. Hadji, A. Alnujaie, HA. Ghazwani, “Predictive control and modeling of a point absorber wave energy harvesting connected to the grid using a LPMSG-based power converter,” Ocean Systems Engineering, Vol. 14, No. 1, pp. 17-52, March 2024.##[22] R. Rezavandi, D. A. Khaburi, M. Siami, M. Khosravi, S. Heshmatian,” Model Predictive Control of a BCDFIG With Active and Reactive Power Control Capability for Grid-Connected Applications Iranian Journal of Electrical and Electronic Engineering, Vol. 17, No. 2, pp. 1-11, June 2021. ##[23] L. Bossi, C.Rottenbacher, G.Mimmi, L.Magni,“Multivariable Predictive Control for Vibrating Structures: An application,” Control Engineering Practice Vol.19, No. 10, pp. 1087–1098, October 2011.##[24] A.Younesi, S. Tohidi, M.R. Feyzi. “Fixed switching frequency scheme for current predictive control of DFIG,” Journal of Energy Management and Technology,” Vol. 6, No. 2, pp. 73-82, 2022.##[25] H. Khouidmi, A. Massoum,“Neural Networks Generalized Predictive Speed Controller for Vector Controlled Double Stator Induction Motor,” Majlesi Journal of Mechatronic Systems, Vol. 03, No. 2, pp. 13-18, 2014.##[26] A.F. Syed, Ch.A. Fahad, H. Desa, A T. Hussain,“Model Predictive Controller-based, Single Phase Pulse Width Modulation (PWM) Inverter for UPS Systems,” Journal of Applied Sciences, Acta Polytechnica Hungarica, Vol. 11, No. 6, pp. 23-38, 2014.## ##

A High Voltage Gain DC-DC Converter Based on Quadratic Boost Converter Suitable for Renewable Energy Resources 2 2 Various forms of distributed generation (DG), such as photovoltaic (PV) systems, play a crucial role in advancing a more sustainable future, driven by economic factors and environmental policies implemented by governments. DC-DC converters are essential for harnessing power from solar cells, as they maintain a constant output voltage despite fluctuations in input voltage. Typically, step-up converters are employed to raise output voltage levels, though they often apply the same voltage to an active switch as the output voltage, which can be limiting. To effectively integrate distributed generation sources with the utility grid, high-voltage gain step-up converters are necessary since these sources typically operate at low voltage levels. This study presents an enhanced design of non-isolated DC-DC converters with high voltage gain tailored for photovoltaic (PV) applications. The proposed architecture achieves a quadratic increase in output voltage gain, which alleviates voltage stress on the active switch. Our converter design features a quadratic boost converter complemented by a voltage-boosting cell, facilitating significant voltage amplification. This topology benefits from employing an active switch while minimizing the number of inductors required, resulting in a more compact circuit design. Furthermore, the proposed architecture shares characteristics with recently published topologies regarding passive component utilization, voltage gain, and other relevant parameters. To validate our findings, we conducted mathematical analyses and simulations, with results corroborated by experimental data from laboratory prototype tests. 38 52 2022/12/082023/12/152024/01/202024/03/06 1402/12/16 2024/08/222024/09/052024/09/162024/08/03 1403/5/13 Saeed Hasanzadeh Saeed Hasanzadeh Department of Electrical and Computer Engineering, Qom university of Technology, Qom, Iran. Iran hasanzadeh@qut.ac.ir Seyed Mohsen Salehi Seyed Mohsen Salehi Department of Electrical Engineering, Tarbiat Modares University, Tehran, Iran. Iran sm.salehi3@gmail.com Mohammad Javad Saadatmandfar Mohammad Javad Saadatmandfar Department of Electrical and Computer Engineering, Qom university of Technology, Qom, Iran Iran Mohammadsaadat167@iran.ir DC-DC Converter High Voltage Gain Quadratic Boost Converter Renewable Energy Resources. [1] H. Shojaeian, M. Heydari and S. Hasanzadeh, “Improved interleaved high step-up converter with high efficiency for renewable energy applications,” 8th Power Electronics, Drive Systems & Technologies Conference (PEDSTC), Mashhad, Iran, 2017, pp. 288-293.##[2] Veerabhadra and S. Nagaraja Rao, “Assessment of high-gain quadratic boost converter with hybrid-based maximum power point tracking technique for solar photovoltaic systems,” Clean Energy, vol. 6, no. 4, pp. 632–645, 2022.##[3] M. Forouzesh, Y. P. Siwakoti, S. A. Gorji, F. Blaabjerg, and B. Lehman, “Step-Up DC–DC Converters: A Comprehensive Review of Voltage-Boosting Techniques, Topologies, and Applications,” IEEE Trans. Power Electron., vol. 32, no. 12, pp. 9143–9178, 2017.##[4] V. K. Goyal and A. Shukla, “Isolated DC–DC boost converter for wide input voltage range and wide load range applications,” IEEE Trans. Ind. Electron., vol. 68, no. 10, pp. 9527–9539, 2020.##[5] M. Shaabani, A. Mirzaei, M. Rezvanyvardom, F. Khosravi, and S. A. Gorji, “A Hybrid Switched-Inductor/Switched-Capacitor DC-DC Converter with High Voltage Gain Using a Single Switch for Photovoltaic Application,” Energies, vol. 16, no. 14, p. 5524, 2023.##[6] P. Sarvghadi, A. Y. Varjani, and M. Shahparasti, “A high step-up transformerless DC–DC converter with new voltage multiplier cell topology and coupled inductor,” IEEE Transactions on Industrial Electronics, vol. 69, no. 10, pp. 10162–10171, 2021.##[7] V. Abbasi, N. Talebi, M. Rezaie, A. Arzani, and F. Y. Moghadam, “Ultrahigh Step-Up DC-DC Converter Based on Two Boosting Stages with Low Voltage Stress on Its Switches,” IEEE Transactions on Industrial Electronics, 2023.##[8] M. Rezaie and V. Abbasi, “Ultrahigh step-up DC–DC converter composed of two stages boost converter, coupled inductor, and multiplier cell,” IEEE Transactions on Industrial Electronics, vol. 69, no. 6, pp. 5867–5878, 2021.##[9] H. S. Gohari, N. A. Mardakheh, H. Tarzamni, N. V. Kurdkandi, K. Abbaszadeh, and J. Kyyra, “Non-isolated Ultra-high Voltage Gain Coupled Inductor-based DC-DC Converter,” IEEE Transactions on Circuits and Systems II: Express Briefs, 2023.##[10] S. M. Salehi, S. M. Dehghan and S. Hasanzadeh, “Ultra step-up DC-DC converter based on three windings coupled inductor,” 7th Power Electronics and Drive Systems Technologies Conference (PEDSTC), Tehran, Iran, 2016, pp. 171-176.##[11] M. A. Vaghela and M. A. Mulla, “High Step-Up Gain Converter Based on Two-Phase Interleaved Coupled Inductor Without Right-Hand Plane Zero,” IEEE Trans Power Electron, vol. 38, no. 5, pp. 5911–5927, 2023.##[12] S.-J. Chen, S.-P. Yang, C.-M. Huang, and P.-S. Huang, “Analysis and Design of a New High Voltage Gain Interleaved DC–DC Converter with Three-Winding Coupled Inductors for Renewable Energy Systems,” Energies, vol. 16, no. 9, p. 3958, 2023.##[13] M. Farsijani, S. Abbasian, H. Hafezi, and A. Abrishamifar, “A high step-up cost-effective DC-to-DC topology based on three-winding coupled-inductor,” IEEE Journal of Emerging and Selected Topics in Industrial Electronics, vol. 4, no. 1, pp. 50–59, 2022.##[14] T. Jin, X. Yan, H. Li, J. Lin, Y. Weng and Y. Zhang, "A New Three-Winding Coupled Inductor High Step-Up DC–DC Converter Integrating With Switched-Capacitor Technique," IEEE Transactions on Power Electronics, vol. 38, no. 11, pp. 14236-14248, Nov. 2023.##[15] A. Samadian, M. G. Marangalu, H. Tarzamni, S. H. Hosseini, M. Sabahi, and A. Mehrizi-Sani, “High Step-Up Common Grounded Switched Quasi Z-Source DC–DC Converter Using Coupled Inductor with Small Signal Analysis,” IEEE Access, vol. 11, pp. 120516–120529, 2023.##[16] A. S. Mansour, A.-H. H. Amer, E. E. El-Kholy, and M. S. Zaky, “High gain DC/DC converter with continuous input current for renewable energy applications,” Scientific Reports, vol. 12, no. 1, p. 12138, 2022.##[17] A. H. Mahdizadeh, M. Kashani, M. Soltani, A. Hajizadeh and S. A. Gorji, "A Quadratic Boost Converter Suitable for Fuel Cell-Powered Electric Vehicles," IECON 2023- 49th Annual Conference of the IEEE Industrial Electronics Society, Singapore, Singapore, 2023, pp. 1-6.##[18] M. Izadi, A. Mosallanejad, and A. Lahooti Eshkevari, “An improved coupled inductor‐based quadratic step‐up DC–DC converter with a high step‐up factor and reduced voltage overshoot on the power switch,” IET Power Electronics, 2023.##[19] N. Tewari, N. Paul, M. Jayaraman, and M. Prabhakar, “Reconfigurable high step‐up DC to DC converter for microgrid applications,” IET Power Electronics, 2023.##[20] J. C. Hernandez-Ochoa, A. Alejo-Reyes, J. C. Rosas-Caro, and J. E. Valdez-Resendiz, “Improved Operation of the Step-Up Converter with Large Voltage Gain and Low Voltage on Capacitors,” Applied Sciences, vol. 13, no. 5, p. 2854, 2023.##[21] R. Fani and N. Erfani Majd, “Interleaved converter with ultra-high voltage gain for DC microgrid application,” International Journal of Electronics, pp. 1–20, 2023.##[22] S. A. Gorji and H. Gholizadeh, “A Modified Positive Output Super-Lift Luo DC-DC Converter with Improved Voltage Boost Ability,” in 2022 5th International Conference on Renewable Energy and Power Engineering (REPE), IEEE, 2022, pp. 282–286.## ##

Performance Comparison of Hybrid Switch, Phase Shifter and Lens Network over Hybrid Beamforming in Millimeter Wave Massive MIMO 2 2 Due to cost and energy concerns with digital beamformers, much of the beamforming is done by hybrid beamformers in mm-wave (mm) massive multiple input multiple output (MIMO). Various works in hybrid beamforming structures considered either phase shifters, switches, or radio frequency lenses individually as switching mechanisms between antennas and precoding systems. Works that consider the hybrid use of phase shifters, switches, and radio frequency lenses need further investigation since there is a tradeoff between cost and system performance in each switching mechanism. The main aim of this research is to analyze the performance of a hybrid switch, a 1-bit phase shifter, and radio frequency (RF)-Lens in a hybrid beamforming network as a switching network. Simulation results showed that the hybrid of three has a spectral efficiency (SE) performance of 59.04 bps/Hz, which increases by 6.9 bps/Hz from that of the switch and lens antenna array network. The energy efficiency (EE) of the switch, phase shifter, and lens showed a performance of 46.41 bps/Hz/W, while the switch and lens antenna array, phase shifter, and lens antenna array showed a performance of 48.52 bps/Hz/W. The result also shows that the hybrid network achieves optimum performance at the expense of higher computational complexity. 53 66 2022/12/082023/12/152024/01/202024/03/062024/03/19 1402/12/29 2024/08/222024/09/052024/09/162024/08/032024/06/27 1403/4/7 Tadele A Abose Tadele A Abose Mattu University Ethiopia tadele.abera@meu.edu.et Thomas O Olwal Thomas O Olwal Tshwane University of Technology South Africa thomas.olwal@gmail.com Abel D Daniel Abel D Daniel Dire Dawa University Ethiopia abel35bel@gmail.com Murad R Hassen Murad R Hassen Addis Ababa University Ethiopia muradridwan@gmail.com 1-bit Phase Shifter Hybrid Beamforming Lens Antenna Array Multiple Input Multiple Output Radio Frequency Chain Switch. [1] S. Ashraf, J. A. Sheikh, A. Ashraf, and U. Rasool, "5G Millimeter Wave Technology: An Overview," Intelligent Signal Processing and RF Energy Harvesting for State of art 5G and B5G Networks, pp. 97-112, 2024.##[2] T. S. Rappaport, M. K. Samimi, and S. Sun, "Wideband millimeter-wave propagation measurements and channel models for future wireless communication system design," IEEE Trans. Commun, Vol. 63, No. 9, pp. 3029–3056, Sept. 2015.##[3] T. S. Rappaport, "Millimeter wave mobile communications for 5G cellular: It will work," IEEE Access, Vol. 1, pp. 335–349, May 2013.##[4] Jayakumar, Roscia JS, and Allwyn Clarence Asis Arul, "A Survey on Beamspace Millimeter-wave Massive Mimo Systems: An Overview of Open Issues, Challenges, and Future Research Trends," International Journal of Sensors Wireless Communications and Control, Vol.14, No.1, pp.1-20, 2024.##[5] S. Hamid, S. R. Chopra, A. Gupta, S.Tanwar, B. C. Florea, D. D.Taralunga, and A. M. Shehata, "Hybrid Beamforming in Massive MIMO for Next-Generation Communication Technology," Sensors, Vol. 23, No.16, 2023.##[6] J. Lv, T. Wang, and S.Wang, "Optimal analog precoder design for hybrid beamforming is possible," IEEE Transactions on Vehicular Technology, 2023.##[7] A. Alkhateeb, J. Mo, N. Gonzalez-Prelcic, and R. W. Heath, "MIMO precoding and combining solutions for millimeterwave systems," IEEE Commun. Mag., Vol. 52, No. 12, pp. 186 – 195, Feb. 2014.##[8] J. Li, L. Zhao, and Y. Jiang, “Hybrid Analog and Digital Precoding Design for Minimum BER in Massive MIMO System," IEEE Transactions on Vehicular Technology, 2024.##[9] S. Biru, S. Mishra, R. S. Singh, S. Chura, and S. Satapathy, "Energy‐efficient hybrid beamforming for millimeter‐wave‐based massive multiple‐input multiple‐output system," International Journal of Communication Systems, Vol. 37, No. 8, 2024.##[10] K. Umaria, and S. Shah, "Spectral efficiency of hybrid precoding and combining design for mm-Wave multi-user massive MIMO systems," Analog Integrated Circuits and Signal Processing, pp.1-9, 2024.##[11] X. Qi, M. Peng, H. Zhang, and X. Kong, "Anti-Jamming Hybrid Beamforming design for Millimeter-Wave Massive MIMO systems," IEEE Transactions on Wireless Communications, 2024.##[12] Y. N. Samir, H. B. Nafea, and F. W. Zaki, "Performance Evaluation of Spectral Efficiency Hybrid Precoding and Combining Algorithm for Millimeter Wave-MIMO Systems," Wireless Personal Communications, Vol. 133, No. 3, pp. 1769-1784, 2024.##[13] R. A. Mohammad, Yassin, and H. Abdallah, "Hybrid Beamforming in Multiple User Massive Multiple Input Multiple Output 5G Communications System," in 2020 7th International Conference on Electrical and Electronics Engineering (ICEEE), Antalya, Turkey, 2020.##[14] Nosrati, H., Aboutanios, E., Wang, X., & Smith, D., "Switch-based hybrid beamforming for massive MIMO communications in mmWave bands," Signal Processing, Vol. 200, 2022.##[15] Cetinkaya, S., Afeef, L., Mumcu, G., & Arslan, H, "Heuristic inspired precoding for millimeter-wave MIMO systems with lens antenna subarrays," In 2022 IEEE 95th Vehicular Technology Conference:(VTC2022-Spring), Helsinki, Finland, 2022.##[16] Méndez-Rial, R., Rusu, C., González-Prelcic, N., Alkhateeb, A., & Heath, R. W., "Hybrid MIMO architectures for millimeter wave communications: Phase shifters or switches?" IEEE access, Vol. 4, pp. 247-267, 2016.##[17] Payami, S., Khalily, M., Loh, T. H., & Nikitopoulos, K., "Hybrid beamforming with switches and phase shifters over frequency-selective channels," IEEE Wireless Communications Letters, Vol. 9, No.8, pp. 1305-1308, 2020.##[18] Nosrati, H., Aboutanios, E., Wang, X., & Smith., "Switch-based hybrid beamforming for massive MIMO communications in mmWave bands," Signal Processing, Vol. 200, 2022. ##[19] L. Zhao, J. Li, S. Huang, X. Wu, and M. Jiang, "Low-complexity hybrid precoding for sub-connected millimeter wave massive MIMO systems," Signal Processing, Vol. 219, 2024.##[20] T.Yuwono, M. Ismail, and I. Hajar, "Design of Massive MIMO for 5G 28 GHZ," In 2019 2nd International Conference on Computer Applications & Information Security (ICCAIS), Riyadh, Saudi Arabia, 2019.##[21] M. Abdelfatah, A. Zekry, and S. ElSayed, "Orthogonal beamforming technique for massive MIMO systems," Annals of Telecommunications, pp. 1-19, 2024.##[22] X. Gao, L. Dai, S. Han, I. Chih-Lin, and X. Wang, "Reliable Beamspace Channel Estimation for Millimeter-Wave Massive MIMO Systems with Lens Antenna Array," IEEE Transactions on Wireless Communications, Vol. 16, No. 9, 2017.##[23] H. Song, and A. Sayeed, "Beamspace MIMO transceivers for low-complexity and near-optimal communication at mm-wave frequencies," in 2013 IEEE International Conference on Acoustics, Speech and Signal Processing, Vancouver, BC, Canada, Apr. 2013.##[24] A. Alkhateeb, G. Leus, and R. W. Heath, "Channel estimation and hybrid precoding for millimeter wave cellular systems," IEEE J. Sel. Top. Signal Process., Vol. 8, No. 5, pp. 831–846, Oct. 2014. ##[25] T. A. Abose, T. O. Olwal, and M. R. Hassen, "Hybrid beam-forming techniques for multi-cell massive MIMO," International Journal of Advanced Technology and Engineering Exploration, Vol. 9, No.94, 2022.##[26] T. A. Abose, T. O. Olwal, and M. R. Hassen, "Hybrid beamforming for millimeter wave massive MIMO under multicell multiuser environment," Indian J Sci Technol, Vol.15, No. 20, pp.1001-1011, 2022.##[27] T. A. Abose, T. O. Olwal, and M. R. Hassen, "Hybrid beamforming for millimeter wave massive MIMO under hardware impairments and imperfect channel state information," in 2021 IEEE International Conference on Mobile Networks and Wireless Communications (ICMNWC), Tumkur, Karnataka, India, 2021.##[28] J. Brady, N. Behdad, and A. M. Sayeed, "Beamspace MIMO for millimeter-wave communications: System architecture, modeling, analysis, and measurements," IEEE Trans. Antennas Propag., Vol. 61, No. 7, pp. 3814–3827, Jul. 2013.##[29] J. Hogan and A. Sayeed, "Beam selection for performance-complexity optimization in high-dimension MIMO systems," in 2016 Annual Conference on Information Science and Systems (CISS), Princeton, NJ, USA, Mar. 2016.##[30] X. Yu, J. Zhang, and K. B. Letaief, "Hybrid Precoding in Millimeter Wave Systems: How Many Phase Shifters Are Needed?" in 2017 IEEE Global Communications Conference (GLOBECOM 2017), Singapore, 2017.##[31] W. U. Bajwa, J. Haupt, A. M. Sayeed, and R. Nowak, "Compressed channel sensing: A new approach to estimating sparse multipath channels," Proc. IEEE, Vol. 98, No. 6, pp. 1058–1076, Jun. 2010.##[32] P. V. Amadori and C. Masouros, "Low RF-complexity millimeter-wave beamspace-MIMO systems by beam selection," IEEE Trans. Commun.,, Vol. 63, No. 6, pp. 2212–2223, 2015.##[33] Nguyen, N. T., and K. Lee, "Coverage and Cell-Edge SumRate Analysis of mmWave Massive MIMO Systems with ORP Schemes and MMSE Receivers," IEEE Trans. Signal Process, Vol. 66, No. 20, pp. 5349–5363, 2018.## ##

Enhancement of Distribution Transformer Lifespan by using Distributed Generation under Transactive Control Rescheduling 2 2 Due to the anticipated increase in loads, the power grid will encounter the issue of system peak loads in the future, which is typically addressed through grid reinforcement. However, implementing a flexibility service option can prevent the need for grid development. As the overall load continues to rise, the distribution transformer becomes overloaded. The presented work focuses on enhancing one of the parameters that define the insulation life of the transformer, known as the Loss-of-Life (LOL). Transactive approach involves the rescheduling of the battery and photovoltaic generation. Dominated Group Search Optimization (DGSO) algorithm is utilized to optimize the objective function of reducing the peak transformer load under the power flow and voltage constraints of the network. Experimental validation of the proposed method is conducted using MATLAB 2018 software. Modified IEEE 34-bus system is used to implement the proposed methodology. Numerical results obtained from various cases elucidate that the proposed model reduces the LOL of the transformer from 0.0103 to 0.0017 p.u.Comparative analysis of the proposed method with the already used methods of voltage-control and Volt-Var control have been presented. 67 77 2022/12/082023/12/152024/01/202024/03/062024/03/192024/03/28 1403/1/9 2024/08/222024/09/052024/09/162024/08/032024/06/272024/08/25 1403/6/4 Akanksha Jain Akanksha Jain Maulana Azad National Institute of Technology,Bhopal India akanksha091091@gmail.com S.C. Gupta S.C. Gupta Maulana Azad National Institute of Technology,Bhopal India guptashiv@manit.ac.in Loss-of-Life Power Distribution System Insulation Life transformer. [1] National Energy Board,Canada, “Canada’s energy future 2016: energy supply and demand projections to 2040,” 2016.##[2] A. Eller and A. Dehamna, ““Residential energy storage: advanced lead- acid, flow, and lithium ion battery systems for residential applications: global market analysis and forecasts,” global market analysis and forecasts,” Navigant Research, 2016.##[3] M. Gray and W. G. Morsi, “ On the role of prosumers owning rooftop solar photovoltaic in reducing the impact on transformer’s aging due to plug-in electric vehicles charging,” ,” Elect. Power Syst. Res., vol. 143, pp. 563–572, Feb 2017.##[4] M. ElNozahy and M. M. A. Salama, “A comprehensive study of the impacts of PHEVs on residential distribution networks,” IEEE Trans. Sustain. Energy, pp. 332–342, Jan.2014.##[5] P. Moses, M. Masoum, and S. Hajforoosh, “Overloading of distribution transformers in smart grid due to uncoordinated charging of plug-in electric vehicles,” Proc. Innovative Smart Grid Technologies (ISGT), pp. 1–6, 2012.##[6] M. Gray and W. G. Morsi, “Power quality assessment in distribution systems embedded with plug-in hybrid and battery electric vehicles,,” IEEE Trans. Power System, vol. 30, pp. 663–671, Mar.2015.##[7] Y. Assolami and W. G. Morsi, “Impact of second-generation plug- in battery electric vehicles on the aging of distribution transformers considering TOU prices,” IEEE Trans. Sustain. Energy, vol. 6, pp. 1606– 1614, Oct.2015.##[8] “IEEE Guide for Loading Mineral-Oil-Immersed Transformers and StepVoltage Regulators,” 2011.##[9] F. M. Uriarte, A. Toliyat, A. Kwasinski, and R. E. Hebner, “Consumer- data approach to assess the effect of residential grid-tied photovoltaic systems and electric vehicles on distribution transformers,” Proc. IEEE 5th Int. Symp. Power Electron. Distrib. Gener. Syst. (PEDG), Galway, Ireland, pp. 1–8, Jun.2014.##[10] S. F. Abdelsamad, W. G. Morsi, and T. S. Sidhu, “Probabilistic Impact of Transportation Electrification on the Loss-of-Life of Distribution Transformers in the Presence of Rooftop Solar Photovoltaic,” IEEE Trans. on Sustainable Energy, vol. 6, no. 4, pp. 1565–1573, 2015.##[11] T. Geiles and S. Islam, “Impact of PEV charging and rooftop PV penetration on distribution transformer life,” Proc. IEEE Power and Energy Society General Meeting (PESGM),Vancouver, BC, pp. 1–5, Jul.2013.##[12] M. Syed, P. Crolla, G. M. Burt, and J. K. Kok, “ Ancillary service provision by demand side management: a real-time power hardware-in- the loop co-simulation demonstration,” Proc. International Symposium on EDST, Vienna, pp. 492–498, 2015.##[13] S. Behboodi, D. Chassin, C. Crawford, and N. Djilali, “Electric vehicle participation in transactive power systems using real-time retail prices,” Proc. HICSS, Koloa, HI, pp. 2400–2407, 2016.##[14] M. B. J. Appen, T. Stetz and A. Schmiegel, “Local voltage control strategies for PV storage systems in distribution grids,” IEEE Trans. Smart Grid, vol. 5, pp. 1002–1009, Mar. 2014.##[15] J. Villar, R. Bessa, and M. Matos, “‘Flexibility products and markets: Literature review,” Power Syst. Res, vol. 154, pp. 329–340, 2018.##[16] P. Siano and D. Sarno, “‘Assessing the benefits of residential demand response in a real time distribution energy market,” Appl. Energy, vol. 161, pp. 533–551, 2016.##[17] A. Vijay and A. Hawkes, “‘Demand side flexibility from residential heating to absorb surplus renewables in low carbon futures,” Renew. Energy, vol. 138, pp. 598–609, 2019.##[18] N. G. Paterakis, O. Erdinç, and J. P. S. Catalão, “‘An overview of Demand Response: Key-elements and international experience,” Renew. Sustain.Energy Rev, vol. 69, pp. 871–891, 2017.##[19] P. Siano, G. Marco, A. Rolan, and V. Loia, “‘A survey and evaluation of the potentials of distributed ledger technology for peer-to-peer transac- tive energy exchanges in local energy markets,” IEEE Systems J, vol. 13, no. 3, pp. 3454–3466, 2019.##[20] S. Minniti, N. Haque, P. Nguyen, and G. Pemen, pp. 3074–3074, 2018.##[21] Universal Smart Energy Framework (USEF): The Framework Explained, USEF Foundation, Arnhem, The Netherlands, 2015.##[22] P. Olivella-Rosell, E. Bullich-Massagué, M. Aragüés-Peñalba, A. Sumper, S. Ø. Ottesen, J.-A Vidal-Clos, and R. Villafáfila- Robles, “‘Optimization problem for meeting distribution system operator requests in local flexibility markets with distributed energy resources,” Appl. Energy, vol. 210, pp. 881–895, 2018.##[23] K. Heussen, D. E. M. Bondy, J. Hu, O. Gehrke, and L. H. Hansen, “A clearinghouse concept for distribution-level flexibility services,” in IEEE PES ISGT Europe, and others, Ed., 2016.##[24] M. R. Sarker, D. J. Olsen, and M. A. Ortega-Vazquez, “Co-Optimization of Distribution Transformer Aging and Energy Arbitrage Using Electric Vehicles,” IEEE Trans. on Smart Grid, no. 99, pp. 1–11, 2016.##[25] T. J. Geiles and S. Islam, “Impact of PEV Charging and Rooftop PV Penetration on Distribution Transformer Life,” in IEEE Power & Energy Society General Meeting, 2013.##[26] A. VISAKH and M. P. SELVAN, “Smart charging of electric vehicles to minimize the cost of chargingand the rate of transformer aging in a residential distribution network,” Turk. J. Electr. Eng. Comput. Sci. , 2022.##[27] N. B. G. Brinkel, W. L. Schram, T. A. AlSkaif, I. Lampropoulos, and W. van Sark, “ Should we reinforce the grid? Cost and emission optimization of electric vehicle charging under different transformer limits ,” Applied Energy, 2020.##[28] N. Shkitina and D. Akimov, “Analysis of the influence of the stochastic load of electric vehicles on the distribution network,” Elektroenerg. Peredacha i Raspred, vol. 1, no. 20, pp. 40–45, 2021.##[29] H. Nafisi, “Investigation on distribution transformer loss-of-life due to plug-in hybrid electric vehicles charging,” Int. J. Ambient Energy , 2021.##[30] A. Palomino and M. Parvania, “Data-driven risk analysis of joint electric vehicle and solar operation in distribution networks,” IEEE Open Access J. Power Energy , 2020.##[31] L. He, L. Li, M. Li, Z. Li, and X. Wang, “ A deep learning approach to the transformer life prediction considering diverse aging factors,” Front. Energy Res. , 2022.##[32] S. A. El-Bataway and W. G. Morsi, “Distribution transformer’s loss of life considering residential prosumers owning solar shingles, high- power fast chargers and secondgeneration battery energy storage,,” IEEE Trans. Ind. Inf. , 2019.##[33] I. Diahovchenko et al., “Mitigation of transformers’ loss of life in power distribution networks with high penetration of electric vehicles,,” Results Eng., vol. 15, p. 100592, Sep.2022.##[34] C. M. Affonso, Q. Yan, and M. Kezunovic, “Risk Assessment of Transformer Loss-of-Life due to PEV Charging in a Parking Garage with PV Generation,” in IEEE Power & Energy Society General Meeting (PESGM), and others, Ed., 2018.##[35] A. Jain and S.C.Gupta, “Evaluation of electrical load demand forecast- ing using various machine learning algorithms,” Frontiers in Energy Research, vol. 12, 2024.##[36] K. Kumar, S. Satsangi, and G. B.Kumbhar, “Extension of life of distribution transformer using Volt-VAr optimisation in a distribution system,” IET Generation, Transmission & Distribution, vol. 13, no. 10, pp. 1777–1785, 2019.## ##

Millimeter Wave Energy Absorption by Human Tissues: Evaluation of Tissue Penetration 2 2 Presented in this paper is an evaluation of human tissue penetration by millimeter wave (mmW) energy, particularly at 30, 35, 40 and 45 GHz. Numerical simulations show that the penetration depths in the tissue are (0.1000, 0.0937, 0.08869 and 0.08882) mm at the aforementioned frequency, respectively. It is also demonstrated that all mmW at those frequencies attenuate to zero at the epidermis which is the layer adjacent to the skin surface, without getting into the dermis which is the next layer. Crucially, these discoveries present fresh, previously unmentioned data within the current research literature. Furthermore, at the lower frequency of 24 GHz, computer simulations presented show that the propagating wave penetrates deeper (depth of 0.12 mm) and attenuates to zero at the dermis. This shows that the depth of penetration increases further at lower frequencies which strongly conforms to the principles of physical reasoning, thereby bolstering the reliability of the findings presented in this paper. The results collectively indicate that the absorption of mmW into the human tissue have limited significance when assessing compliance with electromagnetic field standards at mmW frequencies. It is reinforced in this paper why the human skin reduces the harmful effects of ultra-violet radiation.  To lend credence to our formulation, certain aspects of the results obtained in this investigation when compared with similar results in the literature, show good agreements. 78 91 2022/12/082023/12/152024/01/202024/03/062024/03/192024/03/282024/04/16 1403/1/28 2024/08/222024/09/052024/09/162024/08/032024/06/272024/08/252024/08/20 1403/5/30 Godday Biowei Godday Biowei Electrical and Electronics Engineering Department, Faculty of engineering, Niger-Delta University, Wilberforce Island, Yenogoa, Nigeria Nigeria biogod@ndu.edu.ng Sulaiman Adeniyi Adekola Sulaiman Adeniyi Adekola Department of Electrical and Electronic Engineering, Federal University Otuoke, Nigeria Nigeria adekolaadeniyi43@gmail.com Kamoli Akinwale Amusa Kamoli Akinwale Amusa Electrical and Electronics Engineering Department, College of Engineering, Federal University of Agriculture, Abeokuta, Nigeria Nigeria amusaka@funaab.edu.ng Human tissue mmWave penetration depth damping oscillations SAR [1] Biowei G., S.A. Adekola, and K.A. Amusa. (2024). “The Dynamics of (5G) Millimeter Wave Energy Absorption in Human Tissue: A Comprehensive Analysis at the Free Space - Human Skin Interface”, Iranian Journal of Electrical and Electronic Engineering 02. (2024) 3256, Vol. 20, No. 2, pp. 1-14, 2024.##[2] Mehrotra P., B. Chatterjee and S. Sen. “EM-Wave Biosensors: A Review of RF, Microwave, mm-Wave and Optical Sensing”. Sensors, Vol. 19(1013), pp. 1- 46, 2019.##[3] Bailey W.H., R. Bushberg, J. Chou, C.K. Cleveland et. al. 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Optimal Reconfiguration using Firefly Algorithm for Integrated Electrical Distribution Network with Distributed Generation, Case Study: 20 kV Tarahan Substation, Province of Bandar Lampung, Indonesia 2 2 The unbalanced load distribution in the electrical distribution network caused crucial power losses. This condition occurs in one of the electrical distribution networks, 20 kV Tarahan Substation, Province of Bandar Lampung, Indonesia. This condition can be maintained using optimal reconfiguration with the integration of Distributed Generation (DG) based on Renewable Energy (RE). This study demonstrates the optimal reconfiguration of the 20 kV Tarahan Substation with the integration of the Photovoltaic (PV) and Battery Energy Storage System (BESS). The reconfiguration process is optimized by using the Firefly Algorithm (FA). This process is conducted in the 24-hour simulation with various load profiles. The optimal reconfiguration is investigated in two scenarios based on without and with DG integration. The optimal configuration with more balanced load distribution conducted by FA reduces the power losses by up to 31.39% and 32.38% in without and with DG integration, respectively. Besides that, the DG integration improves the lowest voltage bus in the electrical distribution network from 0.95 p.u to 0.97 p.u. 92 105 2022/12/082023/12/152024/01/202024/03/062024/03/192024/03/282024/04/162024/05/16 1403/2/27 2024/08/222024/09/052024/09/162024/08/032024/06/272024/08/252024/08/202024/07/23 1403/5/2 Mohamad Almas Prakasa Mohamad Almas Prakasa Doctoral Student at Department of Electrical Engineering, Institut Teknologi Sepuluh Nopember Indonesia 7022222015@student.its.ac.id Mohamad Idam Fuadi Mohamad Idam Fuadi Department of Electrical Engineering, Institut Teknologi Sepuluh Nopember Indonesia mohamadidam123@gmail.com Muhammad Ruswandi Djalal Muhammad Ruswandi Djalal Doctoral Student at Department of Electrical Engineering, Institut Teknologi Sepuluh Nopember Indonesia 7022221006@student.its.ac.id Imam Robandi Imam Robandi Professor at Department of Electrical Engineering, Institut Teknologi Sepuluh Nopember Indonesia imam.robandi@its.ac.id Dimas Fajar Uman Putra Dimas Fajar Uman Putra Lecturer at Department of Electrical Engineering, Institut Teknologi Sepuluh Nopember Indonesia dimasfup@ee.its.ac.id Electrical Distribution Network Firefly Algorithm Optimal Reconfiguration Renewable Energy. 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Truong, “Distribution network reconfiguration for power loss minimization and voltage profile improvement using cuckoo search algorithm,” Int. J. Electr. Power Energy Syst., vol. 68, pp. 233–242, 2015, doi: 10.1016/j.ijepes.2014.12.075.##[6] S. Hamid-Oudjana, M. Mosbah, R. Zine, and S. Arif, Optimum Dynamic Network Reconfiguration in Smart Grid Considering Photovoltaic Source, vol. 102. Springer International Publishing, 2020. doi: 10.1007/978-3-030-37207-1_59.##[7] Global Solar Atlas, “Tarahan,” 2022.##[8] Subiyanto, M. A. Prakasa, P. Wicaksono, and M. A. Hapsari, “Intelligence technique based design and assessment of photovoltaic-battery-diesel for distributed generation system in campus area,” Int. Rev. Model. Simulations, vol. 13, no. 1, 2020, doi: 10.15866/iremos.v13i1.18147.##[9] M. Almas Prakasa and S. 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Nguyen, F. M. Zou, and S. C. Chu, “Dynamic reconfiguration of distribution network based on dynamic optimal period division and multi-group flight slime mould algorithm,” Electr. Power Syst. Res., vol. 208, no. August 2021, p. 107925, 2022, doi: 10.1016/j.epsr.2022.107925.##[14] L. L. Li, J. L. Xiong, M. L. Tseng, Z. Yan, and M. K. Lim, “Using multi-objective sparrow search algorithm to establish active distribution network dynamic reconfiguration integrated optimization,” Expert Syst. Appl., vol. 193, no. January, p. 116445, 2022, doi: 10.1016/j.eswa.2021.116445.##[15] F. J. Ruiz-Rodríguez, S. Kamel, M. H. Hassan, and J. A. Dueñas, “Optimal reconfiguration of distribution systems considering reliability: Introducing long-term memory component AEO algorithm,” Expert Syst. Appl., vol. 249, no. November 2023, 2024, doi: 10.1016/j.eswa.2024.123467.##[16] L. Kondisetti and S. Katragadda, “A multi-objective artificial hummingbird algorithm for dynamic optimal volt-var controls for high electric vehicle load penetration in a photovoltaic distribution network,” e-Prime - Adv. Electr. Eng. Electron. Energy, vol. 7, no. December 2023, p. 100474, 2024, doi: 10.1016/j.prime.2024.100474.##[17] A. Rezaee.Jordehi, “DG allocation and reconfiguration in distribution systems by metaheuristic optimisation algorithms: A comparative analysis,” Proc. - 2018 IEEE PES Innov. Smart Grid Technol. Conf. Eur. ISGT-Europe 2018, pp. 1–6, 2018, doi: 10.1109/ISGTEurope.2018.8571802.##[18] A. L. Rojas, S. Koziel, M. F. Abdel-Fattah, and G. Gutierrez-Alcaraz, “Distribution Network Reconfiguration for Voltage Stability Enhancement via Feasibility-Preserving Evolutionary Optimization,” 2018 IEEE Electr. Power Energy Conf. EPEC 2018, 2018, doi: 10.1109/EPEC.2018.8598332.##[19] Y. Ma, X. Tong, X. Zhou, and Z. 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A Novel Meta-Heuristic Optimization Algorithm to Determine Optimal Access Point and Generation of Distributed Generators for Maximizing Economic and Technical Benefits 2 2 This paper presents an intelligent meta-heuristic algorithm, named improved equilibrium optimizer (IEO), for addressing the optimization problem of multi-objective simultaneous integration of distributed generators at unity and optimal power factor in a distribution system. The main objective of this research is to consider the multi-objective function for minimizing total power loss, improving voltage deviation, and reducing integrated system operating costs with strict technical constraints. An improved equilibrium optimizer is an enhanced version of the equilibrium optimizer that can provide better performance, stability, and convergence characteristics than the original algorithm. For evaluating the effectiveness of the suggested method, the IEEE 69-bus radial distribution system is chosen as a test system, and simulation results from this method are also compared fairly with many previously existing methods for the same targets and constraints. Thanks to its ability to intelligently expand the search space and avoid local traps, the suggested method has become a robust stochastic optimization method in tackling complex optimization tasks. 106 116 2022/12/082023/12/152024/01/202024/03/062024/03/192024/03/282024/04/162024/05/162024/06/10 1403/3/21 2024/08/222024/09/052024/09/162024/08/032024/06/272024/08/252024/08/202024/07/232024/07/23 1403/5/2 Nguyen Cong Chinh Nguyen Cong Chinh Thuyloi University, Hanoi, Vietnam Vietnam chinhnc@tlu.edu.vn Meta-heuristic algorithm Improved equilibrium optimizer Voltage deviation Total power loss Distributed generator [1] A. Boukaroura, L. Slimani, and T. 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Ravi, and K. R. Devabalaji, “Optimal allocation of DG and DSTATCOM in radial distribution system using cuckoo search optimization algorithm,” Modelling and Simulation in Engineering, vol. 12, no. 11, pp. 1-11, 2017.##[10] K. S. Ramudu, M. P. Lalitha, and P.S. Babu, “Optimal Placement of DG for Loss Reduction and Voltage Sag Mitigation in Radial Distribution Systems using ABC Algorithm,” International Journal on Electrical and Power Engineering, vol. 5, no. 1, pp. 25-30, 2014.##[11] E. A. Al-Ammar, K. Farzana, A. Waqar, M. Aamir, A. U. Haq, M. Zahid, and M. Batool, “ABC algorithm based optimal sizing and placement of DGs in distribution networks considering multiple objectives,” Ain Shams Engineering Journal, vol. 12, no. 1, pp. 697-708, 2021.##[12] A. F. A. Kadir, A. Mohamed, H. Shareef, M. C. Wanik, and A. A. 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Mithulananthan, “Optimal allocation of distributed generation using hybrid grey wolf optimizer,” IEEE Access, vol. 5, pp. 14807-14818, 2017.##[17] K. Nekooei, M. M. Farsangi, H. Nezamabadi-Pour, and K. Y. Lee, “An improved multi-objective harmony search for optimal placement of DGs in distribution systems,” IEEE Transactions on smart grid, vol. 4, no. 1, pp. 557-567, 2013.##[18] T. H. B. Huy, D. N. Vo, K. H. Truong, and T. T. Van, “Optimal Distributed Generation Placement in Radial Distribution Networks Using Enhanced Search Group Algorithm,” IEEE Access, vol. 11, pp. 103288- 103305,2023.##[19] V. R. Pandi, H. H. Zeineldin, and W. Xiao, “Determining optimal location and size of distributed generation resources considering harmonic and protection coordination limits,” IEEE transactions on power systems, vol. 28, no. 2, pp. 1245-1254, 2012.##[20] Z. Wang, B. Chen, J. Wang, J. Kim, and M. M. 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Alilou, “Technical-economic management of smart home energy system in the presence of stochastic and seasonal behavior of PV and EV,” Journal of Energy Management and Technology, vol. 6, no. 4, pp. 270-281, 2022.##[25] A. Faramarzi, M. Heidarinejad, B. Stephens, and S. Mirjalili, “Equilibrium optimizer: A novel optimization algorithm," Knowledge-based systems, vol. 191, pp. 105190, 2019.##[26] T. D. Pham, T. T. Nguyen and L. C. Kien, “Optimal Placement of Photovoltaic Distributed Generation Units in Radial Unbalanced Distribution Systems Using MATLAB and OpenDSS‐Based Cosimulation and a Proposed Metaheuristic Algorithm”, International Transactions on Electrical Energy Systems, vol. 2022, pp. 1-21, 2022.##[27] R. S. Rao, K. Ravindra, K. Satish, and S. V. L. Narasimham, “Power loss minimization in distribution system using network reconfiguration in the presence of distributed generation,” IEEE transactions on power systems, vol. 28, no. 1, pp. 317-325, 2012.##[28] S. K. Injeti, and N. 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Design and implementation of Mobile Robot for Fire Fighting Using Photovoltaic Panel with Artificial Intelligent 2 2 Fire accidents are a disaster that can cause loss of life, property damage and permanent disability to the affected victim. Firefighting is a very important and dangerous job. Firefighters must extinguish the fire quickly and safely to prevent further damage and destruction. Detecting and extinguishing fires is a dangerous task that always puts the lives of firefighters at risk. One of the most effective tools for early fire extinguishing is the firefighting robot. Fire sensing in most industries is absolutely essential to prevent catastrophic losses. Robots with this type of embedded system can save the lives of engineers in industrial sites with hazardous conditions. This project aims to design and implement a solar-powered  with artificial intelligent of mobile fire detection robot to detect fires in disaster-prone areas and thus reduce human work effort and level of destruction. Design a robot capable of moving using a rotary motor, finding a flame using a flame sensor, and extinguishing a fire using a water spray using a pump, all of which is controlled by an Arduino Uno microcontroller and programmed using an artificial intelligence (fuzzy) logic technology) using MATLAB, the inputs It has two variations:: flame and gas with three organic functions, each of which has a gas variable (low, medium, high), flame sensor (small, normal, large), and the output is a pump, (pump off , pump on ) with 9 rules. In addition to the experimental setup of the proposed system which demonstrates the performance of sensors (gas, flame) using fuzzy and implemented logic tools. The performance of the solar panels was first tested using MATLAB software as well as experimentally under different weather conditions. The pump's performance is being tested experimentally, and the robot is also being tested to detect and extinguish fires. The process of designing and implementing robotics involves creating mechanical and electrical systems. The results showed the effect of temperature change on the solar panel, as when it increases, the panel’s production capacity decreases, as well as the effect of decreased solar radiation resulting from clouds and other things, and the extent of its effect. Impact on the performance efficiency of solar panels, and observing the pump performance in terms of flow rate and height. Hence, it can be noted that the robot designed in the project is capable of discovering fire sources and extinguishing them using fire-fighting systems equipped with a water tank and a controllable pump to spray the water necessary for the process. From this study, can be concluded that the designed model is able to work according to its initial design  with artificial intelligence  with the least amount of errors, and therefore it can be applied in industrial applications, avoiding fire damage and extinguishing it when it occurs for the first time. 117 126 2022/12/082023/12/152024/01/202024/03/062024/03/192024/03/282024/04/162024/05/162024/06/102024/06/18 1403/3/29 2024/08/222024/09/052024/09/162024/08/032024/06/272024/08/252024/08/202024/07/232024/07/232024/07/23 1403/5/2 Raheel Jawad Raheel Jawad University of Technology ,Baghdad , Iraq Iraq eme.51262@uotechnology.edu.iq Rawaa Jawad Rawaa Jawad Department of mechanical engineering , University of Technology ,Baghdad , Iraq Iraq rawaa.j.abdulkadhim@uotechnology.edu.iq Robot Solar Cell Fire Detection Flame Sensor Fuzzy Logic [1] A.H. Bagdadee, N. Uddin, Al-Amin, A. Rahaman, Sh. Islam, R. Ahammed, S.M. M.Rahman khan, A Novel Method for Solar Power-Based Fire-Fighting Robot International Journal of Electrical and Electronics Engineering ISSN: 2348-8379/ https://doi.org/10.14445/23488379/IJEEE-V11I3P110 Original Article Volume 11 Issue 3, 136-147, March 2024 .https://doi.org/10.14445/23488379/IJEEE ##[2] K. Kartik. Prototype Development of Fire Fighting Robot. 10.13140/RG.2.2.36424.1408.,2020.##[3] M. Victoria, N. Haegel, I. M. Peters, R. Sinton, A.Waldau, C. Cañizo, Ch. Breyer, M. Stocks, A. Blakers, I. Kaizuka, K. Komoto, A. Smets,Solar photovoltaics is ready to power a sustainable future, Joule Volume 5, Issue 2021. https://doi.org/10.1016/j.joule.2021.03.005.##[4] B.Muhammad ,Sh.Muhammad ,A.Surajo, ,Y. Dele , M.Abdulmuhaimin. Robots for Fighting Fires: A Comparative Analysis. 3. 57-61. 10.5281/zenodo.10384140, 2023.##[5] A. Eswaran, Fellow , A. Vijay, S. Karthick , C. Sheik Mohammed , M. VimalGnanamani College of Technology Solar Powered Automatic Fire Fighting Robot International Journal of Engineering Research & Technology (IJERT) ETEDM - 2018 Conference Proceedings Volume 6, Issue 04 ,2018.##[6] B. Sarwar, I. Sarwar Bajwa, Sh. Ramzan, B. Ramzan and M. Kausar , Design and Application of Fuzzy Logic Based Fire Monitoring andWarning Systems for Smart Buildings , 9 November 2018.##[7] J. NavyaSree, N. Ganesh, S. Chandrasekhar, V. Chandrika, P. Sairupa, S. Suma Latha, Fire Fighter Robot Using Renewable Energy ENERGY International Research Journal of Modernization in Engineering Technology and Science ( Peer-Reviewed, Open Access, Fully Refereed International Journal ) Volume:05/Issue:04/April-2023.##[8] D. Yogi Goswami ,”Principles of Solar Engineering”. 3rd Edition, CRC Press, February 20, 2015.##[9] H.Bevrani, A.Ghosh, G.Ledwich,: ‘Renewable energy sources and frequency regulation: survey and new perspectives’, IET Rnew.PowerGener., 2010.##[10] https://energyinformative.org/solar-cell-comparison-chart-mono-polycrystalline-thin-film##[11] A. Maksumic, V. Becirovic, S. Hanjalic, H. Samic and S. Maksumic, "Techno-economic analysis of different types of photovoltaic power plants," IEEE. 2018 17th International Symposium INFOTEH-JAHORINA (INFOTEH), East Sarajevo, Bosnia and Herzegovina, 2018, pp. 1-6, doi: 10.1109/INFOTEH.2018.8345517.##[12] Dunlop, James P" Photovoltaic power systems" , Industries Orland Park, Ill. : American Technical Publishers, Inc.2010##[13] AbouJieb, E. Hossain "Photovoltaic Systems" Springer ChamNature Switzerland AG 2022eBook ISBN978-3-030-89780-2Published: 07 December 2021 https://doi.org/10.1007/978-3-030-89780-2##[14] Lazaroiu, A.C.; G. Osman, M.; Strejoiu, C.-V.; Lazaroiu, G. A Comprehensive Overview of Photovoltaic Technologies and Their Efficiency for Climate Neutrality. Sustainability 2023, 15, 16297. https://doi.org/10.3390/su152316297.##[15] R.Jawad,A.Yasser, Ali "Types of coolingtechnique of PV panel" ,lAP LAMBERT Academic Publishing 2019/7/29##[16] J. C. Teo,etal.,"Impact of Partial Shading on the P-V Characteristics and the Maximum Power of a Photovoltaic String," MDPI Energies, Vol. 11, 2018.##[17] A. A. Elbaset and, M.S. Hassan, "Design and Power Quality Improvement of Photovoltaic Power System,"Springer, International Publishing AG, Switzerland, 2017.##[18] R. Malik, “Fire Fighting Robot : An Approach”, Indian Streams Research Journal Vol.2, Issue.II/March; 12pp.1-4 ##[19] K.Kosasih, E. Merry Sartika, M. Jimmy Hasugian, danMuliady, “The Intelligent Fire Fighting Tank Robot”, Electrical Engineering Journal Vol. 1, No. 1, October 2010 ##[20] H. P. Singh, AkanshuMahajan, N. Sukavanam, VeenaBudhraja, ”Control Of An Autonomous Industrial Fire Fighting Mobile Robot”, DU Journal of Undergraduate Research and Innovation##[21] H. Xu, H. Chen, C. Cai, X. Guo, J. Fang and Z. Sun, "Design and Implementation of Mobile Robot Remote Fire Alarm System," 2011 International Conference on Intelligence Science and Information Engineering, Wuhan, China, 2011, pp. 32-36, doi: 10.1109/ISIE.2011.46.##[22] M. Kanwar and L. Agilandeeswari, "IOT Based Fire Fighting Robot," 2018 7th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO), Noida, India, 2018, pp. 718-723, doi: 10.1109/ICRITO.2018.8748619.##[23] YongjunXu, Xin Liu, et.al, Artificial intelligence: A powerful paradigm for scientific research, The Innovation, Volume 2, Issue 4, 2021, https://doi.org/10.1016/j.xinn.2021.100179.##[24] Eyad I. Abbas Dr. Sundus D. HasanRawaaJawad "PATH FINDING BASED ON ARTIFICIAL INTELLIGENCE TECHNIQUES: A REVIEW "International Journal of Engineering Applied Sciences and Technology (IJEAST), 2020 Vol. 5, Issue 4, ISSN No. 2455-2143, Pages 91-100 August 2020.##[25] N. Kumar, M. Takács, and Z. Vámossy, " Robot navigation in unknown environment using fuzzy logic " IEEE 15th International Symposium on Applied Machine Intelligence and Informatics (SAMI), 2017.##[26] Wang Y, Yu C, Tu R, Zhang Y. Fire detection model in Tibet based on grey-fuzzy neural network algorithm. Expert Systems with Applications. 2011; 38(8):9580-6.##[27] Přibyl P, Přibyl O. Calibration of a fuzzy model estimating fire response time in a tunnel. Tunnelling and Underground Space Technology. 2017; 69:28-36.##[28] Kumar K, Sen N, Azid S, Mehta U. A fuzzy decision in smart fire and home security system. Procedia Computer Science. 2017; 105:93-8.##[29] Ross TJ. Fuzzy logic with engineering applications. New York: Wiley; 2004.## ##

BiliBin: An Intelligent Mobile Phone-based Platform to Monitor Newborn Jaundice 2 2 Using mobile phones for medical applications are proliferating due to high-quality embedded sensors. Jaundice, a yellow discoloration of the skin caused by excess bilirubin, is a prevalent physiological problem in newborns. While moderate amounts of bilirubin are safe in healthy newborns, extreme levels are fatal and cause devastating and irreversible brain damage. Accurate tests to measure jaundice require a blood draw or dedicated clinical devices facing difficulty where clinical technology is unavailable. This paper presents a smartphone-based screening tool to detect neonatal hyperbilirubinemia caused by the high bilirubin production rate. A machine learning regression model is trained on a pretty large dataset of images, including 446 samples, taken from newborns' sternum skin in four medical centers in Iran. The learned model is then used to estimate the level of bilirubin. Experimental results show a mean absolute error of 1.807 mg/dl and a correlation of 0.701 between predicted bilirubin by the proposed method and the TSB values as ground truth. 127 140 2022/12/082023/12/152024/01/202024/03/062024/03/192024/03/282024/04/162024/05/162024/06/102024/06/182024/07/21 1403/4/31 2024/08/222024/09/052024/09/162024/08/032024/06/272024/08/252024/08/202024/07/232024/07/232024/07/232024/07/31 1403/5/10 Eisa Zarepour Eisa Zarepour Assistant Professor in the School of Computer Engineering at Iran University of Science and Technology Iran zarepour@iust.ac.ir Mohammad Reza Mohammadi Mohammad Reza Mohammadi Assistant Professor in the School of Computer Engineering at Iran University of Science and Technology. Iran mrmohammadi@iust.ac.ir Morteza Zakeri-Nasrabadi Morteza Zakeri-Nasrabadi Ph.D. graduate from the School of Computer Engineering at Iran University of Science and Technology Iran zakeri@comp.iust.ac.ir Sara Aein Sara Aein M.Sc. graduate from the School of Computer Engineering at Iran University of Science and Technology. Iran aeinsara@yahoo.com Razieh Sangsari Razieh Sangsari Children Medical Center, Tehran University of Medical Sciences. And also, associate Professor in the School of Medicine at Tehran University of Medical Sciences Iran raz3532@yahoo.com Leila Taheri Leila Taheri Children Medical Center, Tehran University of Medical Sciences. And also, faculty member of Nursing and Midwifery College at Qom University of Medical Sciences. Iran taheri.leila@ymail.com Mojtaba Akbari Mojtaba Akbari Children Medical Center, Tehran University of Medical Sciences. 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Grover, “Predicting neonatal hyperbilirubinemia using first day serum bilirubin levels,” The Indian Journal of Pediatrics, vol. 77, no. 2, pp. 147–150, Feb. 2010, doi: 10.1007/s12098-009-0335-3.##[5] F. Ebbesen, L. Rasmussen, and P. Wimberley, “A new transcutaneous bilirubinometer, BiliCheck, used in the neonatal intensive care unit and the maternity ward,” Acta Paediatr, vol. 91, no. 2, pp. 203–211, Jan. 2007, doi: 10.1111/j.1651-2227.2002.tb01696.x.##[6] G. Nagar, B. Vandermeer, S. Campbell, and M. Kumar, “Reliability of transcutaneous bilirubin devices in preterm infants: a systematic review,” Pediatrics, vol. 132, no. 5, pp. 871–881, Nov. 2013, doi: 10.1542/peds.2013-1713.##[7] N. C. C. for W. and C. H. (UK), “Neonatal jaundice,” RCOG Press. Accessed: Oct. 15, 2020. [Online]. Available: https://www.ncbi.nlm.nih.gov/books/NBK65113/##[8] M. J. Maisels, V. K. Bhutani, D. Bogen, T. B. Newman, A. R. Stark, and J. F. 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Wideband Electromagnetic Shielding Using Wire-mesh-mounted Chiral Particle Array in Concrete Composite Materials 2 2 This paper proposes a structure for concrete composite materials that effectively attenuates transmitted power through the composite slab across a wide frequency range. The proposed structure is practical for electromagnetic interference shielding applications. To assess its effectiveness, the proposed structure has been compared with two other structures: a traditional wire mesh used in reinforced composites and an array of helices, a cutting-edge technique for manufacturing lightweight concretes with significant improvements in shielding properties. The comparison among full-wave simulation results indicates that the proposed method leverages the benefits of both techniques. It achieves a shielding effectiveness exceeding 30 dB from low frequencies up to 8.5 GHz and beyond 55 dB from low frequencies up to 4 GHz. Furthermore, an experimental measurement was conducted to validate the full-wave simulation results. An experimental sample was fabricated according to the simulated proposed structure, and the measured shielding effectiveness confirmed the composite's capability in wideband electromagnetic shielding. Theoretically, the proposed structure can enhance the concrete's mechanical characteristics while improving its shielding effectiveness, making it suitable for designing ultra-high-performance concretes. 141 154 2022/12/082023/12/152024/01/202024/03/062024/03/192024/03/282024/04/162024/05/162024/06/102024/06/182024/07/212024/08/09 1403/5/19 2024/08/222024/09/052024/09/162024/08/032024/06/272024/08/252024/08/202024/07/232024/07/232024/07/232024/07/312024/08/26 1403/6/5 Ayoub Hamidi Ayoub Hamidi School of Electrical Engineering, Iran University of Science and Technology, Tehran 13114-16846, Iran Iran ayoub_hamidi@cmps2.iust.ac.ir Ahmad Cheldavi Ahmad Cheldavi School of Electrical Engineering, Iran University of Science and Technology, Tehran 13114-16846, Iran Iran cheldavi@iust.ac.ir Asghar Habibnejad Korayem Asghar Habibnejad Korayem School of Civil Engineering, Iran University of Science and Technology, Tehran 13114-16846, Iran Department of Civil Engineering, Monash University, Melbourne, VIC, 3800, Australia Iran ahkorayem@iust.ac.ir Composite materials Electromagnetic interference shielding Helical additives Planar arrays Wideband shielding Wire mesh [1] M. 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