Abstract

Electric vehicles (EVs) are a specific class of vehicles that use one or more electric motors to create propulsion. Numerous recent research studies have focused on energy storage systems (ESS) as a major research area. However, as EV usage grows, there are several challenges related to the electricity required for charging that result in peak demand of smart grids with EV stations. The probable impacts of integrating EVs and photovoltaic (PV) into the grid, on certain individuals, are the subjects of numerous researches. The main motivation for PV’s incorporation in grid-to-vehicle (G2V) and vehicle-to-grid (V2G) services is to provide supplementary power services to preserve the grid stability. PV arrays have to meet one more need before they choose to offer V2G services. Controlling the power between different load and source conditions requires a number of analyses. Therefore, a hybrid intuitive model was developed that implements a honey badger algorithm and artificial neural network (HBA-ANN) controller to balance grids and frequency. With the inclusion of PV generation, the proposed HBA-ANN optimizes the G2V or V2G outline of the EVs using dynamic programming. The result analysis clearly shows that the proposed HBA-ANN controller's overall efficacy surpasses that of existing controllers based on artificial neural network-based particle swarm optimization (ANN-PSO) and resettable integrator (RI). The evaluation, conducted in terms of overall harmonic distortion, power loss, and efficiency, demonstrates that the proposed HBA-ANN controller achieves 3.26%, 0.186 kW, and 97.14%, respectively.

Keyword

Artificial neural network, Electric vehicle, Energy storage system, Honey badger algorithm, Photovoltaic, Smart grid.

Cite this article

Asundi AK, Shaik AL, Mohiuddin S, NaseeruddinKalburgi FB.Electric vehicle with smart grid integration using a hybrid honey badger algorithm and artificial neural network. International Journal of Advanced Technology and Engineering Exploration. 2024;11(116):979-991. DOI:10.19101/IJATEE.2023.10102555

Refference

[1]Lutsenko I, Fedoriachenko S, Beshta OO, Vesela M, Koshelenko I. Estimation of the potential impact of electric vehicles on the distribution network’s operation modes. Mechanics, Materials Science & Engineering. 2017.

[2]Jain F, Bhullar S. Operating modes of grid integrated PV-solar based electric vehicle charging system-a comprehensive review. E-Prime-Advances in Electrical Engineering, Electronics and Energy. 2024:100519.

[3]Kumari A, Trivedi M, Tanwar S, Sharma G, Sharma R. SV2G-ET: a secure vehicle‐to‐grid energy trading scheme using deep reinforcement learning. International Transactions on Electrical Energy Systems. 2022; 2022(1):9761157.

[4]Ahmadi SE, Kazemi-razi SM, Marzband M, Ikpehai A, Abusorrah A. Multi-objective stochastic techno-economic-environmental optimization of distribution networks with G2V and V2G systems. Electric Power Systems Research. 2023; 218:109195.

[5]Kumar BA, Jyothi B, Singh AR, Bajaj M, Rathore RS, Berhanu M. A novel strategy towards efficient and reliable electric vehicle charging for the realisation of a true sustainable transportation landscape. Scientific Reports. 2024; 14(1):3261.

[6]Anjaiah K, Dash PK, Bisoi R, Dhar S, Mishra SP. A new approach for active and reactive power management in renewable based hybrid microgrid considering storage devices. Applied Energy. 2024; 367:123429.

[7]Spanoudakis NI, Akasiadis C, Iatrakis G, Chalkiadakis G. Engineering IoT-based open MAS for large-scale V2G/G2V. Systems. 2023; 11(3):1-28.

[8]Sun Q, Xie H, Liu X, Niu F, Gan C. Multiport PV-assisted electric-drive-reconstructed bidirectional charger with G2V and V2G/V2L functions for SRM drive-based EV application. IEEE Journal of Emerging and Selected Topics in Power Electronics. 2023; 11(3):3398-408.

[9]Zheng Y, Xue X, Xi S, Xin W. Enhancing microgrid sustainability: dynamic management of renewable resources and plug-in hybrid electric vehicles. Journal of Cleaner Production. 2024; 450:141691.

[10]Shaheen HI, Rashed GI, Yang B, Yang J. Optimal electric vehicle charging and discharging scheduling using metaheuristic algorithms: V2G approach for cost reduction and grid support. Journal of Energy Storage. 2024; 90:111816.

[11]Visakh A, Selvan MP. Feasibility assessment of utilizing electric vehicles for energy arbitrage in smart grids considering battery degradation cost. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects. 2022; 44(2):4664-78.

[12]Shakeel FM, Malik OP. Vehicle-to-grid technology in a micro-grid using DC fast charging architecture. In Canadian conference of electrical and computer engineering 2019 (pp. 1-4). IEEE.

[13]Makeen P, Ghali HA, Memon S, Duan F. Insightful electric vehicle utility grid aggregator methodology based on the G2V and V2G technologies in Egypt. Sustainability. 2023; 15(2):1-14.

[14]Ur RU. A robust vehicle to grid aggregation framework for electric vehicles charging cost minimization and for smart grid regulation. International Journal of Electrical Power & Energy Systems. 2022; 140:108090.

[15]İnci M, Savrun MM, Çelik Ö. Integrating electric vehicles as virtual power plants: a comprehensive review on vehicle-to-grid (V2G) concepts, interface topologies, marketing and future prospects. Journal of Energy Storage. 2022; 55:105579.

[16]Shakeel FM, Malik OP. ANFIS based energy management system for V2G integrated micro-grids. Electric Power Components and Systems. 2022; 50(11-12):584-99.

[17]Singirikonda S, Obulesu YP, Kannan R, Reddy KJ, Kumar GK, Alhakami W, et al. Adaptive control-based isolated bi-directional converter for G2V& V2G charging with integration of the renewable energy source. Energy Reports. 2022; 8:11416-28.

[18]Abuelrub A, Hamed F, Hedel J, Al-masri HM. Feasibility study for electric vehicle usage in a microgrid integrated with renewable energy. IEEE Transactions on Transportation Electrification. 2023; 9(3):4306-15.

[19]Oad A, Ahmad HG, Talpur MS, Zhao C, Pervez A. Green smart grid predictive analysis to integrate sustainable energy of emerging V2G in smart city technologies. Optik. 2023; 272:170146.

[20]Kashiri S, Siahbalaee J, Koochaki A. Stochastic management of electric vehicles in an intelligent parking lot in the presence of hydrogen storage system and renewable resources. International Journal of Hydrogen Energy. 2024; 50:1581-97.

[21]Nouri A, Lachheb A, El AL. Optimizing efficiency of vehicle-to-grid system with intelligent management and ANN-PSO algorithm for battery electric vehicles. Electric Power Systems Research. 2024; 226:109936.

[22]Cheng H, Wang Z, Yang S, Huang J, Ge X. An integrated SRM powertrain topology for plug-in hybrid electric vehicles with multiple driving and onboard charging capabilities. IEEE Transactions on Transportation Electrification. 2020; 6(2):578-91.

[23]He T, Lu DD, Wu M, Yang Q, Li T, Liu Q. Four-quadrant operations of bidirectional chargers for electric vehicles in smart car parks: G2V, V2G, and V4G. Energies. 2020; 14(1):1-17.

[24]Kanimozhi G, Natrayan L, Angalaeswari S, Paramasivam P. An effective charger for plug‐in hybrid electric vehicles (PHEV) with an enhanced PFC rectifier and ZVS‐ZCS DC/DC high‐frequency converter. Journal of Advanced Transportation. 2022; 2022(1):7840102.

[25]Justin F, Peter G, Stonier AA, Ganji V. Power quality improvement for vehicle‐to‐grid and grid‐to‐vehicle technology in a microgrid. International Transactions on Electrical Energy Systems. 2022; 2022(1):2409188.

[26]Alsharif A, Tan CW, Ayop R, Lau KY, Mohd DA. A rule-based power management strategy for vehicle-to-grid system using antlion sizing optimization. Journal of Energy Storage. 2021; 41:102913.

[27]Heydari-doostabad H, O’donnell T. A wide-range high-voltage-gain bidirectional DC–DC converter for V2G and G2V hybrid EV charger. IEEE Transactions on Industrial Electronics. 2021; 69(5):4718-29.

[28]Gonzalez M, Asensio FJ, San MJI, Zamora I, Cortajarena JA, Oñederra O. Vehicle‐to‐grid charging control strategy aimed at minimizing harmonic disturbances. International Journal of Energy Research. 2021; 45(11):16478-88.

[29]Ramos LA, Van KRF, Mezaroba M, Batschauer AL. A control strategy to smooth power ripple of a single-stage bidirectional and isolated AC-DC converter for electric vehicles chargers. Electronics. 2022; 11(4):1-19.

[30]Elshaer M, Bell C, Hamid A, Wang J. DC–DC topology for interfacing a wireless power transfer system to an on-board conductive charger for plug-in electric vehicles. IEEE Transactions on Industry Applications. 2021; 57(6):5552-61.

[31]Nam VH, Tinh DV, Choi W. A novel hybrid LDC converter topology for the integrated on-board charger of electric vehicles. Energies. 2021; 14(12):1-18.

[32]Zinchenko D, Blinov A, Chub A, Vinnikov D, Verbytskyi I, Bayhan S. High-efficiency single-stage on-board charger for electrical vehicles. IEEE Transactions on Vehicular Technology. 2021; 70(12):12581-92.

[33]Shahir FM, Gheisarnejad M, Sadabadi MS, Khooban MH. A new off-board electrical vehicle battery charger: topology, analysis and design. Designs. 2021; 5(3):1-15.

[34]Mojumder MR, Ahmed AF, Hasanuzzaman M, Alamri B, Alsharef M. Electric vehicle-to-grid (V2G) technologies: impact on the power grid and battery. Sustainability. 2022; 14(21):1-15.

[35]Bot Y, Yousfi A, Allali A. Smart control of the bidirectional energy exchange of electric vehicles with the electrical network. International Journal of Advanced Studies in Computers, Science and Engineering. 2022; 11(12):29-35.

[36]Amir M, Zaheeruddin, Haque A, Kurukuru VB, Bakhsh FI, Ahmad A. Agent based online learning approach for power flow control of electric vehicle fast charging station integrated with smart microgrid. IET Renewable Power Generation. 2022.

[37]Gan W, Wen J, Yan M, Zhou Y, Yao W. Enhancing resilience with electric vehicles charging redispatching and vehicle-to-grid in traffic-electric networks. IEEE Transactions on Industry Applications. 2023; 60(1):953-65.

[38]Hanna B. Vehicle-to-grid and electric vehicle-integrated demand response management. In artificial intelligence applications in battery management systems and routing problems in electric vehicles 2023 (pp. 250-68). IGI Global.

[39]Manickam VK, Dhayalini K. Hybrid optimized control of bidirectional off-board electric vehicle battery charger integrated with vehicle-to-grid. Journal of Energy Storage. 2024; 86:111008.

[40]Zhou J, Wang D, Band SS, Mirzania E, Roshni T. Atmosphere air temperature forecasting using the honey badger optimization algorithm: on the warmest and coldest areas of the world. Engineering Applications of Computational Fluid Mechanics. 2023; 17(1):2174189.

[41]Sathyan S, Pandi VR, Antony A, Salkuti SR, Sreekumar P. ANN-based energy management system for PV-powered EV charging station with battery backup and vehicle to grid support. International Journal of Green Energy. 2024; 21(6):1279-94.

[42]Khan MA, Saleh AM, Waseem M, Sajjad IA. Artificial intelligence enabled demand response: prospects and challenges in smart grid environment. IEEE Access. 2022; 11:1477-505.

[43]Madichetty S, Banda MK, Banda SK. Implementation of deep learning based bi-directional DC-DC converter for V2V and V2G applications in microgrid-an experimental investigation. Energies. 2023; 16(22):7614.

[44]Hashim FA, Houssein EH, Hussain K, Mabrouk MS, Al-atabany W. Honey badger algorithm: new metaheuristic algorithm for solving optimization problems. Mathematics and Computers in Simulation. 2022; 192:84-110.

[45]Wang F, Bi S, Feng S, Zhang H. A novel honey badger algorithm with golden sinusoidal survival rate selection for solving optimal power flow problem. Electrical Engineering. 2024:1-9.

[46]Huang P, Zhou Y, Deng W, Zhao H, Luo Q, Wei Y. Orthogonal opposition-based learning honey badger algorithm with differential evolution for global optimization and engineering design problems. Alexandria Engineering Journal. 2024; 91:348-67.

[47]Diab AA, Tolba MA, El-rifaie AM, Denis KA. Photovoltaic parameter estimation using honey badger algorithm and African vulture optimization algorithm. Energy Reports. 2022; 8:384-93.