References
- G. Michailidis, M. Devetsikiotis, F. Granelli et al., “Electric power allocation in a network of fast charging stations,” Selected Areas in Communications, IEEE Journal on, vol. 31, no. 7, pp. 1235–1246, 2013.
- I. S. Bayram, G. Michailidis, and M. Devetsikiotis, “Unsplittable load balancing in a network of charging stations under qos guarantees,” Smart Grid, IEEE Transactions on, vol. 6, no. 3, pp. 1292–1302, 2015.
- C. Rottondi, G. Neglia, and G. Verticale, “On the complexity of optimal electric vehicles recharge scheduling,” in IEEE GreenComm 2014.
- E. Biondi, C. Boldrini and R. Bruno, “Optimal charging of electric vehicle fleets for a car sharing system with power sharing,” 2016 IEEE International Energy Conference (ENERGYCON), 2016, pp. 1-6, doi: 10.1109/ENERGYCON. 2016.7514070.
- Y. Tao, M. Huang, Y. Chen, and L. Yang, “Orderly charging strategy of battery electric vehicle driven by real-world driving data,” Energy, vol. 193, Feb. 2020, Art. no. 116806, doi: 10.1016/j.energy.2019.116806.
- K. Chaudhari, A. Ukil, K. N. Kumar, U. Manandhar, and S. K. Kollimalla, “Hybrid optimization for economic deployment of ESS in PV-integrated EV charging stations,” IEEE Trans. Ind. Informat., vol. 14, no. 1, pp. 106–116, Jan. 2018, doi: 10.1109/ TII.2017.2713481.
- S. Golshannavaz, “Cooperation of electric vehicle and energy storage in reactive power compensation: An optimal home energy management system considering PV presence,” Sustain. Cities Soc., vol. 39, pp. 317–325, May 2018, doi: 10.1016/j. scs.2018.02.018.
- J.-H. Ahn and B. K. Lee, “High-efficiency adaptive-current charging strategy for electric vehicles considering variation of internal resistance of lithiumion battery,” IEEE Trans. Power Electron., vol. 34, no. 4, pp. 3041–3052, Apr. 2019, doi: 10.1109/ TPEL.2018.2848550.
- S. U. Jeon, J.-W. Park, B.-K. Kang, and H.-J. Lee, “Study on battery charging strategy of electric vehicles considering battery capacity,” IEEE Access, vol. 9, pp. 89757–89767, 2021, doi: 10.1109/ ACCESS.2021.3090763.
- W. Tushar, C. Yuen, S. Huang, D. B. Smith, and H. V. Poor, “Cost minimization of charging stations with photovoltaics: An approach with EV classification,” IEEE Trans. Intell. Transp. Syst., vol. 17, no. 1, pp. 156– 169, Jan. 2016, doi: 10.1109/TITS.2015.2462824.
- S. Limmer and T. Rodemann, “Peak load reduction through dynamic pricing for electric vehicle charging,” Int. J. Electr. Power Energy Syst., vol. 113, pp. 117– 128, Dec. 2019, doi: 10.1016/j.ijepes.2019.05.031.
- A. Mehrabi, H. S. V. S. K. Nunna, A. Dadlani, S. Moon, and K. Kim, “Decentralized greedy-based algorithm for smart energy management in plug-in electric vehicle energy distribution systems,” IEEE Access, vol. 8, pp. 75666–75681, 2020, doi: 10.1109/ACCESS.2020.2987970.
- A. Mehrabi, M. Siekkinen, A. Yla-Jaaski, and G. Aggarwal, “Mobile edge computing assisted green scheduling of on-move electric vehicles,” IEEE Syst. J., vol. 16, no. 1, pp. 1661–1672, Mar. 2022, doi: 10.1109/JSYST.2021.3084746.
- A. Y. S. Lam, J. J. Q. Yu, Y. Hou, and V. O. K. Li, “Coordinated autonomous vehicle parking for vehicle-to-grid services: Formulation and distributed algorithm,” IEEE Trans. Smart Grid, vol. 9, no. 5, pp. 4356–4366, Sep. 2018, doi: 10.1109/ TSG.2017.2655299.
- A. Bilh, K. Naik, and R. El-Shatshat, “A novel online charging algorithm for electric vehicles under stochastic net-load,” IEEE Trans. Smart Grid, vol. 9, no. 3, pp. 1787–1799, May 2018, doi: 10.1109/ TSG.2016.2599819.
- C. Crozier, T. Morstyn, and M. McCulloch, “The opportunity for smart charging to mitigate the impact of electric vehicles on transmission and distribution systems,” Appl. Energy, vol. 268, Jun. 2020, Art. no. 114973, doi: 10.1016/j.apenergy.2020.114973.
- J. Quirós-Tortós, L. F. Ochoa, S. W. Alnaser, and T. Butler, “Control of EV charging points for thermal and voltage management of LV networks,” IEEE Trans. Power Syst., vol. 31, no. 4, pp. 3028–3039, Jul. 2016, doi: 10.1109/TPWRS. 2015.2468062.
- H. Suyono, M. T. Rahman, H. Mokhlis, M. Othman, H. A. Illias, and H. Mohamad, “ Optimal Scheduling of Plug-in Electric Vehicle Charging Including Time-of-Use Tariff to Minimize Cost and System Stress,” Energies, vol. 12, no. 8, pp. 17–21, 2019, doi: 10.3390/en12081500.
- V. Torres-Sanz, J. A. Sanguesa, F. J. Martinez, P. Garrido, and J. M. Marquez-Barja, “Enhancing the charging process of electric vehicles at residential homes,” IEEE Access, vol. 6, pp. 22875–22888, 2018, doi: 10.1109/ACCESS. 2018.2829158.
- A. Y. S. Lam, J. J. Q. Yu, Y. Hou, and V. O. K. Li, “Coordinated autonomous vehicle parking for vehicle-to-grid services,” in Proc. IEEE Int. Conf. Smart Grid Commun. (SmartGridComm), Sydney, NSW, Australia, Nov. 2016, pp. 6–9, doi: 10.1109/ SmartGridComm.2016.7778775.
- M. Zare Oskouei, B. Mohammadi-Ivatloo, M. Abapour, A. Anvari-Moghaddam, and H. Mehrjerdi, “Practical implementation of residential load management system by considering vehicle-for-power transfer: Profit analysis,” Sustain. Cities Soc., vol. 60, Sep. 2020, Art. no. 102144, doi: 10.1016/j. scs.2020.102144.
- M. Jawad, M. B. Qureshi, S. M. Ali, N. Shabbir, M. U. S. Khan, A. Aloraini, and R. Nawaz, “A cost-effective electric vehicle intelligent charge scheduling method for commercial smart parking lots using a simplified convex relaxation technique,” Sensors, vol. 20, no. 17, pp. 1–19, Aug. 2020, doi: 10.3390/s20174842.
- Zhong, Shuwei & Che, Yanbo & Zhang, Shangyuan. (2023). Electric Vehicle Charging Load Optimization Strategy Based on Dynamic Time-of-Use Tariff. 10.21203/rs.3.rs-2916080/v1.
- Balakumar Palaniyappan, Senthil Kumar R, Vinopraba T, Dynamic pricing for load shifting: Reducing electric vehicle charging impacts on the grid through machine learning-based demand response, Sustainable Cities and Society, Volume 103, 2024, 105256, ISSN 2210-6707, https://doi.org/10.1016/j.scs.2024.105256.
- E. Dokur, N. Erdogan and S. Kucuksari, “EV Fleet Charging Load Forecasting Based on Multiple Decomposition With CEEMDAN and Swarm Decomposition,” in IEEE Access, vol. 10, pp. 62330-62340, 2022, doi: 10.1109/ACCESS.2022.3182499.
- Zafeirios N. Bampos, Vasilis M. Laitsos, Konstantinos D. Afentoulis, Stylianos I. Vagropoulos, Pantelis N. Biskas, Electric vehicles load forecasting for day-ahead market participation using machine and deep learning methods, Applied Energy, Volume 360, 2024, 122801, ISSN 0306-2619, https://doi.org/10.1016/j.apenergy.2024.122801.
- Xiaodong Shen, Houxiang Zhao, Yue Xiang, Peng Lan, Junyong Liu, Short-term electric vehicles charging load forecasting based on deep learning in low-quality data environments, Electric Power Systems Research, Volume 212, 2022, 108247, ISSN 0378-7796, https://doi.org/10.1016/j.epsr.2022.108247.
- Hui Hwang Goh, Lian Zong, Dongdong Zhang, Hui Liu, Wei Dai, Chee Shen Lim, Tonni Agustiono Kurniawan, Kenneth Tze Kin Teo, Kai Chen Goh, Mid- and long-term strategy based on electric vehicle charging unpredictability and ownership estimation, International Journal of Electrical Power & Energy Systems, Volume 142, Part A, 2022, 108240, ISSN 0142-0615, https://doi.org/10.1016/j.ijepes.2022.108240.
- Regulatory Commission for Energy in the Federation of Bosnia and Herzegovina (FERK) (2023) General Conditions for the Delivery of Electricity, Article 11, Paragraph 2. Available at: https://www.ferk.ba/_ba/images/stories/2023/opci_uvjeti_precisceni_tekst_ bs.pdf (Accessed: October 2023).
- National Grid (2023) ‘Voltage reduction analysis’, available at: https://www.nationalgrid.co.uk/innovation/projects/voltage-reduction-analysis (Accessed: October 2023).
- Elektroprivreda BiH (2023) ‘Tarifni stavovi’, available at: https://www.epbih.ba/stranica/tarifni-stavovi#javnosnadbijevanje (Accessed: October 2023).
- Energy Stats UK (2023) ‘Download historical pricing data’, available at: https://energy-stats.uk/download-historical-pricing-data/ (Accessed: October 2023).