Abstract
Plug-in electric vehicle (PEV) has experienced major transformations since the last few decades. The success of smart electric grid with the addition of renewable energy solely depends on the extensive diffusion of PEV for a carbon-free and sustainable transport sector. Current technical studies concerning numerous optimization methods connected to PEV-integrated smart electric grid such as battery charging and control , unit commitment, vehicle-to-grid (V2G), solar and wind energy integration along with demand-side management have proved that vehicle electrification is a fast developing arena of research. Charging optimization of PEV is an emerging field which is gradually being implemented in many charging infrastructures at a global scale. A near-comprehensive understanding of smart charging capability is crucial for large participation of PEV. Only proper charging can ensure PEV users to be free from ‘range anxiety’ and switch into the new revolution of green vehicle with less CO2 emissions. This chapter discusses on the aspects of bio-inspired computational intelligence (CI)-based optimizations for efficient charging of PEVs. A holistic assessment of significant research works using bio-inspired CI techniques for PEV charging is presented. A summary of future optimization techniques is also discussed, covering cuckoo search (CS), artificial fish swarm algorithm (AFSA), artificial bee colony (ABC), etc., with broad reviews on previous applied techniques and their overall performances for solving various practical problems in the domain of PEV charging. Furthermore, noteworthy shifts in the direction of hybrid and multi-objective CI techniques are also highlighted in this chapter.
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References
I. Rahman, P.M. Vasant, B.S.M. Singh, M. Abdullah-Al-Wadud, Intelligent energy allocation strategy for PHEV charging station using gravitational search algorithm, in AIP Conference Proceedings (2014), pp. 52–59
N. Adnan, S.M. Nordin, I. Rahman, Adoption of PHEV/EV in Malaysia: a critical review on predicting consumer behaviour. Renew. Sustain. Energy Rev. 72, 849–862 (2017)
N. Adnan, S.M. Nordin, I. Rahman, P.M. Vasant, A. Noor, A comprehensive review on theoretical framework‐based electric vehicle consumer adoption research. Int. J. Energy Res. (2016)
Q. Wang, X. Liu, J. Du, F. Kong, Smart charging for electric vehicles: a survey from the algorithmic perspective. IEEE Commun. Surv Tutorials 18, 1500–1517 (2016)
M.H. Amini, M.P. Moghaddam, O. Karabasoglu, Simultaneous allocation of electric vehicles’ parking lots and distributed renewable resources in smart power distribution networks. Sustain. Cities Soc. 28, 332–342 (2017)
H. Shareef, M.M. Islam, A. Mohamed, A review of the stage-of-the-art charging technologies, placement methodologies, and impacts of electric vehicles. Renew. Sustain. Energy Rev. 64, 403–420 (2016)
J. Hu, H. Morais, T. Sousa, M. Lind, Electric vehicle fleet management in smart grids: a review of services, optimization and control aspects. Renew. Sustain. Energy Rev. 56, 1207–1226 (2016)
Z. Yang, K. Li, A. Foley, Computational scheduling methods for integrating plug-in electric vehicles with power systems: a review. Renew. Sustain. Energy Rev. 51, 396–416 (2015)
E.S. Rigas, S.D. Ramchurn, N. Bassiliades, Managing electric vehicles in the smart grid using artificial intelligence: a survey. IEEE Trans. Intell. Trans. Syst. 16, 1619–1635 (2015)
A. Foley, I. Winning, B.Ó. Gallachóir, State-of-the-art in electric vehicle charging infrastructure, in 2010 Vehicle Power and Propulsion Conference (VPPC) (IEEE, 2010), pp. 1–6
F. Mwasilu, J.J. Justo, E.-K. Kim, T.D. Do, J.-W. Jung, Electric vehicles and smart grid interaction: a review on vehicle to grid and renewable energy sources integration. Renew. Sustain. Energy Rev. 34(6), 501–516 (2014)
P. Kulshrestha, L. Wang, M.-Y. Chow, S. Lukic, Intelligent energy management system simulator for PHEVs at municipal parking deck in a smart grid environment, in 2009 Power and Energy Society General Meeting, PES’09. (IEEE, 2009), pp. 1–6
C. Pang, P. Dutta, S. Kim, M. Kezunovic, I. Damnjanovic, PHEVs as dynamically configurable dispersed energy storage for V2B uses in the smart grid, in IET Conference Proceedings (2010), pp. 174–174, http://digital-library.theiet.org/content/conferences/10.1049/cp.2010.0903
L. Herrera, R. Murawski, F. Guo, E. Inoa, E. Ekici, and J. Wang, PHEVs charging stations, communications, and control simulation in real time, in Vehicle Power and Propulsion Conference (VPPC) (IEEE, 2011), pp. 1–5
E. Inoa, F. Guo, J. Wang, W. Choi, A full study of a PHEV charging facility based on global optimization and real-time simulation, in 2011 IEEE 8th International Conference on Power Electronics and ECCE Asia (ICPE & ECCE) (2011), pp. 565–570
Z. Ren, H. Jiang, J. Xuan, Z. Luo, Hyper-heuristics with low level parameter adaptation. Evol. Comput. 20, 189–227 (2012)
P. Tulpule, V. Marano, G. Rizzoni, Effects of different PHEV control strategies on vehicle performance, in 2009 American Control Conference, ACC’09 (2009), pp. 3950–3955
N.H. Tehrani, G. Shrestha, P. Wang, Optimized power trading of a PEV charging station with energy storage system, in IPEC (2012), p. 305
F. Pan, R. Bent, A. Berscheid, D. Izraelevitz, Locating PHEV exchange stations in V2G, in 2010 First IEEE International Conference on Smart Grid Communications (SmartGridComm) (2010), pp. 173–178
A. Elgammal, A. Sharaf, Self-regulating particle swarm optimised controller for (photovoltaic-fuel cell) battery charging of hybrid electric vehicles. Electr. Syst. Trans. IET 2, 77–89 (2012)
F. Fazelpour, M. Vafaeipour, O. Rahbari, M.A. Rosen, Intelligent optimization to integrate a plug-in hybrid electric vehicle smart parking lot with renewable energy resources and enhance grid characteristics. Energy Convers. Manag. 77, 250–261 (2014)
W. Su, Performance Evaluation of an EDA-Based Large-Scale Plug-In Hybrid Electric Vehicle Charging Algorithm (2012)
M.H. Amini, A. Kargarian, O. Karabasoglu, ARIMA-based decoupled time series forecasting of electric vehicle charging demand for stochastic power system operation. Electr. Power Syst. Res. 140, 378–390 (2016)
H.M. Neumann, D. Schär, F. Baumgartner, The potential of photovoltaic carports to cover the energy demand of road passenger transport. Prog. Photovoltaics Res. Appl. 20, 639–649 (2012)
G. Rizzo, I. Arsie, M. Sorrentino, Solar energy for cars: perspectives, opportunities and problems, in GTAA Meeting (2010), pp. 1–6
P.J. Tulpule, V. Marano, S. Yurkovich, G. Rizzoni, Economic and environmental impacts of a PV powered workplace parking garage charging station. Appl. Energy 108, 323–332 (2013)
D.P. Birnie, Solar-to-vehicle (S2V) systems for powering commuters of the future. J. Power Sources 186, 539–542 (2009)
Q. Zhang, T. Tezuka, K.N. Ishihara, B.C. Mclellan, Integration of PV power into future low-carbon smart electricity systems with EV and HP in Kansai Area, Japan. Renew. Energy 44, 99–108 (2012)
S. Binitha, S.S. Sathya, A survey of bio inspired optimization algorithms. Int. J. Soft Comput. Eng. 2, 137–151 (2012)
M. Črepinšek, S.-H. Liu, M. Mernik, Exploration and exploitation in evolutionary algorithms: a survey. ACM Comput. Surv. (CSUR) 45, 35 (2013)
M. Črepinšek, S.-H. Liu, M. Mernik, Replication and comparison of computational experiments in applied evolutionary computing: common pitfalls and guidelines to avoid them. Appl. Soft Comput. 19, 161–170 (2014)
X.-S. Yang, Z. Cui, R. Xiao, A.H. Gandomi, M. Karamanoglu, Swarm Intelligence and Bio-Inspired Computation: Theory and Applications (Newnes, 2013)
S. Xu, D. Feng, Z. Yan, L. Zhang, N. Li, L. Jing, et al., Ant-based swarm algorithm for charging coordination of electric vehicles. Int. J. Distrib. Sens. Netw. (2013)
M.L. Crow, Economic scheduling of residential plug-in (hybrid) electric vehicle (PHEV) charging. Energies 7, 1876–1898 (2014)
J. Soares, H. Morais, Z. Vale, Particle swarm optimization based approaches to vehicle-to-grid scheduling, in 2012 Power and Energy Society General Meeting (IEEE, 2012), pp. 1–8
T. Ghanbarzadeh, S. Goleijani, M.P. Moghaddam, Reliability constrained unit commitment with electric vehicle to grid using hybrid particle swarm optimization and ant colony optimization, in 2011 Power and Energy Society General Meeting (IEEE, 2011), pp. 1–7
M. Govardhan, R. Roy, Economic analysis of unit commitment with distributed energy resources. Int. J. Electr. Power Energy Syst. 71, 1–14 (2015)
S. Bashash, S.J. Moura, J.C. Forman, H.K. Fathy, Plug-in hybrid electric vehicle charge pattern optimization for energy cost and battery longevity. J. Power Sources 196, 541–549 (2011)
W. Su, M.-Y. Chow, Performance evaluation of a PHEV parking station using particle swarm optimization, in 2011 Power and Energy Society General Meeting (IEEE, 2011), pp. 1–6
I. Fister, D. Strnad, X.-S. Yang, I. Fister Jr, Adaptation and hybridization in nature-inspired algorithms, in Adaptation and Hybridization in Computational Intelligence (Springer, 2015), pp. 3–50
B. Xing, W.-J. Gao, Innovative Computational Intelligence: A Rough Guide to 134 Clever Algorithms, vol. 62 (Springer, 2014)
P.-Y. Kong, G.K. Karagiannidis, Charging schemes for plug-in hybrid electric vehicles in smart grid: a survey. IEEE Access 4, 6846–6875 (2016)
I. Rahman, P.M. Vasant, B.S.M. Singh, M. Abdullah-Al-Wadud, Novel metaheuristic optimization strategies for plug-in hybrid electric vehicles: a holistic review. Intell. Decision Technol. 10, 149–163 (2016)
Y.R. Rorigues, M.F. Souza, B. Lopes, A. Souza, D. Oliveira, Recharging process of plug in vehicles by using artificial immune system and tangent vector (2013)
M. Poursistani, M. Abedi, N. Hajilu, G. Gharehpetian, Smart charging of plug-in electric vehicle using gravitational search algorithm, in 2014 Smart Grid Conference (SGC) (2014), pp. 1–7
I. Rahman, P.M. Vasant, B.S.M. Singh, M. Abdullah-Al-Wadud, On the performance of accelerated particle swarm optimization for charging plug-in hybrid electric vehicles. Alexandria Eng. J. 55, 419–426 (2016)
P.M. Vasant, I. Rahman, B. Singh Mahinder Singh, M. Abdullah-Al-Wadud, Optimal power allocation scheme for plug-in hybrid electric vehicles using swarm intelligence techniques. Cogent Eng. 3, 1203083 (2016)
T. Ting, X.-S. Yang, S. Cheng, K. Huang, Hybrid metaheuristic algorithms: past, present, and future, in Recent Advances in Swarm Intelligence and Evolutionary Computation (Springer, 2015), pp. 71–83
A. Awasthi, D. Chandra, S. Rajasekar, A.K. Singh, K.M. Perumal, Optimal infrastructure planning of electric vehicle charging stations using hybrid optimization algorithm, in 2016 Power Systems Conference (NPSC) (National, 2016), pp. 1–6
M. Basu, A. Chowdhury, Cuckoo search algorithm for economic dispatch. Energy 60, 99–108 (2013)
N. Sulaiman, J. Mohamad-Saleh, A.G. Abro, A modified artificial bee colony (JA-ABC) optimization algorithm, in Proceedings of the International Conference on Applied Mathematics and Computational Methods in Engineering (2013), pp. 74–79
M. Neshat, G. Sepidnam, M. Sargolzaei, A.N. Toosi, Artificial fish swarm algorithm: a survey of the state-of-the-art, hybridization, combinatorial and indicative applications. Artif. Intell. Rev. 1–33 (2014)
D.H. Wolpert, W.G. Macready, No free lunch theorems for optimization. IEEE Trans. Evol. Comput. 1, 67–82 (1997)
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Rahman, I., Mohamad-Saleh, J. (2018). Plug-in Electric Vehicle Charging Optimization Using Bio-Inspired Computational Intelligence Methods. In: Amini, M., Boroojeni, K., Iyengar, S., Pardalos, P., Blaabjerg, F., Madni, A. (eds) Sustainable Interdependent Networks. Studies in Systems, Decision and Control, vol 145. Springer, Cham. https://doi.org/10.1007/978-3-319-74412-4_9
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