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Application of new multi-objective optimization algorithm for EV scheduling in smart grid through the uncertainties

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A Correction to this article was published on 14 March 2019

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Abstract

Ecological and economics issues are caused to give careful consideration to electric vehicles (EV) and sustainable power source assets. One of the proposed answers for increment the impact of these assets, is to utilize the electric vehicles potential. The capability of electric vehicles require planning for Smart Distribution Systems (SDS). Request reaction programs, as a suitable device to utilize endorsers’ potential in ideal administration of the system, gives dynamic nearness of supporters in control framework execution change and these projects, in basic conditions, can give the request prerequisites diminishment, in a brief timeframe. In this work, attempts to presents a multi-objective scheduling of EV based on the sustainable assets in smart grid, cover uncertainty caused by inexhaustible assets and EVs, by considering of the request reaction projects and EV battery stockpiling framework, limit the working expenses and the measure of intensity framework contamination, with enhancing procedures. Improved optimization algorithm is utilized for taking care of the advancing issue. Operating costs dropped much further utilizing monetary model of the demand response and vehicle charge/discharge and smart program in the hours when the load is lower. Effectiveness of proposed method is applied on 33 bus standard power system.

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Change history

  • 14 March 2019

    In the original publication, first author WanJun Yin’s affiliation was incorrectly added.

References

  • Abedinia O, Naderi MS, Jalili A, Mokhtarpour A (2011) A novel hybrid GA-PSO technique for optimal tuning of fuzzy controller to improve multi-machine power system stability. Int Rev Electr Eng 6(2)

  • Abedinia O, Amjady N, Kiani K (2012) Optimal complex economic load dispatch solution using particle swarm optimization with time varying acceleration coefficient. Int Rev Electr Eng 7(2)

  • Abedinia O, Amjady N, Ghasemi A, Hejrati Z (2013) Solution of economic load dispatch problem via hybrid particle swarm optimization with time-varying acceleration coefficients and bacteria foraging algorithm techniques. Int Trans Electr Energy Syst 23(8):1504–1522

    Article  Google Scholar 

  • Abedinia O, Ghasemi A, Ojaroudi N (2016) Improved time varying inertia weight PSO for solved economic load dispatch with subsidies and wind power effects. Complexity 21(4):40–49

    Article  MathSciNet  Google Scholar 

  • Abedinia O, Amjady N, Ghadimi N (2018) Solar energy forecasting based on hybrid neural network and improved metaheuristic algorithm. Comput Intell 34(1):241–260

    Article  MathSciNet  Google Scholar 

  • Ahangarnejad AH, Azar A (2014) Designing of an assembly machine for center deviation adaptive bearing pressure. Life Sci J 11(2s):863–873

    Google Scholar 

  • Ahangarnejad AH, Başlamışlı S (2016) Adap-tyre: DEKF filtering for vehicle state estimation based on tyre parameter adaptation. Int J Veh Des 71(1–4):52–74

    Article  Google Scholar 

  • Ahangarnejad AH, Melzi S (2018) Numerical analysis of the influence of an actively controlled spoiler on the handling of a sports car. J Vib Control 24(22):5437–5448

    Article  MathSciNet  Google Scholar 

  • Azar SA, Ahangarnejad AH (2014) Simulating the diesel engine vibration with fuzzy neural network. Res J Appl Sci Eng Technol 8(9):1045–1051

    Article  Google Scholar 

  • Babaeean A, Tashk AB, Bandarabadi M, Rastegar S (2008) Target tracking using wavelet features and RVM classifier. In: Fourth international conference on natural computation, 2008. ICNC’08, vol 4. IEEE, New York, pp 569–572

  • Boait P, Mahdavi Ardestani B, Snape JR (2013) Accommodating renewable generation through an aggregator-focused method for inducing demand side response from electricity consumers. IET Renew Power Gener 7(6):689–699

    Article  Google Scholar 

  • Chedid R, Akiki H, Rahman S (1998) A decision support technique for the design of hybrid solar-wind power systems. IEEE Trans Energy Convers 13(1):76–83

    Article  Google Scholar 

  • Chen Y, Zou X, Xie W (2011) Convergence of multi-objective evolutionary algorithms to a uniformly distributed representation of the Pareto front. Inf Sci 181(16):3336–3355

    Article  MathSciNet  Google Scholar 

  • Chu ZQ, Sasanipour J, Saeedi M, Baghban A, Mansoori H (2017) Modeling of wax deposition produced in the pipelines using PSO-ANFIS approach. Pet Sci Technol 35(20):1974–1981

    Article  Google Scholar 

  • Duan M, Darvishan A, Mohammaditab R, Wakil K, Abedinia O (2018) A novel hybrid prediction model for aggregated loads of buildings by considering the electric vehicles. Sustain Cities Soc 41:205–219

    Article  Google Scholar 

  • Fakoor M, Kosari A, Jafarzadeh M (2015) Revision on fuzzy artificial potential field for humanoid robot path planning in unknown environment. Int J Adv Mechatron Syst 6(4):174–183

    Article  Google Scholar 

  • Fakoor M, Kosari A, Jafarzadeh M (2016) Humanoid robot path planning with fuzzy Markov decision processes. J Appl Res Technol 14(5):300–310

    Article  Google Scholar 

  • Fallahtafti F, Alavikia M, Arshi AR (2013) Bond graph application in sports engineering: evaluating the effects of impact parameters on tennis elbow injury. In: 20th Iranian conference on biomedical engineering (ICBME), 2013. IEEE, New York, pp 255–259

  • Feili H, Rabiei E, Ahmadian P, Karimi J, Majidi B (2016) Prioritization of renewable energy systems using AHP method with economic analysis perspective in Iran. In: 2nd International conference on modern researches in management, economics and accounting, Kuala Lumpur, Malaysia

  • Gao W, Yan L, Saeedi MH, Nik HS (2018) Ultimate bound estimation set and chaos synchronization for a financial risk system. Math Comput Simul 154:19–33

    Article  MathSciNet  Google Scholar 

  • Gao W, Darvishan A, Toghani M, Mohammadi M, Abedinia O, Ghadimi N (2019) Different states of multi-block based forecast engine for price and load prediction. Int J Electr Power Energy Syst 104:423–435

    Article  Google Scholar 

  • Ghadimi N, Akbarimajd A, Shayeghi H, Abedinia O (2018) Two stage forecast engine with feature selection technique and improved meta-heuristic algorithm for electricity load forecasting. Energy 161:130–142

    Article  Google Scholar 

  • Hajimiragha AH, Cañizares CA, Fowler MW, Moazeni S, Elkamel A (2011) A robust optimization approach for planning the transition to plug-in hybrid electric vehicles. IEEE Trans Power Syst 26(4):2264–2274

    Article  Google Scholar 

  • Hamian M, Darvishan A, Hosseinzadeh M, Lariche MJ, Ghadimi N, Nouri A (2018) A framework to expedite joint energy-reserve payment cost minimization using a custom-designed method based on Mixed Integer Genetic Algorithm. Eng Appl Artif Intell 72:203–212

    Article  Google Scholar 

  • Khodaei H, Hajiali M, Darvishan A, Sepehr M, Ghadimi N (2018) Fuzzy-based heat and power hub models for cost-emission operation of an industrial consumer using compromise programming. Appl Therm Eng 137:395–405

    Article  Google Scholar 

  • Laumanns M, Thiele L, Deb K, Zitzler E (2002) Combining convergence and diversity in evolutionary multiobjective optimization. Evol Comput 10(3):263–282

    Article  Google Scholar 

  • Leeder T, Fallahtafti F, Schieber M, Myers SA, Boron JB, Yentes JM (2018) Optic flow improves step width and length in older adults while performing dual task. Aging Clin Exp Res. https://doi.org/10.1007/s40520-018-1059-x

    Article  Google Scholar 

  • Li LM, Lu KD, Zeng GQ, Wu L, Chen MR (2016) A novel real-coded population-based extremal optimization algorithm with polynomial mutation: a non-parametric statistical study on continuous optimization problems. Neurocomputing 174:577–587

    Article  Google Scholar 

  • Liu X, Yazdanpanah AR, Mancini GJ, Tan J (2015) Control of a magnetic actuated robotic surgical camera system for single incision laparoscopic surgery. In: IEEE international conference on robotics and biomimetics (ROBIO), 2015. IEEE, New York, pp 1396–1402

  • Liu T, Jiao L, Ma W, Ma J, Shang R (2016) A new quantum-behaved particle swarm optimization based on cultural evolution mechanism for multiobjective problems. Knowl Based Syst 101:90–99

    Article  Google Scholar 

  • Liu Z, Hajiali M, Torabi A, Ahmadi B, Simoes R (2018) Novel forecasting model based on improved wavelet transform, informative feature selection, and hybrid support vector machine on wind power forecasting. J Ambient Intell Humaniz Comput 9(6):1919–1931

    Article  Google Scholar 

  • Moavenian M, Gharib MR, Daneshvar A, Alimardani S (2011) Control of human hand considering uncertainties. In: International conference on advanced mechatronic systems (ICAMechS), 2011. IEEE, New York, pp 17–22

  • Mohammadi M, Talebpour F, Safaee E, Ghadimi N, Abedinia O (2018) Small-scale building load forecast based on hybrid forecast engine. Neural Process Lett 48(1):329–351

    Article  Google Scholar 

  • Mohammadzadeh A, Ghoddoosian A, Noori-Damghani M (2011) Balancing of the flexible rotors with particle swarm optimization method. Int Rev Mech Eng 5(3):490–496

    Google Scholar 

  • Morsali R, Mohammadi M, Maleksaeedi I, Ghadimi N (2014) A new multiobjective procedure for solving nonconvex environmental/economic power dispatch. Complexity 20(2):47–62

    Article  MathSciNet  Google Scholar 

  • Nejad HC, Farshad M, Rahatabad FN, Khayat O (2016a) Gradient-based back-propagation dynamical iterative learning scheme for the neuro-fuzzy inference system. Expert Syst 33(1):70–76

    Article  Google Scholar 

  • Nejad HC, Farshad M, Khayat O, Rahatabad FN (2016b) Performance verification of a fuzzy wavelet neural network in the first order partial derivative approximation of nonlinear functions. Neural Process Lett 43(1):219–230

    Article  Google Scholar 

  • Nouri A, Khodaei H, Darvishan A, Sharifian S, Ghadimi N (2018) Optimal performance of fuel cell-CHP-battery based micro-grid under real-time energy management: an epsilon constraint method and fuzzy satisfying approach. Energy 159:121–133

    Article  Google Scholar 

  • Nouri Damghani M, Mohammadzadeh Gonabadi A (2017) Numerical study of energy absorption in aluminum foam sandwich panel structures using drop hammer test. J Sandw Struct Mater 21(1):3–18. https://doi.org/10.1177/1099636216685315

    Article  Google Scholar 

  • Rabiei E, Feili H, Ahmadian P, Majidi B, Karimi J (2015) The economic analysis between wind energy and biogas energy to determine economic policy in the renewable energy systems in Iran

  • Rastegar S, Babaeian A, Bandarabadi M, Toopchi Y (2009) Airplane detection and tracking using wavelet features and SVM classifier. In: 41st Southeastern symposium on system theory, 2009. SSST 2009. IEEE, New York, pp 64–67

  • Safa A, Abdolmalaki RY (2019) Robust output feedback tracking control for inertially stabilized platforms with matched and unmatched uncertainties. IEEE Trans Control Syst Technol 27(1):118–131

  • Shao Z, Wu P, Gao Y, Gutman I, Zhang X (2017) On the maximum ABC index of graphs without pendent vertices. Appl Math Comput 315:298–312

    MathSciNet  MATH  Google Scholar 

  • Shao Z, Wakil K, Usak M, Heidari MA, Wang B, Simoes R (2018a) Kriging empirical mode decomposition via support vector machine learning technique for autonomous operation diagnosing of CHP in microgrid. Appl Therm Eng 145:58–70

    Article  Google Scholar 

  • Shao Z, Wu P, Zhang X, Dimitrov D, Liu JB (2018b) On the maximum ABC index of graphs with prescribed size and without pendent vertices. IEEE Access 6:27604–27616

    Article  Google Scholar 

  • Shi Y, Eberhart R (1998) A modified particle swarm optimizer. In: The 1998 IEEE international conference on evolutionary computation proceedings, 1998. IEEE world congress on computational intelligence. IEEE, New York, pp 69–73

  • Torabi A, Mousavy SAK, Dashti V, Saeedi M, Yousefi N (2018) A new prediction model based on cascade NN for wind power prediction. Comput Econ. https://doi.org/10.1007/s10614-018-9795-8

    Article  Google Scholar 

  • Zakariazadeh A, Jadid S, Siano P (2014) Multi-objective scheduling of electric vehicles in smart distribution system. Energy Convers Manag 79:43–53

    Article  Google Scholar 

  • Zhao J, Kucuksari S, Mazhari E, Son YJ (2013) Integrated analysis of high-penetration PV and PHEV with energy storage and demand response. Appl Energy 112:35–51

    Article  Google Scholar 

Download references

Acknowledgements

This work is partially supported by the Education Department of Sichuan Province (GZY18C49), The Key Program of Guangyuan Municipal Science and Technology Project (2018ZCZDYF016).

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Authors and Affiliations

  1. School of Electronic & Mechanical Engineering, Xidian University, Xi’an, 710071, People’s Republic of China

    WanJun Yin

  2. Sichuan Vocational College of Information Technology, Guangyuan, 628040, Sichuan, People’s Republic of China

    WanJun Yin

  3. College of Computing and Informatics, Saudi Electronic University, Riyadh, Saudi Arabia

    Dinesh Mavaluru

  4. Department of Management Sciences, COMSATS University Islamabad, Vehari Campus, Islamabad, Pakistan

    Munir Ahmed & Mazhar Abbas

  5. Department of Industrial Engineering, University of Houston, Houston, TX, USA

    Aida Darvishan

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  1. WanJun Yin
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  5. Aida Darvishan
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Correspondence to Aida Darvishan.

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Yin, W., Mavaluru, D., Ahmed, M. et al. Application of new multi-objective optimization algorithm for EV scheduling in smart grid through the uncertainties. J Ambient Intell Human Comput 11, 2071–2103 (2020). https://doi.org/10.1007/s12652-019-01233-1

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