Advertisement

An Agent-Based Model for Optimal Voltage Control and Power Quality by Electrical Vehicles in Smart Grids

  • Amirabbas HadizadeEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 801)

Abstract

The electric power industry is the main part of Science development, and today, with the advent of technology, the demand for electric power has been expanded. On the other hand, smart grids are developing heavily. One of the notable features of these networks is the presence of a plug-in hybrid electric vehicle (PHEV). The addition of these cars to the network has its own advantages and disadvantages. One of the most important issues in smart grids is network management and control of critical system parameters. In this paper the effect of these cars on the grid is investigated. These vehicles impose an increase in production capacity in the uncontrolled charge mode. They also have the ability to inject power into the network and can assist the grid at peak consumption time, leading to peak shaving in daily load curve. Our main goal is to provide a way to manage the charge and discharge of these vehicles using the agent based model, in order to control the voltage of the system buses.

Keywords

Optimal voltage control PHEV Smart grid Agent based model Power quality 

References

  1. 1.
    Nassaj, A., Shahrtash, S.M.: An accelerated preventive agent based scheme for post-disturbance voltage control and loss reduction. IEEE Early Access Articles (2018)Google Scholar
  2. 2.
    Nassaj, A., Shahrtash, S.M.: A predictive agent-based scheme for post-disturbance voltage control. Int. J. Electr. Power Energy Syst. 98, 189–198 (2018)CrossRefGoogle Scholar
  3. 3.
    Fernández, L.P., Román, T.G.S., Cossent, R., Domingo, C.M., Frías, P.: Assessment of the impact of plug-in electric vehicles on distributionnetworks. IEEE Trans. Power Syst. 26(1), 206–213 (2011)CrossRefGoogle Scholar
  4. 4.
    Hashemi-Dezaki, H., et al.: Risk management of smart grids based onmanaged charging of PHEVs and vehicle-to-grid strategy using Monte Carlosimulation. Energy Convers. Manag. 100, 262–276 (2015)CrossRefGoogle Scholar
  5. 5.
    Shokri Gazafroudi, A., Pinto, T., Prieto-Castrillo, F., Prieto, J., Corchado, J.M., Jozi, A., Vale, Z., Venayagamoorthy, G.K.: Organization-based multi-agent structure of the smart home electricity system. In: IEEE Congress on Evolutionary Computation (CEC), June 2017Google Scholar
  6. 6.
    Shokri Gazafroudi, A., Prieto-Castrillo, F., Pinto, T., Jozi, A., Vale, Z.: Economic evaluation of predictive dispatch model in MAS-based smart home. In: 15th International Conference on Practical Applications of Agents and Multi-Agent Systems (PAAMS), June 2017Google Scholar
  7. 7.
    Shokri Gazafroudi, A., De Paz, J.F., Prieto-Castrillo, F., Villarrubia, G., Talari, S., Shafie-khah, M., Catalão, J.P.S.: A review of multi-agent based energy management systems. In: 8th International Symposium on Ambient Intelligence (ISAmI), June 2017Google Scholar
  8. 8.
    Shokri Gazafroudi, A., Prieto-Castrillo, F., Pinto, T., Corchado, J.M.: Organization-based multi-agent system of local electricity market: bottom-up approach. In: 15th International Conference on Practical Applications of Agents and Multi-Agent Systems (PAAMS), June 2017Google Scholar
  9. 9.
    Shokri Gazafroudi, A., Abrishambaf, O., Jozi, A., Pinto, T., Preito-Castrillo, F., Corchado, J.M., Vale, Z.: Energy flexibility assessment of a multi agent-based smart home electricity system. In: 17th edition of the IEEE International Conference on Ubiquitous Wireless Broadband (ICUWB), September 2017Google Scholar
  10. 10.
    Chamoso, P., Rivas, A., Martín-Limorti, J.J., Rodríguez, S.: A hash based image matching algorithm for social networks. In: Advances in Intelligent Systems and Computing, vol. 619, pp. 183–190 (2018)Google Scholar
  11. 11.
    Sittón, I., Rodríguez, S.: Pattern extraction for the design of predictive models in industry 4.0. In: International Conference on Practical Applications of Agents and MultiAgent Systems, pp. 258–261 (2017)Google Scholar
  12. 12.
    García, O., Chamoso, P., Prieto, J., Rodríguez, S., De La Prieta, F.: A serious game to reduce consumption in smart buildings. In: Communications in Computer and Information Science, vol. 722, pp. 481–493 (2017)Google Scholar
  13. 13.
    Palomino, C.G., Nunes, C.S., Silveira, R.A., González, S.R., Nakayama, M.K.: Adaptive agent-based environment model to enable the teacher to create an adaptive class. Adv. Intell. Syst. Comput. vol. 617 (2017)Google Scholar
  14. 14.
    Canizes, B., Pinto, T., Soares, J., Vale, Z., Chamoso, P., Santos, D.: Smart City: a GECAD-BISITE energy management case study. In: 15th International Conference on Practical Applications of Agents and Multi-Agent Systems PAAMS 2017, Trends in CyberPhysical Multi-Agent Systems, vol. 2, pp. 92–100 (2017)Google Scholar
  15. 15.
    Chamoso, P., de La Prieta, F., Eibenstein, A., Santos-Santos, D., Tizio, A., Vittorini, P.: A device supporting the self management of tinnitus. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). LNCS, vol. 10209, pp. 399–410 (2017)CrossRefGoogle Scholar
  16. 16.
    Román, J.A., Rodríguez, S., de da Prieta, F.: Improving the distribution of services in MAS. Commun. Comput. Inf. Sci. 616 (2016)Google Scholar
  17. 17.
    Buciarelli, E., Silvestri, M., González, S.R.: Decision economics. In: 13th International Conference Commemoration of the Birth Centennial of Herbert A. Simon 1916–2016 (Nobel Prize in Economics 1978): Distributed Computing and Artificial Intelligence. Advances in Intelligent Systems and Computing, vol. 475. Springer (2016)Google Scholar
  18. 18.
    Li, T., Sun, S., Bolić, M., Corchado, J.M.: Algorithm design for parallel implementation of the SMC-PHD filter. Sig. Process. 119, 115–127 (2016)CrossRefGoogle Scholar
  19. 19.
    Lima, A.C.E.S., De Castro, L.N., Corchado, J.M.: A polarity analysis framework for Twitter messages. Appl. Math. Comput. 270, 756–767 (2015)Google Scholar
  20. 20.
    Redondo-Gonzalez, E., De Castro, L.N., Moreno-Sierra, J., Maestro De Las Casas, M.L., Vera-Gonzalez, V., Ferrari, D.G., Corchado, J.M.: Bladder carcinoma data with clinical risk factors and molecular markers: a cluster analysis. BioMed Res. Int. (2015)Google Scholar
  21. 21.
    Li, T., Sun, S., Corchado, J.M., Siyau, M.F.: Random finite set-based Bayesian filters using magnitude-adaptive target birth intensity. In: FUSION 2014 - 17th International Conference on Information Fusion (2014)Google Scholar
  22. 22.
    Prieto, J., Alonso, A.A., de la Rosa, R., Carrera, A.: Adaptive framework for uncertainty analysis in electromagnetic field measurements. Radiat. Prot. Dosimetry (2014). ncu260Google Scholar
  23. 23.
    Chamoso, P., Raveane, W., Parra, V., González, A.: UAVs applied to the counting and monitoring of animals. In: Advances in Intelligent Systems and Computing, vol. 291, pp. 71–80 (2014)CrossRefGoogle Scholar
  24. 24.
    Pérez, A., Chamoso, P., Parra, V., Sánchez, A.J.: Ground vehicle detection through aerial images taken by a UAV. In: 2014 17th International Conference on Information Fusion (FUSION) (2014)Google Scholar
  25. 25.
    Choon, Y.W., Mohamad, M.S., Deris, S., Illias, R.M., Chong, C.K., Chai, L.E., Corchado, J.M.: Differential bees flux balance analysis with OptKnock for in silico microbial strains optimization. PLoS ONE 9(7) (2014)CrossRefGoogle Scholar
  26. 26.
    Li, T., Sun, S., Corchado, J.M., Siyau, M.F.: A particle dyeing approach for track continuity for the SMC-PHD filter. In: FUSION 2014 - 17th International Conference on Information Fusion (2014)Google Scholar
  27. 27.
    García Coria, J.A., Castellanos-Garzón, J.A., Corchado, J.M.: Intelligent business processes composition based on multi-agent systems. Exp. Syst. Appl. 41(4 PART 1), 1189–1205 (2014)Google Scholar
  28. 28.
    Prieto, J., Mazuelas, S., Bahillo, A., Fernández, P., Lorenzo, R.M., Abril, E.J.: Accurate and robust localization in harsh environments based on V2I communication. In: Vehicular Technologies - Deployment and Applications. INTECH Open Access Publisher (2013)Google Scholar
  29. 29.
    De La Prieta, F., Navarro, M., García, J.A., González, R., Rodríguez, S.: Multiagent system for controlling a cloud computing environment. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). LNAI, vol. 8154 (2013)Google Scholar
  30. 30.
    Tapia, D.I., Fraile, J.A., Rodríguez, S., Alonso, R.S., Corchado, J.M.: Integrating hardware agents into an enhanced multi-agent architecture for Ambient Intelligence systems. Inf. Sci. 222(47–65), 5 (2013)Google Scholar
  31. 31.
    Prieto, J., Mazuelas, S., Bahillo, A., Fernandez, P., Lorenzo, R.M., Abril, E.J.: Adaptive data fusion for wireless localization in harsh environments. IEEE Trans. Signal Process. 60(4), 1585–1596 (2012)MathSciNetCrossRefGoogle Scholar
  32. 32.
    Muñoz, M., Rodríguez, M., Rodríguez, M.E., Rodríguez, S.: Genetic evaluation of the class III dentofacial in rural and urban Spanish population by AI techniques. In: Advances in Intelligent and Soft Computing. AISC, vol. 151 (2012)Google Scholar
  33. 33.
    Costa, Â., Novais, P., Corchado, J.M., Neves, J.: Increased performance and better patient attendance in an hospital with the use of smart agendas. Logic J. IGPL (2012)Google Scholar
  34. 34.
    García, E., Rodríguez, S., Martín, B., Zato, C., Pérez, B.: MISIA: middleware infrastructure to simulate intelligent agents. In: Advances in Intelligent and Soft Computing, vol. 91 (2011)Google Scholar
  35. 35.
    Rodríguez, S., De La Prieta, F., Tapia, D.I., Corchado, J.M.: Agents and computer vision for processing stereoscopic images. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). LNAI, vol. 6077 (2010)Google Scholar
  36. 36.
    Rodríguez, S., Gil, O., De La Prieta, F., Zato, C., Corchado, J.M., Vega, P., Francisco, M.: People detection and stereoscopic analysis using MAS. In: Proceedings of INES 2010 - 14th International Conference on Intelligent Engineering Systems (2010)Google Scholar
  37. 37.
    Prieto, J., Mazuelas, S., Bahillo, A., Fernández, P., Lorenzo, R.M., Abril, E.J.: On the minimization of different sources of error for an RTT-based indoor localization system without any calibration stage. In: 2010 International Conference on Indoor Positioning and Indoor Navigation (IPIN), pp. 1–6 (2010)Google Scholar
  38. 38.
    Rodríguez, S., Tapia, D.I., Sanz, E., Zato, C., De La Prieta, F., Gil, O.: Cloud computing integrated into service-oriented multi-agent architecture. In: IFIP Advances in Information and Communication Technology. AICT, vol. 322 (2010)CrossRefGoogle Scholar
  39. 39.
    Corchado, J., Fyfe, C., Lees, B.: Unsupervised learning for financial forecasting. In: Proceedings of the IEEE/IAFE/INFORMS 1998 Conference on Computational Intelligence for Financial Engineering (CIFEr) (Cat. No. 98TH8367), pp. 259–263 (1998)Google Scholar
  40. 40.
    Durik, B.O.: Organisational metamodel for large-scale multi-agent systems: first steps towards modelling organisation dynamics. ADCAIJ Adv. Distrib. Comput. Artif. Intell. J. 6(3) (2017)Google Scholar
  41. 41.
    Bremer, J., Lehnhoff, S.: Decentralized coalition formation with agent based combinatorial heuristics. ADCAIJ Adv. Distrib. Comput. Artif. Intell. J. 6(3) (2017)CrossRefGoogle Scholar
  42. 42.
    Cauê Cardoso, R., Bordini, R.H.: A multi-agent extension of a hierarchical task network planning formalism. ADCAIJ Adv. Distrib. Comput. Artif. Intell. J. 6(2) (2017)Google Scholar
  43. 43.
    Gonçalves, E., Cortés, M., De Oliveira, M., Veras, N., Falcão, M., Castro, J.: An analysis of software agents, environments and applications school: retrospective, relevance, and trends. ADCAIJ Adv. Distrib. Comput. Artif. Intell. J. 6(2) (2017)CrossRefGoogle Scholar
  44. 44.
    Teixeira, E.P., Goncalves, E.M.N., Adamatti, D.F.: Ulises: a agent based system for timbre classification. ADCAIJ Adv. Distrib. Comput. Artif. Intell. J. 6(2) (2017)CrossRefGoogle Scholar
  45. 45.
    De Castro, L.F.S., Vaz Alves, G., Borges, A.P.: Using trust degree for agents in order to assign spots in a Smart Parking. ADCAIJ Adv. Distrib. Comput. Artif. Intell. J. 6(2.6) (2017)Google Scholar
  46. 46.
    Cunha, R., Billa, C., Adamatti, D.: Development of a graphical tool to integrate the prometheus AEOlus methodology and Jason platform. ADCAIJ Adv. Distrib. Comput. Artif. Intell. J. 6(2) (2017)CrossRefGoogle Scholar
  47. 47.
    Rincón, J., Poza, J.L., Posadas, J.L., Julián, V., Carrascosa, C.: Adding real data to detect emotions by means of smart resource artifacts in MAS. ADCAIJ Adv. Distrib. Comput. Artif. Intell. J. 5(4) (2016)CrossRefGoogle Scholar
  48. 48.
    Villavicencio, C.P., Schiaffino, S., Andrés Díaz-Pace, J., Monteserin, A.: A group recommendation system for movies based on MAS. ADCAIJ Adv. Distrib. Comput. Artif. Intell. J. 5(3) (2016)CrossRefGoogle Scholar
  49. 49.
    Briones, A.G., Chamoso, P., Barriuso, A.: Review of the main security problems with multi-agent systems used in e-commerce applications. ADCAIJ Adv. Distrib. Comput. Artif. Intell. J. 5(3) (2016)Google Scholar
  50. 50.
    Carbó, J., Molina, J.M., Patricio, M.A.: Asset management system through the design of a Jadex agent system. ADCAIJ Adv. Distrib. Comput. Artif. Intell. J. 5(2) (2016)CrossRefGoogle Scholar
  51. 51.
    Santos, G., Pinto, T., Vale, Z., Praça, I., Morais, H.: Enabling communications in heterogeneous multi-agent systems: electricity markets ontology. ADCAIJ Adv. Distrib. Comput. Artif. Intell. J. 5(2) (2016)CrossRefGoogle Scholar
  52. 52.
    Murciego, Á.L., González, G.V., Barriuso, A.L., De La Iglesia, D.H., Herrero, J.R.: Multi agent gathering waste system. ADCAIJ Adv. Distrib. Comput. Artif. Intell. J. 4(4) (2015)Google Scholar
  53. 53.
    Barriuso, A.L., De La Prieta, F., Murciego, Á.L., Hernández, D., Herrero, J.R.: JOUR-MAS: a multi-agent system approach to help journalism management. ADCAIJ Adv. Distrib. Comput. Artif. Intell. J. 4(4) (2015)Google Scholar
  54. 54.
    De La Iglesia, D.H., González, G.V., Barriuso, A.L., Murciego, Á.L., Herrero, J.R.: Monitoring and analysis of vital signs of a patient through a multi-agent application system. ADCAIJ Adv. Distrib. Comput. Artif. Intell. J. 4(3) (2015)Google Scholar
  55. 55.
    Gallego, J.Á.R., González, S.R.: Improvement in the distribution of services in multi-agent systems with SCODA. ADCAIJ Adv. Distrib. Comput. Artif. Intell. J. 4(3) (2015)Google Scholar
  56. 56.
    Chamoso, P., De La Prieta, F.: Simulation environment for algorithms and agents evaluation. ADCAIJ Adv. Distrib. Comput. Artif. Intell. J. 4(3) (2015)Google Scholar
  57. 57.
    González, A., Ramos, J., De Paz, J.F., Corchado, J.M.: Obtaining relevant genes by analysis of expression arrays with a multi-agent system. ADCAIJ Adv. Distrib. Comput. Artif. Intell. J. 3(3) (2014)CrossRefGoogle Scholar
  58. 58.
    Faia, R., Pinto, T., Vale, Z.: Dynamic fuzzy clustering method for decision support in electricity markets negotiation. ADCAIJ Adv. Distrib. Comput. Artif. Intell. J. 5(1) (2016)CrossRefGoogle Scholar
  59. 59.
    Silva, A., Oliveira, T., Neves, J., Novais, P.: Treating colon cancer survivability prediction as a classification problem. ADCAIJ Adv. Distrib. Comput. Artif. Intell. J. 5(1.7) (2016)CrossRefGoogle Scholar
  60. 60.
    Sánchez, D.L., Arrieta, A.G.: Preliminary results on nonparametric facial occlusion detection. ADCAIJ Adv. Distrib. Comput. Artif. Intell. J. 5(1) (2016)Google Scholar
  61. 61.
    Chamoso, P., Pérez-Ramos, H., García-García, Á.: ALTAIR: supervised methodology to obtain retinal vessels caliber. ADCAIJ Adv. Distrib. Comput. Artif. Intell. J. 3(4) (2014)CrossRefGoogle Scholar
  62. 62.
    Cofini, V., De La Prieta, F., Di Mascio, T., Gennari, R., Vittorini, P.: Design smart games with requirements, generate them with a click, and revise them with a GUIs. ADCAIJ Adv. Distrib. Comput. Artif. Intell. J. 1(3) (2012)Google Scholar
  63. 63.
    Kushch, S., Castrillo, F.P.: A review of the applications of the Blockchain technology in smart devices and distributed renewable energy grids. ADCAIJ Adv. Distrib. Comput. Artif. Intell. J. 6(3) (2017)CrossRefGoogle Scholar
  64. 64.
    Pinto, A., Costa, R.: Hash-chain-based authentication for IoT. ADCAIJ Adv. Distrib. Comput. Artif. Intell. J. 5(4) (2016)CrossRefGoogle Scholar
  65. 65.
    García-Valls, M.: Prototyping low-cost and flexible vehicle diagnostic systems. ADCAIJ Adv. Distrib. Comput. Artif. Intell. J. 5(4) (2016)CrossRefGoogle Scholar
  66. 66.
    Fernández-Fernández, A., Cervelló-Pastor, C., Ochoa-Aday, L.: Energy-aware routing in multiple domains software-defined networks. ADCAIJ Adv. Distrib. Comput. Artif. Intell. J. 5(3) (2016)CrossRefGoogle Scholar
  67. 67.
    Koskimaki, H., Siirtola, P.: Accelerometer vs. electromyogram in activity recognition. ADCAIJ Adv. Distrib. Comput. Artif. Intell. J. 5(3) (2016)CrossRefGoogle Scholar
  68. 68.
    Chamoso, P., De La Prieta, F., Villarrubia, G.: Intelligent system to control electric power distribution networks. ADCAIJ Adv. Distrib. Comput. Artif. Intell. J. 4(4) (2015)Google Scholar
  69. 69.
    Herrero, J.R., Villarrubia, G., Barriuso, A.L., Hernández, D., Lozano, Á., De La Serna González, M.A.: Wireless controller and smartphone based interaction system for electric bicycles. ADCAIJ Adv. Distrib. Comput. Artif. Intell. J. 4(4) (2015)Google Scholar
  70. 70.
    Fernández-Isabel, A., Fuentes-Fernández, R.: Simulation of road traffic applying model-driven engineering. ADCAIJ Adv. Distrib. Comput. Artif. Intell. J. 4(2) (2015)CrossRefGoogle Scholar
  71. 71.
    Chamoso, P., De La Prieta, F.: Swarm-based smart city platform: a traffic application. ADCAIJ Adv. Distrib. Comput. Artif. Intell. J. 4(21) (2015)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Sharif University of TechnologyTehranIran

Personalised recommendations