Demand response due to the penetration of electric vehicles in a microgrid through stochastic optimization

Authors

Keywords:

Electric Power, Demand Response, Electric Vehicle, Microgrid

Abstract

The study carries out an economic technical analysis of the effect of the penetration of electric vehicles in a microgrid with various types of renewable energy sources and loads of different nature. The electric vehicle has been modeled through its main component, the battery, by using criteria of randomness in the entry and type of load used by each vehicle. Following this process, the energy demand curves and voltage profiles resulting from such penetration were obtained. In a second phase, three demand response programs based on incentives and prices were applied, and the impact of these decisions on the system through new demand curves and voltage profiles were quantified, the comparison with the base scenario is also carried out. In its final stage, the different scenarios proposed are evaluated financially and the NPV financial index is calculated, which is included in a binary-type optimization model, allowing through simulations to make decisions about the best demand response program alternative for the system.

Downloads

Download data is not yet available.

Author Biographies

Danny Trujillo , Universidad Politécnica Salesiana

Electrical Engineer from the Escuela Politécnica Nacional - Ecuador (2009), Master in Business Management – Escuela Politécnica Nacional - Ecuador (2012), Master of Electricity mention in Power Electrical Systems – Universidad Politécnica Salesiana. He has worked in various public and private institutions such as CENACE - Ecuador, Escuela Politécnica Nacional, Universidad Internacional SEK.

Edwin Marcelo García Torres, Universidad Politécnica Salesiana

Graduated in Electrical Engineering from the Universidad Politécnica Salesiana - Ecuador. Master in Energy Management. He is currently working towards his doctorate in Engineering with the Universidad Pontificia Bolivariana - Colombia. Area of interest: demand response, energy management systems, smart microgrids. He is a professor of Universidad Politécnica Salesiana - Ecuador.

References

F. Ji, L. Xu, and Z. Wu, “Effect of driving cycles on energy efficiency of electric vehicles,” Science in China, Series E: Technological Sciences, vol. 52, no. 11, pp. 3168–3172, 2009.

G. J. Offer, D. Howey, M. Contestabile, R. Clague, and N. P. Brandon, “Comparative analysis of battery electric, hydrogen fuel cell and hybrid vehicles in a future sustainable road transport system,” Energy Policy, vol. 38, no. 1, pp. 24–29, 2010.

S. Iqbal, A. Xin, M. U. Jan, M. A. Abdelbaky, H. U. Rehman, S. Salman, S. A. A. Rizvi, and M. Aurangzeb, “Aggregation of EVs for Primary Frequency Control of an Industrial Microgrid by Implementing Grid Regulation Charger Controller,” IEEE Access, vol. 8, pp. 141977–141989, 2020.

L. Sun, C. C. Chan, R. Liang, and Q. Wang, “State-of-art of Energy System for New Energy Vehicles,” in IEEE Vehicle Power and Propulsion Conference (VPPC), 2008.

A. Khaligh and Z. Li, “Battery, ultracapacitor, fuel cell, and hybrid energy storage systems for electric, hybrid electric, fuel cell, and plugin hybrid electric vehicles: State of the art,” IEEE Transactions on Vehicular Technology, vol. 59, no. 6, pp. 2806–2814, 2010.

F. R. Salmasi, “Control strategies for hybrid electric vehicles: Evolution, classification, comparison, and future trends,” IEEE Transactions on Vehicular Technology, vol. 56, no. 5 I, pp. 2393–2404, 2007.

B. Frieske, M. Kloetzke, and F. Mauser, “Trends in vehicle concept and key technology development for hybrid and battery electric vehicles,” 2013 World Electric Vehicle Symposium and Exhibition, EVS 2014, pp. 1–12, 2014.

D. Vuljaj, B. Ban, and M. Vraži´c, “Hibrid drive dimensioning using MATLAB software package,” 2016 13th International Conference on Development and Application Systems, DAS 2016 - Conference Proceedings, pp. 172–175, 2016.

K. S. Grewal and P. M. Darnell, “Model-based EV range prediction for electric hybrid vehicles,” in IET Conference Publications, pp. 1–6, 2013.

K. K. Thanapalan, J. R. Kim, S. J. Carr, F. Zhang, G. C. Premier, J. Maddy, and A. J. Guwy, “Progress in the development of renewable hydrogen vehicles, storage, infrastructure in the UK: Hydrogen Centre in its early years of operation,” Proceedings of the 2nd International Conference on Intelligent Control and Information Processing, ICICIP 2011, vol. 44, no. PART 2, pp. 738–742, 2011.

K. N. Kumar and K. J. Tseng, “Impact of demand response management on chargeability of electric vehicles,” Energy, vol. 111, pp. 190–196, 2016.

D. Qin, Q. Sun, R. Wang, D. Ma, and M. Liu, “Adaptive bidirectional droop control for electric vehicles parking with vehicle-to-grid service in microgrid,” CSEE Journal of Power and Energy Systems, vol. 6, no. 4, pp. 793–805, 2020.

W. Hoiles and V. Krishnamurthy, “Nonparametric demand forecasting and detection of energy aware consumers,” IEEE Transactions on Smart Grid, vol. 6, no. 2, pp. 695–704, 2015.

D. Papadaskalopoulos and G. Strbac, “Decentralized Participation of Flexible Demand in Electricity Markets - Part II: Application With Electric Vehicles and Heat Pump Systems,” IEEE Transactions on Power Systems, vol. 28, no. 4, pp. 3658–3666, 2013.

M. M. Mahfouz and M. R. Iravani, “Grid-Integration of Battery-Enabled DC Fast Charging Station for Electric Vehicles,” IEEE Transactions on Energy Conversion, vol. 35, no. 1, pp. 375–385, 2020.

H. U. R. Habib, U. Subramaniam, A. Waqar, B. S. Farhan, K. M. Kotb, and S. Wang, “Energy cost optimization of hybrid renewables based V2G microgrid considering multi objective function by using artificial bee colony optimization,” IEEE Access, vol. 8, pp. 62076–62093, 2020.

M. B. Arias and S. Bae, “Electric vehicle charging demand forecasting model based on big data technologies,” Applied Energy, vol. 183, pp. 327–339, 2016.

A. Morales-Acevedo, “Forecasting future energy demand: Electrical energy in Mexico as an example case,” Energy Procedia, vol. 57, pp. 782–790, 2014.

D. Trujillo and E. Torres, “Respuesta de demanda de energía por introducción de vehículos eléctricos: estado del arte,” I+D Tecnológico, vol. 16, no. 1, pp. 5–11, 2020.

I. E. A. International and E. Agency, “Global EV Outlook 2018 Towards cross-modal electrification,” Global EV Outlook 2018, 2018.

F. Rassaei, W. S. Soh, and K. C. Chua, “Demand Response for Residential Electric Vehicles with Random Usage Patterns in Smart Grids,” IEEE Transactions on Sustainable Energy, vol. 6, no. 4, pp. 1367–1376, 2015.

J. Asamer, A. Graser, B. Heilmann, and M. Ruthmair, “Sensitivity analysis for energy demand estimation of electric vehicles,” Transportation Research Part D: Transport and Environment, vol. 46, pp. 182–199, 2016.

N. Z. Xu and C. Y. Chung, “Challenges in Future Competition of Electric Vehicle Charging Management and Solutions,” IEEE Transactions on Smart Grid, vol. 6, no. 3, pp. 1323–1331, 2015.

D. Niculae, M. Iordache, M. Stanculescu, M. Lavinia Bobaru, and S. Deleanu, “A Review of Electric Vehicles Charging Technologies Stationary and Dynamic,” The 11th International Symposium on Advanced Topics in Electrical Engineering, pp. 9–12, 2019.

M. Sternad, M. Cifrain, D. Watzenig, G. Brasseur, and M. Winter, “Condition monitoring of lithium-ion batteries for electric and hybrid electric vehicles,” Elektrotechnik und Informationstechnik, vol. 126, no. 5, pp. 186–193, 2009.

F. Rassaei, W. S. Soh, and K. C. Chua, “Distributed Scalable Autonomous Market-Based Demand Response via Residential Plug-In Electric Vehicles in Smart Grids,” IEEE Transactions on Smart Grid, vol. 9, no. 4, pp. 3281–3290, 2018.

J. Gomez Marín, S. Carvajal, and A. Arango Manrique, “Programas de gestión de demanda de electricidad para el sector residencial en Colombia: Enfoque Sistémico,” Energética, vol. 46, pp. 73–83, 2015.

S. Chen and C. C. Liu, “From demand response to transactive energy: state of the art,” Journal of Modern Power Systems and Clean Energy, vol. 5, no. 1, pp. 10–19, 2017.

O. Andonian, M. Rópolo, and E. Rabbia, “Un modelo de programación de inversiones,” in XXXVII Jornadas nacionales de profesores universitarios de matemática financiera, pp. 1–18, 2016.

D. Trujillo, F. Mosquera, and E. Garcia, “Análisis de viabilidad de microrredes eléctricas con alta penetración de recursos renovables en zonas urbanas: caso de estudio condominios residenciales,” Enfoque UTE, vol. 12, no. 2, 2021.

J. A. Guacaneme, D. Velasco, and C. L. Trujillo, “Revisión de las características de sistemas de almacenamiento de energía para aplicaciones en micro redes,” Informacion Tecnologica, vol. 25, no. 2, pp. 175–188, 2014.

G. López Jiménez, I. Isaac, J. González Sanchez, and H. Cardona Agudelo, “Integración de energias renovables (solar fotovoltaica) en campus upb laureles-micro red inteligente,” Investigaciones Aplicadas, vol. 8, no. 2, pp. 152–159, 2014.

D. Jarrín and M. Garcia, “Gestión energética para una óptima respuesta a la demanda en micro redes inteligentes,” 2017 International Conference on Information Systems and Computer Science (INCISCOS), pp. 14–20, 2017.

I. Arul Doss Adaikalam and C. K. Babulal, “Demand Response Program with Different Elasticities,” Iranian Journal of Science and Technology - Transactions of Electrical Engineering, vol. 44, no. 3, pp. 1165–1171, 2020.

J. Inga-Ortega, E. Inga-Ortega, C. Gómez, and R. Hincapié, “Electrical load curve reconstruction required for demand response using compressed sensing techniques,” 2017 IEEE PES Innovative Smart Grid Technologies Conference - Latin America, ISGT Latin America 2017, vol. 2017-Janua, pp. 1–6, 2017.

Y. Wang, Q. Chen, C. Kang, M. Zhang, K. Wang, and Y. Zhao, “Load profiling and its application to demand response: A review,” Tsinghua Science and Technology, vol. 20, no. 2, pp. 117–129, 2015.

Ž. Zore, L. Cˇ ucˇek, D. Širovnik, Z. Novak Pintaricˇ, and Z. Kravanja, “Maximizing the sustainability net present value of renewable energy supply networks,” Chemical Engineering Research and Design, vol. 131, pp. 245–265, 2018.

H. R. Omran, S. M. EL-Marsafy, F. H. Ashour, and E. F. Abadir, “Economic evaluation of aromatics production, a case study for financial model application in petrochemical projects,” Egyptian Journal of Petroleum, vol. 26, no. 4, pp. 855–863, 2017.

F. Morales, G. Carrasco, and G. Terranove, “La evaluación de proyectos de inversión: una perspectiva financiera,” Opuntia Brava, vol. 11, pp. 465–473, 2019.

M. C. Tato, “El Valor Actual Neto (VAN) como criterio fundamental de evaluación de negocios. (Spanish),” Economía y Desarrollo, vol. 128, no. 1, pp. 180–194, 2001.

X. Lei, T. Shiyun, D. Yanfei, and Y. Yuan, “Sustainable operationoriented investment risk evaluation and optimization for renewable energy project: a case study of wind power in China,” Annals of Operations Research, vol. 290, pp. 223–241, 2020.

S. S. Reddy, V. Sandeep, and C. M. Jung, “Review of stochastic optimization methods for smart grid,” Frontiers in Energy, vol. 11, no. 2, pp. 197–209, 2017.

Published

2021-07-21

How to Cite

Trujillo , D. ., & García Torres, E. M. (2021). Demand response due to the penetration of electric vehicles in a microgrid through stochastic optimization. IEEE Latin America Transactions, 100(XXX). Retrieved from https://latamt.ieeer9.org/index.php/transactions/article/view/5836