On the robustness of a multiperiod energy management system including electric vehicles and V2G operation

 

A. Jiménez-Marín, J. Pérez-Ruiz

 

2017/04/25

Abstract

In recent years, the potential capability of plug-in electric vehicles to offset the intermittency of renewable generation is being analyzed widely. In power systems literature, these electric vehicles are often merged into an aggregator, i.e. an agent responsible of their charging/discharging operation. However, the available power from the aggregator is likewise subject to uncertainty. In this paper, a robust linear programming problem is considered to model the power system operation. In order to clarify the influence of the electric vehicles on the solution, only the available power from the electric vehicles aggregator is taken into account. A multiperiod case study is used to show the behavior of the robust optimization framework in the solution of a multiperiod energy management system. The role of the uncertainty level and different criteria to reduce the cost of uncertainty are also analyzed.

Published in: Renewable Energy & Power Quality Journal (RE&PQJ, Nº. 15)
Pages: 734-739 Date of Publication: 2017/04/25
ISSN: 2172-038X Date of Current Version:

REF: 452-17

Issue Date: April 2017
DOI:10.24084/repqj15.452 Publisher: EA4EPQ

Authors and affiliations

A. Jiménez-Marín, J. Pérez-Ruiz
Department of Electrical Engineering. Universidad de Málaga. (Spain)

Key word

Energy management, electric vehicles, robust optimization, uncertainty level.

References

[1] C. Guille and G. Gross. “A conceptual framework for the vehicle-to-grid (V2G) implementation”, in Energy Policy 37 (2009), pp. 4379-4390.
[2] J.A. Peças Lopes, F.P. Soares and P.M. Rocha Almeida. “Integration of electric vehicles in the electric power system” in Proceedings of the IEEE 99 (2011), No. 1, pp. 168-183.
[3] K. Clement-Nyns, E. Haesen, and J. Driesen, “The Impact of Charging Plug-In Hybrid Electric Vehicles on a Residential Distribution Grid,” in IEEE Transactions on Power Systems 25 (2010), No. 1, pp. 371-380.
[4] K. Clement-Nyns, E. Haesen, and J. Driesen, “The impact of vehicle-to-grid on the distribution grid”, in Electric Power Systems Research 81 (2011), pp. 185-192.
[5] J. Romero-Ruiz, J. Pérez-Ruiz, S. Martin, J.A. Aguado and S. de la Torre. “Probabilistic congestion management using EVs in a smart grid with intermittent renewable generation” in Electric Power Systems Research 137 (2016), pp. 155-162.
[6] J.M. Morales and J. Pérez-Ruiz. “Point estimate schemes to solve the probabilistic power flow” in IEEE Transactions on Power Systems 22 (2007), No. 4, pp. 1594-1601.
[7] A. Ben-Tal, L. El Ghaoui and A. Nemirovski. Robust Optimization (Princeton Series in Applied Mathematics). Princeton University Press. 2015.
[8] D. Bertsimas, D.B. Brown and C. Caramanis. “Theory and Applications of Robust Optimization”, in SIAMM Review 53 (2011), No. 3, pp. 464-501.
[9] C. Battistelli, L. Baringo and A.J. Conejo. “Optimal energy management of small electric energy systems including V2G facilities and renewable energy sources”, in Electric Power Systems Research 92 (2012), pp. 50-59.
[10] A.L. Soyster. “Convex programming with set-inclusive constraints and applications to inexact linear programming”, in Operations Research 21 (1973), No. 5, pp. 1154-1157.
[11] D. Bertsimas and M. Sim, “The price of robustness,” in Operations Research 52 (2004), no. 1, pp. 35-53, 2004.
[12] R.E. Rosenthal. GAMS, A User’s Guide. GAMS Development Corporation. Washington DC, 2016.
Available at: www.gams.com/help/topic/gams.doc/userguides/GAMSUsersGuide.pdf