Abstract
This chapter is intended to identify grid operational management and control strategies that should be available to deal with a large-scale deployment of electric plug-in vehicles (EVs). EVs are high flexible loads that can be used as mobile storage devices, thus being capable of providing several power system services [1]. In fact, EV batteries when in charging mode can behave as controllable loads, providing spinning reserves as a result of a load decrease or even providing power back to the grid under the so-called vehicle-to-grid (V2G) mode, helping peak load demand management. In this way, the growing prospects of an EV market expansion may strengthen the concepts that aim at the active grid management.
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Notes
- 1.
As the V2G mode of operation (described in Sect. 6.2.1) is the most aggressive mode for charging EV, due to possible implications with EV batteries’ life cycle, this option is not likely to be a reality neither in the short run nor in the medium term. Only in the very long term, when battery technology has reached a high maturation stage, this strategy may be adopted. For this reason, the V2G mode of operation was neither considered in the development of Methodologies 1 and 2 nor in the implementation of these approaches in the steady-state algorithms presented.
- 2.
The lower electricity price period assumed was that of the dual tariff policy currently implemented in Portugal: 22–8 h. More information can be found in http://www.edpsu.pt/pt/particulares/tarifasehorarios/ (in Portuguese).
- 3.
All the required power flows were run using the PSS/E software.
- 4.
The optimization problem was solved using LINGO 13.0, which is an optimization modeling software that includes a set of built-in solvers for linear, nonlinear, quadratic, quadratically constrained, second-order cone, stochastic, and integer optimization. More information can be found in http://www.lindo.com/index.php?option=com_content&view=article&id=2&Itemid=10
- 5.
“Flexible EVs” are the EVs whose owners adhered to the smart charging scheme.
- 6.
“Inflexible EVs” are the EVs whose owners adhered to the dumb charging or multiple tariff schemes.
- 7.
“Mandatory load” is the conventional load of the network plus the load from the EV whose owners adhered to the dumb charging or multiple tariff schemes.
- 8.
All the required power flows were run using the PSS/E software.
- 9.
Fortran is a general-purpose, procedural, imperative programming language that is especially suited to numeric computation and scientific computing developed by IBM in the 1950s.
References
Kempton W, Tomic J (2005) Vehicle-to-grid power fundamentals: calculating capacity and net revenue. J Power Sources 144:268–279
Lopes JAP et al (2007) Integrating distributed generation into electric power systems: a review of drivers, challenges and opportunities. Electric Power Syst Res 77:1189–1203
Gil NJ, Lopes JAP (2007) Hierarchical frequency control scheme for islanded multi-microgrids operation. In: Power Tech, 2007 IEEE, Lausanne, p 473–478
Lopes JAP et al (2006) Defining control strategies for MicroGrids islanded operation. IEEE Trans Power Syst 21:916–924
Bending S et al (2010) Specification for an enabling smart technology. Deliverable D1.1 of the European Project MERGE, August 2010
Guille C, Gross G (2009) A conceptual framework for the vehicle-to-grid (V2G) implementation. Energy Policy 37:4379–4390
Lopes JAP et al (2011) Integration of electric vehicles in the electric power system. Proc IEEE 99:168–183
Lopes JAP et al (2005) Microgrids black start and islanded operation. Presented at the 15th PSCC, Liège, Belgium
European Network of Transmission System Operators for Electricity (ENTSO-E, formerly UCTE) (2004) Operation Handbook. Available: https://www.entsoe.eu/resources/publications/system-operations/operation-handbook/
Barsali S et al (2002) Control techniques of dispersed generators to improve the continuity of electricity supply. In: Power Engineering Society Winter Meeting, 27-31 January, 2002, New York, NY, USA, IEEE, vol 2, p 789–794
Kundur P (1994) Power system stability and control. McGraw-Hill, New York, NY
Madureira AG (2010) Coordinated and optimized voltage management of distribution networks with multi-microgrids. Ph.D., Faculty of Engineering, Universidade do Porto
AGM Battery Technology: Lithium-ion Cell ICR34490HC—Product Datasheet. Available: http://www.agmbatteries.com/documents/ICR34490HC.pdf
Lopes JAP et al (2009) Identifying management procedures to deal with connection of electric vehicles in the grid. In: PowerTech, 2009 IEEE, Bucharest, p 1–8
Clement-Nyns K et al (2010) The impact of charging plug-in hybrid electric vehicles on a residential distribution grid. IEEE Trans Power Syst 25:371–380
Soares FJ (2011) Impact of the deployment of electric vehicles in grid operation and expansion. Ph.D. thesis, Department of Electrical and Computer Engineering, Faculty of Engineering, University of Porto, Porto
Ball R et al (2010) Modelling electric storage devices for EV. Deliverable D2.1 of the European Project MERGE, January 2010
Inquérito à mobilidade da população residente. INE - Instituto Nacional de Estatística, 2000 (in Portuguese)
Fisz M (1980) Probability theory and mathematical statistics. Krieger Pub. Co., Huntington, NY
Karlin S, Rostand F (1969) Initiation aux processus aléatoires. Dunod, Paris
Rozanov YA (1973) Procesos Aleatorios: Editorial Mir Moscu
Bittanti S, De Nicolao G (1991) Markovian representations of cyclostationary processes. In: Gerencséer L, Caines P (eds) Topics in stochastic systems: modelling, estimation and adaptive control, vol 161. Springer, Berlin, pp 31–46
Soares FJ et al (2011) A stochastic model to simulate electric vehicles motion and quantify the energy required from the grid. Presented at the PSCC, Stockholm, Sweden
Almeida PMR (2011) Impact of vehicle-to-grid in the power system dynamic behaviour. Ph.D. thesis, Department of Electrical and Computer Engineering, Faculty of Engineering, University of Porto, Porto
Siemens PTI - Software Solutions (2009) PSS®E 32.0 Program Application Guide: Volume II. Siemens Energy, Inc., Power Technologies International
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Soares, F.J., Almeida, P.M.R., Lopes, J.A.P. (2013). Advanced Models and Simulation Tools to Address Electric Vehicle Power System Integration (Steady-State and Dynamic Behavior). In: Garcia-Valle, R., Peças Lopes, J. (eds) Electric Vehicle Integration into Modern Power Networks. Power Electronics and Power Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-0134-6_6
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