Abstract
Smart Grid is transforming the way energy is being generated and distributed today, leading to the development of environment-friendly, economic and efficient technologies such as plug-in electric vehicles (PEVs), distributed energy resources and smart appliances at homes. Among these technologies, PEVs pose both a risk by increasing the peak load as well as an opportunity for the existing energy management systems by discharging electricity with the help of Vehicle-to-grid (V2G) technology. These complications, together with the PEV battery degradation, compound the challenge in the management of existing energy systems. In this context, microgrids are proposed as an aggregation unit to smartly manage the energy exchange of these different state-of-the-art technologies. In this chapter, we consider a microgrid with a high level of PEV penetration into the transportation system, widespread utilization of smart appliances at homes, distributed energy generation and community-level electricity storage units. We propose a mixed integer linear programming energy management optimization model to schedule the charging and discharging times of PEVs, electricity storage units, and running times of smart appliances. Our findings show that simultaneous charging and discharging of PEV batteries and electricity storage units do not occur in model solutions due to system energy losses.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Asmus P (2010) Microgrids, virtual power plants and our distributed energy future. Energ J 23(10):72–82
Morais H, Kàdàr P, Faria P, Vale ZA, Khodr H (2010) Optimal scheduling of a renewable micro-grid in an isolated load area using mixed-integer linear programming. Renew Energ 35(1):151–156
Khodr H, Halabi NE, García-Gracia M (2010) Intelligent renewable microgrid scheduling controlled by a virtual power producer: a laboratory experience. Renew Energ 48:269–275
Kriett PO, Salani M (2012) Optimal control of a residential microgrid. Energy 42(1):321–330
Naraharisetti PK, Karimi I, Anand A, Lee DY (2011) A linear diversity constraint application to scheduling in microgrids. Energy 36(7):4235–4243
Moghaddam AA, Seifi A, Niknam T, Pahlavani MRA (2011) Multi-objective operation management of a renewable MG (micro-grid) with back-up micro-turbine/fuel cell/battery hybrid power source. Energy 36(11):6490–6507
Basu AK, Chowdhury S, Chowdhury S, Paul S (2011) Microgrids: energy management by strategic deployment of DERs—a comprehensive survey. Renew Sustain Energ Rev 15(9):4348–4356
Xiong G, Chen C, Kishore S, Yener A (2011) Smart (in-home) power scheduling for demand response on the smart grid. In: Innovative smart grid technologies (ISGT), IEEE PES, pp 1–7
Pedrasa MAA, Spooner TD, MacGill IF (2011) A novel energy service model and optimal scheduling algorithm for residential distributed energy resources. Electr Power Syst Res 81(12):2155–2163
Rastegar M, Fotuhi-Firuzabad M, Aminifar F (2012) Load commitment in a smart home. Appl Energ 96:45–54
Elma O, Selamogullari US (2012) A comparative sizing analysis of a renewable energy supplied stand-alone house considering both demand side and source side dynamics. Appl Energ 96:400–408
Fernandes C, Frías P, Latorre JM (2012) Impact of vehicle-to-grid on power system operation costs: the Spanish case study. Appl Energ 96:194–202
Arslan O, Karasan OE (2013) Cost and emission impacts of virtual power plant formation in plug-in hybrid electric vehicle penetrated networks. Energy 60:116–124
Sioshansi R, Denholm P (2010) The value of plug-in hybrid electric vehicles as grid resources. Energ J 31(3):1–24
Sioshansi R (2012) Modeling the impacts of electricity tariffs on plug-in hybrid electric vehicle charging, costs, and emissions. Oper Res 43(4):1199–1204
Su W, Chow MY (2012) Computational intelligence-based energy management for a large-scale PHEV/PEV enabled municipal parking deck. Appl Energ 96:171–182
Saber A, Venayagamoorthy G (2012) Resource scheduling under uncertainty in a smart grid with renewables and plug-in vehicles. IEEE Syst J 6(1):103–109
Kristoffersen TK, Capion K, Meibom P (2011) Optimal charging of electric drive vehicles in a market environment. Appl Energ 88(5):1940–1948
Sousa T, Morais H, Soares J, Vale Z (2012) Day-ahead resource scheduling in smart grids considering vehicle-to-grid and network constraints. Appl Energ 96:183–193
Arslan O, Yildiz B, Karasan OE (2014) Impacts of battery characteristics, driver preferences and road network features on travel costs of a plug-in hybrid electric vehicle (PHEV) for long-distance trips. In: Energy policy, http://dx.doi.org/10.1016/j.enpol.2014.08.015
Arslan O, Yildiz B, Karasan OE (2014) Minimum cost path problem for plug-in hybrid electric vehicles. In: Technical report, Bilkent University, Department of Industrial Engineering
Peterson SB, Apt J, Whitacre J (2010) Lithium-ion battery cell degradation resulting from realistic vehicle and vehicle-to-grid utilization. J Power Sources 195:2385–2392
Shiau CSN, Samaras C, Hauffe R, Michalek JJ (2009) Impact of battery weight and charging patterns on the economic and environmental benefits of plug-in hybrid vehicles. Energ Policy 37:2653–2663
Motors T (2014) Supercharger. http://www.teslamotors.com/supercharger. Accessed 10 Jun 2014
U.S. Department of Transportation (2011) 2009 National household travel survey version 2.1
U.S. Department of Energy, Energy Efficiency and Renewable Energy (2013) Federal energy management program. http://www1.eere.energy.gov/femp/technologies/derchp_derbasics.html. Accessed 01 Aug 2013
California ISO (2014) Daily renewable watch, hourly breakdown of renewable resources. http://content.caiso.com/green/renewrpt/20140315_DailyRenewablesWatch.txt. Accessed 10 May 2014
National Oceanic and Atmospheric Administration (2014) Comparative climatic data. http://ols.nndc.noaa.gov/plolstore/plsql/olstore.prodspecific?prodnum=C00095-PUB-A0001. Accessed 30 May 2014
Pacific Gas and Electric (PG&E) (2013) Hourly electric commodity prices. http://www.pge.com/nots/rates/tariffs/pxdy0212.html. Accessed 04 May 2013
U.S. Department of Energy (2014) Estimating appliance and home electronic energy use. http://www.energy.gov/energysaver/articles/estimating-appliance-and-home-electronic-energy-use Accessed 24 May 2014
Pasific Gas and Electric (PG&E) (2002) Residential load profiles. http://www.pge.com/nots/rates/2002_static.shtml. Accessed 01 Jun 2014
Motors T (2014) Model S specs. http://www.teslamotors.com/models/design. Accessed 16 May 2014
Motors T (2014) Features and specs. http://www.teslamotors.com/models/features#/battery. Accessed 02 Jun 2014
Motors T (2014) How long does charging take? http://www.teslamotors.com/goelectric#charging. Accessed 02 Jun 2014
U.S. Environmental Protection Agency (EPA) (2012) Average annual emissions and fuel consumption for gasoline-fueled passenger cars and light trucks report
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer Science+Business Media Singapore
About this chapter
Cite this chapter
Arslan, O., Karaşan, O.E. (2015). Energy Management in Microgrids with Plug-in Electric Vehicles, Distributed Energy Resources and Smart Home Appliances. In: Rajakaruna, S., Shahnia, F., Ghosh, A. (eds) Plug In Electric Vehicles in Smart Grids. Power Systems. Springer, Singapore. https://doi.org/10.1007/978-981-287-302-6_11
Download citation
DOI: https://doi.org/10.1007/978-981-287-302-6_11
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-287-301-9
Online ISBN: 978-981-287-302-6
eBook Packages: EnergyEnergy (R0)