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Energy Management in Microgrids with Plug-in Electric Vehicles, Distributed Energy Resources and Smart Home Appliances

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Plug In Electric Vehicles in Smart Grids

Part of the book series: Power Systems ((POWSYS))

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.

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References

  1. Asmus P (2010) Microgrids, virtual power plants and our distributed energy future. Energ J 23(10):72–82

    Google Scholar 

  2. 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

    Article  Google Scholar 

  3. 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

    Article  Google Scholar 

  4. Kriett PO, Salani M (2012) Optimal control of a residential microgrid. Energy 42(1):321–330

    Article  Google Scholar 

  5. Naraharisetti PK, Karimi I, Anand A, Lee DY (2011) A linear diversity constraint application to scheduling in microgrids. Energy 36(7):4235–4243

    Article  Google Scholar 

  6. 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

    Article  Google Scholar 

  7. 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

    Article  Google Scholar 

  8. 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

    Google Scholar 

  9. 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

    Article  Google Scholar 

  10. Rastegar M, Fotuhi-Firuzabad M, Aminifar F (2012) Load commitment in a smart home. Appl Energ 96:45–54

    Article  Google Scholar 

  11. 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

    Article  Google Scholar 

  12. 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

    Article  Google Scholar 

  13. 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

    Article  Google Scholar 

  14. Sioshansi R, Denholm P (2010) The value of plug-in hybrid electric vehicles as grid resources. Energ J 31(3):1–24

    Article  Google Scholar 

  15. 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

    Google Scholar 

  16. 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

    Article  Google Scholar 

  17. 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

    Article  Google Scholar 

  18. Kristoffersen TK, Capion K, Meibom P (2011) Optimal charging of electric drive vehicles in a market environment. Appl Energ 88(5):1940–1948

    Article  Google Scholar 

  19. 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

    Article  Google Scholar 

  20. 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

  21. 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

    Google Scholar 

  22. 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

    Article  Google Scholar 

  23. 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

    Article  Google Scholar 

  24. Motors T (2014) Supercharger. http://www.teslamotors.com/supercharger. Accessed 10 Jun 2014

  25. U.S. Department of Transportation (2011) 2009 National household travel survey version 2.1

    Google Scholar 

  26. 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

  27. California ISO (2014) Daily renewable watch, hourly breakdown of renewable resources. http://content.caiso.com/green/renewrpt/20140315_DailyRenewablesWatch.txt. Accessed 10 May 2014

  28. 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

  29. Pacific Gas and Electric (PG&E) (2013) Hourly electric commodity prices. http://www.pge.com/nots/rates/tariffs/pxdy0212.html. Accessed 04 May 2013

  30. 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

  31. Pasific Gas and Electric (PG&E) (2002) Residential load profiles. http://www.pge.com/nots/rates/2002_static.shtml. Accessed 01 Jun 2014

  32. Motors T (2014) Model S specs. http://www.teslamotors.com/models/design. Accessed 16 May 2014

  33. Motors T (2014) Features and specs. http://www.teslamotors.com/models/features#/battery. Accessed 02 Jun 2014

  34. Motors T (2014) How long does charging take? http://www.teslamotors.com/goelectric#charging. Accessed 02 Jun 2014

  35. U.S. Environmental Protection Agency (EPA) (2012) Average annual emissions and fuel consumption for gasoline-fueled passenger cars and light trucks report

    Google Scholar 

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Correspondence to Okan Arslan .

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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

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  • DOI: https://doi.org/10.1007/978-981-287-302-6_11

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-287-301-9

  • Online ISBN: 978-981-287-302-6

  • eBook Packages: EnergyEnergy (R0)

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