Zum Hauptinhalt springen
Artikel
Lizenziert
Nicht lizenziert Erfordert eine Authentifizierung

High Penetration of Electrical Vehicles in Microgrids: Threats and Opportunities

  • EMAIL logo und
Veröffentlicht/Copyright: 16. September 2014

Abstract

Given that the microgrid concept is the building block of future electric distribution systems and electrical vehicles (EVs) are the future of transportation market, in this paper, the impact of EVs on the performance of microgrids is investigated. Demand-side participation is used to cope with increasing demand for EV charging. The problem of coordination of EV charging and discharging (with vehicle-to-grid (V2G) functionality) and demand response is formulated as a market-clearing mechanism that accepts bids from the demand and supply sides and takes into account the constraints put forward by different parts. Therefore, a day-ahead market with detailed bids and offers within the microgrid is designed whose objective is to maximize the social welfare which is the difference between the value that consumers attach to the electrical energy they buy plus the benefit of the EV owners participating in the V2G functionality and the cost of producing/purchasing this energy. As the optimization problem is a mixed integer nonlinear programming one, it is decomposed into one master problem for energy scheduling and one subproblem for power flow computation. The two problems are solved iteratively by interfacing MATLAB with GAMS. Simulation results on a sample microgrid with different residential, commercial and industrial consumers with associated demand-side biddings and different penetration level of EVs support the proposed formulation of the problem and the applied methods.

Nomenclature

Acronyms
DSB

Demand-side bidding

CCH

Constrained charging

UCCH

Unconstrained charging

SDR

Smart charging with demand response

SCH

Smart Charging

SOC

State of charge

CS

Compact Sedan

MS

Midsize Sedan

MSUV

Midsize SUV

FSUV

Full Size SUV

LT30

Light Truck EV 30

LT40

Light Truck EV 40

Indices
c

Index of price-responsive consumers

t

Time

LP

Index of load priorities

g

Index of generating units

v

Index of electric vehicles

i

Index of system buses

Variables and functions
Plowc,t

Low priority power consumed by consumer c at period t

Pmedc,t

Medium priority power consumed by consumer c at period t

Pcrtc,t

High priority power consumed by consumer c at period t

Pc,t

Total power consumed by consumer c at period t

GSt

Consumers gross surplus at period t

Pg,t

Power output of unit g at period t

PGi,t

Injected power at bus i at period t

PDi,t

Total power consumed at bus i at period t

θijt

Voltage angle difference between buses i and j at period t

ug,t

Binary variable that is equal to 1 if unit g is online and 0 otherwise at period t

Pusnt

Power purchased from upstream network at period t

OCt

Operation cost at period t

uchv,t

Binary variable that is equal to 1 if EV v is in charge state at period t

udchv,t

Binary variable that is equal to 1 if EV v is in discharge state at period t

uidlev,t

Binary variable that is equal to 1 if EV v is in idle state at period t

SOCv,t

State of charge of EV v at period t

Echv,t

Energy charged by EV v at period t

Edchv,t

Energy discharged by EV v at period t

VBt

Vehicles’ benefit at period t

Constants
α

Low priority demand proportion

β

Medium priority demand proportion

γ

High priority demand proportion

DLc,t

Demand by consumer c at period t

Dmaxc,t

Maximum consumable power by consumer c at period t

πLPc

Price for the energy bid submitted by consumer c

λt

Price of power purchased from upstream network at period t

Pmaxg

Maximum power output of unit g

Pming

Minimum power output of unit g

Ibatt

Charge and discharge current

Cbattv

Capacity of battery of EV v

Av,t

Presence state of EV v at parking site at period t

Emaxv

Battery pack size

Bij

Absolute value of the imaginary part of the admittance of line (i, j)

Mi,c

Mapping of the set of consumers into the set of buses

Li,v

Mapping of the set of electric vehicles into the set of buses

Ni,g

Mapping of the set of generators into the set of buses

Davg

Average demand

References

1. DerakhshandehSY, MasoumAS, DeilamiS, MasoumMA, Hamedani GolshanME. Coordination of generation scheduling with PEVs charging in industrial microgrids. IEEE Trans Power Syst2013;28:345161.10.1109/TPWRS.2013.2257184Suche in Google Scholar

2. IEEE Standard 1547.4. IEEE guide for design, operation, and integration of distributed resource island systems with electric power systems, July 2011.Suche in Google Scholar

3. AbdelazizMM, ShaabanMF, FaragHE, El-SaadanyEF. A multistage centralized control scheme for islanded microgrids with PEVs. IEEE Trans Sustainable Energy2014;59:92737.10.1109/TSTE.2014.2313765Suche in Google Scholar

4. GuoJY. Consumer adoption and impact models for plug-in hybrid electric vehicles in Wisconsin: part B: grid impact studies. Environmental and economic research and development program, executive summary report, 2010.Suche in Google Scholar

5. ZhangM, ChenJ. The energy management and optimized operation of electric vehicles based on microgrid. IEEE Trans Power Deliv2014;29:142735.10.1109/TPWRD.2014.2303492Suche in Google Scholar

6. TsikalakisAG, HatziargyriouND. Operation of microgrids with demand side bidding and continuity of supply for critical loads. Eur Trans Electrical Power2011;21:123854.10.1002/etep.441Suche in Google Scholar

7. TsikalakisAG, HatziargyriouND. Centralized control for optimizing microgrids operation. In: IEEE power and energy society general meeting, 2011:18.10.1109/PES.2011.6039737Suche in Google Scholar

8. SuW, WangJ, RohJ. Stochastic energy scheduling in microgrids with intermittent renewable energy resources. IEEE Trans Smart Grid2014;5:187683.10.1109/TSG.2013.2280645Suche in Google Scholar

9. XuNZ, ChungCY. Well-being analysis of generating systems considering electric vehicle charging. IEEE Trans Power Syst 2014;29:23112320.10.1109/TPWRS.2014.2307865Suche in Google Scholar

10. JinC, ShengX, GhoshP. Optimized electric vehicle charging with intermittent renewable energy sources. IEEE J Selected Top Signal Process 2014;PP:110.Suche in Google Scholar

11. GoranssonL, Karlsson S, Johnsson F. Integration of plug-in hybrid electric vehicles in a regional wind-thermal power system. Energy Policy2010;38:548292.10.1016/j.enpol.2010.04.001Suche in Google Scholar

12. HuangS, InfieldD. The potential of domestic electric vehicles to contribute to power system operation through vehicle to grid technology. In: Proceedings of the 44th international universities power engineering conference (UPEC), Glasgow, Scotland, 2009.Suche in Google Scholar

13. PalenskyP, DietrichD. Demand side management: demand response, intelligent energy systems, and smart loads. IEEE Trans Ind Inform2011;7:3818.10.1109/TII.2011.2158841Suche in Google Scholar

14. HopperN, GoldmanC, BharvirkarR, NeenanB. Customer response to day-ahead market hourly pricing: choices and performance. Ernst Orlando Lawrence Berkeley National Laboratory, Report No. LBNL-58114, 2006.10.1016/j.jup.2005.10.001Suche in Google Scholar

15. SuCL, KirschenDS. Quantifying the effect of demand response on electricity markets. IEEE Trans Power Syst2009;24:1199207.10.1109/TPWRS.2009.2023259Suche in Google Scholar

16. KirschenDS. Demand-side view of electricity markets. IEEE Trans Power Syst2003;18:5207.10.1109/TPWRS.2003.810692Suche in Google Scholar

17. RassentiSJ, Smith VL, Wilson BJ. Controlling market power and price spikes in electricity networks: demand-side bidding. Proc Nat Acad Sci2003;100:29983003.10.1073/pnas.0437942100Suche in Google Scholar PubMed PubMed Central

18. PatrickRH, WolakFA. Real-time pricing and demand-side participation in restructured electricity markets. In: Proceedings of the Conference on retail participation in competitive power markets, 2001.10.1007/978-1-4615-0833-5_23Suche in Google Scholar

19. NguyenDT, NegnevitskyM, de GrootM. Walrasian market clearing for demand response exchange. IEEE Trans Power Syst2012;27:53544.10.1109/TPWRS.2011.2161497Suche in Google Scholar

20. BrookeA, KendrickD, MeerausA, RamanR. GAMS, a user’s guide. Washington, DC: GAMS Development, 1998.Suche in Google Scholar

21. Amsterdam Power Exchange. Available at: http://www.apx.nlSuche in Google Scholar

22. PapathanassiouS, HatziargyriouN, StrunzK. A benchmark low voltage microgrid network. In: Proceedings of CIGRE symposium: power systems with dispersed generation, Athens, 2005.Suche in Google Scholar

23. RudionK, StyczynskiZA, HatziargyriouN, PapathanassiouS. Development of benchmarks for low and medium voltage distribution networks with high penetration of dispersed generation. In: Proceedings of MEPS conference, Wroclaw, Poland, 2006.Suche in Google Scholar

24. WangJ, LiuC, TonD, ZhouY, KimJ, VyasA. Impact of plug-in hybrid electric vehicles on power systems with demand response and wind power. Energy Policy2011;39:401621.10.1016/j.enpol.2011.01.042Suche in Google Scholar

25. LiZ, GuoQ, SunH, XinS, WangJ. A new real-time smart-charging method considering expected electric vehicle fleet connections. IEEE Trans Power Syst 2014;PP:1–2.10.1109/TPWRS.2014.2311954Suche in Google Scholar

26. SiddiquiO. Assessment of achievable potential from energy efficiency and demand response programs in the US (2010–2030). Electric Power and Research Institute (EPRI), 2009. Available at: https://www.isa.org/WorkArea/DownloadAsset.aspx?id=123260.Suche in Google Scholar

Published Online: 2014-9-16
Published in Print: 2014-10-1

©2014 by De Gruyter

Heruntergeladen am 23.4.2026 von https://www.degruyterbrill.com/document/doi/10.1515/ijeeps-2014-0083/html?lang=de
Button zum nach oben scrollen