Mathematical modeling of electrochemical storage for incorporation in methods to optimize the operational planning of an interconnected micro grid

Journal of Zhejiang University: Science C

Volumn 11, Issue 9, 2010, Pages 737-750

  Mashhour, Elaheh ^a   Moghaddas Tafreshi, S M ^a  

^a K N TOOSI UNIVERSITY OF TECHNOLOGY   (Iran)

Author keywords

Distributed energy resources; Electrochemical storage; Micro grid; Operational planning

Indexed keywords

DISTRIBUTED ENERGY RESOURCES; ECONOMICAL EFFICIENCY; ELECTROCHEMICAL STORAGE; END CONSUMERS; LOW-VOLTAGE GRID; MATHEMATICAL MODELING; MICRO GRID; OPERATIONAL PLANNING; OPTIMIZATION MODELS; OPTIMIZATION PROBLEMS; TIME INTERVAL; TOTAL BENEFITS; WHOLESALE ENERGY MARKET;

MATHEMATICAL MODELS; OPTIMIZATION;

ENERGY RESOURCES;

EID: 78650123310     PISSN: 18691951     EISSN: 1869196X     Source Type: Journal    
DOI: 10.1631/jzus.C0910721     Document Type: Article

References (36)

1. Abu-Sharkh, S., Arnold, R.J., Kohler, J., Li, R., Markvart, T., Ross, J.N., Steemers, K., Wilson, P., Yao, R., 2006. Can microgrids make a major contribution to UK energy supply? Renew. Sustain. Energy Rev., 10(2):78-127. [doi:10.1016/j.rser.2004.09.013]
2. Agovic, K., Jokic, A., Bosch, P.P.J., 2005. Dispatching Power and Ancillary Services in Autonomous Network-Based Power Systems. IEEE Int. Conf. on Future Power Systems, p.1-6.
3. Biradar, S.K., Patil, R.A., Ullegaddi, M., 1998. Energy Storage System in Electricity Vehicle. IEEE Conf. on Power Quality, p.247-255.
4. Ceraolo, M., 2000. New dynamical models of lead-acid batteries. IEEE Trans. Power Syst., 15(4):1184-1190. [doi:10.1109/59.898088]
5. Ceraolo, M., Buonarota, A., Giglioli, R., Menga, P., Scarioni, V., 1992. An Electric Dynamic Model of Sodium Sulfur Batteries Suitable for Power System Simulations. 11th Int. Electric Vehicle Symp.
6. Christiansen, J.C., Dortolina, C.A., Bermudez, J.P., 2000. An Approach to Solve the Unit Commitment Problem Using Genetic Algorithm. IEEE Int. Society on Power Engineering (Sumer Meeting), p.261-266.
7. Divya, K.C., Østergaard, J., 2009. Battery energy storage technology for power systems: an overview. Electr. Power Syst. Res., 79(4):511-520. [doi:10.1016/j.epsr. 2008.09.017]
8. Djapic, P., Ramsay, C., Pudjianto, D., Strbac, G., Mutale, J., Jenkins, N., Allan, R., 2007. Taking an active approach. IEEE Power Energy Mag., 5(4):68-77. [doi:10.1109/ MPAE.2007.376582]
9. Dondi, P., Beyoumi, D., Haederli, C., Julian, D., Suter, M., 2002. Network integration of distributed power generation. J. Power Source, 106(1-2):1-9. [doi:10.1016/S0378- 7753(01)01031-X]
10. Erdinc, O., Vural, B., Uzunoglu, M., 2009. A Dynamic Lithiumm- Ion Battery Model Considering the Effects of Temperature and Capacity Fading. IEEE Int. Conf. on Clean Electrical Power, p.383-386. [doi:10.1109/ICCEP. 2009.5212025]
11. Fahrioglu, M., Alvearado, F., 2001. Using utility information to calibrate customer demand management behavior models. IEEE Trans. Power Syst., 16(2):317-322. [doi:10.1109/59.918305]
12. Gen, M., Cheng, R., 2000. Genetic Algorithms and Engineering Optimization. John Wiley & Sons, Inc., New York, USA.
13. Giglioli, R., Buonarota, A., Menga, P., Ceraolo, M., 1990. Charge and Discharge Fourth Order Dynamic Model of the Lead-Acid Battery. 10th Int. Electric Vehicle Symp., p.371-382.
14. Gilat, A., 2007. MATLAB: an Introduction with Applications. John Wiley & Sons, Inc., New York, USA.
15. Habibollahzadeh, H., Bubenko, J.A., 1986. Application of decomposition techniques to short term operation planning of hydro thermal power systems. IEEE Trans. Power Syst., 1(1):41-47. [doi:10.1109/TPWRS.1986.433 4842]
16. Hatziargyrious, N., Tsikalakis, A., Vlachogiannis, J., Papadogiannis, K., Kariniotakis, G., Pecas, L.J., Oyarzabal, J., Moreira, C., Madureira, A., Cobelo, I., 2004. MICROGRIDS: Large Scale Integration of Micro-Generation to Low Voltage Grids. EU Contract ENK5-CT-2002-00610, Tech. Final Version, Deliverable-DC1, Part 1. Available from http://microgrids.power.ece.ntua.gr
17. Hatziargyrious, N.D., Dimeas, A., Tsikalakis, A.G., Pecas, L.J., Kariniotakis, G.K., Oyarzabal, J., 2005. Management of Microgrids in Market Environment. IEEE Int. Conf. on Future Power Systems, p.1-7.
18. Hernandez-Aramburo, C.A., Green, T.G., Mugniot, N., 2005. Fuel consumption minimization of a microgrid. IEEE Trans. Ind. Appl., 41(3):673-681. [doi:10.1109/TIA.2005. 847277]
19. Jiang, Z., Dougal, R.A., 2008. Hierarchical Microgrid Paradigm for Integration of Distributed Energy Resources. IEEE Power and Energy Society General Meeting on Conversion and Delivery of Electrical Energy in the 21st Century, p.1-8. [doi:10.1109/PES.2008.4596349]
20. Katiraei, F., Iravani, R., Hatziargyriou, N., Dimeas, A., 2008. Microgrids management: controls and operation aspects of microgrids. IEEE Power Energy Mag., 6(3):54-65. [doi:10.1109/MPE.2008.918702]
21. Kroposki, B., Lasseter, R., Ise, T., Morozumi, S., Papathanassiou, S., Hatziargyriou, N., 2008. A look at microgrid technologies and testing projects from around the world: making microgrids work. IEEE Power Energy Mag., 6(3):40-53. [doi:10.1109/MPE.2008.918718]
22. Li, H., Li, Y., Li, Z., 2007. A multiperiod energy acquisition model for a distribution company with distributed generation and interruptible load. IEEE Trans. Power Syst., 22(2):588-596. [doi:10.1109/TPWRS.2007.894862]
23. Medora, N.K., Kusko, A., 2006. An Enhanced Dynamic Battery Model of Lead-Acid Batteries Using Manufacturers' Data. IEEE 28th Annual Int. Conf. on Telecommunications Energy, p.1-8.
24. Moghaddas-Tafreshi, S.M., Mashhour, E., 2009. Distributed generation modeling for power flow studies and a threephase unbalanced power flow solution for radial distribution systems considering distributed generation. Electr. Power Syst. Res., 79(4):680-686. [doi:10.1016/j.epsr. 2008.10.003]
25. Mohamed, A.A., Koivo, H.N., 2007. System Modeling and Online Optimal Management of Microgrid Using Multiobjective Optimization. IEEE Int. Conf. on Clean Electrical Power, p.148-153. [doi:10.1109/ICCEP.2007.384 202]
26. Oshima, T., Atsumi, S., Takayama, T., Okuno, A., 2005. NaS Battery Installation in Japan. Proc. Annual Meeting of Electricity Storage Association.
27. Paloheimo, H., Omidiora, M., 2009. A Feasibility Study on Compressed Air Energy Storage System for Portable Electrical and Electronic Devices. IEEE Int. Conf. on Clean Electrical Power, p.355-362. [doi:10.1109/ICCEP. 2009.5212029]
28. Pecas Lopes, J.A., Hatziargyriou, N., Mutale, J., Djapic, P., Jenkins, N., 2007. Integrating distributed generation into electric power systems: a review of drivers, challenges and opportunities. Electr. Power Syst. Res., 77(9):1189-1203. [doi:10.1016/j.epsr.2006.08.016]
29. Pudjianto, D., Strbac, G., Overbeeke, F.V., Androutsos, A.I., Larrabe, Z., Sarvaiva, J.T., 2005. Investigation of Regulatory, Commercial, Economics and Environmental Issues in Microgrids. IEEE Int. Conf. on Future Power Systems, p.1-6.
30. Robalino, D.M., Kumar, G., Uzoechi, L.O., Chukwu, U.C., Mahajan, S.M., 2009. Design of a Docking Station for Solar Charged Electric and Fuel Cell Vehicles. IEEE Int. Conf. on Clean Electrical Power, p.655-660. [doi:10. 1109/ICCEP.2009.5211977]
31. Rong, P., Pedram, M., 2006. Dynamic lithium-ion battery model for system simulation. IEEE Trans. VLSI Syst., 14(5):441-451. [doi:10.1109/TVLSI.2006. 876094]
32. Sun, Y.H., Jou, H.L., Wu, J.C., 2008. Multilevel Peukert Equations Based Residual Capacity Estimation Method for Lead-Acid Battery. IEEE Int. Conf. on Sustainable Energy Technologies, p.101-105. [doi:10.1109/ICSET. 2008.4746980]
33. Swarup, K.S., Yamashiro, S., 2002. Unit commitment solution methodology using genetic algorithm. IEEE Trans. Power Syst., 17(1):87-91. [doi:10.1109/59.982197]
34. Tsikalakis, A.G., Hatziargyriou, N.D., 2008. Centralized control for optimizing microgrids operation. IEEE Trans. Energy Conv., 23(1):241-248. [doi:10.1109/TEC.2007. 914686]
35. Yamin, H.Y., 2004. Review on methods of generation scheduling in electric power systems. Electr. Power Syst. Res., 69(2-3):227-248. [doi:10.1016/j.epsr. 2003.10.002]
36. Yang, P.C., Yang, H.T., Huang, C.L., 1996. Solving the unit commitment problem with a genetic algorithm through a constraint satisfaction technique. Electr. Power Syst. Res., 37(1):55-65. [doi:10.1016/0378-7796(96)01036-X]