A low-carbon dispatch model in a wind power integrated system considering wind speed forecasting and energy-environmental efficiency

Energies

Volumn 5, Issue 4, 2012, Pages 1245-1270

  Chen, Daojun ^a   Gong, Qingwu ^a   Zou, Bichang ^a   Zhang, Xiaohui ^a   Zhao, Jian ^a  

^a WUHAN UNIVERSITY   (China)

Author keywords

Low carbon dispatch model; PSO SA; Energy environmental efficiency; Wind power; Wind speed forecasting

Indexed keywords

DECISION MAKING; ELECTRIC POWER SYSTEM PROTECTION; ENERGY EFFICIENCY; FORECASTING; PARTICLE SWARM OPTIMIZATION (PSO); SIMULATED ANNEALING; WEATHER FORECASTING; WIND; WIND EFFECTS; WIND POWER;

ECONOMIC ENVIRONMENTAL DISPATCHES; ENVIRONMENTAL EFFICIENCY; LOW-CARBON DISPATCH MODELS; LOW-CARBON DISPATCHES; MULTI-OBJECTIVE DECISION-MAKING PROBLEMS; SIMULATED ANNEALING ALGORITHMS; WIND SPEED FORECASTING; WIND-SPEED FLUCTUATIONS;

ELECTRIC LOAD DISPATCHING;

EID: 84860879790     PISSN: None     EISSN: 19961073     Source Type: Journal    
DOI: 10.3390/en5041245     Document Type: Article

References (42)

1. [120] Gigawatt of Wind Turbines Globally Contribute to Secure Electricity Generation; World Wind Energy Association: Bonn, Germany. Available online: http://www.wwindea.org/home/index2.php?option=com_content&do_pdf=1&id=223 (accessed on 25 November 2010).
2. Ren, B.Q.; Jiang, C.W. A review on the economic dispatch and risk management considering wind power in the power market. Renew. Sustain. Energy Rev. 2009, 13, 2169-2174.
3. [2010] Chinese Wind Power Capacity Statistics; Chinese Wind Energy Association: Beijing, China. Available online: http://www.cwea.org.cn/download/display_info.asp?id=39 (accessed on 17 August 2011).
4. Chen, C.L.; Lee, T.Y.; Jan, R.M. Optimal wind-thermal coordination dispatch in isolated power systems with large integration of wind capacity. Energy Convers. Manag. 2006, 47, 18-19.
5. Miranda, V.; Hang, P.S. Economic dispatch model with fuzzy wind constraints and attitudes of dispatchers. IEEE Trans. Power Syst. 2005, 20, 2143-2145.
6. Hetzer, J.; Yu, D.C.; Bhattarai, K. An economic dispatch model incorporating wind power. IEEE Trans. Energy Convers. 2008, 23, 603-611.
7. Liu, X.; Xu, W. Minimum emission dispatch constrained by stochastic wind power availability and cost. IEEE Trans. Power Syst. 2010, 25, 1705-1713.
8. Foley, A.M.; Murguvlia, A.; Leahy, P.G.; McKeogh, E.J. Current methods and advances in forecasting of wind power generation. Renew. Energy 2012, 37, 1-8.
9. Pourmousavi, S.A.; Ardehali, M.M. Very short-term wind speed prediction: A new artificial neural network-markov chain model. Energy Convers. Manag. 2011, 52, 738-745.
10. Ackermann, T. Wind Power in Power System; John Wiley & Sons: London, UK, 2005.
11. Chen, Q.X.; Kang, C.Q.; Xia, Q. Modeling flexible operation mechanism of CO2 capture power plant and its effects on power-system operation. IEEE Trans. Energy Convers. 2010, 25, 853-861.
12. Maria, M.B.; Pardo, A. What you should know about carbon markets. Energies 2008, 1,120-153.
13. Carrion, M.; Arroyo, J.M. A computationally efficient mixed-integer linear formulation for the thermal unit commitment problem. IEEE Trans. Power Syst. 2006, 21, 1371-1378.
14. Han, X.S.; Gooi, H.B.; Kirschen, D.S. Dynamic economic dispatch: Feasible and optimal solutions. IEEE Trans. Power Syst. 2001, 16, 22-28.
15. Chaturvedi, K.T.; Manjaree, P.; Laxmi, S. Self-organizing hierarchical particle swarm optimization for nonconvex economic dispatch. IEEE Trans. Power Syst. 2008, 23, 1079-1087.
16. Liu, D.R.; Cai, Y. Taguchi method for solving the economic dispatch problem with nonsmooth cost functions. IEEE Trans. Power Syst. 2005, 20, 2006-2014.
17. Lu, Y.L.; Zhou, J.Z.; Qin, H.; Wang, Y.; Zhang, Y.C. Environmental/Economic dispatch problem of power system by using an enhanced multi-objective differential evolution algorithm. Energy Convers. Manag. 2011, 52, 1175-1183.
18. Abido, M.A. A niched pareto genetic algorithm for multiobjective environmental/economic dispatch. Int. J. Electr. Power Energy Syst. 2003, 25, 97-105.
19. Abido, M.A. Multiobjective particle swarm optimization for environmental/economic dispatch problem. Electr. Power Syst. Res. 2009, 79, 1105-1113.
20. Talaq, J.H.; El-Hawary, F.; El-Hawary, M.E. Summary of environmental/economic dispatch algorithms. IEEE Trans. Power Syst. 1994, 9, 1508-1516.
21. King, T.D.; El-Hawary, M.E.; El-Hawary, F. Optimal environmental dispatching of electric power systems via an improved Hopfield neural network model. IEEE Trans. Power Syst. 1995, 10, 1559-1565.
22. Cai, J.J.; Ma, X.Q.; Li, Q.; Li, L.X.; Peng, H.P. A multi-objective chaotic particle swarm optimization for environmental/economic dispatch. Energy Convers. Manag. 2009, 50, 1318-1325.
23. Chena, S.D.; Chen, J.F. A direct Newton-Raphson economic emission dispatch. Int. J. Electr. Power Energy Syst. 2003, 25, 411-417.
24. Cheng, C.K. Wind energy dispatch considering environmental and economic factors. Renew. Energy 2010, 35, 2217-2227.
25. Ummels, B.C.; Gibescu, M.; Pelgrum, E.; Kling, W.L.; Brand, A.J. Impacts of wind power on thermal generation unit commitment and dispatch. IEEE Trans. Energy Convers. 2007, 22, 44-51.
26. Boehme, T.; Wallace, A.R.; Harrison, G.P. Applying time series to power flow analysis in networks with high wind penetration. IEEE Trans. Power Syst. 2007, 22, 951-957.
27. Sfetsos, A. A comparison of various forecasting techniques applied to mean hourly wind speed time series. Renew. Energy 2000, 21, 23-35.
28. Pashardes, S.; Christofides, C. Statistical analysis of wind speed and direction in Cyprus. Sol. Energy 1995, 55, 405-414.
29. Wind Turbine Control Methods; National Instruments Corporation: Austin, TX, USA. Available online: http://zone.ni.com/devzone/cda/tut/p/id/8189 (accessed on 7 October 2010).
30. Cardu, M.; Baica, M. Regarding a global methodology to estimate the energy-ecologic efficiency of thermopower plants. Energy Convers. Manag. 1999, 40, 71-87.
31. Cardu, M.; Baica, M. Regarding a new variant methodology to estimate globally the ecologic impact of thermopower plants. Energy Convers. Manag. 1999, 40, 1569-1575.
32. Cardu, M.; Baica, M. Regarding the energy ecologic efficiency of desulphurization and denox systems and installations in thermopower plants. Energy Convers. Manag. 2000, 41, 1155-1164.
33. Kennedy, J.; Eberhart, R. Particle swarm optimization. In Proceedings of the 1995 IEEE International Conference on Neural Networks, Perth, Australia, 27 November-1 December 1995; pp. 1942-1948.
34. Kirkpatrick, S.; Gelatt, C.D.; Vecchi, M.P. Optimization by simulated annealing. Science 1983, 220, 671-680.
35. Fu, A.L.; Lei, X.J.; Xiao, X. The aircraft departure scheduling based on particle swarm optimization combined with simulated annealing algorithm. In Proceedings of the 2008 IEEE Congress on Evolutionary Computation, Hong Kong, China, 1-6 June 2008; pp. 1393-1398.
36. Sadati, N.; Amraee, T.; Ranjbar, A.M. A global particle swarm-based-simulated annealing optimization technique for under-voltage load shedding problem. Appl. Soft Comput. 2009, 9, 652-657.
37. Li, J.B.; Liu, X.G. Melt index prediction by RBF neural network optimized with an MPSO-SA hybrid algorithm. Neurocomputing 2011, 74, 735-740.
38. Wang, Z.S.; Li, L.C.; Li, B. Based on particle swarm optimization and simulated annealing combined algorithm for reactive power optimization. In Proceedings of the 2009 Asia-Pacific Power and Energy Engineering Conference, Wuhan, China, 28-30 March 2009; pp. 1909-1913.
39. Ajami, A.L.; Aghajani, G.H.; Pourmahmood, M. Optimal location of FACTS devices using adaptive particle swarm optimization hybrid with simulated annealing. J. Electr. Eng. Technol. 2010, 5, 179-190.
40. Cui, Y.B. Application of simulated annealing particle swarm optimization algorithm in power coal blending optimization. In Proceedings of the 2008 International Conference on Wireless Communication, Networking and Mobile Computing, Dalian, China, 12-14 October 2008; pp. 1-4.
41. Zangeneh, A.; Jadid, S. Fuzzy multiobjective model for distributed generation expansion planning in uncertain environment. Eur. Trans. Electr. Power 2011, 21, 129-141.
42. Huang, C.M.; Yang, H.T.; Huang, C.L. Bi-objective power dispatch using fuzzy satisfaction-maximizing decision approach. IEEE Trans. Power Syst. 1997, 12, 1715-1721.