Security and Stochastic Economic Dispatch of Power System Including Wind and Solar Resources with Environmental Consideration

Abstract

With increasing concern of environmental protection, renewable energy sources are widely applied as a mean to reach emission reduction. In this paper, Dynamic Economic Emission Dispatch (DEED) model with security constraints  is developed for a system incorporating wind, photovoltaic and non-convex thermal units. Weighted aggregation method is used to enable particle swarm optimization (PSO) to solve environmental/economic multiobjective (MO) problem. The optimization is aimed at minimizing the cost function and emissions of the system while satisfying all operational constraints considering both conventional and renewable energy generators. The model takes into account cost of modern thermal units with multiple valves and penalty costs due to mismatch between the actual and scheduled wind and PV power outputs. The costs include weighted cost depends on the stochastic nature of wind speed and solar irradiance. Moreover, the Newton Rapson optimal power flow is applied in order to maintain transmission line constraints without violation and calculate the total transmission losses depending on the square power flow. With the stochastic wind speed and solar irradiance based on weibull probability density function (pdf), the optimization problem is numerically solved for a scenario involving three conventional, two wind farms and two PV power plants. The simulation results show the feasibility and effectiveness of the proposed model.

Keywords

• Dynamic economic emission dispatch; optimal power flow; Newton Raphson, non-convex conventional generators; solar and wind power uncertainty; Weibull probability density function.

References

1. A. J. Wood, F. Wollenberg, Power Generation Operation and Control, 3rded, New York: Wiley, 1996.
2. K. Vaisakh, P. Praveena, S. Rama MohanaRao, Kala Meah, “ olving dynamic economic dispatch problem with security constraints using bacterial foraging PSO- D algorithm”, lectrical Power and nergy ystems, Vol. 39, 2012, pp. 56-67.
3. Aiguo Zhang, Jianhua Zhang, Jingfu Shang, Jialin Qin, "Security and economic dispatch of power system with environmental consideration", IEEE/PES Gen. Meet, , pp.1-6. R. A. Abarghooee, T. Niknam, A. Roosta, A. R. alekpour, . Zare, “Probabilistic multiobjective wind- thermal economic emission dispatch based on point estimated method”, International Journal of lectrical Power & Energy Systems, Vol. 37, 2012, pp. 322-335.
4. Cheng-ChienKuo, Teng-FaTaso," Generation dispatch under large penetration of wind power considering emission and economy ", International Conference on Energy and Environment Technology, pp. 679-682, 2009.
5. QingleiGuo, Jonghoon Han, Minhan Y oon, Gilsoo Jang, " A study of economic dispatch with emission constraint in smart grid including wind turbines and electric vehicles", IEEE Vehicle Power and Propulsion Conference, Seoul, Korea, pp. 1002-1005, Oct. 9- ,2012.
6. H. T. Jadhav, Harsh Bhandari, YamanDalal, Ranjit Roy, "Economic Load Dispatch Including Wind Power Using Plant Growth Simulation Algorithm", Environment and Electrical Engineering (EEEIC), International conference, pp. 388-393, 2012.
7. RH. Liang, JH. Liao, “A fuzzy-optimization approach for generation scheduling with wind and solar energy systems”, I Trans Power yst., Vol. 22, 2007, pp. 74.
8. GA.T.AlAwami,h . ortomme,handk .A. l harkawi, “ Optimizingheconomic /environmental dispatch with wind and thermal units”, I EE/PES Gen. Meet, 2009, pp.1-6.

9. KK. andal, . hakraborty, “ ffect of control parameters on differential evolution based combined economic emission dispatch with valve-point loading and transmission loss”, Int. Journal on merging lectric Power Systems, Vol. 9, 2008, pp. 1- 18.
10. A. A. ElDesouky, R. Aggarwal, M. M. Elkateb, F. Li, " Advanced hybrid genetic algorithm for short- term generation scheduling", IEE Proc. Gener. Transm. Distrib., Vol148, No. 6, November, 2001, pp. 511-517.
11. G.Tina, .Raiti, “Hybrid solar/wind power system probabilistic modeling for long term performance assessment”, olar nergy, Vol.80, 2006, pp.578-588.
12. Hetzer, D.C.Yu, K. Bhattaria, “An economic dispatch model incorporating wind power”, I Trans. Energy Conversion, Vol. 23, No.2, June 2008, pp. 603- onti, .Raiti, “Probabilistic load flow Using
13. Monte Carlo techniques for distribution networks with photovoltaic generators”, Solar Energy, Vol.81, 2007, pp. 1481.
14. J.F. rgill, K.T.G. Hollands, “ orrelation equation for hourly diffuse radiation on horizontal surface”, olar Energy, Vol.19, 1977.
15. G.Tina, .Gagliano, “Probability analysis of weather data for energy assessment of hybrid solar/wind power system”, In proceedings of 4th IA /W A international conf. Energy, Environment, Ecosystems and sustainable Portugal,11-13 June,j2008. , pp.217-223, Algarve,
16. Y.M. Atwa, E.F. El-Saadany, M.M.A.Salama, “Adequacy evaluation of distribution system including wind/solar DG during different modes of operation", IEEE Trans. power system, Vol.26, No.4, 2011, pp.1945
17. A. Papoulis, Probability, Random Variables and Stochastic Processes, McGraw Hill, 2001.
18. M. M. Eladany, A. A. Daoud , A. A. ElDesouky, A.A. Sallam," Stochastic multiobjective wind/PV/non- convex thermal dynamic economic emission dispatch using particle swarm technique", Proceedings of the th onference ( P ’ 2), Alexandria University, Egypt, , Paper ID 159, December 23-25, 2012. Systems
19. F.A. ohamed,hH. .Koivo, “ ystem modeling and online optimal management of microgrid using mesh adaptive direct search ”, lectrical power and energy system, No.32, 2010, pp.398-407.
20. A. T. Al-Awami, E. Sortomme, M. A. El-Sharkawi, "Optimizing economic/environmental dispatch with wind and thermal units", IEEE/PES Gen. Meet, 2009, pp. 1-6. A. Abido, “ ultiobjective evolutionary algorithms for electric power dispatch problem”, I
21. Trans On Evolutionary Computation, Vol 10, 2006, pp. 29.
22. Gaing ZL," Particle swarm optimization to solving the economic dispatch considering the generator constrain. ”, I Trans. Power yst., vol. 18, 2003, pp. 32.
23. J . Dhillon, DP. Kothari, “ conomic-emission load dispatch (EELD) using binary successive approximation- based evolutionary search ”, I T Gener. Transm. Distrib., Vol. 3, 2009, pp. 1-16. S. ChetanVarma, K.S. Linga Murthy,
24. K.SriChandan," Gaussian particle swarm optimization for combined economic emission dispatch", Energy Efficient Technologies for Sustainability (ICEETS) International conference, pp. 1336-1340, 2013.
25. Neha Mishra, ManjareePandit, "Economic emission dispatch using weighted sum based PSO with fuzzy decesion making application of artificial intelligence", International Communication and Renewable Energy (ICMiCR), 2013. on Microelectronics,
26. J . Dhillon, . Parti, K. Bhattarai, “ tochastic economic emission load dispatch.” lectric Power yst., Vol. 26, 1993, pp. 179-86.