JZUS - Journal of Zhejiang University SCIENCE

Journal of Zhejiang University SCIENCE A 2008 Vol.9 No.3 P.401-409

Robust design and optimization for autonomous PV-wind hybrid power systems

Author(s): Jun-hai SHI, Zhi-dan ZHONG, Xin-jian ZHU, Guang-yi CAO
Affiliation(s): Institute of Fuel Cells, Shanghai Jiao Tong University, Shanghai 200240, China
Corresponding email(s): shjh@sjtu.edu.cn
Key Words: PV-wind power system, Robust design, Constraint multi-objective optimizations, Multi-objective genetic algorithms, Monte Carlo Simulation (MCS), Latin Hypercube Sampling (LHS)

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Abstract: This study presents a robust design method for autonomous photovoltaic (PV)-wind hybrid power systems to obtain an optimum system configuration insensitive to design variable variations. This issue has been formulated as a constraint multi-objective optimization problem, which is solved by a multi-objective genetic algorithm, NSGA-II. monte Carlo Simulation (MCS) method, combined with latin Hypercube Sampling (LHS), is applied to evaluate the stochastic system performance. The potential of the proposed method has been demonstrated by a conceptual system design. A comparative study between the proposed robust method and the deterministic method presented in literature has been conducted. The results indicate that the proposed method can find a large mount of Pareto optimal system configurations with better compromising performance than the deterministic method. The trade-off information may be derived by a systematical comparison of these configurations. The proposed robust design method should be useful for hybrid power systems that require both optimality and robustness.

Reference

[1] Avramidis, A.N., Wilson, J.R., 1996. Integrated variance reduction strategies for simulation. Operations Research, 44(2):327-346.

[2] Bernal-Agustín, J.L., Dufo-López, R., Rivas-Ascaso, D.M., 2006. Design of isolated hybrid systems minimizing costs and pollutant emissions. Renewable Energy, 31(14):2227-2244.

[3] Celik, A.N., 2003. Techno-economic analysis of autonomous PV-wind hybrid energy systems using different sizing methods. Energy Conversion and Management, 44(12):1951-1968.

[4] Deb, K., 2000. An efficient constraint handling method for genetic algorithms. Computer Methods in Applied Mechanics and Engineering, 186(2-4):311-338.

[5] Deb, K., Pratap, A., Agarwal, S., Meyariva, T., 2002. A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation, 6(2):182-197.

[6] Kellogg, W., Nehrir, M.H., Venkataramannan, G., Gerez, V., 1996. Optimal unit sizing for a hybrid wind/photovoltaic generating system. Electric Power Systems Research, 39(1):35-38.

[7] Kicinger, R., Arciszewski, T., de Jong, K., 2005. Evolutionary computation and structural design: A survey of the state-of-the-art. Computers and Structures, 83(23-24):1943-1978.

[8] Lagaros, N.D., Plevris, V., Papadrakakis, M., 2005. Multi-objective design optimization using cascade evolutionary computations. Computer Methods in Applied Mechanics and Engineering, 194(30-33):3496-3515.

[9] Notton, G., Muselli, M., Poggi, P., 1998. Costing of a stand-alone photovoltaic system. Energy, 23(4):289-308.

[10] Notton, G., Muselli, M., Poggi, P., Louche, A., 2001. Decentralized wind energy systems providing small electrical loads in remote areas. International Journal of Energy Research, 25(2):141-164.

[11] Protogeropoulos, C., Brinkworth, B.J., Marshall, R.H., 1997. Sizing and techno-economical optimization for hybrid solar photovoltaic/wind power systems with battery storage. International Journal of Energy Research, 21(6):465-479.

[12] Shi, J.H., Zhu, X.J., Cao, G.Y., 2007. Design and techno-economical optimization for stand-alone hybrid power systems with multi-objective evolutionary algorithms. International Journal of Energy Research, 31(3):315-328.

[13] Wichert, B., 1997. PV-diesel hybrid energy systems for remote area power generation—A review of current practice and future developments. Renewable and Sustainable Energy Reviews, 1(3):209-228.

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