Optimization and Design of PV-Wind Hybrid System for DC Micro Grid Using NSGA II
- 1 Department of Electrical and Electronics Engineering, Anna University Regional Campus Madurai, Madurai, India
- 2 Department of Electrical and Electronics Engineering, Anna University Regional Campus Madurai, Madurai, India
- 3 Department of Electrical and Electronics Engineering, Anna University Regional Campus Madurai, Madurai, India
Abstract
The world is heading towards renewable energy, but the two key disputes that stop its well-known adoption are the power production level and the price of the production. Distributed generation (DG), and hybrid systems with battery backup are the solution for uninterrupted power supply. It is obtained using the Multi-Objective Genetic Algorithm (NSGA II). Techno-economic methodology is used in this proposed system for the size optimization. The result is based on the system cost, in order to meet the load requirements. The effect of temporal sampling is optimized using low-rate temporal data. It is compared with hybrid DC microgrid, which has been optimized using high temporal resolution data.
- Xu, L. and Chen, D. (2011) Control and Operation of a DC Microgrid with Variable Generation and Energy Storage. IEEE Transactions on Power Delivery, 26, 2513-2522. http://dx.doi.org/10.1109/TPWRD.2011.2158456
- Baochao, W., Sechilariu, M. and Locment, F. (2012) Intelligent DC Microgrid with Smart Grid Communications: Control Strategy Consideration and Design. IEEE Transaction on Smart Grid, 3, 2148-2156. http://dx.doi.org/10.1109/TSG.2012.2217764
- Zhang, P., Wang, Y., Xiao, W.D. and Li, W.Y. (2012) Reliability Evaluation of Grid-Connected Photovoltaic Power Systems. IEEE Transactions on Sustainable Energy, 3, 1949-3029. http://dx.doi.org/10.1109/tste.2012.2186644
- Majumder, R. (2014) A Hybrid Microgrid with DC Connection at Back to Back Converters. IEEE Transaction on Smart Grid, 5, 251-259. http://dx.doi.org/10.1109/TSG.2013.2263847
- Kimball, J.W., Kuhn, B.T. and Balog, R.S. (2009) A System Design Approach for Unattended Solar Energy Harvesting Supply. IEEE Transactions on Power Electronics, 24, 952-962. http://dx.doi.org/10.1109/TPEL.2008.2009056
- Xu, S., Huang, A.Q., Lukic, S. and Baran, M.E. (2012) On Integration of Solid-State Transformer with Zonal DC Microgrid. IEEE Transaction on Smart Grid, 3, 975-985. http://dx.doi.org/10.1109/TSG.2012.2187317
- Bidram, A. and Davoudi, A. (2012) Hierarchical Structure of Microgrids Control System. IEEE Transaction on Smart Grid, 3, 1963-1976. http://dx.doi.org/10.1109/TSG.2012.2197425
- Heydt, T. (2010) The Next Generation Of Power Distribution Systems. IEEE Transactions on Smart Grid, 1, 225-235. http://dx.doi.org/10.1109/TSG.2010.2080328
- Balog, R., Shadmand, M.B. and Pasupuleti, M. (2011) Photovoltaic-Wind Hybrid System with Battery Back-Up Optimized for Apartment Complexes and Other Community Living Environments. IEEE Transaction on Energy Conversion Congress and Exposition (ECCE), 26, 3626-3632.
- Gao, Y., Shi, L. and Yao, P.J. (2000) Study on Multi-Objective Genetic Algorithm. Proceedings of the 3rd World Congress on Intelligent Control and Automation, 1, 646-650.
- Zitzler, E., Deb, K. and Thiele, L. (2000) Comparison of Multiobjective Evolutionary Algorithms: Empirical Results. IEEE Transactions on Evoluationary Computation, 8, 173-195. http://dx.doi.org/10.1162/106365600568202
- Deb, K., Pratap, A., Agarwal, S. and Meyarivan, T. (2002) A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II. IEEE Transactions on Evoluationary Computation, 6, 182-197. http://dx.doi.org/10.1109/4235.996017