Please use this identifier to cite or link to this item: https://doi.org/10.1109/CEC.2012.6256143
Title: Optimal sizing of distributed energy resources for integrated microgrids using evolutionary strategy
Authors: Logenthiran, T.
Srinivasan, D. 
Khambadkone, A.M. 
Sundar Raj, T. 
Keywords: Distributed energy resources
Evolutionary strategy
Integrated microgrid
Microgrid
Optimal sizing
Issue Date: 2012
Source: Logenthiran, T.,Srinivasan, D.,Khambadkone, A.M.,Sundar Raj, T. (2012). Optimal sizing of distributed energy resources for integrated microgrids using evolutionary strategy. 2012 IEEE Congress on Evolutionary Computation, CEC 2012 : -. ScholarBank@NUS Repository. https://doi.org/10.1109/CEC.2012.6256143
Abstract: Optimal selection and sizing of Distributed Energy Resources (DER) is an important research problem for the advancement of distributed power systems. This paper presents detail studies on optimal sizing of DER for integrated microgrids using Evolutionary Strategy (ES). Integrated microgrid is an innovative architecture in distributed power systems, in which several microgrids are interconnected with each other for superior control and management of the distributed power systems. Right coordination among DER in microgrids, and proper harmony among the microgrids and the main distribution grid are critical challenges. Types of DER and capacities of them are needed to optimize such that proposed integrated microgrid provides reliable supply of energy at cheap cost. In this research, the problem is formulated as a nonlinear mixed-integer minimization problem which minimizes capital and annual operational cost of DER subject to a variety of system and unit constraints. Evolutionary strategy was developed for solving the minimization problem. The proposed methodology was used to design integrated microgrids for A*Star IEDS (Intelligent Energy Distribution System) project. The design results have shown that the proposed methodology provides excellent convergence and feasible optimum solution. © 2012 IEEE.
Source Title: 2012 IEEE Congress on Evolutionary Computation, CEC 2012
URI: http://scholarbank.nus.edu.sg/handle/10635/71304
ISBN: 9781467315098
DOI: 10.1109/CEC.2012.6256143
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