Optimal Sizing of Distributed Energy Resources for Integrated Microgrids using Evolutionary Strategy T. Logenthiran Department of ECE National University of Singapore Singapore logenthiran@nus.edu.sg D. Srinivasan Department of ECE National University of Singapore Singapore dipti@nus.edu.sg A. M. Khambadkone Department of ECE National University of Singapore Singapore eleamk@nus.edu.sg T. Sundar Raj Department of CHBE National University of Singapore Singapore chesrt@nus.edu.sg 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. Keywords-Optimal sizing, Distributed energy resources, Microgrid, Integrated microgrid, Evolutionary strategy I. INTRODUCTION Microgrids are low voltage distribution networks comprising various distributed generators, storage devices, and controllable loads [1,2]. Enhanced power quality, high reliability, cheap energy cost, and reduced emissions are the important capabilities of microgrids to shift distributed power systems towards smart grid [1]. Smart grid [3,4] is a vision of future power systems, which encourages optimal design and optimal operation of power systems. Integrated microgrid [5] is a recent concept which integrates many microgrids together to achieve much benefits from them. In an integrated microgrid, each microgrid could contain different types of loads and energy sources depending on the infrastructure and nature of the area. As a result, interaction among the microgrids, and interaction between the microgrids and the main distribution grid are become crucial tasks for implementing control and management schemes. Therefore, detailed research on integrated microgrid which is a part of larger electrical distribution network is necessary for the design, development and control of distributed power systems. Proper selection and sizing of distributed energy resources are some of the challenging tasks in long-term planning of distributed power systems. Diverse criteria [6,7] were considered in selecting distributed energy resources for an integrated microgrid. Some of the important criteria are load type (i.e. residential, commercial or industrial), load priority (i.e. base load, backup load or peck load shaving), operational mode (i.e. grid-connected or islanded), average load, and available distributed energy resource technologies. Once, an appropriate distributed energy resource is chosen, the subsequent questions will arise. Some of them are power rating, reliability, capital cost, installation cost, operation and management cost, method of payment, and life time of distributed energy resource. Cost-benefit of distributed energy resources can be determined by comparing the electricity price from distributed energy resources with the electricity price of the main distribution grid. In reality, cheap energy cost is not only the sole objective. The other objectives such as environmental friendliness and energy security [7] are also need to consider while planning distributed power systems. In the literature, several research works were addressed different approaches for sizing of distributed energy resources such as wind turbines, photovoltaic systems, and batteries without applying any optimizing methodologies [8-13]. In few research works have applied optimization methodologies. For examples, tangent method [6, 13] is a well known approach used to size wind turbines, photovoltaic systems, and batteries for standalone hybrid wind and photovoltaic systems. Genetic algorithm [14] was employed to optimize sizes of wind turbines, photovoltaic systems, and batteries for a distribution system using genetic algorithm. The authors have proposed Evolutionary Strategy (ES) [15] for sizing of distributed energy resources for islanded microgrids. This work proved that evolutionary strategy is a promising algorithm for the problem based on the convergence characteristics and the quality of the solutions. In this paper, the evolutionary strategy is proposed for the optimal selection and sizing of distributed energy resources for integrated microgrids. Even though decisions about the This work was supported by Science and Engineering Research Council of the Agency for Science, Technology and Research (A*STAR), Singapore IEDS programme grant R-263-000-507-305. U.S. Government work not protected by U.S. copyright WCCI 2012 IEEE World Congress on Computational Intelligence June, 10-15, 2012 - Brisbane, Australia IEEE CEC