Optimal design of decentralized energy conversion systems for smart microgrids using decomposition methods

The design of decentralized energy conversion systems in smart residential microgrids is a challenging optimization problem due to the variety of available generation and storage devices. Common measures to reduce the problem's size and complexity are to reduce modeling accuracy, aggregate multiple loads or change the temporal resolution. However, since these attempts alter the optimization problem and consequently lead to different solutions as intended, this paper presents and analyses a decomposition method for solving the original problem iteratively. The decomposed method is verified by comparison with the original compact model formulation, proving that both models deviate by less than 1.8%. Both approaches furthermore lead to similar energy systems that are operated similarly, as well. The findings also show that the compact model formulation is only applicable to small- and medium-scale microgrids due to current limitations of computing resources and optimization algorithms, whereas the distributed approach is suitable for even large-scale microgrids. We apply the decomposed method to a large-scale microgrid in order to evaluate economic and ecological benefits of interconnected buildings inside the grid. The results show that with local electricity exchange, costs can be reduced by 4.0% and emissions by even 23.7% for the investigated scenario. (C) 2018 Elsevier Ltd. All rights reserved.