LAUSR

Microgrids play a pivotal role in the attempts to achieve universal access to electricity; hence, their accurate planning, which also includes the evolution of the system over the project lifetime, is essential for maximizing the profitability of the investments. This paper proposes an iterative multi-year mixed-integer linear programming (MILP) optimization, in which power-dependent efficiency and capacity degradation of storage as functions of the operative strategy are considered. In this study, the computational burden of such a large problem is significantly reduced by means of an external loop that accounts for the hourly storage efficiency and residual capacity and serves to update the parameters for the MILP optimization of the following iteration. This approach is tested on a case study of a community in Soroti, in central-eastern Uganda. Comparison with the output of a one-shot MILP and with a procedure that overlooks the effects of the dispatching strategy on storage characteristics is shown, highlighting the benefits gained with the proposed algorithm in terms of both simulation time and accuracy of the design.