Single- and multi-objective parameter optimization in a tool for designing PV-diesel-battery systems

摘要

In many isolated off-grid areas diesel generators are the common way of providing electricity. The high energy cost and CO2 emissions might be reduced by implementing PV plants with an attached battery storage into the micro-grid. However, the correct dimensioning of both PV and battery storage is crucial. Using a MATLAB/Simulink tool based on previous work, such PV-Diesel systems can be calculated for variable storage capacity, PV sizing and dispatch strategies. To find a preferably efficient optimization method in MATLAB, a genetic and a simplex algorithm are compared. Optimization objectives were low levelized cost of electricity (LCOE) or carbon dioxide (CO2) emissions, by sizing photovoltaics and battery of the system. The specific algorithms were chosen since they don't rely on derivatives as the Simulink calculation is discrete and non-linear. It is shown that the simplex algorithm converges within a couple of minutes and quiet faster than the genetic algorithm. Furthermore, a multi-objective optimization is implemented using an epsilon-constraint method. The user is able to identify appropriate dimensioning with emphasis on different targets by calculating distinct pareto optimal solutions.