Multi-objective Optimization of a DC Microgrid with a Back-up Diesel Generator

Nowadays, microgrid applications are proliferate all around the world. Owing to many grounds, such the ease of control, the high efficiency and reliability, the improvement of power electronics devices, the rise of DC type loads and sources, etc. researchers’ interest was diverted from AC to DC microgrids. Yet, on a global control and management level, several challenges are confronted. A variety of objectives can be achieved by controlling the power flow of each of the distributed energy sources. By means of this, an optimization problem is formulated and solved using heuristic methods such the genetic algorithm (GA), the particle swarm optimization (PSO), the pattern search (PS), etc. However, other techniques were exploited in the literature such the dynamic programming (DP) which is a stepby-step optimization algorithm. In this paper, a (DP) technique is applied to solve a multi-objective optimization problem. Two objectives are set: DC microgrid operation cost minimization, and pollutant gas emissions reduction. A sole cost function is established, and weights are assigned to each of the predefined goals. Besides, each objective function is detailed apart, and several constrains are set. Two simulations tests are performed to prove the convergence, and the viability of the applied (DP) technique. Finally, different weights are selected in each of simulation tests to validate the effectiveness, and robustness of the (DP) in solving such problems.