• Combined heating and power (CHP);
  • Hydrogen Production;
  • MicroGrid (MG);
  • PEM Fuel Cell;
  • Point Estimate Method;
  • Self-Adaptive Bee Swarm Optimization (SBSO)


This paper models and solves the operation management problem of MicroGrids (MGs) including cost and emissions minimization under uncertain environment. The proposed model emphasizes on fuel cells (FCs) as a prime mover of combined heat and power (CHP) systems. An electro-chemical model of the proton exchange membrane fuel cell (PEMFC) is used and linked to the daily operating cost and emissions of the MGs. A reformer is considered to produce hydrogen for PEMFCs. Moreover, in high thermal load intervals, in order to make the MG more efficient, a part of produced hydrogen is stored in a hydrogen tank. The stored hydrogen can be reused by PEMFCs to generate electricity or be sold to other hydrogen consumers. A probabilistic optimization algorithm is devised which consists of 2m + 1 point estimate method to handle the uncertainty in input random variables (IRVs) and a multi-objective Self-adaptive Bee Swarm Optimization (SBSO) algorithm to minimize the cost and emissions simultaneously. Several techniques are proposed in the SBSO algorithm to make it a powerful black-box optimization tool. The efficiency of the proposed approach is verified on a typical grid-connected MG with several distributed energy sources.