Optimum renewable generation capacities in a microgrid using generation adequacy study

Microgrids, as small power systems, may be comprised of different types of loads and distributed generation. As the integration of renewable power generation increases, the total available generation capacity of the system will be more derated due to the effect of equipment failures and the intermittent nature of these resources. Therefore, it is critical to determine optimum renewable generation capacities and provide enough reserve margin to meet the target reliability of the microgrid. In this paper, we first model a microgrid, including conventional and renewable distributed generation and the loads. Second, we determine the renewable generation capacity required to meet growth in demand at a certain level of grid reliability through a generation adequacy study. Adequacy of the microgrid is evaluated using parameters such as loss of load probability (LOLP) and expected energy not served (EENS). Third, the impact of different conditions, such as wind speed diversity (captured by correlating the wind power output), a combination of wind and solar power, and load diversity, on generation adequacy is studied through sensitivity analyses. Finally, the optimum renewable generation capacities are determined such that the total cost of generation and unserved power is minimized. The optimization process is based on the particle swarm optimization (PSO) method which uses Monte Carlo (MC) simulation for generation adequacy studies in each iteration.