Using the Monkey Algorithm for Hybrid Power Systems Optimization

In the present work, the Monkey Algorithm was adapted to find the proper component configuration for a Hybrid Micro-Grid with the introduction of simulation techniques into the evaluation step of the heuristic in order to account for the stochastic behavior of the renewable energy components. The forecasting methods allow the simulation to solve the parameters required in the Monkey Algorithm evaluation step. The Renewable Energy Integration Problem is solved as a Multi-Objective Optimization Problem where the objectives take in account are the minimization of the total lifecycle cost of the system, involving the capital, replacement, operation, maintenance and the minimization of green house gas emissions. The Monkey Algorithm developed in this paper introduces a new methodology along the evaluation step of the heuristic based on meteorological factors, which allows the Hybrid Model to be simultaneously solved for both objectives.