Skip to Main Content
Miscellaneous sorts of renewable energies, despite of their positive impacts on the power system operation cost and environmental concerns, could jeopardize the system reliability due to introducing significant degrees of intermittency and uncertainty. This challenge could be overcome by composing various sources of renewable energies with complimentary natures. This paper devises an explicit mathematical framework to compromise the contribution of wind and solar energies. The optimization problem is to maximize the system reliability subject to a fixed monetary investment associated with both wind and solar. The problem formulation is based on mixed-integer programming (MIP) format in which the optimality of the solution is guaranteed or can be traded with the execution time. The decision variables are the number of wind turbines and solar modules to be deployed. In addition, uncertainties associated with the hourly load, wind speed, and solar radiation are captured by scenarios based on the probability density functions (PDF). These scenarios are generated by the Monte Carlo simulation method. They are then decreased to a tractable set using a scenario reduction technique. Effectiveness of the proposed methodology is demonstrated through numerical evaluations using real field data.