Optimal siting of wind and solar power plants in an electric power system

This study developed a single‑criterion mathematical model for selecting optimal sites for wind and solar power plants within an electric power system, taking into account renewable generation variability and economic efficiency. The objective functions included maximizing total electricity output, minimizing the overall rate of power change, minimizing total power increments, and maximizing base power, subject to constraints on installed capacity and the number of units per site. A test system was designed with six potential sites for wind power plants and two sites for solar power plants, with a combined installed capacity of 600 MW. The study proposed an algorithm integrating daily power profile simulations for a single wind turbine and a photovoltaic module group across candidate sites with varying topography and daylight duration. Optimization of installed capacity distribution among sites was then performed. Application of the model to the test system showed that the type of objective function significantly affects the configuration of the optimal system and the allocation of capacity among sites. Transitioning from the criterion of maximum electricity output to criteria related to power dynamics reduces generation by 6–7%, while decreasing the total rate of power change and total power increments by 19–39% and increasing base power by up to 38%. The proposed optimization algorithm provides a systematic framework for decision-making in the design of renewable energy systems with minimal internal volatility of generation. The selection of the objective function depends on the flexibility characteristics of a given power system and can be applied at early stages of planning renewable energy facilities.

power systems, renewable energy sources, wind farms, solar power plants, capacity factor, rate of power change, base power, optimization, single-criterion problem, flexibility