Presenting An Economic Planning Model to Determine the Optimal Capacity of a Flexible Wind Power Plant

Abstract

Calculating the optimal size of renewable power plants, including wind power plants, along with storage in a power system is an important issue due to the increasing demand for renewable energy sources. One method for calculating the optimal size is to use the dynamic economic distribution formulation. The goal of this formulation is to find the optimal combination of different energy sources at any given time, based on factors such as production cost, energy demand, investment cost, and other economic-technical factors. However, in all economic distribution problems, it is often assumed that the variables are completely certain. While many variables are subject to uncertainty. Feasible optimization can model these uncertain variables. Feasibility optimization is a method that allows planners to consider uncertainty in their models. Instead of assuming that all variables are known for certain, feasibility optimization considers a range of values ​​for each variable and calculates the degree of necessity and possibility for a given outcome in each scenario. This situation allows planners to plan better even in conditions where there is a high degree of uncertainty. In this thesis, by considering the uncertainty in interest rates, electrical load and wind energy, 7 degrees of necessity and possibility are created and the optimal planning of energy production resources will be discussed by considering different costs with the aim of maximizing the profit of the wind power plant. In order to validate the proposed method, this method is implemented on a standard IEEE 33-bus network and the simulation results show its performance improvement and realism.