Differential Evolution Optimized Automatic Generation Control of a Two Area Renewable Energy Source Based Power System Incorporating Electric Vehicles

It is crucial to provide consumers quality electric power consistently. The frequency stability and power flow between different control zones are used to determine the standard power quality. As a consequence of which automatic generation control (AGC) is frequently employed to stabilize the power system. This work presents the AGC of a hybrid power system’s including thermal, small hydro power plant (SHPP), wind Turbine System (WTS) and Electric vehicles (EVs). The addition of electric vehicles to the utility grid, thermal plant generating rate constraints, and time delays in both control regions make the suggested power system more realistic and practicable. This makes the system a little more complicated, and it necessitates the use of a reliable controller to perform properly. Proportional Integral Derivative (PID) and Fractional Order Proportional Integral Derivative (FOPID) controllers are implemented in each region to control the system’s output power and sustain power balance. This leads to the frequency remaining near to its optimum value. To optimize the gain values of FOPID and PID controllers for AGC of the proposed system, Differential Evolution algorithm (DEA) is implemented. In Area1 and Area2 the system dynamics are assessed using a step load perturbation. The suggested control strategy using a FOPID controller enhances the frequency responsiveness of the system in terms undershoot, overshoot, settling time, steady state errors, and amplitude oscillations according to test results.