Optimal integral minus proportional derivative controller design by evolutionary algorithm for thermal‐renewable energy‐hybrid power systems

Abstract

The goal of this work is to investigate the application of integral minus proportional derivative (IPD) controller for the automatic generation control (AGC) problem comprising of a two-area thermal system integrated with renewable energy (RE)based sources such as wind, solar and fuel cells. In order to facilitate a realistic environment, each thermal system is equipped with a governor dead band, reheat turbine and generation rate constraint. Moreover, each RE-based power system is modelled by incorporating certain drift and random variations as the key characteristic of RE-based sources. The control performance of IPD is compared with the PID and PI controllers all tuned using an evolutionary technique genetic algorithm by incorporating a step load perturbation in both areas. In order to verify the effectiveness of the control scheme, detailed performance investigations are carried out using random variations in load perturbations and in RE-based power. In addition, sensitivity analysis is also included for wider variations in system parameters in order to test robustness. Based on the extensive simulations for robustness and accuracy, it was observed that IPD outperforms the other controllers and therefore serves as a promising solution to the problem of AGC.

Review of hierarchical control strategies for DC microgrid

“…Provides global restoration terms for both voltage and current. Rigorous mathematical analysis and communication delay affects system stability tertiary control PSO [85][86][87][88][89][90][91][92][93][94] obtains the optimal solution using its available solution (population). Unidirectional information sharing with internal memory having no genetic operator.…”

“…Optimisation technique based on PSO begins with the selection of a population of random solutions where each particle wants to achieve its best personal best and also upgrade its position to be global best (gbest) of the swarm. The gbest is the value towards which each particle upgrades its position and velocity [85][86][87].…”

A Matignon’s Theorem Based Stability Analysis of Hybrid Power System for Automatic Load Frequency Control Using Atom Search Optimized FOPID Controller

“…The detail explanation of thermal power generation and its parameter for simulation is presented in [7], [40]. Further, the various RE model are described in detail [41] as follows;…”

“…MW/Hz, Governor speed regulation:R i = 2.4 pu MW/Hz, Change in step load perturbation with frequency:D i =8.33 × 103 p.u. MW/Hz, System inertia: H i = 5 s. Solar collector gain and time constant: K s = 1.8,T s = 1.8 s, Solar thermal steam turbine gain and time constant: K T = 1, , T T = 0.3 s, Wind turbine gain and time constant: K W T P G = 1, T W T P G = 1.5 s, Aqua electrolyzer gain and time constant: K AE = 0.002, T AE = 0.5 s, Fuel cell gain and time constant: K F C = 0.01, T F C = 4s, area capacity ratio: a 12 = 1, constant for renewable power sharing K n = 0.6 and loading = 50 % [7],[41]…”

Cascade‐I λ D μ N controller design for AGC of thermal and hydro‐thermal power systems integrated with renewable energy sources

“…Considering the above analysis, the novel contributions of this work are stated as follows: . As this study is conducted in low frequency domain, the transfer functions (TFs) for these RES are denoted by first order lag [2][3][4][5]. The STG entails solar and thermal parts.…”