New approach in two-area interconnected AGC including various renewable energy sources using PSO

Abstract

This paper presents a novel approach for automatic generation control (AGC) as an integrated two-area thermal-hybrid power generation system (THPGS) where thermal generators are interconnected with various renewable power generators (RPGs) like a solar power generator (SPG), wind power generator (WPG), fuel cell, and aqua electrolyzer. A comparison is carried out between the THPGS and a normal thermal power system considering proportional integral and derivative controllers. Particle swarm optimization (PSO) is used for optimizing the gain parameters of the controller. Investigation of dynamic responses is carried out considering step load perturbation as well as random load perturbation (RLP). Problems are formulated considering the variation in SPG and WPG power output in the presence of RLP in area 1 and the change in generation of SPG and WPG power in both areas for analyzing system stability and robustness. The investigation proves that PSO-optimized controllers are so robust that it is not necessary to change the parameter values of the controllers for a wide variation in SPG and WPG output power. Thus, integration of RPGs in AGC is properly applied for investigating the dynamic behaviors of the system. All the simulation works are implemented in MATLAB/Simulink software.

A review of control strategies for automatic generation control in power systems with renewable energy

“…PID controller is a classical and widely used controller, which is applied in power systems containing renewable energy, such as PI controller, PID controller, PD controller, and PIDD controller. The application of PI/PID controllers has been investigated in academic research for various studies, including the integration of control and scheduling of power systems incorporating renewable energy sources [32,33], the examination of frequency control techniques in power systems with PV power generation [16,34,35], the analysis of frequency control methods in power systems with wind power sources [18,21,[36][37][38][39][40][41][42], the investigation of frequency control strategies in power systems with combinations of wind, solar, and energy storage [43,44], the exploration of frequency control approaches in power systems with integrated wind and solar sources [45][46][47], as well as the study of frequency control mechanisms in microgrids [48]. Depending • Multi-regional power systems on the power system different controllers are required, Toulabi et al utilized and designed a PD controller for frequency control of a wind farm power system consisting of multiple variable-speed wind turbines, thus demonstrating the feasibility of the controller [49].…”

“…There are more intelligent optimization algorithms applied in renewable energy-containing power systems, which are briefly listed next for reference. The sine cosine algorithm (SCA) [24,29,63,65], the grasshopper optimization algorithm (GOA) [20,54,73], and the particle swarm optimisation algorithm (PSO) [21,42,47]. Other optimisation algorithms are grey wolf optimisation algorithm (GWO) [18,35], quasi-oppositional optimisation algorithm (QOLOA) [53], intensity pareto evolutionary algorithm [32], adaptive distributed auctions algorithm (ADAA) [33], imperial competition algorithm (ICA) [23,72], lightning search algorithm [56], whale optimisation algorithm (WOA) [57,58], firefly algorithm (FA) [16], water cycle algorithm (WCA) [61,87], dragonfly algorithm (DA) [67], teaching learning optimisation (TLBO) [50], butterfly optimisation algorithm (BOA) [62], in harmony algorithm (IHA) [36], spotted hyena algorithm (SHO) [28], crow search algorithm (CSA) [59,66], moth flame algorithm (MFO) [37], moth swarm algorithm (MSA) [38], genetic algorithm (GA) [44,49], differential evolution algorithm (DE) [39], biogeographic optimisation algorithm (BBO) [46], volleyball league algorithm (VPL) [60], yellow saddlefish (YSGA) [64], wild goat algorithm (WGA)…”

Student psychology-based optimization-tuned cascaded controller for frequency regulation of a microgrid

“…Furthermore, the extensive capability of SPG units makes them a deserving alternative to traditional power generators. The power generation from SPG highly depends on solar irradiance and ambient temperature (Sanki and Basu, 2018;Sahu et al, 2022). The basic equation of SPGgenerated power can be presented as Eq.…”