Automatic Generation Control in an Interconnected Power System Incorporating Diverse Source Power Plants Using Bacteria Foraging Optimization Technique

AGC of a multi-area multi-source hydrothermal power system interconnected via AC/DC parallel links under deregulated environment

“…In most of the studies with multi-source generations, the effect of restriction on the rate of change of power generation is not considered [18,47,52,55]. But in practice, generation of a power system incorporating steam/hydro plants can change only at a specified maximum rate.…”

“…Recently some researchers have investigated the AGC of conventional power systems with diverse sources such as hydro, thermal, gas, and nuclear, operating in each control area [14,18,47,[52][53][54][55][56]. Optimal AGC regulators are designed and implemented effectively on a two-area power system with hydrothermal-gas generating units in each area [47].…”

“…Various aspects of AGC of conventional interconnected power systems are discussed in . Several control strategies, like optimal control [4,5,[8][9][10][11][12], variable structure control [11,12], continuous-discrete mode control [13], sliding mode [14], beta wavelet artificial neural networks [15], differential evolution [16], non-dominated sorting genetic algorithm-II [17], bacteria foraging [18,19], hybrid bacterial foraging-particle swarm optimization [19], craziness based particle swarm optimization [20], teaching-learning technique [14,21], fuzzy logic control [21][22][23][24][25], bat algorithm [23], big bang-big crunch [24], quasi-oppositional harmony search [25], cuckoo search algorithm [26,27] and firefly algorithm [28] are applied to design various AGC controllers for different single and multi-area interconnected conventional electrical power systems.…”

Fruit fly algorithm-based automatic generation control of multiarea interconnected power system with FACTS and AC/DC links in deregulated power environment

“…Bhatt et al presented a modification of classical AGC after deregulation in multiarea and explained various bilateral cases with Distribution Company (DISCO) participation matrix. In modern power system, control area generating sources has become diverse like thermal, hydro, and gas with different characteristics and increase nonlinearity . So AGC control has to be modified in change scenario.…”

Optimal control strategy–based AGC of electrical power systems: A comparative performance analysis

“…Moreover, these studies provide a big collection of bibliography on AGC. In recent decades, various intelligent approaches such as differential evolution, teaching‐learning–based optimization, bacterial‐foraging optimization algorithm, firefly algorithm, craziness‐based particle swarm optimization, artificial bee colony, particle swarm optimization, hybrid differential evolution‐particle swarm optimization, fuzzy logic and genetic algorithm have harnessed to optimize supplementary controller parameters, but usually these techniques sometimes betray solution.…”