Page 162 - AJWEP-v22i2

Reddy and Kumar

3.1.4. SSSC model for complex system dynamics, responding to changing
The SSSC, a series converter, injects a voltage into conditions, and maximizing the overall responsiveness
the line in parallel with the line flow. It can be used to of FACTS devices to effectively reduce oscillation
manage the power flow in the system. An SSSC is a issues and maintain grid stability. In our proposed
series-connected capacitor consisting of a VSC, diode, system, FACTS device tuning is optimized using ACO,
and DC link capacitor, coupled to the transmission line a swarm-based optimization technique.
through a coupling transformer, as shown in Figure 5.
This device can provide several compensations by 4. Optimization technique
injecting a controllable voltage into the line, thereby
altering the transmission line impedance. The SSSC This section outlines the specifics of the ACO algorithm
29
enables both reactive and active power exchange with applied to the coordinated parameter-tuning architecture
the power system, allowing the flow of both types of of the STATCOM, SSSC, UPFC, and SVC controllers.
power to be controlled. ACO, a probabilistic method for addressing computing
Compared to the thyristor-controlled series issues, can speed up finding a suitable path through a
compensator (TCSC), the SSSC has the benefit of network. The method was initially proposed by Macro
eliminating the capacitance and inductance of reactors Doriso in his 1992 doctoral thesis. The initial algorithm
and capacitors. In addition, it is symmetrically proficient was created using the concept of the ant colony’s search
in both capacitive and inductive modes. Each of these for food in relation to a food supply. Ants begin the food
FACTS devices has its own control system. Innovative search by wandering randomly throughout the nest. 30,31
methods and strategies have successfully been employed Once they locate a food source, they transport small
to control power systems, increase the capacity and quantities of food to their nest. When traveling back,
reliability of electrical power transmission, and they deposit a chemical pheromone, which is influenced
maintain system stability. The controllers are expanding by the characteristics of the ants and the food source.
the available power transmission capacity to deliver The pheromone trail left by ants when they migrate
more efficient and stable electricity coefficients, thereby from one location to another is followed by others.
strengthening the system. The parameter settings of the Ants are more likely to follow the trail with the
abovementioned controllers must be adjusted due to the highest concentration of pheromones. In doing so,
optimization challenges they face. The performance of they effectively mark the trail, making it easier to be
FACTS controllers in dampening oscillations in power recognized and followed by other ants. Subsequent
systems is greatly improved by optimization techniques. ants can then choose the shortest path among several
They allow for fine-tuning control settings, accounting options. The parametric random decision rules govern
the sequential decision-making process that generates
the solution. The learning of the parameters, which the
decision policy depends on, forms the foundation of

Figure 4. Circuit for the static synchronous Figure 5. Static synchronous series compensator
compensator model
Abbreviation: DC: Direct current. Abbreviation: DC: Direct current.

Volume 22 Issue 2 (2025) 156 doi: 10.36922/ajwep.8393