Comparative Analysis of Static Var Compensator Impact on Power Flow and System Losses Using Computational Simulation Tools

2.1 Operational constraints and FACTS evolution

Modern power transmission networks have limitations on operation. There are two types of limitations that the power transmission networks face the first is steady-state constraint and secondly dynamic constraint. Both constraints restrict the power worthy and limit the margin of security of the system. The smooth operation limits are mainly related to electrical voltage magnitude limits, thermal rating limits and stability limits. On the other hand, dynamic limits mainly include transient stability limits, voltage stability limits and limits to the electromechanical oscillation damping [5].

Grid owners have traditionally been using conventional compensation techniques with fixed or mechanically switched shunt/series capacitor and reactors for addressing these problems. Although they provided the basic functions of reactive power support. These traditional methods had delays in responses, which typically ranged from several cycles to seconds and very limited controllability. Because of which they were not efficient for dynamic event-related disturbances [6]. The development of power electronics led to the emergence of FACTS which brought a significant change in the control of the transmission network. FACTS controllers use high-power semiconductor devices to rapidly and continuously modify various parameters of the transmission, including voltage, impedance, and angle. Through this technology we can optimize power flows in real-time to enhance system stability and better utilise existing transmission systems without major reinforcements [7].

2.2 Steady-state and dynamic applications

2.2.1 Steady-state enhancement

Devices of FACTS plays an important role in controlling bus voltage profiles and power flow distribution to overcome steady-state limitations. By regulating the reactive power injection/absorption, series compensation, or phase angle adjustment, it helps to reduce voltage violations, line congestion and loading pattern. Studies show that FACTS controllers increase transmission capacity by 20-40% compared to conventional compensation methods while achieving the same operational security [8].

2.2.2 Dynamic performance improvement

FACTS controllers help to improve transient stability, voltage stability, and oscillation damping of power systems. FACTS devices can provide reactive power support within one cycle during disturbances. This action protects against voltage collapse and loss of synchronism. Specific applications include.

• STATCOM helps to stabilize voltage during faults.
• Using TCSC to improve transient stability and dampen power oscillations.
• UPFC simultaneously controls voltage, impedance, and phase angle.

Table 1 describes the technical merits of different FACTS controllers which are useful to complement each other to meet various system requirements.

Table 1. Technical benefits of various FACTS devices

2.3 Economic and environmental considerations

FACTS installation requires economic analysis due to the high capital expenditures involved, even though they perform better technically. Comprehensive feasibility studies must consider:

• Cost of company formation versus cost of operation.
• Optimizing placement for maximum impact strategically.
• Analysis of lifecycle cost and maintenance reliability.
• Estimating a payback period through loss reduction and investment deferment.

Economic analyses usually show that FACTS prove to be cost-benefit effective for congestion-prone networks or systems with stability issues. The payback periods are typically between 3-7 years depending on the system characteristics and electricity markets [9].

From an environmental point of view, FACTS technology is sustainable by:

• Make the most of current transmission corridors.
• Lessening the reliance on new land acquisitions.
• To allow for an increase in renewable energy penetration.
• Reducing transmission losses and greenhouse gas emissions.

2.4 Implementation considerations

A successful integration of FACTS requires careful planning which includes.

• Device selection based on specific system requirements.
• Optimal placement determined through sensitivity analysis or optimization algorithms.
• Capacity sizing to address identified constraints without over-investment.
• Control strategy development for coordinated operation with existing system controllers.
• Protection coordination to ensure system security during contingencies.

The sections that proceed focus SVC implementation of this paper with effect of SVC on 6 bus test system which is analyzed by using MATLAB, PSAT simulation.

4.1 SVC control strategy and operational mechanism

The SVC acts as shunt susceptance which is variable and provides reactive power dynamically through thyristor gates. The working principle is based on the fast change of $B_{S V C}$ (synchronous compensator equivalent susceptance) when the system voltage varies from its reference voltage $V_{\text {ref }}$. The SVC can respond as instantaneously as a power frequency cycle, which differentiates it from the more traditional compensation methods used for voltage regulation [18].

In this study, the SVC is configured in voltage control mode with a 3% droop characteristic, maintaining the voltage at the point of common coupling (Bus 5) at 1.0 per unit under normal operating conditions. The control algorithm continuously monitors bus voltage and adjusts thyristor firing angles to inject or absorb reactive power according to the linear characteristic:

$Q_{S V C}=\frac{1}{X_{\text {droop }}}\left(V_{{ref }}-V_{{meas }}\right)$     (7)

where, $X_{{droop }}$ represents the slope setting (0.03 p.u.) and $V_{{meas }}$ is the measured voltage at the SVC terminal.

4.2 Strategic placement rationale at Bus 5

The decision to select Bus 5 for the SVC installation has been made following a comprehensive sensitivity analysis employing the voltage stability index $L_{{index}}$ and loss sensitivity factors. The methodology involves:

• To calculate the $L_{{index}}$ values for all load buses, the voltage Stability will be assessed [19].

$L_j=\left|1-\sum_{i=1}^{N_g} F_{i j} \frac{V_i}{V_j}\right|$     (8)

where, $F_{i j}$ refers to the system matrix components which are related to generator and load buses. Bus 5 had the highest $L_{{index}}$ value (0.42) meaning Bus 5 was nearest.

• After carrying out the sensitivity analysis of $\frac{\partial P_{{loss}}}{\partial Q_{{loss}}}$, it is found that injection of reactive power at Bus 5 provides the maximum reduction in total loss of the system with 0.85 is the sensitivity factor.
• Bus 5 supports the largest and extremely variable load (100 MW + h70 MVAR) in the given test system. It is also the bus where voltage support must be provided.

4.3 Analytical framework for power transfer enhancement

The effect of SVC on power transfer capacity can be mathematically derived by two-bus equivalent system shown in Figure 4. When a transmission line having reactance $X_L$, is not compensated, the maximum power that can be transmitted is limited [20-25].

$P_{\max }=\frac{V_1 V_2}{X_L} \sin (\delta)$     (9)

Figure 4. Two-bus equivalent system: (a) Uncompensated configuration; (b) With midpoint SVC compensation

Figure 5. Power-angle characteristics comparison: Uncompensated system (dashed) vs. SVC-compensated system (solid)

Figure 5 illustrates the consequent enhancement in the power-angle characteristics. With SVC installation at the midpoint, the system effectively decouples into two independent segments, each with reactance $\frac{X_L}{2}$. The power-angle relationship transforms to [26-28]:

$P_{\text {comp }}=\frac{2 V_1 V_2}{X_L} \sin \left(\frac{\delta}{2}\right)$     (10)

When voltage at the sending and receiving end is the same $\left(V_1=V_2=V\right)$ then improvement factor is [29-32]:

$\eta=\frac{P_{\text {comp }}}{P_{\max }}=\frac{2 \sin \left(\frac{\delta}{2}\right)}{\sin (\delta)}$     (11)

At the stability limit $\left(\delta=90^{\circ}\right)$, this yields $\eta=\sqrt{2}$, representing a $41.4 \%$ increase in theoretical transfer capacity.

4.4 Voltage profile enhancement mechanism

The SVC enhances voltage stability via three synergistic mechanisms [33-36]:

• The SVC supplies reactive power at the point of use which reduces the flow of reactive current through transmission lines and thereby lowers voltage drop proportional to the line reactance.

$\Delta V_{{improvement }}=\frac{Q_{S V C} X_{e q}}{V_{{nominal}}}$     (12)

• System Strength Augmentation: The SVC positively affects the bus to which it is connected (the SCR) and improves voltage stiffness.

$\mathrm{SCR}_{\text {new }}=\mathrm{SCR}_{\text {old }}+\frac{Q_{S V C, \max }}{S_{s c}}$     (13)

• Stopping Voltage Collapse: If the system suffers a shock, it is better that SVC increases the voltage state rather than letting it fall further [37-40].

4.5 Loss reduction quantification methodology

By current decomposition, analytical expression under SVC integration for active power loss reduction is possible.

$\Delta P_{\text {loss }}=\sum_{k=1}^{N_l} R_k\left(I_{k, \text { before }}^2-I_{k, \text { after }}^2\right)$     (14)

where, the line current consists of active and reactive components.

$\mathrm{I}^2=\left(\frac{P}{V}\right)^2+\left(\frac{Q}{V}\right)^2$     (15)

The SVC mainly cuts down the reactive current component. Thus, loss reduction is proportional to it.

$\Delta P_{\text {loss }} \approx \sum_{k=1}^{N_l} \frac{2 R_k Q_k \Delta Q_k}{v_k^2}$     (16)

Theoretical analysis indicates that optimal placement of SVC can reduce the total active power losses by 8-12% for the 6-bus test system.

4.6 Stability margin enhancement

The SVC helps the system stay stable by giving voltage support during faults that reduces speeding up of generator. The enhancement in CCT can be determined like so.

$\Delta C C T \approx \frac{2 H \Delta V}{P_m-P_e}$     (17)

In this formula, H stands for the generator's inertia constant, $\Delta \mathrm{V}$ indicates the voltage support from SVC, while $P_m$ and $P_e$ represent mechanical and electrical power, respectively.

4.7 Validation through comparative analysis

The analytical equations provided in this section are verified through numerical simulations in Section 7. The consistency between theory (41.4% theoretical capacity increase for the Santos 4-pump procedure) and simulations (38.7% observed increase) is confirmed. Furthermore, practical implementation will be applicable due to controller dynamics and system nonlinearities.

6.1 IEEE 6-bus test system specification

The IEEE 6-bus, 3-machine standard is a popular benchmark in power system studies for evaluating optimal control strategies. As seen in Figure 6, the configuration of the system is a meshed transmission network with balanced generation-load and realistic parameters.

Figure 6. Single-line diagram of the IEEE 6-bus, 3-machine test system with 11 transmission lines

System Base Values:

• Power Base: 100 MVA
• Voltage Base: 230 kV (transmission level)
• Frequency: 60 Hz

The three generation sources and three large load centres with eleven transmission corridors are a representative network, which can be used to study FACTS device performance under various conditions.

6.2 Detailed component specifications

6.2.1 Generation resources

The system incorporates three synchronous generators with the following characteristics:

The specifications and operational parameters of the three synchronous generators are listed in Table 4.

Table 4. Generator specifications and operational parameters

Generator Control Characteristics:

• Automatic Voltage Regulators (AVRs) with standard IEEE models
• Governor systems with 5% droop characteristics
• Excitation systems capable of ±10% voltage adjustment

6.2.2 Load centers

There are three big load centres such as industrial, commercial and residential.

Details of the three major load centres are provided in Table 5.

Load modelling applies constant power (PQ) characteristics in steady state studies while the dynamic simulations employ voltage dependency factor value of $\alpha=1.0$ (active) and $\beta=2.0$ (reactive).

Table 5. Load specifications and distribution

6.2.3 Transmission network configuration

There are 11 transmission corridors which connect the components of the system according to the following parameters.

The complete transmission line specifications are given in Table 6.

Table 6. Transmission line specifications

Transmission line modeling:

• π-model representation with distributed parameters
• Thermal ratings based on 75°C conductor temperature
• Voltage drops limited to 5% under normal conditions
• Loss coefficients calculated from IEEE standard conductor data

6.3 System operating conditions

6.3.1 Base case scenario

The uncompensated system operates under the following conditions:

• Total generation: 293.74 MW, 174.48 MVar
• Total load: 280.00 MW, 190.00 MVar
• System losses: 13.74 MW (4.7% of generation), 43.94 MVar (25.2% of reactive generation)
• Minimum voltage: 0.9395 p.u. at Bus 5
• Maximum voltage: 1.0500 p.u. at Bus 1

6.3.2 SVC-enhanced scenario

The optimized configuration includes a TSC-TCR type SVC at Bus 5 with:

• Installation at the midpoint of the most heavily loaded corridor
• Dynamic range: ± 50 MVar
• Control mode: Voltage regulation with 3% droop
• Reference voltage: 1.00 p.u
• Response time: <1 cycle (16.67 ms at 60 Hz)

6.4 Analytical metrics and performance indicators

The study evaluates system performance using multiple quantitative metrics:

• Voltage Stability Index (L-index):

$L_j=\left|1-\sum_{i=1}^{N_g} F_{j i} \frac{V_i}{V_j}\right|$     (19)

where, values approaching 1.0 indicate proximity to voltage collapse.

• Loss Reduction Factor:

$L_R=\frac{P_{\text {loss }, \text { base }}-P_{\text {loss }, S V C}}{P_{\text {loss }, \text { base }}} \times 100 \%$     (20)

• Voltage Profile Improvement:

$V P I=\frac{\sum_{i=1}^N\left|V_{i, S V C^{-1.0}}\right|}{\sum_{i=1}^N\left|V_{i, b a s e}-1.0\right|} \times 100 \%$     (21)

• Transfer Capacity Enhancement:

$T C E=\frac{P_{\max , S V C}-P_{\max , \text { base }}}{P_{\max , \text { base }}} \times 100 \%$     (22)

6.5 System representation in simulation environments

6.5.1 MATLAB implementation

The test system is coded using structured matrices:

• Bus data matrix: busdata = [bus_number, type, V_setpoint, P_gen, Q_gen, P_load, Q_load]
• Line data matrix: linedata = [from_bus, to_bus, R, X, B/2, rating]
• SVC data structure: svc_data = [bus, V_ref, Q_max, Q_min, droop, control_mode]

6.5.2 PSAT implementation

System definition through GUI interface and data files:

• Network construction via drag-and-drop components
• Parameter specification through dialog boxes
• Automated model validation and consistency checks

6.6 Justification for test system selection

The IEEE 6-bus system was selected for this research based on:

• Standardization: Widely recognized benchmark with published reference results
• Complexity Balance: Sufficient complexity to demonstrate FACTS benefits while remaining computationally manageable
• Educational Value: Established as a teaching tool in power system courses
• Research Relevance: Previous FACTS studies using this system enable comparative analysis
• Scalability: Results can be extrapolated to larger systems through similarity principles

6.7 Network topology characteristics

The meshed configuration (Figure 6) exhibits:

• Average nodal degree: 3.67 (indicating high connectivity)
• Network diameter: 2 (maximum number of lines between any two buses)
• Average line loading: 68% under base conditions
• Critical corridor: Bus 2-Bus 6 (loading: 82%)

This arrangement features many pathways. This may be used to demonstrate how SVC affects the power flow in a system. The power loss may also be minimized by using this arrangement.

The inclusion of SVC in transmission of power system can be proved beneficial based on this research work on IEEE 6 Bus test network. This research employs MATLAB’s Newton-Raphson algorithm and the PSAT to verify that SVC placements at Bus 5 improve results significantly with a 7.46% reduction in active power losses, 6.94% reduction in reactive power losses, and an enhancement in voltage profile of 38%. The two simulation methods yielded similar results; with a correlation greater than 98% between them, the method will be reliable.

The technical enhancements translate into significant economic and operational benefits. Implementation of SVC increases the power transfer capacity by 38.7% and the voltage stability margins which were increased by 47.4% other than that SVC installation gives positive economic returns and the payback period is 5.2 years. The benefits to the environment include improved system performance which reduced approximately 4820 tons of CO₂ emissions every year. Power system engineers responsible for optimizing current infrastructure can use these findings for FACTS technology applications.

Future research can investigate dynamic performance under transient conditions, coordinated control with other FACTS devices, and coupling with renewable energy sources. The methodology established in this study will enable future compensation evaluation in the power system, allowing greater reliability and efficiency in electrical networks as the power system evolves in demand and power quality.