Power Flow In System Research Articles

Application of simplifying jacobian matrix and introducing iterative threshold to improve newton-raphson method in three-phase power flow calculation

Abstract With the expansion of the scale and complexity of the power system, traditional three-phase power flow calculation methods are facing dual challenges of computational efficiency and accuracy. Power flow calculation is a mathematical method for analyzing the power flow of an electrical system. And the Newton-Raphson (NR) method is an effective algorithm for solving nonlinear problems. However, updating the Jacobian matrix in the NR method can take a lot of time. Based on the asymmetry in three-phase power systems and the time-consuming nature of the NR method, an enhanced version of the NR method is proposed in this paper that improves the efficiency of power flow calculations by simplifying the Jacobian matrix and optimizing the iteration speed. Furthermore, in order to minimize the number of iterations in the NR method, it is proposed to use the PO method to determine the ideal iteration threshold.

Power flow and power system stability: Evolution of analysis methods

Power flow and power system stability: Evolution of analysis methods

Power Flow Analysis in Unbalanced Three-Phase Distribution Systems using Backward/Forward Sweep and Current Injection Methods

The electrical power distribution system is a part of the power system that distributes electricity from the transmission network to customers. In the distribution system, imbalances often occur due to the varying load profiles in each phase. This can cause voltage imbalances in the distribution system. This study aims to compare two power flow analysis methods, Backward/Forward Sweep and Current Injection. The study analyses the voltage and power loss conditions on each phase at each bus and line in the three-phase distribution system under unbalanced conditions. Simulations were conducted on two IEEE test buses, IEEE 19-Bus and IEEE 33-Bus with radial configurations. The power flow calculation results using the Backward and Forward Sweep method showed that in the IEEE 19-Bus system, the highest voltage drop percentage occurred on phase b at bus 19, at 3.14%, the highest voltage imbalance percentage occurred at bus 19, at 0.1409%, and the total active and reactive power losses were 7.352 kW and 3.164 kVAR. In the IEEE 33-Bus system, the highest voltage drop percentage occurred on phase c at bus 18, at 5.85%, the highest imbalance percentage occurred at bus 15, at 0.2077%, and the total active and reactive power losses were 19.107 kW and 8.22 kVAR. The percentage difference between the two methods used is less than one percent, indicating that both methods are sufficiently accurate in analyzing power flow in an unbalanced distribution system.

Optimizing size and location of UPFC for enhanced system dynamic stability using hybrid approach

This paper proposed a novel hybrid optimization technique, combining the Enhanced Multi-Strategic Sparrow Search Algorithm (EMSA) and White Shark Optimizer (WSO), to determine the optimal location and size of a Unified Power Flow Controller (UPFC) for enhancing power system dynamic stability. The proposed method offers improved search capabilities, reduced randomness, and lower computational complexity compared to existing approaches. Generator faults can significantly impact system dynamic stability constraints, including voltage and power loss. EMSA algorithm is employed to identify optimal location for UPFC placement by selecting bus with minimum power loss. Subsequently, WSO algorithm is used to optimize UPFC's capacity, ensuring that affected system parameters and dynamic stability constraints are restored within safe limits. Optimized UPFC is then installed at identified location, and system's power flow is analyzed. Proposed method is implemented in MATLAB/Simulink environment and tested on both IEEE 30 and IEEE 14 standard benchmark systems. Proposed method's performance is evaluated by comparison with existing methods.

The Calibrated Safety Constraints Optimal Power Flow for the Operation of Wind-Integrated Power Systems

As the penetration of renewable energy sources (RESs), particularly wind power, continues to rise, the uncertainty in power systems increases. This challenges traditional optimal power flow (OPF) methods. This paper proposes a Calibrated Safety Constraints Optimal Power Flow (CSCOPF) model that uses the Improved Acceleration Coefficient-Based Bee Swarm algorithm (IACBS) in combination with the equivalent current injection (ECI) model. The proposed method addresses key challenges in wind-integrated power systems by ensuring preventive safety scheduling and enabling effective power incident safety analysis (PISA). This improves system reliability and stability. This method incorporates mixed-integer programming, with continuous and discrete variables representing power outputs and control mechanisms. Detailed numerical simulations were conducted on the IEEE 30-bus test system, and the feasibility of the proposed method was further validated on the IEEE 118-bus test system. The results show that the IACBS algorithm outperforms the existing methods in both computational efficiency and robustness. It achieves lower generation costs and faster convergence times. Additionally, the CSCOPF model effectively prevents power grid disruptions during critical incidents, ensuring that wind farms remain operational within predefined safety limits, even in fault scenarios. These findings suggest that the CSCOPF model provides a reliable solution for optimizing power flow in renewable energy-integrated systems, significantly contributing to grid stability and operational safety.

Reactive Power Compensation for Standalone Hybrid Power System Using Facts Devices

Reactive power compensation is essential in hybrid grid-connected systems because power electronic inverters utilized for supplying DC energy into the grid causes a reduction in the overall power factor of the power systems. Due to the ability to provide a reliable and efficient power supply to remote and off-grid areas, hybrid power systems are growing in popularity. It can provide greater opportunities for operational growth by combining economic and technology advancement. To meet the demand for electrical energy in both regular and critical situations, operators must be in charge of the power systems reliable and secure operation. The primary objective of the work is to control the reactive power flow in a grid-connected hybrid renewable energy system (PV-wind-battery). The power quality problems that these systems frequently experience include voltage sags, harmonics, and flicker. A FACTS device Unified Power Quality controller (UPQC) with a Genetic Algorithm based PI controller is suggested to handle these power quality issues. In order to improve the performance of the power system, the proposed optimization approaches are used to tune the UPQC in a multiline transmission system. The model was developed with the help of the MATLAB/Simulink work framework.

Analysis of Reactive Power Flow in an Electric Power System

Optimal power flow analysis is a calculation to minimize an objective function, namely generation costs or transmission losses by regulating the active power and reactive power generation of each interconnected power system generator by taking into account certain limits. The growth of industrial loads which are dominated by inductive loads requires a fairly large reactive power supply. This reactive power requirement will of course reduce the available power that can be transmitted to the load. Reactive power flow in transmission lines will reduce the active power distribution capacity required by the load. Reactive power flow that is too large can also cause losses. However, this reactive power is also an important component in the stability of the electric power system. For this reason, the flow of active and reactive power in transmission lines needs to be regulated so that the capacity and stability of the electric power transmission system is maintained.

Decentralized Stochastic Recursive Gradient Method for Fully Decentralized OPF in Multi-Area Power Systems

This paper addresses the critical challenge of optimizing power flow in multi-area power systems while maintaining information privacy and decentralized control. The main objective is to develop a novel decentralized stochastic recursive gradient (DSRG) method for solving the optimal power flow (OPF) problem in a fully decentralized manner. Unlike traditional centralized approaches, which require extensive data sharing and centralized control, the DSRG method ensures that each area within the power system can make independent decisions based on local information while still achieving global optimization. Numerical simulations are conducted using MATLAB (Version 1.0.0.1) to evaluate the performance of the DSRG method on a 3-area, 9-bus test system. The results demonstrate that the DSRG method converges significantly faster than other decentralized OPF methods, reducing the overall computation time while maintaining cost efficiency and system stability. These findings highlight the DSRG method’s potential to significantly enhance the efficiency and scalability of decentralized OPF in modern power systems.

Hybrid Power Generating System Sources and Load Synchronization Using Adaptive-Neural-Fuzzy-Inference-System and Pelican Optimization Algorithm Technique

The integration of renewable energy sources (RESs) into current power networks addresses rising global energy demand and mitigates greenhouse gas emissions. This transition shifts the role of frequency regulation from synchronous generators to power converters, serving as interfaces between the grid and RESs. This paper proposes a hybrid method for optimizing power flow in hybrid power-generating systems. The proposed hybrid technique is the combined execution of an Adaptive-Neural-Fuzzy-Inference-System (ANFIS) and Pelican Optimization Algorithm. Hence it is named as ANFIS-POA technique. POA optimizes current and voltage controllers, while ANFIS predicts optimal system parameters. Implemented in MATLAB, the proposed strategy achieves an impressive efficiency of 96%, outperforming existing strategies like genetic algorithm (GA) and particle swarm optimization (PSO). With a faster settling time (0.56 s), a shorter rising time (1.32 s), and a reduced peak time (5.78 s), the proposed approach performs better than existing methods. Additionally, it significantly lessens system costs (Rs. 99,450) and demonstrates superior statistical performance in terms of lower error rates and improved key metrics like accuracy, precision, and recall compared to existing methods.

Performance analysis of PID and SMC for PEMFC-based grid integrated system using nine switch converter - A comparative study

Hydrogen fuel cells are gaining popularity as a reliable and efficient sustainable energy source. They have found uses in electric vehicles and microgrid applications. A grid-connected microgrid system with a 60 kW proton exchange membrane fuel cell (PEMFC) is proposed. A PEM fuel cell-based generating unit is studied, using a sliding mode controller (SMC) in the control scheme and a nine-switch converter (NSC) for the system integration. The NSC is used to integrate the FC system with the utility grid and controls the system's power flow. This study is focused on the performance evaluation of the proportional-integral-derivative (PID) and SMC controllers. The controllers' gains are tuned using an improved arithmetic optimization method (IAOA). The article also emphasizes improving system performance and stability by incorporating SMC in the control scheme. The suggested system is exposed to different source and load-side disturbances for performance evaluation. Matlab/Simulink is used to model the proposed system and validated by the real-time OPAL-RT 4510.

Optimal power flow in hybrid AC-DC systems considering N-k security constraints in the preventive-corrective control stage

The optimal power flow methods for AC-DC systems containing VSC-HVDC generally only consider the economy during normal operation, overlooking the distribution of line transmission power in fault conditions. As a result, lines that continue to operate after a fault may experience overloading or operate at full capacity. Thus, a method for optimal power flow calculation is proposed that incorporates N-k security constraints in the preventive-corrective control stage for secure and economic operation of hybrid AC-DC systems. This method ensures that the line transmission power in the system meets the limits in the normal, short-term fault, and long-term fault states. In addition to the optimal power flow in the normal state, the method incorporates the system's imbalance as an indicator to evaluate system resilience. It combines this indicator with the economic, network loss, and performance metrics of the system, forming a two-stage bi-level multi-objective optimization model. Furthermore, to address the curse of dimensionality in anticipating system fault sets, a method for generating the anticipated fault set using non-sequential Monte Carlo simulation is proposed, along with a fault scenario search approach based on robust thinking to identify the most severe faults. Finally, the traditional IEEE 30-bus system was improved, and simulation verification was conducted using examples of an AC/DC system with a three-terminal DC network and a wind-solar-storage hybrid AC/DC system with a three-terminal DC network. The simulation results indicate that the proposed optimal power flow method considering the preventive-corrective control stage with N-k security constraints can effectively enhance system resilience. Furthermore, it improves the economic efficiency while ensuring the secure operation of the system.

Modified control approach for MPP tracking and DC bus voltage regulation in a hybrid standalone microgrid

This paper proposes modified MPPT control technique for hybrid standalone microgrid. Standalone PV based microgrid has emerged as potential solutions to electricity challenges in the region where grid is not available. The battery energy storage system (BESS) is integrated into the system to facilitate synchronized load control and power flow. Variation in solar irradiation, load demand and fluctuation in battery SOC results in DC voltage fluctuation and maximum power point tracking challenges. Hybrid PV-Battery systems therefore must require control algorithms that can both flexibly adjust power flows as well as stabilize bus voltages. Proposed control technique is successful in regulating DC bus voltage and balancing the power flow in system under various operating conditions. A bidirectional converter is employed to maintain the nominal DC voltage conditions by charging/discharging the battery due to intermittent PV generation. It regulates the voltage of the DC bus to the maximum power point of the PV array. The main goal of this research article is to implement modified MPPT technique which includes Incremental conductance algorithm with double closed loop controller to track maximum power and to regulate the DC bus voltage of the system under different type of dynamic and atmospheric conditions.

Improved Newton-Raphson method with simplified Jacobian matrix and optimized iteration rate for power flow calculation of power system

With high penetration of renewable energy and novel loads connected to the distribution network, the voltage fluctuation becomes more severe and frequent, which may cause over- and under-voltage. The distribution system operator should calculate the power flow and validate the state to optimize the distribution network. Power flow calculation is the solution to the multivariate nonlinear problem, and the Newton-Raphson method is an effective algorithm for solving nonlinear problems. However, calculating the Jacobian matrix is a crucial process of the Newton-Raphson method, which is time-consuming. Therefore, this paper proposed an improved Newton-Raphson method, which simplifies and decreases the iterations of the calculation process of the Jacobian matrix to improve the calculation rate. To verify the effectiveness of the proposed method, the power flow of the IEEE 33-node power distribution system is calculated by the improved Newton-Raphson method and the conventional Newton-Raphson method.

Optimal Power Flow of Power System with Unified Power Flow Controller Using Moth Flame Optimization with Locational Marginal Price

Consideration of transmission line capacity and the optimal power flow (OPF) determines the locational marginal price (LMP), which in turn determines the performance and profitability of a producing unit. Reducing the total cost of the generators can lead to a drop in the market price of electricity. It is recommended to use numerical and repetition-based approaches for solving power flow equations due to their nonlinear nature. In order to achieve the ideal power flow at an affordable price, this paper employs a Moth Flame Optimization (MFO) to solve the equations. We then enhance the MFO’s structure to make it more effective at performing the simultaneous calculations of power passing through transmission lines. Flexible AC transmission systems (FACTS) tool that has been utilized to overcome this problem is the Unified Power Flow Controller (UPFC). Lastly, the proposed MFO algorithm would include the following parameters in its output: bus voltages, line losses, generated power, total generating expenditures, and generator profits. In this work, the proposed method is tested on the IEEE 57-bus network also shows that it improves upon the OPF problem.

A new comprehensive framework for cascading outage simulation in power systems

Simulating accurately and fast cascading outages play a critical role in power system security and resilience assessment. This paper proposes a new comprehensive framework for cascading outage simulation, articulated around an extended AC power flow. To address the key modelling features of cascading outage simulation, the proposed framework develops new algorithms for: a) detecting possible islanding, b) frequency control in each island: primary frequency control (PFC), under-frequency load shedding (UFLS) and over-frequency generator tripping (OFGT) and c) improved under-voltage load shedding (UVLS) and load models to avoid the divergence of AC power flow and allow handling voltage instability during the cascade. Tests on a realistic 60-bus system show that the proposed cascading outage simulator can successfully handle islanding, PFC, UFLS, OFGT, and UVLS; it simulates the cascade until there is no violation of system frequency, voltage, and power flow limits in islands that do not experience blackout.

Distribution System Survey and Analysis: A Case Study of Kathmandu University

Load flow analysis helps to understand a power system's voltage profile and power flow distribution, enabling the identification of potential issues such as overloading and under-voltage conditions. Fault analysis ensures reliability and safety by understanding and mitigating abnormal conditions in electrical distribution systems. Together, they contribute to efficient operation, equipment protection, and overall system reliability. This paper presents the Kathmandu University distribution system's load flow and fault analysis. Starting from the careful study of the power usage of the Kathmandu University distribution system then followed by the load flow analysis employed in the Dig Silent Power factory software, critical insights into the system’s performance were unveiled. Additionally, fault analysis within the simulated distribution system provides valuable data to enhance the understanding of the different patterns of currents for the various types of faults that occur at different locations of the Kathmandu University distribution system. This study provides a comprehensive understanding of the Kathmandu University distribution system. It identifies potential issues that can help to make the Kathmandu University power system more reliable and efficient in the future.

An Improved Embedded based PID Controller for Boosting Operation in Solar Energy-Battery Systems

The proposed work introduces an improved PID controller for boosting operation in solar energy-battery systems, leveraging model-based controller (MBC) techniques. In general, boost converters are crucial for managing and optimizing power flow in renewable energy systems. While PID controllers are commonly used in boosting applications due to their simplicity, they often face challenges in adapting to the dynamic and nonlinear characteristics of solar energy systems. This can result in suboptimal performance and efficiency. Hence, a model-based controller with manual tuning is proposed to improve the stability and efficiency by systematically tuning controller gain parameters based on its system model. Extensive simulation studies conducted using MATLAB/Simulink shows that the proposed controller outperforms the conventional PID controller under various operating conditions, such as fluctuations in solar irradiance and changes in battery state of charge. Further, the experimental tests conducted on a prototype setup validates the feasibility and ability of the model-based controller to accurately regulate the solar panel output and efficiently charge the battery, which leads to enhanced performance. This work offers a promising solution for enhancing energy conversion efficiency and facilitates the effective integration of renewable energy sources into the power grid.

Three‐phase state estimation in transmission networks with unbalanced loading utilising SCADA measurements

AbstractState estimation stands as one of the most crucial applications in energy management systems of control centres, ensuring the secure operation of the power system. The real‐time availability of accurate system variables, including voltages, currents, and power flows, presents an excellent opportunity to consider the actual network characteristics, including imbalances. This paper presents a linear and non‐iterative method to solve the three‐phase state estimation problem in transmission systems with unbalanced loading. The method utilises supervisory control and data acquisition measurements obtained from remote terminal units. The formulation is based on complex variables derived from traditional supervisory control and data acquisition measurements, with assumptions made regarding the availability of certain three‐phase bus voltages, as well as a number of three‐phase currents and active and reactive power flows. The proposed algorithm employs the classical weighted least squares technique for solving the three‐phase state estimation problem. Due to its straightforward and linear nature, the method ensures no convergence issues. To validate its effectiveness, the proposed method is validated on a three‐bus network and the IEEE 39‐bus network simulated using the three‐phase model within the DIgSILENT Power Factory environment.

Risk Assessment and Analysis of New Power System Operation Under Extreme Disasters

Abstract In recent years, new power systems have been developing continuously, and the operational risk assessment of new power systems under extreme disaster conditions has attracted much attention. This paper uses Latin hypercube sampling technology to establish a power system failure model under extreme disasters and proposes a new power system risk assessment method that applies the power system power flow model to establish a comprehensive system risk index. In addition, taking the power grid of a certain province in eastern China as an example, a case analysis is conducted on the IEEE39 node system to verify the effectiveness of the method.

Power system load frequency management using fuzzy logic

A power system is a sizable, intricately linked network that has multiple sources and loads. The population growth causes variations and unpredictability in load demand. The utilities are responsible for meeting load demand while abiding by operational restrictions on the power system. Control of load frequency is alone in charge of providing the customers with sustainable electrical power. Its primary purpose is to control system frequency and power flow in additional areas within advised bounds by controlling tie-line power and the utility generator's output power in reaction to changes in load without compromising system frequency. The paper's recommended concept illustrates the load frequency control of two area systems using fuzzy logic, fuzzy tuned proportional integral, conventional proportional integral, and proportional integral derivative controllers. SIMULINK is used for simulation research.