Power Flow Analysis Research Articles

OPTIMAL LOCATION OF AN IDEAL TRANSFORMER UPFC MODEL USING OPF FIRST-ORDER SENSITIVITIES

This paper presents a screening technique for greatly reducing the computation involved in determining the optimal location of a unified power flow controller (UPFC) in a power system. The first-order sensitivities of the generation cost with respect to UPFC control parameters are derived. This technique requires running only one optimal power flow (OPF) to obtain UPFC sensitivities for all possible transmission lines. To implement a sensitivity-based screening technique for guidance in optimally locating a single UPFC in a power system, we propose a new UPFC model, wrach consists of an ideal transformer with a complex turns ratio and a variable shunt admittance. In this model, the UPFC control variables do not depend explicitly on UPFC input and output currents and voltages. Accordingly, this model does not require adding extra buses for UPFC input and output terminals. IEEE five-, 14- and 30-bus systems were used to frustrate the technique. Index Terms-Flexible ac transmission systems (FACTS), FACTS location, first-order sensitivity, optimal power flow (OPF), screening technique, unified power flow controller (UPFC), UPFC ideal transformer model, UPFC placement, UPFC uncoupled model. This study focuses on the development of an Ideal Transformer Unified Power Flow Controller (UPFC) model and its integration with Optimal Power Flow (OPF) first-order sensitivities analysis for determining optimal UPFC locations in power systems. The abstract outlines the significance of UPFCs in enhancing power system stability and efficiency by controlling voltage and power flow. It highlights the objectives of the research, including the development of the UPFC model, analysis of OPF first-order sensitivities, and their combined application for screening optimal UPFC locations. The study aims to contribute to the improvement of power system operation and control through strategic UPFC placement. The abstract provides a concise overview of the study, summarizing the key aspects of the research. It outlines the development of an ideal transformer Unified Power Flow Controller (UPFC) model, the analysis of Optimal Power Flow (OPF) first-order sensitivities, and their application in determining optimal locations for UPFC installation in power systems

Maximum span determination and optimal sizing of cable for improved performance of droop-controlled DC microgrid

DC microgrids are seen as smart solutions to interface DC loads and distributed energy resources (DERs). However, in DC microgrids, the placement of sources and loads as well as the size of cable impact the system’s span, regulation of voltage, and losses. This paper proposes novel algorithms to determine the maximum span and optimal size of cable for the improved performance of a droop-controlled DC microgrid. The proposed algorithms utilize an improved power flow analysis (IPFA) method based on Newton-Raphson technique to determine the maximum span and the optimal size of cable, enhancing the voltage regulation and reducing the cost. Additionally, the impacts of power rating, droop constants, and size of cable on the DC microgrid’s maximum span are investigated and reported. Owing to the intricate nature of the problem concerning the ideal size of cable for the droop-controlled DC microgrid, a heuristic optimization approach is employed. Further to enhance the rate of convergence and computational performance, an improved particle swarm optimization (IPSO) is also proposed. The constraint of keeping the bus voltage variations below the allowable voltage regulation limits is applied to the objective function of the optimization problem. In the case of a droop-controlled, DC microgrid having a specified configuration, the suggested algorithm can determine the ideal size of cable, guaranteeing both the least cost and enhanced voltage regulation. Comprehensive numerical and modelling results have been presented for a droop-controlled DC microgrid with different loads and DERs to verify the effectiveness of the proposed methods. Furthermore, the analysis reveals that configuration III of the DC microgrid with an optimal cable size of 19 mm2 lowers the absolute voltage regulation to as low as 1.06 V. The results of the detailed analysis validate the enhanced performance of the proposed algorithms and are highly useful to both system designers and consumers of the DC microgrids, eventually paving the way for the widespread use of DC microgrids in the future.

Power Flow Calculation for AC/DC Power Systems with Line-Commutated Converter–Modular Multilevel Converter (LCC-MMC) Hybrid High-Voltage Direct Current (HVDC) Based on the Holomorphic Embedding Method

To harness the strengths and mitigate the limitations of line-commutated converter (LCC) and modular multilevel converter (MMC) HVDC systems, the LCC-MMC hybrid HVDC system has been developed. This paper proposes a holomorphic embedding (HE)-based power flow calculation method for AC/DC power systems with the LCC-MMC hybrid HVDC system. Firstly, the methodology involves establishing the mathematical model of the LCC-MMC hybrid HVDC system and its control modes. Subsequently, the HE formulation for the constructed LCC-MMC model is derived using the HE method. The proposed method simplifies the HE formulation using substitute variables, making it adaptable to various control modes. The designed HE formulation facilitates the derivation of the germ solution and the calculation of high-order power series coefficients. A sequential solution flow chart compatible with AC power flow algorithms is constructed to enhance the practicality of the HE method for real-world large-scale systems. The accuracy and effectiveness of the proposed method are verified through numerical tests on the modified IEEE 14-bus, IEEE 57-bus, and large 2383-bus system. The proposed method provides a reliable and efficient solution for power flow analysis in hybrid HVDC systems.

Power Flow Analysis Using Fuzzy for Single Phase Transformer Less PV System Connected with a Nine-Level Converter

Power electronics technology advancements and growing environmental concerns worldwide have made photovoltaic (PV) systems more visible in distributed generation systems. Photovoltaics, or solar PV, is an important component of solar energy for generating electricity. Grid-connected inverters must be able to regulate the amount of power they inject into the grid, track maximum power points, be highly efficient, and inject currents into the grid with minimal harmonic distortion. Two step-down converters were used to construct an inverter without a single-phase transformer. This study investigates two multi-sequence inverter types that use different voltages and are based on single-phase grid-connected photovoltaic (PV) technology. A new nine-level grid-connected transformer-less photovoltaic converter was proposed in this study. MATLAB was used to construct the complicated FFT simulation using fuzzy logic controls. Analyzing efficiency through simulation in order to enhance efficiency. This work aims to replace PI controllers with fuzzy controlled systems so that single-stage operation can be improved with reduced switches in an economic manner. An improvement of 10% over the existing system is achieved by implementing fuzzy computing.

Power flow and reliability analysis of a non-isolated PV/grid connected quasi resonant converter for off-board EV charging station

ABSTRACT Growing awareness of greenhouse gas emissions and exhaustion of fossil fuels leads to the adoption of electric vehicles (EVs). However, the major limitations with respect to EV technology are the driving range and charging time. Also, the proliferation of EVs overloads the power grid and paves the way of incorporating renewable energy sources and energy storage devices. The use of multiple sources necessitates the deployment of compact, low-cost, and high-power electronic converters. This paper proposes a novel configuration of a Multi-Source Non-Isolated Quasi-Resonant Converter (MSNQRC) to overcome the limitations in the charging infrastructure. Due to the presence of a quasi-resonant network, the proposed MSNQRC with a single switch can achieve high voltage gain even at low-duty cycles, provide continuous current and low voltage stress. In addition, this paper elaborates on the parametric design of the converter along with PV modeling based on load ratings and the reliability research of MSNQRC by analysing component failures. A prototype model of 300W is built to verify the efficacy of the designed converter model. The results thus obtained validate the designed model and prove that the proposed system can be used for off-board battery charging systems.

Coordination of PSS and Multiple FACTS-POD to Improve Stability and Operation Economy of Wind-thermal-bundled Power System

Aims and Background: Focusing on the low-frequency oscillation and system power loss problem in wind-thermal-bundled (WTB) transmission systems and the interaction problem due to different controllers, this study aimed to improve the low-frequency oscillation characteristics of WTB transmission system while ensuring the economy of operation and suppressing the adverse interaction between controllers. Methods: For this purpose, a coordination and optimization strategy for a power system stabilizer (PSS), static synchronous series compensator with additional power oscillation damping controller (SSSC-POD), and static synchronous compensator with additional power oscillation damping controller (STATCOM-POD) is proposed based on multi-objective salp swarm algorithm (MSSA). The controller regulation characteristics are taken into account in the coordination method. Results: Several designed scenarios, including changing the transmission power of the tie line and increasing wind power output, are considered in the IEEE 4-machine 2-area to test the proposed method. The power flow analysis, characteristic root analysis, and time-domain simulation are used to analyze the simulation results. Conclusion: Simulation results demonstrate that the proposed approach can effectively suppress the low-frequency oscillation of the WTB system while reducing its net loss. The application in engineering issues for MSSA is supplemented.

Improved Adaptive Network-Based Fuzzy Inference System Approach for Power Flow Analysis in Interconnected DC Microgrid

High-performance power conversion needs are becoming more and more important for microgrid applications. In actuality, many contemporary DC distribution systems use isolated bidirectional dc-dc converters. Hence, in this paper, an Improved Adaptive Network-based Fuzzy Inference System (IANFIS)is developed to control the output power of the components and reduce the variation among the consumption and generation of the power while managing a constant DC bus voltage. This work proposes a power management control strategy that ensures the power balance of a stand-alone DC microgrid where DAB converters link the battery energy storage (BES) unit and the renewable energy source (RES). The generation side, or photovoltaic (PV) system and BES, is coupled to the storage systems and renewable energy sources. Furthermore, a DC microgrid is connected to the load demand. The load demand is compensated with the help of the storage and generation systems with the help of a dual active bridge converter. The DAB is connected with the dual DC microgrid system for managing power flow among the two DC microgrids. This dual active bridge converter is utilized to balance the power among Dual DC microgrids. The proposed methodology is developed to manage the power among generation and load demand management. The proposed method is evaluated on a dual active bridge converter connected microgrid system with the components of PV and BESS respectively.

Power flow and efficiency analysis of 2K-V gear transmission via virtual power

Power flow and efficiency analysis of 2K-V gear transmission via virtual power

Two Successive Approximate Models and Linear Formulations for Power Flow Analysis of DC Grid

Two Successive Approximate Models and Linear Formulations for Power Flow Analysis of DC Grid

Large scale penetration impact of PMS-WTGS on voltage profile and power loss for 5-bus, 330kV system of the Nigerian grid

In recent times, adverse environmental changes and the gradual reduction in fossil fuel deposits is making integration of renewable energy secure global attention. This paper therefore investigates the effect of high penetration of wind power on power loss and voltage profile of 52-bus, 330kV Nigerian grid. Modeling and simulation of the study were successfully done using the Continuation Power Flow method and Power System Analysis Toolbox in the Matrix Laboratory environment. The Ant Colony Optimization (ACO) technique codes were used to determine the best sites and sizes of Permanent Magnet Synchronous-based Wind Turbine Generators (PMS-WTGs) on the grid as nonoptimal placement and size of PMS-WTGs will result into active power losses and poor voltage profile. The ACO and power flow analysis indicated two load buses, Aladja bus and Yola bus as best sites for PMS-WTGs with optimal sizes of 100MW and 197MW respectively. The result shows a decrease in the system's active (42.1%) and reactive (43.9%) power losses while heightening voltage magnitudes of critical buses to statutory values and enhancing the grid power quality. The overall results indicate that integrating 297MW PMS-WTGs improves voltage stability and power loss reduction by maximizing system loadability and reducing line losses.

Hierarchical-power-flow-based energy management for alternative/direct current hybrid microgrids

Modern microgrids are systems comprising both Alternative Current (AC) and Direct Current (DC) subgrids, integrated with Distributed Generations (DGs), storage systems, and Electric Vehicles (EVs) parking facilities. Achieving stable and reliable load flow control amidst varying load, generation, and charging/discharging strategies requires a hierarchical control scheme. This paper proposes an hourly power flow (PF) analysis within an Energy Management System (EMS) for AC/DC Hybrid Microgrids interconnected via an Interlinking Converter (IC) in both grid-connected and islanded modes. The framework operates within a two-level hierarchically controlled platform. Tertiary control at the top level optimizes DGs' reference power for generation and consumption, minimizing power purchase costs and load shedding in grid-connected and islanded modes, respectively. DG converters employ current control mode to share their power references as the primary controller. While no secondary controller is adopted in this scheme, the Battery Energy Storage System (BESS) in islanded mode utilizes P/Q droop control to maintain voltage and frequency in the AC subsystem. Power sharing between AC and DC subgrids through IC is determined by the difference between AC grid frequency and DC link voltage. Integration of controlled converters’ buses into PF equations enables solving the unified system using the traditional Newton-Raphson (NR) method. A segment of a real distribution grid planned for installation in Italy under the HYPERRIDE project serves as a case study. Comparison with MATLAB/Simulink results confirms the effectiveness, precision, and convergence speed of the proposed model and control schemes, demonstrating efficient load distribution and voltage/frequency restoration in islanded mode.

Power flow analysis of the three-beam system on double parameter elastic foundations based on the wave propagation approach

This article investigates the power flow of the three-beam system on Winkler–Pasternak elastic foundations under elastic boundary conditions. The time-averaged power flow of the beam on elastic foundations with elastic boundary conditions is calculated based on the internal shear force and bending moment and the wave propagation approach. The reliability and accuracy of the calculation method are verified by comparing the vibration acceleration calculated by calculation examples and the finite element method. In addition, the effects of structural parameters and boundary conditions on the power flow of the three-beam system are investigated. This contributes to the analysis of the dynamic characteristics of the beam on double parameter elastic foundations under complex boundary conditions.

Optimal Power Flow in Hybrid AC/DC Microgrid using ANN for Cost Minimization

Currently, this work lays the ground work for sophisticated control methods and decision support systems in hybrid microgrid operations by providing insightful information about integrating artificial intelligence for improved microgrid control. In this work, a neural network (NN) method is proposed for power flow analysis in an IEEE 12-bus-based Hybrid AC/DC Microgrid. The study optimizes power dispatch, minimizes expenses, and minimizes losses in both AC and DC components. Simulation is carried using MATLAB software and the results are presented and analysed. The accuracy of the NN’s predictions of active power flows is demonstrated by training it on historical data and validating it on real-time observations. Regression plots comparing anticipated and real values demonstrate the effectiveness of NN-based analysis in reaching the ideal power distribution.

Optimal Power Flow and Performance Analysis of SPV Penetration to IEEE Bus System Using MI Power

The need to meet changing demand in an economical manner while making the best use of already-expensive electrical systems led to inescapable problems with overloading, increased power transfer coupled with extremely high system loss, and unstable voltage profiles that ultimately resulted in an unreliable system. Power distribution is impacted by the remarkable changes that are currently taking place in the use and provision of energy services. Numerous new avenues for the provision and use of electrical energy have been opened up as a result of developed and diverse distributed technologies, including distributed electricity generation. The emergence of powerful and affordable software has enabled us to cope with the fast-paced development in the power industry which requires updating resources with modern technologies to manage substations. The goal of the proposed work is to integrate solar photovoltaic and optimize the power flow, voltage profile, and real power loss through the building of a simulation model on Mi Power. Power flow analysis was used to calculate the actual power loss, which was then minimized through SPV placement. Additionally, the impact of PV penetration on single bus loading was assessed for all load buses operating in succession with either active, reactive, or combined active and reactive loads.

PENGEMBANGAN SISTEM ENERGI TERBARUKAN: PENDEKATAN MULTIGENERATOR DAN SIMULASI ETAP

This research focuses on the analysis of power flow in an electrical energy system involving 5 generators, with a nominal voltage of 345 KV, and a total power of 500 MW. Utilizing the ETAP simulation software, we evaluated the distribution of power, currents, and power factor across the entire system. The results of the analysis provide deep insights into the system's response to loads, power flow, and the efficiency of electrical power utilization. At the 345 KV voltage level, the simulation demonstrates the system's capability to maintain stability and power balance effectively. Power distribution and currents among generators provide a clear overview of the performance of the electrical network. Power factor analysis offers additional information regarding the efficiency of electrical power usage within the system. These findings serve as a crucial foundation for making informed decisions in managing and developing renewable energy infrastructure. In the era of transitioning towards more sustainable energy sources, a comprehensive understanding of power flow and system responsiveness to loads is essential to ensure the reliability and efficiency of the electrical power system

Spatial modeling sensitivity analysis: Copula selection for wind speed dependence

As the adoption of wind energy as a key renewable energy source accelerates, precise power flow analysis becomes crucial for accurate power delivery forecasting. This paper addresses the inherent uncertainties in wind speed data at different wind farm locations by conducting a sensitivity analysis to assess wind farm pairs. The analysis accommodates various data sizes, namely, short, medium, and large, and diverse spatial relationships between wind farms. By leveraging National Renewable Energy Laboratory wind speed data from nine distinct wind farms, the dependence structure between wind farm pairs is modeled using copulas. This modeling takes both the wind speed knowledge level and the various spatial interplays among the wind farm pairs into consideration. The findings indicate an inverse proportionality between the strength of dependence and the distance separating the wind farm pairs.

Optimal Allocation of Distributed Generation Using Improved Cuckoo Search Algorithm

This work presents an improved cuckoo search algorithm based on Success Rate (CSA-SR) for optimal allocation of Distributed Generation (DG). This is necessary in order to improve the power quality of the distribution system by minimizing power loss and improving voltage stability. Voltage Stability Index (VSI) is applied to identify restricted unhealthy buses/areas in the distribution networks. The work is implemented on standard IEEE 33 Bus test systems. Newton Raphson Power Flow (NRPF) technique is used in MATLAB R2019b environment for the power flow analysis. The overall IEEE 33 Bus system real power loss obtained from the simulation result is found to be 202.7071MW at the base case. Following the application of 3 DGs using CSA-SR, the real power loss is found to be 113.9630 MW which shows a reduction of 88.441MW which is equivalent to 43.77% as related to the base case. The results minimized the system losses while significantly enhancing the voltage profile of the bus voltages as a result of optimal siting and sizing of the DG. These show that the CSA-SR technique outperformed PSO, which was used to ascertain the effectiveness of the developed scheme.

Performance improvement of radial distribution system with distributed generation and intermittent load

The distribution network's load situation is typically variable and non-uniform. Therefore, a modified Distributed Generation (DG) algorithm is proposed in this paper, which uses the analytical approach and applies to all kinds of radial distribution feeder networks. The specified parameter of the distribution network is given accurately to the programme manually or through the file uploading mode, and the power flow analysis is done by MATLAB software. The results are obtained, including the specific location of DG placement which is optimised analytically. Here, the voltage and power profiles are monitored seriously, and the minimisation of voltage drop, and power loss is obtained, which is precise of a high value. The system is implemented for the IEEE 33 bus system which is got from Panchasakha Feeder Network. In this proposed method, DGs are deployed to reduce the loss in the transmission line as well as to maintain the voltage stability in the system by an analytical algorithm approach.

Extension of the fixed point theory to tuned mass dampers with piezoelectric stack energy harvester

A tuned mass damper with a piezoelectric stack energy harvester (TMD-PSEH) is a passive vibration control device for the dual purpose of absorbing vibration and harvesting energy. This paper develops the fixed point theory for the optimal design of a TMD-PSEH attached to an undamped primary structure under harmonic external excitation. It has been proven that the existence of two fixed points of the amplitude-frequency curve doest not depend on the damping of the primary structure. Based on the requirements for suppressing the vibration of the primary structure and enlarging the harvested power, the analytical expressions for the optimal tuning, damping, and resistance ratios are determined. It is found that the minimum damping ratio occurs in the vicinity of the electrical resistance ratio α=1 for various values of the electromechanical coupling coefficient. Power flow analysis is carried out resulting in closed-form expressions of instantaneous and average powers. Numerical examinations of the system with the obtained optimal parameters are performed demonstrating a very good compatibility between theory and computation. In addition, the effect of damping in the primary structure is also investigated. It is shown that not only the vibration of the primary structure effectively reduces, but also a large amount of the harvested energy can be captured in the main resonance region.

Learning model combining convolutional deep neural network with a self-attention mechanism for AC optimal power flow

Alternating current optimal power flow (OPF) analysis is critical for efficient and reliable operation of power systems. For large systems or repetitive computations, the traditional methods such as the direct and gradient methods, or non-traditional methods, such as the genetic algorithm and simulating annealing, are time-consuming and unsuitable for real-time computing. The work in this paper proposes a novel framework to obtain the optimal solution of power flow in real-time using a combination of convolutional neural networks and a self-attention mechanism. All parameters of the power networks are rearranged in an image-like shape of a multi-channel image where each channel is a two-dimensional matrix. The proposed approach is adaptive with every input size of power systems as well as frequent variations of network topologies without intervention to the framework core. The encompassment of all power system contexts in which all parameters of internal elements, generation costs, and topology information are included, contributes to the higher accuracy of inference compared to other current machine-learning-based OPF-solving methods. Besides, the proposed framework established on ubiquitous platforms is effortlessly integrated into current infrastructures of power systems, and the great efficiency along with the computation speed may serve as a critical point for practical implications, such as enabling faster decision-making during real-time operations, predicting system contingencies, and remedial actions based on an offline pre-trained model. This supervised learning process is applied to the dataset of four case studies of meshed power systems: the IEEE 5-bus system (IEEE-5), the IEEE 30-bus system (IEEE-30), the IEEE 39-bus system (IEEE-39), and the IEEE 57-bus system (IEEE-57) to prove the efficacy of the proposed method.