Power Flow Controller Research Articles

Design of novel UPFC based damping controller for solar PV integrated power system using arithmetic optimization algorithm

Abstract Integrating renewable energy sources like solar power into traditional power systems poses challenges. One such challenge is the effect of renewable power plants, which use power electronics, on the grid’s stability. Specifically, these plants can impact small-signal stability by either damping or exacerbating low-frequency oscillations. This paper introduces a novel Unified Power Flow Controller (UPFC) based damping controller specifically designed for Solar Photovoltaic (PV) integrated power systems. It employs an Arithmetic Optimization Algorithm (AOA) to optimize the UPFC damping controller parameters and mitigate low-frequency oscillations in the power system. The objective function minimizes the Integral Time Absolute Error (ITAE) of speed deviations under varying loading conditions. The proposed technique is utilized simultaneously to control the modulation index of series and phase angle of shunt converters of UPFC. The MATLAB/simulation results obtained effectively from the proposed technique which is actualized and identify both detrimental and beneficial impacts of increased PV penetration for small signal stability performance. The study reveals both the small-signal stability of the system and its response to large disturbances that alter the active power balance and frequency stability. The results of the analysis demonstrated with single and multimachine environment by comparing with the other optimizations like PSO, DE, DE-PSO and GWO, the proposed one is effective for damping out the oscillations. The effectiveness of the proposed damping controller is further confirmed through real-time validation using the OPAL-RT setup.

A Novel Techno-Economical Control of UPFC against Cyber-Physical Attacks Considering Power System Interarea Oscillations

In the field of electrical engineering, there is an increasing concern among managers and operators about the secure and cost-efficient operation of smart power systems in response to disturbances caused by physical cyber attacks and natural disasters. This paper introduces an innovative framework for the hybrid, coordinated control of Unified Power Flow Controllers (UPFCs) and Power System Stabilizers (PSSs) within a power system. The primary objective of this framework is to enhance the system’s security metrics, including stability and resilience, while also considering the operational costs associated with defending against cyber-physical attacks. The main novelty of this paper lies in the introduction of a real-time online framework that optimally coordinates a power system stabilizer, power oscillation damper, and unified power flow controller to enhance the power system’s resilience against transient disturbances caused by cyber-physical attacks. The proposed approach considers technical performance indicators of power systems, such as voltage fluctuations and losses, in addition to economic objectives, when determining the optimal dynamic coordination of UPFCs and PSSs—aspects that have been neglected in previous modern research. To address the optimization problem, a novel multi-objective search algorithm inspired by Harris hawks, known as the Multi-Objective Harris Hawks (MOHH) algorithm, was developed. This algorithm is crucial in identifying the optimal controller coefficient settings. The proposed methodology was tested using standard IEEE9-bus and IEEE39-bus test systems. Simulation results demonstrate the effectiveness and efficiency of this approach in achieving optimal system recovery, both technically and economically, in the face of cyber-physical attacks.

Optimal Power Flow in electrical grids based on power routers

In recent years, there has been an exploration of innovative electric grid concepts centered around power routers, devices capable of controlling power flows as desired. One of which is the Power Router Grid, a novel high-controllable network design fully based on power routers. Its ability to arbitrarily change power flows inside controllable lines raises the challenge of determining the optimal operation within such systems. This paper aims to push further the analysis of the operation and benefits of such networks by proposing a novel optimization model tailored for power router grids based on the most recent literature for the convexification of optimal power flows. Moreover, it demonstrated that radial-based models can be expanded for grids meshed through power routers. The model presented is also convex in the form of a second-order cone, ensuring a global optimum for diverse grid configurations. It has been implemented in Python using the PYOMO modeling language and applied to three case studies investigating the effects of power router operation modes on the grid’s optimal operation and associated costs. Results show that the definition of the power router grid design and the ports operation mode must be carefully decided when demand uncertainty of over 25% is taken into consideration. Moreover, controlling power flow near lines of higher impedance can lead up to a 21% increase in line losses.

Optimal loop power flow control of power distribution system using advanced meta-heuristic algorithms

Optimal loop power flow control of power distribution system using advanced meta-heuristic algorithms

A strategy for optimal and selective utilization of multiple interline DC power flow controllers in VSC-HVDC grids

A strategy for optimal and selective utilization of multiple interline DC power flow controllers in VSC-HVDC grids

Multi-objective optimal power flow with wind–solar–tidal systems including UPFC using Adaptive Improved Flower Pollination Algorithm(AIFPA)

ABSTRACT Among the most significant non-linear challenges for power network design and smooth functioning of current modern updated power system networks is the optimum power flow (OPF) problem. Importance of the electrical system modeling has recently come to light due to the incremental use of energy from renewable sources in power systems networks. The goal is to use wind, solar and tidal sources to recreate the issue of OPF. In this work, Weibull, Lognormal, and also Gumbel probability distribution functions were applied to simulate the uncertainties of wind, photovoltaic, and tidal energy system. Additionally, by adding test scenarios of unpredictable wind, solar and tidal energy systems involving minimization of the cost function, loss of active power, voltage deviation, and increase stability of voltage. In accordance with the chosen thermal producing units, the solutions were evaluated using different locations using IEEE 30-bus systems of testing that incorporate renewable energy sources. The proposed power system planning problem was solved by multi-objective function where unified power flow controller are utilized as flexible AC transmission systems controllers via recently introduced optimization algorithms and the simulation outcomes of the aforementioned technique have been compared with Multi Objective Adaptive Guided Differential Evolution algorithms. The adaptive improved flower pollination algorithm (AIFPA) is a strong and reliable algorithm that is presented in this work. The AIFPA can efficiently deal with many kinds of high-complexity objective regions in multi-objective optimization situations. Utilizing an IEEE 30-bus test system, the suggested approaches’ performance was examined and evaluated for a range of objective functions. The simulation results obtained from the proposed algorithm were effective in finding the optimal solution compared to the results of the meta-heuristic algorithm and were reported in the literature.

A Study of Bidirectional Electric Vehicle Charging using MATLAB Simulink

On considering Electric Vehicles, the rise of Vehicle-to-Grid(V2G) concept has been accompanied with lots of advantages. The V2G technology ensures that no extra electricity needs to be consumed from the grid. It helps the power grid on a larger scale. It enables a bidirectional power flow between the EV battery and the grid. Bidirectional Buck- Boost Converter helps in grid stabilization, financial gains, and effective energy management. The DC-DC Converter does two functions: matching the battery voltage to the motor's rated voltage and controlling power flow under steady-state and transient conditions. The Proportional-Integral (PI) controller is used to correct the errors between commanded set point and the actual value based on feedback. The efficiency of the converter can be increased by using PI controller.

Bidirectional DC-DC Converter and Improved Electrical Vehicle Dynamic Response Control

Background: In automotive applications where bidirectional power flow is necessary to lighten the power system, dual active bridge (DAB) converters are frequently employed. Variations in the required output voltage, erratic input voltage, and shifting loads all have an impact on this converter. As a result, converter performance has to be improved. To increase efficiency, the current stress of the DC-DC converter must be optimised. This paper proposes a control scheme for the coupled inductor bidirectional DC-DC (CIB DC-DC) converter utilising both model predictive control (MPC) and a proportional-integral (PI) controller. The integration of these control techniques aims to enhance the performance and efficiency of the converter. Methods: The MPC algorithm is employed to predict the converter's future behaviour based on a dynamic model, taking into account system constraints and performance criteria. By optimising the control action over a finite time horizon, the MPC algorithm ensures an optimal response, considering the current state and anticipated changes. Additionally, a PI controller is incorporated to augment the control strategy. The proportional component of the PI controller enables a fast initial response to the error between the desired and actual converter outputs. The integral component eliminates steady-state errors and provides robustness against disturbances, resulting in improved overall system performance. Results: The proposed control scheme is implemented and evaluated through simulations and experimental tests on a prototype converter. The results demonstrate the effectiveness of the combined MPC and PI controller approach. Conclusion: The coupled inductor bidirectional DC-DC (CIB DC-DC) converter using MPC can provide precise control of power flow between two voltage domains, enabling efficient bidirectional power transfer. The predictive capabilities of MPC allow it to adapt to varying load conditions and respond quickly to changes, ensuring stable operation and accurate regulation of voltage and current. Overall, the coupled inductor bidirectional DC-DC converter controlled using MPC over PI offers improved performance, efficiency, and flexibility compared to traditional control methods. MPC can handle the complex dynamics response and non-linear characteristics of the converter, making it suitable for bi-directional vehicle charging applications, where precise control and high efficiency can be achieved.

Power Flow Control Strategy Based on Space Vector Modulation of a Three-Port Converter

Power Flow Control Strategy Based on Space Vector Modulation of a Three-Port Converter

OPTIMAL PLACEMENT OF UNIFIED POWER FLOW CONTROLLER USING PARTICLE SWARM OPTIMIZATION TECHNIQUE

The load growth in recent times due to advancements in technology and population increase has led to shortage of reactive power in the power system resulting in key issues such as voltage instability, large line losses, power outages among others. In this work, Particle Swarm Optimization (PSO) technique was used for optimal placement of Unified Power Flow Controller (UPFC) for power loss minimization using the IEEE 6-bus system as a test network. The load flow analysis was performed using Gauss-Seidel iterative method with and without inclusion of PSO-based UPFC. The PSO algorithm was used to find the optimum point for UPFC location and determined using the line with the least active power loss among other lines randomly selected by the PSO algorithm, with p.u defined as the voltage statutory limit. The simulation results revealed that the optimum point obtained was line 4-5, and the voltage profile were within the statutory limit with and without optimally placed UPFC. The total active power loss reduced from 495.5 to 273.9 MW, giving a reduction of 44.72 with optimally placed UPFC. The total reactive power loss equally reduced from 1439 to 936.2 MVAr, producing a reduction of 34.94 with optimally placed UPFC. These results obtained showed that PSO-based UPFC placement is suitable for power loss minimization and enhancement of the system voltage profile.

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.

Hybrid neuro-fuzzy-based 3DOF-PDN controller for AGC of multi-area interconnected power system incorporated hydrogen aqua electrolyze fuel cell units and unified power flow controller

Hybrid neuro-fuzzy-based 3DOF-PDN controller for AGC of multi-area interconnected power system incorporated hydrogen aqua electrolyze fuel cell units and unified power flow controller

Control and Protection of Medium Voltage Distribution Network Based on Unified Power Flow Controller

The integration of diverse load types, such as large-scale distributed generators and charging stations, presents considerable challenges to distribution networks. The Unified Power Flow Controller (UPFC) provides multiple benefits, including its compact dimensions, cost efficiency, seamless regulation, and swift response. When deployed in distribution networks, the UPFC facilitates the creation of a Distribution Unified Power Flow Controller (DUPFC) system. The DUPFC system enhances medium voltage distribution network regulation but also affects power quality, fault characteristics, and relay protection accuracy. To address these issues, a power flow equivalent circuit model for the medium voltage distribution loop network was developed. The operating principle and steady-state model of the UPFC were investigated, based on distribution loop network parameters and power flow distribution characteristics. A UPFC control strategy was designed to create a suitable DUPFC system for the medium voltage distribution loop network, ensuring coordination between UPFC protection and the distribution system’s protection mechanisms. This system accomplishes rapid fault isolation and automatic load transfer. Finally, a simulation model based on a typical 20 kV distribution loop network structure was selected to validate the effectiveness of the UPFC control strategy and the DUPFC protection system in MATLAB/Simulink.

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

A novel predictive optimal control strategy for renewable penetrated interconnected power system

AbstractThe stable and efficient regulation of voltage and frequency is a critical issue associated with the functioning of modern power system network having renewable integration. This manuscript focuses on the concurrent regulation of voltage and frequency in a power network comprising multiple generating sources. Herein, along with conventional thermal and diesel plants, renewable generations from different sources have been considered such as wind and solar photovoltaic (PV) resources. Further, in a fresh attempt, the authors have modeled wind and solar PV generation using two different stochastic modeling methods concerning combined voltage and frequency loops in the regulated power system model. Furthermore, the novel Leader Harris Hawks Optimized Model Predictive Controller (MPC‐LHHO) has been applied to concurrently minimize the voltage and frequency deviations in the given power network. To address the intermittent nature of load and renewable generations, various auxiliary frequency controllers, such as the unified power flow controller (UPFC) and electric vehicle (EV) integration with the grid, have been implemented. The robustness of the proposed control method has been successfully validated through diverse scenarios of random loadings.

Detailed modelling and performance analysis of power flow topology in a hybrid electric vehicle having series-parallel architecture

Despite massive investment and carbon-neutral transition goals set around the world, gasoline-based internal combustion engine vehicles still form an absolute majority in the transportation sector. With the advent of technology, access to electricity, uncertainties in fuel prices and health awareness, people worldwide are moving towards a better, reliable, cost-effective and environmentally friendly mode of transportation, a hybrid electric vehicle. Such a vehicle, with its powerful electric motor and compact gasoline-based engine, offers better efficiency in terms of operating cost and reliability. Considering the advent of hybrid electric vehicles taking pace, studies related to its architecture types, power flow dynamics, control and modelling of its various components will form an essential part of the automobile industry and research. This paper proposes a power flow topology for a hybrid electric vehicle with series-parallel architecture. The developed vehicle model with such an architecture type consists of three main sub-systems: the electrical system, the control system and the mechanical system. The presented power flow topology being modelled and analysed in detail in the Simulink tool is being implemented via a mode logic controller, which forms part of the central control system. The developed hybrid electric vehicle model demonstrates various modes of operation, from starting to accelerating to de-accelerating and then finally coming to a complete rest. Each mode yields and explains the following: the vehicle reference speed; the engine and generator turn functions on/off; the dc bus and battery voltage; the motor, battery, and generator current; the motor, generator, and engine speed; engine torque; engine power; throttle demand; and the vehicle’s actual speed. The results thus obtained show that the waveforms associated with such topology, during its various modes of operation, are pretty stable and acceptable, thereby depicting and validating the operation of the developed hybrid electric vehicle model with proposed power flow topology in a precise and transparent manner.

Experimental and Simulation Studies on Stable Polarity Reversal in Aged HVDC Mass-Impregnated Cables

Mass-impregnated (MI) cables have been used for many years as cables in high-voltage direct current (HVDC) systems. In line commutated converter (LCC) HVDC systems, polarity reversal for power flow control can induce significant electrical stress on MI cables. Furthermore, the mass oil and kraft paper comprising the impregnated insulation have significantly different coefficients of thermal expansion. Load fluctuations in the cable lead to expansion and contraction of the mass, creating pressure within the insulation and causing redistribution of the impregnant. During this process, shrinkage cavities can form within the butt gaps. Since the dielectric strength of the cavities is lower than that of the surrounding impregnation, cavitation phenomena in impregnated paper insulation are considered a factor in degrading insulation performance. Consequently, this study analyzes the electrical conductivity of thermally aged materials and investigates the transient electric field characteristics within the cable. Additionally, it closely analyzes the formation and dissolution of cavities in MI cables during polarity reversal based on a numerical model of pressure behavior in porous media. The conductivity of the impregnated paper indicates that it has excellent resistance to thermal degradation. Simulation results for various load conditions highlight that the interval of load-off time and the magnitude of internal pressure significantly influence the cavitation phenomenon. Lastly, the study proposes stable system operation methods to prevent cavitation in MI cables.

Harmonics reduction and power quality improvement in distributed power flow controller by SVPWM and MGWO technique

Harmonics reduction and power quality improvement in distributed power flow controller by SVPWM and MGWO technique

Weak Grid Integrated Improved Power Quality PV-Battery System With Controlled Power Flow and Grid Assistive Capabilities

Weak Grid Integrated Improved Power Quality PV-Battery System With Controlled Power Flow and Grid Assistive Capabilities

Direct Power Flow Controller With Continuous Full Regulation Range

Direct Power Flow Controller With Continuous Full Regulation Range