Reactive Power Research Articles

Enhanced voltage management method based on hybrid transformer for wind power integration applications

The rapid voltage fluctuations and even exceedances caused by power variability of wind generations significantly impede their application within the power system. This paper presents a method for replacing the electromagnetic transformer at the Point of Common Coupling of wind power delivery systems with a hybrid transformer (HT) to enhance its voltage management and grid integration capabilities. Considering the operation voltage in wind farm and scalability, a cascaded H-bridge based HT model has been established. The operation modes and a set of control strategies groups have been analyzed and proposed. The HTs operate by default in reactive power compensation mode to manage the dual-side voltage coordinately. In case of reactive power contention and circulation, this paper proposes an additional reactive power circulation suppression method. Once it exceeds the reactive voltage regulation limits due to the grid faults or changes of gird operation modes, HT adopts ratio fast regulation mode, maintaining the wind-farm side node voltage and preventing wind turbine tripping. The influence of HT leakage reactance has also been studied here. Finally, the effectiveness of the proposed method is validated in simulation, which provides a new paradigm for the operational application of HTs.

Artificial Intelligence-Based Direct Power Control for Power Quality Improvement in a WT-DFIG System via Neural Networks: Prediction and Classification Techniques

This paper discusses the improvement of power quality injected into the AC grid. This approach is achieved by enhancing the quality of injected power signals and mastering the active and reactive power exchanged between the DFIG based wind turbine (WT-DFIG) and the electrical grid, resulting in an improvement of the overall system performance and efficiency. This study includes all WT-DFIG operating modes, successively and continuously, as well as all local reactive power compensation modes. Therefore, novel control strategies are proposed in this paper for wind energy conversion systems based on artificial intelligence techniques. These techniques include Neural Network Prediction (PNN-DPC) and Classification (CNN-DPC). They aim to eliminate the drawbacks and difficulties associated with conventional Direct Power Control (C-DPC), while retaining its advantages. The paper also provides a thorough explanation of the mathematical models for neural network techniques and WT-DFIG system models. The MATLAB/Simulink environment is used to investigate the performance of the proposed techniques under different conditions and operating modes related to different scenarios. The results reveal a significant reduction in the ripple of the generated active power and the compensated local reactive power, better quality of the generated signal currents and a remarkable reduction in the current total harmonic distortion (THD). Furthermore, compared to C-DPC, PNN-DPC achieves a reduction of 72.07% in active power ripples, 77.07% in reactive power ripples, and 76.79% in current Total Harmonic Distortion (THD). CNN-DPC shows similar improvements with 72.04%, 77.13%, and 76.54% of reductions respectively. In addition, CNN-DPC slightly outperforms PNN-DPC. Nevertheless, both proposed control techniques show significant improvements in all characteristics compared to other methods. Consequently, the proposed control strategies indicate that artificial intelligence has the potential to improve the power quality and performance of wind power conversion system.

Research on a New Topology and Reactive Power Compensation Application of Reinjection Multilevel Voltage Source Converter

Based on the principles of reinjection converter technology and submodule operation, a novel topology for a reinjection multilevel voltage source converter (RMVSC) is proposed. In this topology, submodules are dynamically connected in series as the reinjection circuit. This new topology retains all the functions of the RMVSC while offering flexible control of the reinjection circuit and ease of modularization, making it highly suitable for high-voltage, high-power applications. A circulating drive pulse sequence was developed for the 7-level serial submodule RMVSC, ensuring dynamic stability of the submodule voltage and maintaining low harmonic distortion when interfaced with the grid. Building on this, a double-loop control strategy—comprising an outer power loop and an inner current loop—was proposed for the static synchronous compensator (STATCOM) of RMVSC. A simulation model was constructed in PSCAD/EMTDC, and the simulation results confirm the excellent performance of the proposed topology and the effectiveness of both the modulation strategy and the double-loop control strategy. The RMVSC-STATCOM demonstrates continuous and bidirectional reactive power regulation, with high control accuracy and superior compensation current quality.

A Fully Distributed Robust MPC Approach for Frequency and Voltage Regulation in Smart Grids With Active and Reactive Power Constraints

A Fully Distributed Robust MPC Approach for Frequency and Voltage Regulation in Smart Grids With Active and Reactive Power Constraints

AI-optimization operation of biomass-based distributed generator for efficient radial distribution system

This research aims to optimize the size and location of biomass-based distributed generator (BMDG) units to enhance the voltage profile, reduce electrical losses, maximize cost savings, and decrease emissions from power distribution systems. Biomass-based distributed generator (BMDG) systems offer numerous advantages to enhance the efficiency of power distribution systems. However, achieving these benefits relies on determining the optimal size and position of the BMDGs. To achieve these objectives, the metaheuristic technique called particle swarm optimization (PSO) is employed to find the optimal placement and size of BMDGs. The proposed model was validated on MATLAB's IEEE-33 bus radial distribution system (RDS), confirming the aforementioned benefits. Comparative analysis between the PSO-based technique and other algorithms from previous research revealed better results with the proposed method. The results indicate that optimal placement and sizing of BMDG units have led to a reduction of more than 67.68% in active power losses and 65.90% in reactive power losses compared to the base case. Additionally, the reduction in active power loss was 40.44%, 11.39%, 42.85%, 1.81%, 0.85%, 29.83%, 5.82% and 28.38% more than artificial bee colony, backtracking search optimization algorithm, moth-flame optimization, Coordinate control, artificial Hummingbird algorithm, variable constants PSO (VCPSO), artificial gorilla troops optimizer (AGTO), and a jellyfish search optimizer respectively. Furthermore, the reactive power losses were reduced by 38.33% and 15.68% compared to VCPSO and AGTO respectively. Furthermore, this study revealed a cost reduction of 6.38% when compared to the AGTO and 1.30% when compared to the AHA. Moreover, the voltage profile of the power distribution system was improved by 7.28%. The presented methodology has demonstrated promising results for BMDGs in RDS across various applications.

Influence of wind farm fault current control strategies on distance protection during unsymmetrical faults

Abstract This paper evaluates the performance of distance protection near a wind farm with type IV wind turbines with various basic fault current control strategies implemented in the power converters. The considered fault control strategies include control of purely positive sequence currents or combined positive and negative sequence currents for reactive power support of various magnitudes. A multi-variable study is performed in PSCAD to show performance of a basic algorithm of distance protection at a 420 kV line in a vicinity of the wind farm. The results show that the majority of relay failures occur for phase-phase-ground faults, that reactive current control has less influence in strong grid than in weak grid, and that standard wind turbine fault control procedure of providing balanced current might result in fault currents much smaller than maximum allowed (usually 1.2 pu).

Two-Stage Optimal Scheduling Strategy of Microgrid Distribution Network Considering Multi-Source Agricultural Load Aggregation

With the proposed “double carbon” target for the power system, large-scale distributed energy access poses a major challenge to the way the distribution grid operates. The rural distribution network (DN) will transform into a new local power system primarily driven by distributed renewable energy sources and energy storage, while also being interconnected with the larger power grid. The development of the rural DN will heavily rely on the construction and efficient planning of the microgrid (MG) within the agricultural park. Based on this, this paper proposes a two-stage optimal scheduling model and solution strategy for the microgrid distribution network with multi-source agricultural load aggregation. First, in the first stage, considering the flexible agricultural load and the market time-of-use electricity price, the economic optimization is realized by optimizing the operation of the schedulable resources of the park. The linear model in this stage is solved by the Lingo algorithm with fast solution speed and high accuracy. In the second stage, the power interaction between the MG and the DN in the agricultural park is considered. By optimising the output of the reactive power compensation device, the operating state of the DN is optimised. At this stage, the non-linear and convex optimization problems are solved by the particle swarm optimization algorithm. Finally, the example analysis shows that the proposed method can effectively improve the feasible region of safe operation of the distribution network in rural areas and improve the operating income of a multi-source agricultural load aggregation agricultural park.

Receiving-End Voltage Compensation Method with NPC-Inverter-Based Active Power Line Conditioner in Three-Phase Four-Wire Distribution Feeder

This study proposes a receiving-end voltage compensation method employing a phase-specific reactive power control strategy with a neutral-point-clamped (NPC) inverter in a three-phase four-wire distribution system. The principle of the proposed receiving end voltage compensation method is explained. Further, the proposed control strategy can solve the problems of the three-phase, four-wire distribution system, which are an increase in the neutral-line current and the unbalanced voltage. Computer simulation is performed to confirm the validity of the proposed method. The simulation results indicate the receiving-end voltages can be compensated using the proposed method.

Distribution Grid Hosting Capacity Improvement using Reactive Power Control Optimization Algorithm of Inverter-based Photovoltaic Generation System

This paper uses a reactive power control optimization algorithm to present an inverter-based photovoltaic generation system for increasing the distribution grid host capacity. The main objective of this study is to regulate bus voltages by providing sufficient minimal reactive power consumption, which is obtained by a Particle Swarm Optimization-based optimization algorithm. A modeling study of the system network is developed using DIgSILENT PowerFactory, and the control algorithm is implemented in MATLAB. The proposed approach is efficient for various scenarios of the IEEE 13-bus test system and practical distribution network. The analysis results are compared with outcomes from other control methods, including technical and economic assessments. The performance of the proposed optimization-based power system has shown that the proposed algorithm method yielded significantly superior mitigated voltage rises and increased hosting capacity compared to those achieved by existing control methods of a specific distribution network.

Power Quality Enrichment and Power Management using an Adaptive Control Scheme in Microgrid System

This article proposes an ANFIS-based control scheme for improved power quality and power management that will provide optimal and sustainable energy in a grid-connected renewable energy system. The system consists of a wind energy conversion system (WECS), a photo voltaic system (PVS), and a battery energy storage system (BESS). To increase the PVS's and WECS output powers, a unique control approach is suggested in this paper. The adaptive Neuro-Fuzzy Inference System (ANFIS) controller is incorporated into the proposed controller to generate three-phase reference current signals for harmonic elimination in the system during system dynamic conditions. The proposed control technique can work under voltage quality problems such as voltage sag, voltage swell, neutral currents, and reactive power. Renewable energy sources (PV and Wind) are interfaced to improve the DC-link overall performance by minimizing short-term and long-term voltage problems. The proposed controller regulates the energy flows between the renewable energy sources to the end users with a unity power factor. A supervisory control scheme is implemented for optimal power management in the system. Based on the load requirement, and how the renewable, battery, and grid sources are sharing the power, a detailed analysis is given in the paper. Simulation results from the MATLAB/Simulink platform under several test conditions at the grid side and load side illustrate the efficacy of the proposed control mechanisms in the environment of power optimization and energy management. The comparative analysis is performed to show the efficacy of the proposed system. Finally, the proposed system is validated and the THD content of the grid currents is found good.

Analysis of a Doubly-Fed Induction Motor for Soft Start Operation based on Stator Flux Vector Control

This paper aims at analysis of an operation of a doubly-fed induction motor (DFIM). The paper mainly focuses on the soft start method for the DFIM using the conventional topology that is normally used in the case of a doubly-induction generator (DFIG). Likewise, the details about reactive power control is also discussed. With the proposed method, the DFIM can start from zero to any speed by controlling the machine-side converter (MSC). The computer simulation is performed to a 5 kW wound rotor induction motor using PLECS software. The simulation results validate that the DFIM can operate from the rest to any speed while operating only under the conventional topology.

Levy flight elitism-enhanced salp swarm algorithms for solving the ORPD problem

The optimal reactive power dispatch (ORPD) challenge is crucial for ensuring the efficient and reliable operation of power systems, hinging on the effective coordination of multiple devices.As a result, solving the ORPD problem involves tackling a complex nonlinear optimization challenge that demands advanced computational algorithms to determine the optimal solution. This article introduces an enhanced version of the modified algorithm, called L-E-SSA, which is inspired by the coordinated movement of a swarm led by a single member (salp swarm algorithm SSA), incorporating Levy Flight elitism, to effectively solve the ORPD problem. This study aims to reduce power losses (Ploss) and total voltage deviation (TVD) by optimizing the control variables. Numerical simulations are carried out on IEEE (30-bus) and IEEE (118-bus) power systems. To evaluate the performance and effectiveness of the modified algorithm (L-E-SSA). The results indicate that the L-E-SSA algorithm delivered strong performance and secured a competitive ranking through statistical analysis. Simulations demonstrate that the proposed method has the potential to be a highly effective solution for the ORPD problem.

Analyzing the influence of electric vehicle charging scheduling on distribution transformer lifespan

The ongoing growth in global electricity demand and rapid proliferation of electric vehicles (EVs) are posing challenges to the operation of the low voltage power networks and their components. This study aims to analyze the impacts of peak-load demand on the distribution transformers, considering mild and extreme combinations of electric energy demand and localized charging of plug-in EVs under their different penetration levels, hypothesizing that shifting the demand for charging throughout the day can reduce the aging of distribution transformers. The proposed method employs a fuzzy-logic-based tool, which incorporates the influence of ambient temperature, higher harmonics, reactive power compensation, reverse power flows, and overload. Three different charging/discharging modes have been considered: demand charging, off-peak charging, and synergy of off-peak charging and vehicle-to-house technology. The results indicate that off-peak charging emerges as 2.1 times more effective than demand charging in terms of the transformer's loss of life, particularly for ultimate EV penetration of 100 %. It is demonstrated that the utilization of charging scheduling for EVs should be prioritized to defer costly system upgrades and reinforcements, particularly when EV penetration exceeds 50 %.

Implementasi Metode Artificial Bee Colony Untuk Penempatan Distributed Generator Pada Penyulang Rayon Tanjung

Distributed Generation (DG) is a power plant that is spread over the power distribution network. In principle, electrical power output is generated by power plants located far from the load center and electrical power is transmitted to the load center through transmission and distribution networks. The longer the cable from the power plant or substation, the lower the voltage at the end load. Sub-optimal DG placement and size can result in increased power losses and affect the system voltage profile. In addition, suboptimal generation capacity can lead to voltage instability, reduced system security, and potential impacts on system frequency and emissions. Therefore, this study will use the Artificial Bee Colony (ABC) method to determine the optimal DG capacity and location. In the base case condition, the power losses in the system are 118 KW and 99 Kvar. Power losses after the installation of 1 DG active power loss becomes 37.4 KW and reactive power loss becomes 31.65 Kvar. Placement of 2 DGs reduces active power loss to 17 KW and reactive power loss to 15 Kvar. While the placement of 3 DG reduces active power loss to 33 KW and reactive power loss to 28 KVar.

Optimal Configuration Model for Large Capacity Synchronous Condenser Considering Transient Voltage Stability in Multiple UHV DC Receiving End Grids

In a multi-fed DC environment, the UHV DC recipient grid faces significant challenges related to DC phase shift failure and voltage instability due to the high AC/DC coupling strength and low system inertia level. While the new large-capacity synchronous condensers (SCs) can provide effective transient reactive power support, the associated investment and operation costs are high. Therefore, it is valuable to investigate the optimization of SC configuration at key nodes in the recipient grid in a scientific and rational manner. This study begins by qualitatively and quantitatively analyzing the dynamic characteristics of DC reactive power and induction motors under AC faults. The sub-transient and transient reactive power output model is established to describe the SC output characteristics, elucidating the coupling relationship between the SC’s reactive power output and the DC reactive power demand at different time scales. Subsequently, a critical stabilized voltage index for dynamic loads is defined, and the SC’s reactive power compensation target is quantitatively calculated across different time scales, revealing the impact of transient changes in DC reactive power on the transient voltage stability of the multi-fed DC environment with dynamic load integration. Finally, an optimal configuration model for the large-capacity SC is proposed under the critical stability constraint of dynamic loads to maximize the SC’s reactive power support capability at the lowest economic cost. The proposed model is validated in a multi-fed DC area, demonstrating that the optimal configuration scheme effectively addresses issues related to DC phase shift failures and voltage instability resulting from AC bus voltage drops.

Enhancing hosting capacity for electric vehicles in modern power networks using improved hybrid optimization approaches with environmental sustainability considerations

The increasing adoption of electric vehicles (EVs) presents both opportunities and challenges for power networks. While EVs have the potential to reduce carbon emissions, accommodating their growing power demand requires careful planning to prevent overloading and mitigate environmental impacts. This paper introduces an integrated hosting capacity model to facilitate higher EV penetration while maintaining environmental standards. In addition to EV charging stations, the model incorporates transmission lines, reactive power compensators, energy storage systems, and thyristor-controlled series compensators to ensure a reliable power supply. The model aims to maximize EV charging station deployment, minimize greenhouse gas emissions, and optimize net present value through hosting capacity strategies. Three hosting capacity plans are proposed to analyze the impact of prioritizing one of these objectives over the others in network configurations. Accurate EV demand forecasting is critical for this model, and a swarm intelligence forecasting algorithm is proposed to explore various forecasting approaches. The model is complex and involves nonlinear multi-objective optimization. To solve it, a new hybrid optimization algorithm is introduced, combining the features of the Marine Predators Algorithm and the Honey Badger Algorithm. Three hybridization schemes—Series Hybrid Scheme, Population Division Scheme, and Switching Strategy Scheme—are developed to address the optimization challenges effectively. The results show that the first and second hybridization schemes are the most effective for solving the EV load forecasting models, with a robustness of at least 90%. In contrast, the robustness of the third scheme reaches only 30% in some models. Simulation studies on the IEEE 9-bus network and the IEEE 30-bus system validate the model’s effectiveness in integrating EVs while achieving environmental sustainability objectives. The findings show the superiority of the proposed hybrid schemes in solving the hosting capacity model in terms of finding optimal solutions. However, the third scheme required less computing time than the others, with its convergence time being at least 33.3% shorter.

Point of Common Connection Voltage Modulated Direct Power Control with Disturbance Observer to Increase in Renewable Energy Acceptance in Power System

In this paper, we present a disturbance observer-based point of common connection voltage-modulated direct power control (PCCVM-DPC) system, which increases the robustness of the PCCVM-DPC system. First, the mathematical analysis of the disturbances for the step-up transformer’s nonlinearity, the grid voltage harmonics, and the parameter uncertainties is presented. By analyzing the disturbance terms of the PCCVM-DPC system, we present the disturbance observer (DOB) for the PCCVM-DPC system. To assess the efficacy of our approach, we perform comparative studies of the PCCVM-DPC without DOB and PCCVM-DPC with DOB by constructing the simulation environment based on the commercial step-up transformer and ESS inverter datasheet. We have validated that the active and reactive power control performance of the PCCVM-DPC with DOB outperforms the PCCVM-DPC without DOB from the observation that the current total harmonic distortion reduced by more than 40% compared to the PCCVM-DPC without the DOB.

A new integrated modelling and control of ternary pumped storage hydro power generation for small signal stability studies

Pumped storage hydro power generation (PSHPG), a reliable renewable energy source with an energy storage feature, can impart efficient damping torque to power system oscillations to improve small signal stability with appropriate modelling and additional compensation through the governor. But ternary PSHPG (T-PSHPG) has the unique feature of hydraulic short circuit (HSC) mode, where both pumping and generating modes operate simultaneously. This study presents a novel fourth-order modified Heffron Phillips (MHP) model of T-PSHPG in coordination with a multi-band Power system stabilizer (MB-PSS) employing 2-way penstock, where primary penstock circulates water from the upper reservoir to the lower reservoir through the turbine and secondary penstock divides primary penstock, thereby creating short-circuit path through the pump. Also, this model includes additional reactive power droop control to maintain the voltage profile. A new state space matrix has been developed for coordinating T-PSHPG in HSC mode with MB-PSS. The control parameters of the proposed coordinated model are set by a new multi-objective differential evolution-improved particle swam optimization (DE-IPSO) algorithm. With variable load, random solar and wind source penetrations, it has been found that the proposed model can provide adequate damping actions. The sensitivity of the proposed model has been observed by varying critical model parameters by ±50 %. For all conditions, the settling time of speed variation is within 2.672 s to 5.951 s and the minimum damping ratio lies within 0.105 to 0.455. The minimum damping ratio is 0.32 and the settling time is found to be 3.1 s for system response subject to sudden solar power variation, which has been observed by shifting system eigenvalues toward the left half of the complex plane. Time and frequency domain parameters with sensitivity analysis predict system oscillations being damped effectively with consistency for the proposed modelling and control strategy. The results are verified in real-time with OPAL-RT real-time digital simulator. It has been justified by the present study that appropriate modelling of T-PSHPG along with coordinated control action provided by MB-PSS can handle critical power system oscillations efficiently and effective damping torque can be imparted in HSC mode.

An optimal parameter design method for cascaded H‐bridge multi‐level converter in wind farm

AbstractThe cascaded H‐bridge multi‐level converter is the main topology of high‐voltage and high‐capacity converter in renewable energy power generation, energy storage system and reactive power compensation equipment. The parameter design of cascaded H‐bridge multi‐level converters directly determines the material cost and performance. Taking the output current distortion rate and the ripple voltage of the capacitor of the cascaded H‐bridge multi‐level converter as the constraint conditions, this paper proposes an overall parameter optimal design method of the cascaded H‐bridge multi‐level converter based on the optimization of the total material cost. Finally, the effectiveness of the proposed parameter design method is verified by the simulation result.

Modular high frequency resonant inverters in constant power mode

ABSTRACT In this paper, a modular resonant inverter is proposed for high frequency industrial heating applications. To maintain a uniform heating profile, the inverter is operated in constant power mode. A hybrid voltage and frequency control is proposed. Voltage control is used for active power tracking while frequency control is used to minimise circulating current due to reactive power and to achieve soft switching for the inverter switches. Analytical and test results are shown to verify the proposed approach.