Active Reactive Power Research Articles

A multi‐variables loss of excitation protection scheme to improve the factors of accuracy and speed of detection than the conventional impedance relay

AbstractThe most common disadvantages of loss of excitation (LOE) impedance relay are its improper operation in the conditions of power system disturbances (PSD) and its long operation time. In this regard, to solve the mentioned problems and as a result improve the accuracy and speed of detecting the LOE events, four key variables including active power (Psg), reactive power (Qsg), load angle (δsg), and terminal voltage (Vsg) are selected, on the basis of an in‐depth theoretical‐ and simulation studies. These variables have been implemented in a precise combinational logic. In the developed LOE detection logic of this paper, the dependent parameters of Vsg and Qsg as well as Psg and δsg parameters are examined simultaneously in an AND logic cluster. If both the defined combinations detect the occurrence of LOE, the generator trip command is issued. Otherwise, the normal operation of the under‐study machine will continue. The results of the performed simulations in MATLAB/Simulink environment (2017b) during the detailed scenarios of LOE and PSD events on the IEEE 39‐bus standard system confirm the efficiency of the outlined LOE protection model. Meanwhile, its superiority from the viewpoints of accuracy, swiftness, and simplicity and cost of implementation are comprehensively compared with the other schemes.

A Cross-Power Spectral Density Method for Locating Oscillation Sources Using Synchrophasor Measurements

This paper proposes a new measurement-based approach for locating the sources of forced or poorly damped oscillations in a power system. The approach is based on the concept of cross-correlation in the frequency domain known as cross-power spectral density (CPSD). CPSDs of synchronized voltage magnitude and voltage angle versus active power and reactive power signals obtained by phasor measurement units (PMUs) are computed using fast Fourier transform. The largest positive imaginary part of a CPSD is used as an indicator of the oscillation source. The type of an oscillation source is determined by comparing the spectral densities of active and reactive power. In addition, preprocessing of the signals is performed via variational mode decomposition for extracting the dynamic component of the signals. The proposed approach was able to successfully identify all submitted test cases in the IEEE-NASPI Oscillation Source Location Contest. Several case studies presented in this paper highlight the advantages of the proposed approach compared to the state-of-the-art dissipating energy flow method.

Distributed Photovoltaic Installation Admittance Optimization: An End-to-End Approach

Distributed photovoltaic installation admittance capacity (PVAC) refers to the maximum capacity of photovoltaics that can be accommodated by the distribution system. The economic and reliable PVAC evaluation is critical for distributed photovoltaic capacity planning and configuration. However, lacking sufficient measurement devices and unachievable to full-scale perception of the practical distribution system impose challenges for PVAC assessment. This paper proposes an end-to-end approach to evaluate PVAC using the data from gird terminals and smart meters, where network topology and line parameters will be unnecessary. Specifically, an end-to-end power flow variables mapping model is proposed, which is essentially using the adaptive online deep learning algorithm to model and train the functional relationship of terminal active power, reactive power and voltage. Based on the above mapping relationship analysis, an end-user data driven photovoltaic installation admittance optimization model is established, which models the PVAC evaluation issue as a convex optimization model with differentiable objective function. Then a projected gradient descent algorithm based on adversarial attacks mechanism is proposed to solve the optimization model to obtain the maximum PVAC. Finally, the effectiveness of the proposed method is verified on IEEE 33-node, IEEE 123-node and actual distribution systems.

A Passivity-based direct power control scheme of a back to back NPC converter

In this paper, a direct power control (DPC) is proposed in order to improve the power dispatch in electrical power grids, as well as in microgrids. The objective of defining the active power and reactive power as state variables is to get a representation of the first level in a hierarchical control. The DPC model is studied under passivity rules, and an implementation of passivity-based control is proposed. Simulations are carried out to show the effectiveness of the proposed research.

Distributed feedback optimisation based optimal power flow control in fully inverter based islanded AC microgrids

AbstractA novel distributed feedback optimisation (FO) based control method is proposed to control grid‐forming inverters (GFMIs) in fully inverter‐based islanded AC microgrids (MGs). The proposed controller has two control layers. The upper layer uses FO to calculate the frequency and voltage setpoints of GFMIs, whereas the lower layer makes GFMIs track these setpoints. The proposed control method takes advantage of the flexibility of voltage control to regulate the system frequency, maintain both active power and reactive power sharing accuracies, keep bus voltage within allowable range and meanwhile preserves the optimality of the closed‐loop system in term of optimal power flow. The gradient descent method is used to solve the proposed FO problem based on the real‐time measurements in the MGs, which is implemented in a distributed way, and thus eliminates the need for a central controller. Case studies show the effectiveness of the proposed method.The cover image is based on the Research Article Distributed feedback optimisation based optimal power flow control in fully inverter based islanded AC microgrids by Y. Cheng et al., https://doi.org/10.1049/stg2.12132.

Voltage Control Ancillary Service Through Grid-Connected Microgrid, Its Pricing by Optimized Active Power and Reactive Power Management Using IEHO-TOPSIS Approach

Voltage Control Ancillary Service Through Grid-Connected Microgrid, Its Pricing by Optimized Active Power and Reactive Power Management Using IEHO-TOPSIS Approach

Solving optimal power flow problems via a constrained many-objective co-evolutionary algorithm

The optimal power flow problem in power systems is characterized by a number of complex objectives and constraints, which aim to optimize the total fuel cost, emissions, active power loss, voltage magnitude deviation, and other metrics simultaneously. These conflicting objectives and strict constraints challenge existing optimizers in balancing between active power and reactive power, along with good trade-offs among many metrics. To address these difficulties, this paper develops a co-evolutionary algorithm to solve the constrained many-objective optimization problem of optimal power flow, which evolves three populations with different selection strategies. These populations are evolved towards different parts of the huge objective space divided by large infeasible regions, and the cooperation between them renders assistance to the search for feasible and Pareto-optimal solutions. According to the experimental results on benchmark problems and the IEEE 30-bus, IEEE 57-bus, and IEEE 118-bus systems, the proposed algorithm is superior over peer algorithms in solving constrained many-objective optimization problems, especially the optimal power flow problems.

Energy Storage‐Reactive Power Optimal Configuration for High Proportion New Energy Distribution Network Considering Voltage Quality and Flexibility

The increasing penetration rate of distributed energy brings more complex problems of voltage quality, safety and stability to the distribution network. A single optimal configuration of reactive power or energy storage is difficult to meet the increasingly diversified needs of modern power grids. This paper proposes a configuration strategy combining energy storage and reactive power to meet the needs of new energy distribution networks in terms of active power regulation and reactive power compensation, and to achieve tradeoff optimization in flexibility, voltage quality and economy, so as to adapt to the influence of new energy with different permeability. Firstly, the safety and stability evaluation system of distribution network is established with the target of flexibility demand and reactive power demand. Secondly, considering the coupling of planning layer and operation layer, a two‐layer model of energy‐reactive power optimization is established. After that, the gray wolf algorithm is used to solve the model, which enhances the global space exploration ability and reduces the possibility of falling into the local optimal. Finally, the improved IEEE33 node power distribution system is used for simulation test to verify the rationality and effectiveness of this scheme. The simulation results show that the scheme proposed in this paper can effectively improve the economy, security and stability of the distribution network, and can obtain an optimal configuration scheme with multi‐objective considerations under different new energy penetration rates. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

Multi-layer double deep Q network for active distribution network equivalent modeling with internal identification for EV loads

With more and more distributed renewable energy generations and diversified electric vehicle (EV) loads connected to active distribution networks (ADNs), the power interaction between the ADNs and backbone network becomes more complicated. Furthermore, it is difficult to exactly simulate the power flows in the ADN due to large amounts of branches without power measurement units. Consequently, this paper proposes an equivalent modeling for the ADN, consisting of a motor and a synthetic constant impedance (Z), constant current (I), constant power (P) load (ZIP) with an internal identification for EV loads. The equivalent modeling utilizes a multi-layer double deep Q network (MLDDQN) to track the dynamics of the original ADN using few power measurements in the boundary with high precision. In the MLDDQN, the types of the ZIP load and motor are selected from the load pool to obtain the dynamic equivalent modeling of the ADN in the first layer, and the weight of the model is determined to obtain the active power (P) and reactive power (Q) (PQ component) of motor and ZIP load in the second layer through the powerful feature extraction ability of deep learning and the optimization decision-making ability of reinforcement learning. Another layer is adopted to optimize the parameters of the equivalent EV to independently trace the characteristics of the original EV loads. The simulation results show that the proposed MLDDQN improves the sample selection and behavior value function evaluation in deep reinforcement learning through prior experience playback, huber loss function strategy and dueling network. Additionally, the precision and applicability of the equivalent modeling is tested with comparisons with traditional DDQN and DQN.

Hierarchical control of island microgrid based on consensus algorithm

When the load inside the microgrid changes, droop control maintains a stable power supply cycle of the microgrid by controlling the voltage and frequency at the parallel network of the distributed generation. Since the traditional microgrid droop control usually uses a fixed droop coefficient to adjust the output active power and reactive power, the frequency and voltage of the inverter parallel network will deviate from the system frequency and voltage rating to varying degrees, so a new layer of control link is needed to restore the target value. Moreover, most of the hierarchical control methods adopt centralized control methods, which have limitations such as high dependence on communication. This paper combines a hierarchical control framework and a consistency algorithm to propose a distributed sag control strategy for islanded microgrids based on a multi-agent system. It achieves equal-to-ratio output when distributed generation responds to power changes while maintaining the stability of the microgrid’s main performance indicators. Since the distributed system with a consistency algorithm does not require a centralized control centre, it increases the system’s robustness and reduces the dependence of the system on the communication network. Finally, an islanded AC microgrid model is built by MATLAB/Simulink, and the effectiveness of the proposed islanded microgrid hierarchical control strategy is verified by simulation.

Low Frequency Oscillation Suppression Strategy in New Power System Based on Virtual Synchronous Generator

With the blend of massive new energy into power network systems, the inertia and damping features of new power systems are reduced, which is prone to cause low-frequency oscillations (LFO) in the power systems. Virtual synchronous generators (VSG) have received widespread attention by simulating the external characteristics of synchronous generators (SG) to enhance the inertia of new power systems and help suppress low-frequency oscillations. By analyzing the mathematical model of VSG, the control links of each part of VSG are established, the traditional reactive power-voltage (Q-V) of VSG is improved, and the formulas of active voltage control and reactive power control droop coefficient are deduced.Finally, a simulation model of VSG is created by MATLAB/Simulink platform, and new methods for suppressing LFO in power systems are compared and analyzed. The correctness of the formula and the improvement effect of reactive power and voltage control are verified.

Practical Implementation of High-Efficiency Multiple-Input Converter Embedding Renewables and Energy Storage for DC-Microgrid Applications

The use of high frequency power converters to enhance power density and energy efficiency has become widely used in grid-connected hybrid DC microgrids. This paper presents a new modularized high frequency DC-link integration methodology that connects multisource renewable energy sources involving battery energy storage system (BESS) to the AC-grid. A grid-tie-inverter with a line inductor is introduced to control the active-reactive power flow. To minimize the converter physical size with improved system efficiency, a high frequency-based front-end multisource bridgeless boost (MBB) architecture is proposed here. A direct-mount decoupling snubber capacitor and a soft switching are used to reduce the switching losses resulting from the high-frequency operation. The performance of the proposed system is investigated. A direct digital approach is used to design the system controller in MATLAB/Simulink R2022a environment. To validate the system performance, a 10 kW multi-source grid-connected experimental setup with dSPACE-1104 controller is constructed, tested, and compared with other conventional topologies. The test results verify the proposed topology effectiveness for hybrid grid-connected renewable energy resources integration.

Cooperative Voltage and Frequency Regulation with Wind Farm: A Model-Based Offline Optimal Control Approach

Converter blocking is a serious malfunction encountered in high voltage direct current (HVDC) transmission systems. During sending-end converter blocking, the resultant active power and reactive power surplus in the sending-end power system lead to a severe increase in bus voltage and grid frequency. Consequently, this poses a substantial threat to the stability of the power system. Traditional control techniques generally control the frequency and voltage separately, which makes it challenging to regulate them jointly. This research paper introduces a collaborative approach for optimal control of voltage and frequency to address this issue. State space models for converter bus voltage and grid frequency prediction are developed using the bus voltage sensitivity matrices and system swing equation. The regulation of the converter bus voltage and grid frequency are intrinsically integrated using the explicit model predictive control (EMPC). When blocking occurs and results in an increase in the converter bus voltage and grid frequency, the EMPC controller regulates the output of active power and reactive power from the wind farm to realize the cooperative regulation of the converter bus voltage and grid frequency. The applicability and effectiveness of this strategy have been confirmed through simulation studies.

Unified variable regularization factor based static compensator for power quality enhancement in distribution grid

A unified variable regularization factor based strategy for harmonic filtering at the supply side of the distribution system is presented in this paper. For this purpose, a three-phase distribution grid along with a distribution static compensator and a rectifier based nonlinear load is considered. A combined regularization affine projection sign algorithm-based control technique is used to calculate the weight values that denote the active power and reactive power segments of the load current. The proposed algorithm contains a variable mixing factor of two adaptive filters with different regularization parameters. The variable mixing factor enhances the tracking performance of the algorithm and hence it offers quick convergence and less steady-state error when compared with other affine projection-based filtering schemes. The control algorithm is evaluated under varying load patterns to derive its robustness and stability. Empirical assessment is carried out through real time simulation analysis aided by dSPACE-1202 controller. The performance of the applied control technique is found good-enough in mitigating the supply side harmonics and the total harmonic distortion levels rendered by the experimentation are in-line with the IEEE-519 standard.

Reactive Power compensation Optimization of Distribution Network with Distributed Power Supply

In recent years, distributed generation has been fully developed, and its permeability is rising, which also brings great challenges to the reactive power regulation of the power distribution network. By analyzing the output characteristics of active power and reactive power of distributed power supply, in this article, a multi-objective optimization mathematical model of reactive power compensation is established, which takes the economy and security of the power distribution network into consideration. The results indicate that the reactive power compensation optimization model and the solution algorithm in this paper have good effectiveness and superiority. This thesis will provide the theoretical foundation and technology support for the design and realization of the DG reactive power compensation scheme.

EV grid-connected control and economic benefit analysis based on V2G technology

With the large-scale use of EV around the world, it has become a popular research direction to integrate EV into the power grid to achieve the purpose of peaking and valley filling for the power grid. With V2G technology as the core, this paper firstly analyzes the V2G grid-connected control technology, namely active power and reactive power control and clustering control at the theoretical level. From the perspective of cooperative game, it elaborates the commercial operation mode of V2G after grid-connected. Finally it puts forward relevant assumptions on the future development trend of V2G based on the current development status of V2G technology.

Fault Ride Through approach for Grid-Connected Photovoltaic System

This paper presents a fault ride-through approach for grid-connected photovoltaic (PV) systems, aimed at improving the system's response during voltage sags and limiting the maximum inverter current during symmetrical faults. A constant active current reactive power injection approach was developed for low-voltage ride-through (LVRT) operation of grid-connected solar PV inverters in low voltage grids. The method manages the active and reactive power references and satisfies grid code requirements while also addressing tripping problems caused by overcurrent. The approach improves the speed response of the power converters during voltage sags, resulting in better dynamic grid support. The authors evaluated the approach using a 2-kW single-phase grid-connected PV system and demonstrated its ability to inject the required reactive power during a fault to improve the voltage profile and achieve dynamic grid support requirements. The accuracy of the proposed methodology is identified to be 98.3%, and the detection time is reduced by a reasonable margin in accordance with the grid standards. Overall, the fault ride-through approach can enhance the performance and reliability of grid-connected PV systems, particularly in low voltage grids.

VSG Control for Cascaded Three-Phase Bridge Based Battery Inverter

With the increasing number of new energy sources connected to the grid, the unbalanced output of three-phase grid-connected inverters and the lack of no inertia and damping characteristics in the traditional microgrid control system will seriously affect the stability of voltage, frequency, and power angle for microgrids. This paper proposes a novel cascaded three-phase bridge inverter topology for the battery system used for the electric vehicle. Compared with traditional cascaded H-bridge inverters, the proposed multilevel inverter can achieve self-adaptive balance for three phases. The mathematical model of a cascaded three-phase bridge inverter is established in this paper. Based on the voltage and current equations of a multilevel inverter, a new modulation strategy named carrier phase-shifted-distributed pulse width modulation (CPSD-PWM) was developed, which is more suitable for cascaded three-phase bridge inverters. The harmonic analytic equations of carrier phase-shifted pulse width modulation (CPS-PWM) and CPSD-PWM are constructed by the double Fourier analysis method. Compared with the traditional PWM modulation strategy, the CPSD-PWM can reduce the output harmonics and improve the balance of the three-phase output, which can realize the three-phase adaptive balance in the cascaded three-phase bridge inverter. This paper develops a cascaded three-phase bridge multilevel power converter system based on the virtual synchronous generator (VSG) control strategy. The voltage and frequency of inverter output can be accurately controlled in both island mode and grid-connected mode through active power-frequency regulation and reactive power–voltage regulation, and the stability of primary frequency regulation for the multilevel microgrid inverter can be improved by collaborative optimization of virtual inertia and virtual damping. The CPSD-PWM modulation strategy and VSG control strategy are verified by the simulation results and experimental data for the cascaded three-phase bridge inverter.

IGBT reliability analysis of photovoltaic inverter with reactive power output capability

When the PV power supply participates in reactive power regulation of distribution network, its output reactive power will affect the reliability of IGBT in the PV inverter. Aiming at this problem, this paper first qualitatively analyzed the influence of photovoltaic power supply participating in reactive power regulation of distribution network on the reliability of photovoltaic power supply. Then, a quantitative evaluation method of IGBT reliability based on data-driven was proposed. This method uses LightGBM machine learning model to replace the traditional thermoelectric coupling model, which effectively improves the calculation efficiency of IGBT junction temperature and reduces the dependence of IGBT reliability evaluation results on IGBT model parameters. Through this method, the reliability of core power electronic devices in photovoltaic inverters is quantitatively evaluated according to active power, reactive power, solar irradiance and ambient temperature. Finally, based on the IEEE 33 node distribution system, the reliability of IGBT in PV inverters participating in reactive power regulation of the distribution network was evaluated.

Comparison amongst Lagrange, Firefly, and ABC Algorithms for Low-Noise Economic Dispatch and Reactive Power Compensation in Islanded Microgrids

For the microgrids to operate securely, distributed generators must be able to interact with one another without experiencing any communication delays or noise. To develop a more effective economic dispatch strategy, this research focuses on noise’s effect on the performance of an islanded microgrid. Three different strategies, Lagrange, firefly, and artificial bee colony algorithms, are compared for optimal solutions of economic dispatch. Their performance is compared based on stability during noise interference and faster response time with and without the virtual synchronous generator-STATCOM strategy. The virtual synchronous generator is used as a voltage source to regulate active power and reactive power with the grid. A STATCOM controller is introduced in the system for reactive power compensation. Reactive power compensation is the process of controlling reactive power to enhance the efficiency of alternating current power systems. By boosting the active power, reactive power compensation in the transmission system will increase the stability of microgrids. The voltage, output power, power factor, and phase angle of the microgrid benefit from the stability provided by the controller. As a result, the performance and resilience of the microgrid is improved.