Improved Voltage Regulation Research Articles

Energy management in smart distribution networks: Synergizing network reconfiguration, energy storage, and electric vehicles with disjunctive convex hull relaxation

Efficient energy management is critical for modern distribution networks integrating renewable energy, storage systems, and electric vehicles. This paper introduces a novel approach combining network reconfiguration with disjunctive convex hull relaxation to optimize power flow, minimize energy losses, and enhance grid stability. Case studies on 33-node and 84-node networks showcase the model’s effectiveness, reducing energy losses to 0.939 MWh and 7.214 MWh, respectively, outperforming Big-M and McCormick methods. Additionally, the approach achieved a 78 % efficiency improvement, enhanced emissions control, and improved voltage regulation, demonstrating superior renewable energy integration. These results highlight the model's potential to provide a more efficient and sustainable energy management solution, addressing the challenges of modern power grids.

FACTS: Present and Future

Flexible AC Transmission Systems (FACTS) are pivotal in modernizing power systems, enhancing their stability, controllability, and efficiency. Currently, FACTS devices such as Static VAR Compensators (SVCs), Static Synchronous Compensators (STATCOMs), and Unified Power Flow Controllers (UPFCs) are employed to manage power flow, mitigate system instabilities, and improve voltage regulation across transmission networks. These technologies address present challenges, including the integration of renewable energy sources, reduction of transmission losses, and enhancement of system reliability in the face of fluctuating power demands. However, the growing complexity of power grids, driven by the increasing penetration of intermittent renewable energy, electric vehicles, and distributed generation, necessitates advanced and scalable solutions. The future of FACTS lies in the development of more sophisticated, adaptive, and intelligent devices that leverage real-time data analytics, artificial intelligence, and machine learning to optimize power flow dynamically. Future advancements are expected to focus on enhancing the interoperability of FACTS with smart grid technologies, improving the resilience of power systems against cyber-physical threats, and facilitating the transition towards more decentralized and sustainable energy systems. Moreover, the integration of energy storage with FACTS devices could revolutionize their functionality, offering not only reactive power compensation but also energy balancing capabilities. This paper explores the current applications of FACTS and envisions their future role in addressing the evolving challenges of global power systems, emphasizing the importance of innovation and strategic investment in the ongoing transformation of electrical networks.

Sliding mode control based dynamic voltage restorer for voltage sag compensation

The reliability and efficiency of electrical power systems are critical for modern industries, which increasingly rely on electric machines and devices. However, power electronic converters add non-linear demands to the electric power distribution systems (EPDS), that can cause power quality (PQ) problems, which could harm electric devices. As a result, EPDS are pointed for the most effective and economical techniques to enhance PQ. Therefore, Dynamic Voltage Restorer (DVR) is employed to maintain voltage stability in modern EPDS. This study focuses on the application of Sliding Mode Control (SMC) in DVRs to protect against voltage dips, enhancing power system sustainability. It details the construction, operation, and control methods of DVRs, comparing the conventional PI-controller with SMC. The arctic puffin optimizer is utilized to get the optimum gains of the PI regulator, and at the same time, it is used to specify the optimal sliding surface required for SMC. A distribution system contains DVR is suggested and implemented utilizing Simulink/MATLAB. The simulation results of the DVR employing SMC and the conventional PI-controller demonstrate a marked improvement in voltage regulation and power quality. Specifically, the SMC-based DVR exhibited a reduction in voltage sag duration and magnitude by approximately 30 % compared to the PI-controller. Additionally, the total harmonic distortion (THD) in the load voltage was reduced by 25 %, indicating a significant enhancement in power quality. These improvements of the enhanced performance of the SMC-based DVR supports the seamless integration of renewable energy sources, which often introduce variability into the power grid.

Improve conservation voltage regulation effects by integrating more distributed renewable generations

AbstractDue to intermittent renewable energy and fluctuating load demand, distribution networks with renewable distributed generation (DG) installations are more likely to suffer voltage issues and significant power losses. The performance of conservation voltage regulation (CVR) schemes may be adversely affected by the undesirable voltage profile at specific nodes. This paper aims to reduce power losses in CVR‐implemented networks by optimally planning new renewable DGs without changing the existing ones. A scenario‐based optimal renewable DG planning model is proposed with a novel scenario formation method. The uncertainties of load demand and renewables are captured jointly and formed into a finite number of scenarios based on a multivariate Gaussian mixture model (MultiGMM). The locations and capacities of different types of new renewable DGs are optimally planned for CVR performance improvements on power loss saving by aggregating the operation status and probabilities of the scenarios using mixed‐integer non‐linear programming (MINLP). A time‐series simulation is formulated for accuracy verification. The results of case studies show that the proposed model can significantly reduce power losses, active load demand, and reactive load demand. The accuracy of the planning results can be guaranteed with fewer scenarios compared to a widely used classical scenario‐based planning method.

Review of Compensation Topologies Power Converters Coil Structure and Architectures for Dynamic Wireless Charging System for Electric Vehicle

The increasing demand for wireless power transfer (WPT) systems for electric vehicles (EVs) has necessitated advancements in charging solutions, with a particular focus on speed and efficiency. However, power transfer efficiency is the major concern in static and dynamic wireless charging (DWC) design. Design consideration and improvements in all functional units are necessary for an increase in overall efficiency of the system. Recently, different research works have been presented regarding DWC at the power converter, coil structure and compensators. This paper provides a comprehensive review of power converters incorporating high-order compensation topologies, demonstrating their benefits in enhancing the DWC of EVs. The review also delves into the coupling coil structure and magnetic material architecture, pivotal in enhancing power transfer efficiency and capability. Moreover, the high-order compensation topologies used to effectively mitigate low-frequency ripple, improve voltage regulation, and facilitate a more compact and portable design are discussed. Furthermore, optimal coupling and different techniques to achieve maximum power transfer efficiency are discussed to boost magnetic interactions, thereby reducing power loss. Finally, this paper highlights the essential role of these components in developing efficient and reliable DWC systems for EVs, emphasizing their contribution to achieving high-power transfer efficiency and stability.

A Deep Reinforcement Learning Approach to DC-DC Power Electronic Converter Control with Practical Considerations

In recent years, there has been a growing interest in using model-free deep reinforcement learning (DRL)-based controllers as an alternative approach to improve the dynamic behavior, efficiency, and other aspects of DC–DC power electronic converters, which are traditionally controlled based on small signal models. These conventional controllers often fail to self-adapt to various uncertainties and disturbances. This paper presents a design methodology using proximal policy optimization (PPO), a widely recognized and efficient DRL algorithm, to make near-optimal decisions for real buck converters operating in both continuous conduction mode (CCM) and discontinuous conduction mode (DCM) while handling resistive and inductive loads. Challenges associated with delays in real-time systems are identified. Key innovations include a chattering-reduction reward function, engineering of input features, and optimization of neural network architecture, which improve voltage regulation, ensure smoother operation, and optimize the computational cost of the neural network. The experimental and simulation results demonstrate the robustness and efficiency of the controller in real scenarios. The findings are believed to make significant contributions to the application of DRL controllers in real-time scenarios, providing guidelines and a starting point for designing controllers using the same method in this or other power electronic converter topologies.

Fuzzy Logic Controller-Based STATCOM for Reactive Power Compensation in a Grid-Connected Wind Power Plant

Wind energy is one of the most prevalent renewable sources nowadays, which has been projected to play an immense role in realizing the clean energy transition. This paper dives into one of the critical challenges in the grid integration of wind power plants, which is reactive power compensation. The static synchronous compensator (STATCOM) is commonly used to inject/absorb reactive power in wind power plants where the device is controlled with the traditional proportional-integral (PI) controller. This article investigates the effectiveness of the fuzzy logic controller (FLC) in managing the STATCOM to compensate and regulate the reactive power in a 9 MW grid-connected wind power plant. Due to its faster and malleable response, the FLC allows for greater flexibility in controlling the STATCOM. According to the findings, the voltage profile at the point of common coupling (PCC) is improved considerably in the case of the FLC compared to the PI controller, demonstrating the efficacy of the employed strategy. MATLAB-Simulink has been used to model and analyze the proposed system. We achieved a 6 percent improvement in voltage regulation when FLC was utilized instead of PI controllers. DUJASE Vol. 8 (1) 62-70, 2023 (January)

Deep deterministic policy gradient for adaptive power system stabilization and voltage regulation

This paper focuses on the challenges posed by the time-variable and nonlinear nature of energy systems. In this systems set points fluctuate due to load variations, generator losses, and disturbances such as short circuit faults. Maintaining power system stability and effectively damping low-frequency oscillations are crucial objectives. To enhance damping and dynamic stability in modern systems power system stabilizers (PSSs) are typically employed. These facilities generate auxiliary control signals for the generator excitation system, diminishing oscillations. In this study, by involving a deep deterministic policy gradient (DDPG) based on a synergetic control approach to the excitation system of synchronous generators, a novel approach to achieving fast and adaptive stability improvement and voltage regulation is suggested. The presented technique incorporates an intelligent synergetic PSS that effectively stabilizes the voltage response of a single machine connected to an infinite bus power system. To leverage its adaptive capability in controller parameter adjustments, an auxiliary deep DDPG algorithm with an Actor-Critic architecture is designed. The suggested procedure offers a promising avenue for effectively handling electromechanical oscillations and achieving improved voltage regulation and transient stability in power systems.

Optimizing smart microgrid performance: Integrating solar generation and static VAR compensator for EV charging impact, emphasizing SCOPE index

The rapid global increase in electric vehicle (EV) usage, driven by its low CO2 emissions, uncomplicated maintenance, and minimal operating costs, has prompted extensive research in the field of electric vehicle charging station (EVCS). The integration of EVCS into the current distribution grid poses challenges due to potential power losses and voltage variations beyond acceptable limits. This complexity is heightened by the growing penetration of randomly dispersed solar-based distributed generation (SDG) and battery energy storage system (BESS). To address these challenges, distribution static VAR compensator (DSVC) systems have been introduced, offering benefits such as enhanced power transfer capacity, improved voltage regulation, and increased system security without requiring extensive infrastructure upgrades. This study offers SCOPE, a novel multi-objective framework that unifies the optimization goals of minimizing real power loss, lowering bus voltage variation, maximizing system voltage stability, minimizing system operating costs, and mitigating CO2 emissions. The EVCS problem is optimized within this multi-objective framework utilizing an improved bald eagle search algorithm (IBESA). The proposed model accounts for vehicle to grid (V2G) capabilities and the actual driving patterns of users over a 24-h horizon. The formulation of a smart microgrid (SMG) structure is based on modifying the standard IEEE 33-bus test radial distribution network (RDN), comprising three interconnected SMGs serving residential, commercial, and industrial users. The optimization approach based on IBESA is utilized to optimize both the siting and capacity of EVCS as well as renewable energy sources (RESs). The findings show that SDG and DSVC are effective at lowering the SCOPE index, highlighting the advantages of the suggested approach.

Multi-objective optimization based demand response program with network aware peer-to-peer energy sharing

Demand-side energy management programs, such as Demand Response (DR) and Peer-to-Peer (P2P) energy sharing, have recently begun to be implemented to optimize the integration of distributed clean energy resources and to leverage generation and demand-side flexibility in the distribution system. In general, if not optimally planned, P2P energy sharing may have a negative impact on power distribution utilities’ primary objectives, such as minimizing energy losses, flattening the load profile, and improving voltage regulation. The DR program is considered as one of the potential mechanisms to alleviate the possible adverse impact of P2P energy sharing while maintaining the interest of peers participating in decentralized energy sharing. The analysis of the impact of P2P energy sharing with varying peers’ physical locations involved utilizing the Voltage Sensitivity Factor (VSF). The influence on the distribution network is contingent upon the difference in VSF values among the individual peers engaged in energy sharing. This study introduced the k-Means algorithm for VSF-based peer clustering, thereby generating the merit order and realizing the network-aware P2P energy transactions for the selected scenarios. A multi-objective optimization model-based real-time pricing-based DR scheme has been formulated to address the adverse impact of P2P energy sharing. Furthermore, this study quantifies the impact of DR potentials, which vary from 5% to 45% in increments of 10%, on the Peak-to-Average Ratio (PAR), overall energy loss, and total energy cost reduction. The modified IEEE 33 bus system incorporating industrial, commercial, and residential consumers’ load profile of 24 h at selected buses has been considered to test and validate the proposition.

Non Linear Lie derivative Control Technique for Improved Voltage Regulation in Flyback Converter

Non Linear Lie derivative Control Technique for Improved Voltage Regulation in Flyback Converter

Sector Wise Modified Droop Control to Improve Voltage Regulation and Current Sharing in Parallel Boost Converter Interfaced DC Microgrid

Sector Wise Modified Droop Control to Improve Voltage Regulation and Current Sharing in Parallel Boost Converter Interfaced DC Microgrid

Enhancement of Power Transfer Capability of Transmission Line Using Thyristor Controlled Series Capacitor (TCSC)

Electricity demand is increasing with the increase in urbanization and industrialization. And to meet this increasing demand, the power generation system has been rapidly increased. But along with increase in generation capacity, transmission capacity also needs to be increased simultaneously. For this, either new transmission line needs to be added in the network or power transfer capability of the existing transmission line needs to be enlarged. Latter is the more preferred choice as it involves less cost and time than to erect the new transmission lines. Power transfer capability of a transmission line can be improved by the adjustment of various parameters of a power system network such as voltage phase angles of the buses connected by the lines, impedance of the lines, etc. For this several power electronics-based FACTS devices have been developed, which are most effective in manipulating these parameters to control the power flow through the lines. In this paper, the use of thyristor-controlled series capacitor (TCSC) is highlighted. In this paper, TCSC is implemented in series with line, connecting two buses, to reduce line series impedance. From the results, it is seen that TCSC implementation increases power transfer capability and stability limit, while improving voltage regulation.

REACTIVE POWER COMPENSATION TECHNOLOGIES

This article provides an overview of the current state of reactive power compensation technologies. The principles of operation, design characteristics and examples of the use of VAR compensators on thyristors and self-commutated converters are given. VAR static generators are used to improve voltage regulation, stability and power factor in AC transmission and distribution systems. Also described are examples obtained from the respective annexes describing the use of reactive power compensators implementedusing the new static VAR technologies.

A Review of Multilevel Inverter Topologies for Grid-Connected Sustainable Solar Photovoltaic Systems

Solar energy is one of the most suggested sustainable energy sources due to its availability in nature, developments in power electronics, and global environmental concerns. A solar photovoltaic system is one example of a grid-connected application using multilevel inverters (MLIs). In grid-connected PV systems, the inverter’s design must be carefully considered to improve efficiency. The switched capacitor (SC) MLI is an appealing inverter over its alternatives for a variety of applications due to its inductor-less or transformer-less operation, enhanced voltage output, improved voltage regulation inside the capacitor itself, low cost, reduced circuit components, small size, and less electromagnetic interference. The reduced component counts are required to enhance efficiency, to increase power density, and to minimize device stress. This review presents a thorough analysis of MLIs and a classification of the existing MLI topologies, along with their merits and demerits. It also provides a detailed survey of reduced switch count multilevel inverter (RSC-MLI) topologies, including their designs, typical features, limitations, and criteria for selection. This paper also covers the survey of SC-MLI topologies with a qualitative assessment to aid in the direction of future research. Finally, this review will help engineers and researchers by providing a detailed look at the total number of power semiconductor switches, DC sources, passive elements, total standing voltage, reliability analysis, applications, challenges, and recommendations.

Enhancing hybrid energy storage systems with advanced low-pass filtration and frequency decoupling for optimal power allocation and reliability of cluster of DC-microgrids

This study introduces an innovative power-split approach for hybrid energy storage systems (HESS) and diesel generators, utilizing frequency decoupling and a combination of classical and advanced low-pass-filtration techniques. The HESS dual-loop structure incorporates Super-Twisting-Sliding-Mode-Control, known for its remarkable robustness against uncertainties and external disturbances, effectively suppressing chattering. Among the low-pass-filtration techniques, Advanced Low-Pass-Filtering (ALPF) surpasses Classical Low-Pass-Filtering (CLPF), offering enhanced control statistics. The regulation of supercapacitor setpoint current based on the bank voltage ratio and control inaccuracy of battery current enables the ALPF to address dynamic battery issues. Under three waveforms, thorough simulations show superior load power allocation performance. Smoother waveforms boost supply voltage by 36% and power flow by 0.2%. Root-Mean-Squared-Error and Mean-Absolute-Error evaluations show exceptionally low average errors of 0.72% for Bus voltage, 0.16 A for battery current, and 3 A for supercapacitor current. The system also achieves 99.8% supply efficiency with a load setpoint deviation of less than 1%. ALPF improves supercapacitor performance by 8.4–11% while adjusting for uncompensated battery power. ALPF improves voltage regulation, power losses, load setpoint convergence, power peaks, and recovery. Ultimately, the proposed low-pass-filtration technique significantly enhances system dependability, relieving the burden on HESS while achieving superior loading efficiency.

A method to control distributed energy resources in distribution networks using smart meter data

Voltage regulation has been one of the major challenges for distribution network operators (DNOs) due to the integration of distributed energy resources in the recent years. Control approaches mitigating over-voltage (OV) generally require full network model, which for low-voltage distribution networks (LVDNs), can be inaccessible to DNOs. This paper presents a novel data-driven model-free control framework for improving voltage regulation in 4-wire 3-phase LVDNs. In the proposed approach, first, using smart meter data, the aggregated resistance and reactance matrices of the network are estimated. Then, these matrices serve as an input for the proposed optimal power flow (OPF) method to control the DERs’ active and reactive power outputs. This method also lets the DNO adjust the fairness in prosumers’ generation curtailment. The performance of the proposed approach is evaluated in various case studies conducted on a real-world low-voltage test feeder. The simulation results exhibit significant effectiveness in solving the OV problem associated with DERs. For example, in the studied network, the proposed approach limits the maximum voltage of the network to 1.1 pu, while without having control over the DERs output power, it can even overpass 1.17 pu during the peak generation period. In addition, utilizing DERs’ reactive control capability reduces the amount of active power curtailment, and prosumers are able to collectively inject 5.66% more active power.

An Artificial Neural Network Approach to Performance Investigation of Radial Distribution System with Series Capacitor Installation

This paper presents an investigation into the performance of radial distribution systems (DS) with the installation of series capacitors in feeder sections. While the use of shunt capacitors to enhance voltage profile in DS has been acknowledged, the benefits of series capacitors have only been explored to a limited extent. Load flow analysis, while commonly used for offline evaluation of DS, can at times yield inconclusive results due to convergence issues. To mitigate this, an alternative approach is proposed using Artificial Neural Networks (ANN) to directly determine system performance. The viability of the proposed technique is evaluated for IEEE 12 and IEEE 33 bus DS’s having series capacitor in feeder section for voltage improvement and line loss minimization. Therefore, this paper serves to contributes to the two main novelties namely, (1) Development of efficient ANN model to directly determine the maximum voltage regulation and line losses and (2) improvement of voltage and line losses reduction through series capacitor installation in feeder section of the DS. The results show that the utilization of an ANN model enhances accuracy and speeds up predictions, while the installation of series capacitors in feeder sections improves voltage regulation and reduces line losses.

A multifunctional complex droop control scheme for dynamic power management in hybrid DC microgrids

It is crucial for hybrid DC microgrids (MGs) to employ power management strategies that take into account the dynamic characteristics of all energy sources in the system. This paper proposes a novel complex droop control (CDC) for voltage control units in hybrid DC MGs, which enables flexible power management by providing the capability to adjust steady-state and dynamic power sharing in addition to damping provision by leveraging a multifunctional droop function. To accurately tune the splitting frequencies that determine the performance of dynamic power sharing, a novel design procedure based on a reduced-order DC MG model is proposed. To gain insight into the dominant oscillatory modes and the impact of the proposed control on the stability of the hybrid DC MG, a system-level small-signal analysis is also conducted. Offline and real-time simulations of the hybrid DC MG subjected to pulsed-power load variations reveal that the CDC can effectively share dynamic power, while improving voltage regulation and damping.

Enhancement of Voltage Regulation and Transient Stability of Six Phase STATCOM using Decoupled Current Control Strategy

STATCOM is used in a six-phase transmission system to improve voltage regulation and transient stability. Six-phase pulse width modulated voltage source converters are used in the design of STATCOM, and a decoupled current control approach is used to operate it. The voltage references used by the voltage source converters' pulse generator are produced using a decoupled control method. This control technique allows for the decoupling of the coupling effect or the dependence of the d and q currents on one another, which improves system performance under unusual and abnormal conditions. By using the pulse generator of voltage source converters, the inner current control loop and the outer voltage control loop are intended to produce the necessary reference voltages. Simulation results are presented using MATLAB/SIMULINK to check efficacy of proposed six phase STATCOM.