Optimal Voltage Control Research Articles

Evaluation Method for Hosting Capacity of PV System in Distribution System with Micro Hydropower Generator

According to the Korean government’s policy to demonstrate and expand renewable energy sources, distributed generators such as photovoltaic (PV) and wind power (WP) systems are energetically installed and operated in distribution systems. However, there are many issues related to power quality problems including an over-voltage phenomenon when the PV systems were interconnected and operated. In order to overcome these problems the electric power company has installed the step voltage regulator (SVR) in primary feeders interconnected with PV systems, and also has established technical guidelines for distributed generators to stabilize the customer voltages. However, despite such voltage regulators and technical guidelines, it is difficult to maintain the customer voltages within the allowable voltage limit. In order to actively host a large-capacity PV system, this paper proposes an optimal voltage control algorithm of micro hydropower generator (MHG) to keep customer voltages within the allowable voltage limit and presents an evaluation algorithm for hosting capacity of PV system based on a sensitivity analysis method. Furthermore, this paper performs PSCAD/EMTDC modeling based on the proposed algorithm and analyzes characteristics of customer voltages based on various scenarios related to the location and capacity of the PV system and MHG. From the simulation results, it is confirmed that the proposed methods can contribute to the stabilization of the customer voltages and improve the hosting capacity of the PV system in a distribution system.

Fully distributed peer-to-peer optimal voltage control with minimal model requirements

This paper addresses the problem of voltage regulation in a power distribution grid using the reactive power injections of grid-connected power inverters. We first discuss how purely local voltage control schemes cannot regulate the voltages within a desired range under all circumstances and may even yield detrimental control decisions. Communication and, through that, coordination are therefore needed. On the other hand, short-range peer-to-peer communication and knowledge of electric distances between neighbouring controllers are sufficient for this task. We implement such a peer-to-peer controller and test it on a 400 V distribution feeder with asynchronous communication channels, confirming its viability on real-life systems. Finally, we analyze the scalability of this approach with respect to the number of agents on the feeder that participate in the voltage regulation task.

Insights and trends of optimal voltage‐frequency control DG‐based inverter for autonomous microgrid: State‐of‐the‐art review

This paper endeavours a control scheme for optimal control of voltage and frequency of power inverter which relied upon distributed generation in cognitive microgrid using soft computational methods. It gives sound direction on how to control the active power flow, voltage-frequency regulation, and sharing of power among various components of MG. The classical voltage–frequency control strategy in parallel with the modern control method is well excavated in the present paper. Moreover, modulation techniques, variants of reference frames, power quality indices are covered blatantly. Thus, the paper gives fast insight and understanding to the engineers working in this niche area.

Probabilistic State Forecasting and Optimal Voltage Control in Distribution Grids under Uncertainty

Nowadays, the uncertainty in distribution systems rises, notably due to an increasing share of solar panels and electric vehicles whose power production and consumption are characterized by a high volatility. This poses challenges to distribution system operators to ensure stable and secure operation of their grid. Hence, an optimal integration of these distributed energy resources in real-time control schemes inevitably relies on appropriate forecasts of the near-future system state. This paper investigates the short-term probabilistic state prediction of low-voltage grids for operation purposes. The performance of two quantile forecasting algorithms is evaluated for different levels of distributed energy resources penetration and availability of measurements. Quantile forecasts are finally integrated into the framework of an optimization problem that aims at minimizing the costs associated with overvoltages by suitable solar power curtailment. The advantages of quantile forecasts considering different imbalance prices are demonstrated.

Decentralized voltage control of wind farm based on gradient projection method

A decentralized voltage control (DVC) scheme based on the gradient projection (GP) method is proposed for the wind farm (WF). The wind farm controller optimizes the reactive power output of doubly-fed induction generator (DFIG)-based wind turbines (WTs) and static synchronous compensator (STATCOM) at the medium voltage (MV) side of the step-up transformer. The aim is to keep voltages of all buses in the wind farm within the feasible range and maintain a certain reactive power margin for WTs. The solution method based on the GP method is developed to solve the voltage control optimization problem in a decentralized manner without a central controller or communication between local controllers, which achieves optimal voltage control and greatly saves communication costs. A WF with 1 STATCOM and 40 wind turbine generators (WTGs) was used to validate the control performance of the proposed DVC scheme. The case study results demonstrate that the proposed decentralized voltage control can achieve optimal voltage control without the central controller or communication between local controllers under both normal operation and disturbances.

Distributed Online Voltage Control for Wind Farms Using Generalized Fast Dual Ascent

This paper considers the voltage control problem in wind farms, with the goals of maintaining feasible voltage profile and adequate reactive power (VAR) reserves by coordinating the reactive power outputs of wind turbines (WTs) and static synchronous compensators (STATCOMs). Rather than a conventional centralized and offline fashion, we propose a distributed online voltage control scheme based on dual decomposition. First, the optimal voltage control problem is formulated based on the branch flow model. Then, thanks to the sparsity of the constraints in this problem, a distributed solution framework is developed based on the dual decomposition and its online implementation is achieved through voltage feedback. To pursue fast convergence of the distributed algorithm and consequently facilitate the online implementation, the fast gradient method is generalized and then applied to solve the dual problem. The effectiveness of the proposed voltage control scheme is numerically validated under both static and dynamic cases.

Optimal Operation of Electric Springs for Voltage Regulation in Distribution Systems

In this article, we propose an optimal voltage control method for critical buses in an active distribution system using electric springs (ESs). The proposed optimization model relies on both an accurate ES and a load model. The real-time load parameters are determined using the nonintrusive load monitoring (NILM) technique, which provides a flexible and convenient power profile disaggregation. The optimization problem is solved in both a centralized and distributed manner with the minimum ES voltage outputs. A control center communicates with all ESs and collects system information in a centralized scheme, while a multiagent concept is built into the distributed scheme to manage the communication, optimization, and control of ESs located in different areas. The proposed voltage optimal control methods with ESs are verified and compared on a modified IEEE 15-bus distribution network. The results are promising; voltage regulation capability is verified, indicating advantages in the proposed optimal operation strategy over the previous ES control strategy.

Safe deep reinforcement learning-based constrained optimal control scheme for active distribution networks

Reinforcement learning-based schemes are being recently applied for model-free voltage control in active distribution networks. However, existing reinforcement learning methods face challenges when it comes to continuous state and action spaces problems or problems with operation constraints. To address these limitations, this paper proposes an optimal voltage control scheme based on the safe deep reinforcement learning. In this scheme, the optimal voltage control problem is formulated as a constrained Markov decision process, in which both state and action spaces are continuous. To solve this problem efficiently, the deep deterministic policy gradient algorithm is utilized to learn the reactive power control policies, which determine the optimal control actions from the states. In contrast to existing reinforcement learning methods, deep deterministic policy gradient is naturally capable of addressing control problems with continuous state and action spaces. This is due to the utilization of deep neural networks to approximate both value function and policy. In addition, in order to handle the operation constraints in active distribution networks, a safe exploration approach is proposed to form a safety layer, which is composed directly on top the deep deterministic policy gradient actor network. This safety layer predicts the change in the constrained states and prevents the violation of active distribution networks operation constraints. Numerical simulations on modified IEEE test systems demonstrate that the proposed scheme successfully maintains all bus voltage within the allowed range, and reduces the system loss by 15% compared to the no control case.

Output feedback control of electrolyte flow rate for Vanadium Redox Flow Batteries

In this paper, we propose a new strategy for electrolyte flow rate control in Vanadium Redox Flow Batteries. The keystone of our approach is a novel methodology for determination of optimal reference voltage and robust feedback controller design that provides the desired transient and steady state battery performance. In addition, we introduce a hierarchical scheme of the general battery control system that significantly simplifies classification of battery control tasks and gives guidelines for multistage controller design. The research considers a kilo-watt class VRFB system operating in a wide range of loading currents (20–180 A). The proposed control algorithm allows reference trajectory tracking with high accuracy (average error less than 0.0005%), yet providing the required battery performance at twice lower flow rates as compared to the existing solutions, and thus, decreasing pump energy consumption by a factor of 3. As a result, the proposed method can be used for flow rate regulation in practical VRFB systems ensuring their stable and efficient operation under dynamic loading conditions.

Distributed Optimal Voltage Control With Asynchronous and Delayed Communication

The increased penetration of volatile renewable energy into distribution networks necessities more efficient distributed voltage control. In this paper, we design distributed feedback control algorithms where each bus can inject both active and reactive power into the grid to regulate the voltages. The control law on each bus is only based on local voltage measurements and communication to its physical neighbors. Moreover, the buses can perform their updates asynchronously without receiving information from their neighbors for periods of time. The algorithm enforces hard upper and lower limits on the active and reactive powers at every iteration. We prove that the algorithm converges to the optimal feasible voltage profile, assuming linear power flows. This provable convergence is maintained under bounded communication delays and asynchronous communications. We further numerically test the performance of the algorithm using the full nonlinear AC power flow model. Our simulations show the effectiveness of our algorithm on realistic networks with both static and fluctuating loads, even in the presence of communication delays.

Optimal Voltage Control Algorithm of Small Hydropower Generators for Voltage Stabilization in Distribution System with Large Scale PV Systems

Optimal Voltage Control Algorithm of Small Hydropower Generators for Voltage Stabilization in Distribution System with Large Scale PV Systems

Optimize globally, control locally: Coordinated optimal local voltage control in hybrid AC/DC microgrid

The increasing penetration of photovoltaic (PV) generation leads to voltage violations in hybrid AC/DC microgrids. Due to the uncertainty and volatility of PV outputs, fast-responding voltage control devices are obliged to coordinate with each other and regulate nodal voltages in real time. This paper follows the concept of optimizing globally and controlling locally to propose a combined central and local voltage control strategy based on a two-stage voltage control framework. In the first stage, minutely optimal power flow based on predicted PV outputs within one hour is performed in microgrid central controller (MGCC) to calculate voltage and optimal power settings for each controllable device. The uncertainty of PV is considered using chance constraint optimal power flow (CCOPF) method. In the second stage, according to minutely voltage and power settings, local controller (LC) generates improved voltage control curves based on curve fitting method. With minutely measurements of nodal voltages, power outputs of PVs, smart loads (SLs) energy storage systems (ESSs) and VSC are cooperated based on improved local control curves to minimize power losses without communication requirements. In order to coordinate the active and reactive power of SLs ESSs, and VSC, a combined P(V) and Q(V) curve is proposed. The piecewise linear curve fitting method is used to generate optimal voltage control curves due to its higher fitting accuracy compared with other fitting methods. Simulations are performed to verify the effectiveness of the proposed voltage control strategy in mitigating voltage rise problems and reducing power losses.

Distributed Optimal Voltage Control for VSC-HVDC Connected Large-Scale Wind Farm Cluster Based on Analytical Target Cascading Method

This article proposes an analytical target cascading (ATC) based distributed optimal voltage control (DOVC) scheme for the voltage-source-converter high-voltage-direct-current (VSC-HVDC) connected large-scale wind farm cluster (WFC). The aims are to minimize the voltage fluctuations of the point of connection (POC), collector buses, and wind turbine (WT) terminal buses inside the WFC while regulating the bus voltages close to the rated voltage and smooth the reactive power outputs of the WTs. With the DOVC scheme, the large-scale strongly coupled sensitivity-based voltage optimization problem is decomposed and solved in the WFC voltage-source-converter (WFCVSC) controller and sub-wind farm controllers in parallel. The DOVC scheme considers the $N-1$ principle to improve the reliability, and distributes computation burden to several controllers to achieve better scalability of the WFC. The optimization subproblems are solved with local constraints and local measurements while guaranteeing the optimality of the primal optimization problem. A WFC with 5 wind farms and each wind farm consisting of 20 WTs is used to validate the proposed DOVC scheme.

Coordinated and optimal voltage control for voltage regulation using firefly algorithm

The operation and control of electricity in distribution networks has faced great challenges as a large number of distributed generations (DGs) are integrated. Connection of distributed generations (DGs) in the distribution system offers advantages in terms of reducing distribution and transmission costs as well as encouraging the use of renewable energy sources. The power flow in the distribution systems is no longer moving in a single direction and this resulted the system to become as active distribution networks (ADN). One of the main problems in ADN is the voltage regulation issue which is to maintain the voltage to be within its permissible limits. Several methods of voltage control methods are available and focus is given in finding the optimal voltage control using artificial intelligence techniques. This paper presents an optimal and coordinated voltage control method while minimizing losses and voltage deviation of the network. The optimal and coordinated voltage control scheme is implemented on an IEEE 13 bus distribution network for loss and voltage deviation minimization in the networks. Firefly Algorithm (FA) which is a known heuristic optimization technique for finding the optimal solution is used in this work. The results are compared with another optimization method known as Backtracking Search Algorithm (BSA) for identifying the best setting for solving the voltage regulation problem. In order to solve the multi-objective optimization issue, the MATPOWER load flow simulation is integrated in the MATLAB environment with the optimization algorithm.

An Approach to Suppress Low-Frequency Oscillation by Combining Extended State Observer With Model Predictive Control of EMUs Rectifier

Recently, low-frequency oscillation (LFO) occurs in electrified railways, which exhibits a synchronous periodic oscillation of about 2–7 Hz in the traction network and electric multiple units (EMUs). To suppress the LFO, an improved model predictive control (MPC) combining with extended state observer (ESO) is proposed. First, for the design of ESO, the changes of system parameters and the unmodeled item in vehicle mathematical model are extended to a new variable and then estimated to compensate the calculated control voltage in real time. Second, the observer stability is analyzed by obtaining the transfer function, and the appropriate gains of observer are chosen through the pole assignment technique. At last, by the combination of the predictive currents, the optimal control voltages can be obtained. The control performance among MPC, dq decoupling control, passivity-based control, and the proposed method is compared. In addition, the system robustness when system parameters change is discussed. At last, to further verify the effectiveness of the proposed method for suppressing LFO, an integrated dSPACE semi-physical experimental platform including eight simulated EMUs and an equivalent traction network is constructed. Simulation and experimental results show that the proposed method not only effectively suppresses LFO but also accelerates the response speed of traction line-side converter, reduces the distortion of grid-side and vehicle-side currents, and overcomes the disadvantages of MPC and dq decoupling control under the mismatching of system parameters.

An Improved P&O Algorithm for Single-Stage Grid-Connected Photovoltaic System under Rapidly Changing Environment Conditions

In producing its power, Photovoltaic (PV) performance is influenced by environmental factors, such as solar irradiance and temperature. System stability is needed to maintain safe operation of the system. This paper presents a Maximum Power Point Tracking (MPPT) control model of PV array to improve system reliability and the performance of MPPT. The main parameters in Matlab/Simulink simulation that become the highlight influences are the changes in solar irradiance from 500W/m2 to 1000W/m2 and ambient temperatures from 25°C to 50°C. With the control algorithm that has been made in the Perturb and Observe (P&O) method, it obtains the optimal voltage control point in each PV conditions in a power system. System simulation shows that the voltage stability was maintained above 510 Volt in various conditions of solar irradiance and temperature. The results of the control scheme show the stability of the system and the optimal performance of PV.

Optimal Voltage Control Strategy for Voltage Regulators in Active Unbalanced Distribution Systems Using Multi-Agents

The rapid increase in the installation of renewable energy sources, particularly solar photovoltaic (PV) sources associated with unbalanced features of distribution systems (DS), disturbs the classic control strategy of voltage regulation devices and causes voltage violation problems. This paper proposes an effective control strategy for voltage regulators in the DS based on the voltage sensitivity using a multi-agent system (MAS) architecture. The features of the unbalanced distribution system (UDS) with the PV and different types and configurations of voltage regulators are considered in the proposed strategy. The novelty of the proposed method lies in realizing both the control optimality of minimizing voltage violations and the flexibility to accommodate changes in the DS topology using an MAS scheme. An advantageous feature of using the MAS scheme is the robust control performance in normal operation and against system failure. Simulation studies have been conducted using IEEE 34-node and 123-node distribution test feeders considering high PV penetration and different sun profiles. The results show that the proposed voltage control strategy can optimally and effectively manage the voltage regulators in the UDS, which decrease their operation stresses and minimize the overall voltage deviation.

Optimal Voltage Control in Distribution Systems With Intermittent PV Using Multiobjective Grey-Wolf-Lévy Optimizer

The intermittent photovoltaic (PV) units significantly affect the performance of distribution systems, and they often cause several operational problems, most importantly, voltage rise/drop. At high PV penetration, excessive tap movements of transformers and high curtailed PV power are expected to completely solve the voltage violation problem. In this paper, we propose an optimal voltage control method for distribution systems considering the number of tap movements of transformers and the active power curtailment of PV units. The objective function of the proposed method comprises: 1) voltage drop violation, 2) voltage rise violation, 3) tap movement rate (TMR) of transformers, and 4) curtailed power of PV (CPPV). A multiobjective grey wolf optimizer integrated with a Levy mutation operator (GWO-Levy) is formulated to accurately solve the voltage control problem. A 24-h simulation is performed on the 119-bus distribution system with PV and different types of loads. The performance of GWO-Levy is compared with three other optimizers, finding that it achieves the best performance. The simulation results demonstrate the efficacy of the proposed method for solving the voltage violation problem with PV while simultaneously optimizing TMR and CPPV.

Adaptive static synchronous compensation techniques with the transmission system for optimum voltage control

Abstract Static Synchronous Compensation (STATCOM) is considered as one of the famous modules of the Flexible AC Transmission Systems (FACTS) devices. This paper discusses the optimum voltage control technique using the STATCOM module with the transmission system to overcome the drop and the influence factors for the voltage in the power system. In addition, this paper discusses the impact of using the zigzag transformers with the STATCOM control system to prevent the combination between the STATCOM injection voltage and the harmonics to reach pure voltage compensation. The simulation in this paper uses the MATLAB/Simulink software to introduce the STATCOM operation steps, also the proposed analysis of the distribution system network has been validated with IEEE-14 busbar system as a case study to test the increasing loadability by using STATCOM module for enhancing the power system quality.

Optimal voltage control strategy for grid-feeding power converters in AC microgrids

Predominant power generation by renewable energy sources poses an increasing challenge regarding the maintenance of a stable, reliable, but also affordable electricity supply. Power converters are the key system component to interface distributed generation systems to the electrical power grid and are increasingly required to provide grid supporting measures to an extent comparable to classical centralized power stations. Thus, improving the control performance of power converters in microgrids is becoming more significant. This work proposes an optimal voltage control strategy for a grid-feeding active-front-end power converter, which inherently regulates its bus voltage within a defined tolerance band while simultaneously keeping the provided reactive power at a specified optimal level. The focus is put on the proposed multi-loop control which incorporates a fast model predictive based current controller. Simulations and experiments on a power converter test bench are presented to validate the performance of the proposed voltage regulation scheme. The controller implementation is carried out for a three-level neutral-point-clamped voltage source inverter with an LCL output filter. Based on the results of the experimental validation, a simulation-based case study demonstrates its performance for multiple grid-tied power converters in an AC microgrid.