Voltage Stability Of Distribution Network Research Articles

Improving the Voltage Stability of Distribution Network Using Capacitor Banks and PV Arrays Based on OpenDSS

Improving the Voltage Stability of Distribution Network Using Capacitor Banks and PV Arrays Based on OpenDSS

Hierarchical robust Day-Ahead VPP and DSO coordination based on local market to enhance distribution network voltage stability

As distributed energy resources (DER) are increasing, a variety of business models and markets are appearing. Business models such as virtual power plants (VPPs) contribute to enhanced stability of the power system while improving the profits of participating resources. However, the uncertainty of the behavior of DERs and the resulting stability issues are a major barrier to DER deployment and require a coordination framework between grid operators and business models to overcome. Therefore, in this paper, a hierarchical robust day-ahead coordination of a VPP and distribution system operator (DSO) based on the local market is proposed to improve the voltage stability of the distribution network by considering the uncertainty of DERs. For fairness reasons, the contribution of DERs to the distribution system can be addressed by a market-based approach. Local markets are divided into local energy markets (LEM) and local flexibility markets (LFM), which can consider the uncertainty and profitability of DERs. First, the DER determines the seller and buyer status of the LEM based on its self- scheduling with expected prices and is matched based on a double-auction mechanism. At this time, the worst-case scenario of load and renewable energy generation predicted by the Gaussian process (GP) is considered. The mismatched amounts in the LEM are aggregated by the VPP and bid into the wholesale energy market (WEM) operated by the TSO (Transmission system operator). Subsequently, DSO operates a LFM that coordinates microgrid (MG) and VPP on the distribution grid to increase voltage stability. The LFM and WEM problems are considered as interval optimization in the form of mixed integer linear programming and are applied together. The flexibility supply resulting from the adjustment of VPP is compensated by a loss-sensitivity-based flexibility price. Since voltage stability exists in upper and lower bounds, the upper and lower bound of net load through GP-based forecasting is considered along with the linearized network constraints. The results are validated through Monte-Carlo simulation-based scenarios on IEEE benchmark system in MATLAB environment. As a result, it is proved that the proposed model improves the distribution network voltage stability and the profit of the participants.

An Improved Analysis of Distributed Resource Access Location and Capacity on Voltage Stability of Distribution Networks in Smart Grid

Concerns about how Distributed Energy Resources (DERs) may affect distribution network voltage stability have been brought up by the widespread usage of DERs in the elegant Grid. A Smart Grid connects a range of distributed energy resources (DERs) to the distribution network, including electric cars, wind turbines, and solar panels. This connection can alter the working conditions of the network. These changes can lead to voltage stability problems, which can affect the overall efficiency and reliability of the Smart Grid. Thus, there is a need for an improved analysis of the effects of Distributed Resource Access Location and Capacity (DRALC) on voltage strength in distribution networks. Here, we propose an improved analysis of the impact of DRALC on voltage stability in distribution networks in the Smart Grid. Our analysis considers the location and capacity of DERs and their effect on voltage stability using a combination of analytical and simulation methods. We first develop a mathematical model to represent the distribution network, which includes the DERs as voltage sources. Next, we use the voltage stability index and load flow analysis to evaluate the voltage stability of the network under different DRALC scenarios. Finally, we validate our analysis by performing simulations on a real-world distribution network.

Multi-objective Collaborative Optimization Method for Intelligent Distribution Network Operation and Maintenance

Most of the conventional multi-objective coordination methods for active distribution network operation are designed based on the principle of weighted random algorithm, which has limited application scope and cannot simplify the algorithm and reduce the complexity of the solution process, resulting in poor stability of active distribution network lines and potential faults. Based on this, this algorithm is introduced to carry out multi-objective collaborative optimization for intelligent distribution network operation. Firstly, the node types for the intelligent distribution network are defined and the power flow of the distribution network is analyzed. Secondly, a multi-objective configuration model for the lower level of the operation is constructed to maximize the distribution network investment and operation benefit index. A multi-objective collaborative optimization algorithm based on an enhanced particle swarm optimization algorithm is designed to reduce the operation cost of the distribution network and enhance the security and stability of the distribution network system during operation. The simulation test results show that after the application of the new method, the intelligent distribution network voltage stability index Vm is always less than 1, and the line stability has been significantly improved.

Optimizing Voltage Stability in Distribution Networks via Metaheuristic Algorithm-Driven Reactive Power Compensation from MDHD EVs

The deployment of medium-duty and heavy-duty (MDHD) electric vehicles (EVs), characterized by their substantial battery capacity and high charging power demand, poses a potential threat to voltage stability within distribution networks. One possible solution to voltage instability is reactive power compensation from charging MDHD EVs. However, this process must be carefully facilitated in order to be effective. This paper introduces an innovative distribution network voltage stability solution by first identifying the network’s weakest buses and then utilizing a metaheuristic algorithm to schedule reactive power compensation from MDHD EVs. In the paper, multiple metaheuristic algorithms, including genetic algorithms, particle swarm optimization, moth flame optimization, salp swarm algorithms, whale optimization, and grey wolf optimization, are subjected to rigorous evaluation concerning their efficacy in terms of voltage stability improvement, power loss reduction, and computational efficiency. The proposed methodology optimizes power flow with the salp swarm algorithm, which was determined to be the most effective tool, to mitigate voltage fluctuations and enhance overall stability. The simulation results, conducted on a modified IEEE 33 bus distribution system, convincingly demonstrate the algorithm’s efficacy in augmenting voltage stability and curtailing power losses, supporting the reliable and efficient integration of MDHD EVs into distribution networks.

Voltage stability improvement in distribution networks by using soft open points

The integration of renewable energies is gaining popularity as a result of their sustainability and green nature. On the other hand, aged power infrastructure not only has various issues in accommodating such resources, but also poses risks to the distribution network operation. To this aim, soft open points (SOPs) can be used for supporting distribution networks. Although SOP has been used for different purposes, the potential of SOP for increasing the voltage stability entails further study. As a result, an efficient strategy for the operation of SOPs in distribution networks is developed in this study, which considers the voltage stability index as an objective function. The developed framework is optimized using the particle swarm optimization method, which takes network, resource, and other technical limitations into account. The uncertainties of loads and renewable energies are also modeled through the scenario-based method. The suggested approach is tested on an IEEE standard distribution network under two conditions, comprising the normal and fault situations. After analyzing the various case studies and experiments, the effectiveness and applicability are verified accordingly. The findings show that SOP has a significant impact on improving voltage stability of distribution networks, throughout the normal and fault conditions.

Two‐stage self‐adaption security and low‐carbon dispatch strategy of energy storage systems in distribution networks with high proportion of photovoltaics

AbstractWith the goal of achieving carbon neutrality, active distribution networks (DNs) with a high proportion of photovoltaics (PVs) are facing challenges in maintaining voltage stability and low‐carbon operation. Energy storage systems (ESSs), which have the ability to store and transfer energy temporarily, can be used as effective measures to enhance the capacity of consuming PVs and reduce carbon emissions in DNs. However, existing low‐carbon dispatch strategies for multiple sources, storages and loads fail to consider voltage violations, while the temporal carbon emission intensity of the upper‐level power grid is also often overlooked, which is an important factor that affects the dispatch strategy. Therefore, a two‐stage self‐adaptive dispatch strategy of ESSs that considers the temporal characteristics of slack nodal carbon emission intensity to minimise carbon emissions while maintaining voltage stability in DNs with high access to PVs is proposed. First, the framework of the proposed two‐stage self‐adaptive dispatch strategy of ESSs is established by taking into account the effects of ESSs on adjusting voltages and reducing carbon emissions, respectively, with the two‐stage switch principle of two operation modes being determined. On this basis, an optimization dispatch model is established to improve voltages and carbon emissions, and the optimal day‐ahead dispatch strategy of ESSs can be obtained by solving the model using genetic algorithm. Case studies of the modified 10 kV IEEE 33‐node DN and IEEE 123‐node DN verify the feasibility and superiority of the proposed two‐stage self‐adaptive security and low‐carbon day‐ahead dispatch strategy for ESSs, showing that the voltage stabilisation and lower carbon emissions of DNs are both improved.

Research on the Influence of Wind Power Access on Voltage Stability of Distribution Network

This paper proposes a voltage stability index suitable for distributed generation and distribution network which is derived by using the relationship between power balance and voltage balance and the impact of wind power access location, access capacity, and fault on the voltage stability. The results show that the shorter the length and the larger the wind power capacity, the more obvious its role in supporting the distribution network voltage. But the greater the negative impact of wind power’s instability on the distribution network voltage, the above factors must be comprehensively considered in network planning.

Deep Reinforcement Learning for Charging Scheduling of Electric Vehicles Considering Distribution Network Voltage Stability.

The rapid development of electric vehicle (EV) technology and the consequent charging demand have brought challenges to the stable operation of distribution networks (DNs). The problem of the collaborative optimization of the charging scheduling of EVs and voltage control of the DN is intractable because the uncertainties of both EVs and the DN need to be considered. In this paper, we propose a deep reinforcement learning (DRL) approach to coordinate EV charging scheduling and distribution network voltage control. The DRL-based strategy contains two layers, the upper layer aims to reduce the operating costs of power generation of distributed generators and power consumption of EVs, and the lower layer controls the Volt/Var devices to maintain the voltage stability of the distribution network. We model the coordinate EV charging scheduling and voltage control problem in the distribution network as a Markov decision process (MDP). The model considers uncertainties of charging process caused by the charging behavior of EV users, as well as the uncertainty of uncontrollable load, system dynamic electricity price and renewable energy generation. Since the model has a dynamic state space and mixed action outputs, a framework of deep deterministic policy gradient (DDPG) is adopted to train the two-layer agent and the policy network is designed to output discrete and continuous control actions. Simulation and numerical results on the IEEE-33 bus test system demonstrate the effectiveness of the proposed method in collaborative EV charging scheduling and distribution network voltage stabilization.

Frequency and Voltage Stability of Distribution Network using Photovoltaic Stabilization System and Battery Storage System

In a power system, various factors such as changes in generator output power due to load changes and different types of short circuits may change the network frequency/voltage as a consequence of changes in network condition. These volatilities in frequency/voltage may cause system frequency/voltage instability. Among different devices used for power system stability, stabilizers are the most important equipment for network stabilization and generator synchronization. In this paper, a photovoltaic system accompanied by battery storage system is used to improve the power system stability following voltage/frequency sudden variations as a result of unpredicted events in the distribution network. To do that, an IEEE 14-bus standard test network is simulated in MATLAB/Simulink, and the performance of the proposed system after different common disturbances is investigated. The results verify the performance of the proposed stabilizer so that it maintains the system stability successfully with zero percent deviation from the original state of the network.

Three-Stage Hierarchically-Coordinated Voltage/Var Control Based on PV Inverters Considering Distribution Network Voltage Stability

Intermittent photovoltaic (PV) power generation brings voltage fluctuation and stability issues to distribution networks. Meanwhile, PV inverters can support voltage/Var control (VVC) to address these issues. Utilizing PV inverters, this paper proposes a three-stage hierarchically-coordinated (TSHC-) VVC method considering network voltage stability. The first stage schedules on-load tap changers one day ahead, the second stage hourly dispatches reactive power outputs of inverters, and the third stage implements real-time local voltage droop control of inverters. To efficiently address mutual impacts between these stages, the first two central-hierarchy stages are coordinated through interval optimization. Meanwhile, the last two stages are hierarchically coordinated by simultaneously optimizing inverter base reactive power outputs and droop control functions under real-time uncertainty. In the previous work, local droop control functions are not fully optimized, and network voltage stability is not fully considered. To overcome such limitations, this paper develops new constraints of individual control gain for each inverter, taking voltage stability into account. The proposed TSHC-VVC method with the optimized control gains is tested and compared with existing methods. Simulation results verify its better performance in reducing network power losses and bus voltage deviations, as well as maintaining network voltage stability.

Continuous-Domain Real-Time Distributed ADMM Algorithm for Aggregator Scheduling and Voltage Stability in Distribution Network

With an increase in the number of electric vehicles (EVs) and battery storage systems (BSSs), there are major challenges in the distribution grid to maintain a scaling control structure. Also, with the vehicle-to-grid (V2G) technology, EVs can now inject power into the grid for voltage regulation. This article proposes a new distributed real-time alternating direction method of multipliers (ADMM) technique to control EVs and BSSs for voltage regulation while maximizing their utility function. More specifically, a continuous-domain real-time optimization and control algorithm is developed in closed form, which exchanges relevant information among the neighboring nodes through the communication network and optimizes a combined convex objective of EVs and BSSs welfare and voltage regulation with power flow equations as constraints. Convergence analysis is provided using the Lyapunov direct approach, and simulation results are included to illustrate the effectiveness of the proposed scheme. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This article is motivated by the problems that an electric distribution system is facing today due to the penetration of electric vehicles and battery storage systems (BSSs). The presence of a large number of electric vehicles (EVs) and BSSs is causing a substantial degradation of the quality and reliability of the power grid. Despite the adverse effects, EVs and BSSs can be controlled and used as a power source to benefit the grid. Also, this control of EVs and BSS cannot be done by a centralized body since this would be nonscalable and would require huge communication bandwidth. To tackle this ever scaling problem, this article develops a continuous-domain multiagent distributed algorithm to control the EVs and BSSs and utilize them to maintain the grid voltage within the normal operating range while also satisfying the consumers by maximizing their welfare. The algorithm was developed in the continuous domain since, in most of the other algorithms that are iterative and in discrete time, the accuracy of the optimal solution greatly depends on the sampling time, and thus, it is not robust to changes that are prevalent with distributed energy resources such as EVs and BSSs.

Automatic Identification of Low Voltage Distribution Network Topology Based on HPLC

With the rapid development of China’s national economy and the deepening of reform and opening up, people’s demand for electricity is growing. This paper studies the automation of low-voltage distribution network topology based on HPLC power line carrier technology. It is a key technology to effectively extend the communication distance of power line communication network in smart grid. For the power line communication network, we establish the network model of power line carrier layered forwarding tree. Based on the study of the topology and various operation modes of DC distribution network, a new hierarchical coordinated control method is proposed. By coordinating the working mode of each sub module, the power balance and voltage stability of distribution network are maintained under different conditions.

Dynamic Voltage Stability of Distribution Systems in the Presence of High Penetration of Photovoltaic Plants Using PSS/E Software

The intermittent nature of photovoltaic (PV) generation causes the voltage to fluctuate and may lead to instability, especially, in case of high penetration. In this paper, a methodology is proposed to control the reactive power generation of PV-inverters. The objective is to mitigate the voltage fluctuations at the point of common coupling (PCC) resulted from increasing or decreasing the active power output of PV plants which is dependent on solar radiation level. The generic PV-inverter models developed and recommended by the Renewable Energy Modeling Task Force (REMTF) of the Western Electricity Coordinating Council (WECC) is used to analyze the effect of high PV penetration on the dynamic voltage stability of distribution networks. Then, the tested distribution network with the embedded PV plants is modeled and simulated using PSS/E software. Levels of control that are built-in PV-inverters are tested in the case of normal operation and during disturbances. Comparison results show that the most suitable control methodology in case of disturbances and after fault clearance is the local voltage control. While the plant voltage control with coordinated V/Q control is the most preferable control methodology during normal operation.

Research on Method of Improving Voltage Stability of Distribution Network with Distributed Generation

With the increase of distributed generation capacity, grid-connected distributed generation (DG) has an impact on the stability of distribution network. This paper studies the influence of the access of DG on the stability of distribution network. In view of the impact of the access of DG on the distribution network, a method is proposed to improve the voltage stability of the distribution network through the configuration of energy storage equipment in the distribution network. The effectiveness of adding energy storage equipment to improve the voltage stability of distribution network is verified by the simulation results through the MATLAB / Simulink simulation model of DG.

Enhancing the voltage stability of distribution network during PV ramping conditions with variable speed drive loads

The Photovoltaic (PV) sources have become the most popular renewable energy resources as it is modular and are deployed quickly. However, the distributed PVs are highly volatile and can have high ramping characteristics where the ramping can go up to 90% of its capacity in about 20 s due to events such as the passing of fast-moving clouds. This kind of PV ramps with high magnitudes can lead to voltage instability in distribution networks that are usually dominated by Induction motor (IM) loads. This paper explains the mechanism of such an instability analytically using Q-V analysis with distribution feeder and IM load characteristics. Highlighting the gradual replacement of IM loads by Variable Speed Drive (VSD) loads due to energy efficiency policies, the paper demonstrates the enhanced voltage stability under VSD loads by both time simulation and analytical approach. Furthermore, the analysis is extended to a realistic distribution network namely, United Kingdom General Distribution System (UKGDS) and extensive case studies are conducted to analyze the voltage stability during PV ramping events at various load compositions of IMs and VSDs. Moreover, the minimum VSD penetration level required to avert the voltage instability at various PV penetration levels have also been determined.

Analysis of the impact of accessing the distributed energy storage system on power distribution network

When distributed energy storage on user side is connected to the distribution network, it will have a significant impact on the distribution network. So the reasonable access for energy storage system has become a key problem. Therefore, this paper analyzes the impact on power distribution network loss and voltage stability by accessing distributed energy storage on user side. Firstly, the relationship between voltage stability of distribution network and distributed energy storage access is studied. It is concluded that the distributed energy storage is beneficial to the voltage stability of distribution network. Then the calculation method of distribution network loss before and after distributed energy storage access is analyzed. Finally, the access location of distributed energy storage is simulated and analyzed. Considering the network loss and voltage stability, it is concluded that small capacity distributed energy storage should be connected at the end of the line, and a certain large capacity distributed energy storage should be connected at the beginning of the line.

Probabilistic assessment of static voltage stability in distribution systems considering wind generation using catastrophe theory

With increasing penetration of distributed generations, the importance of the voltage stability assessment of distribution networks has been increased. Considering this situation, a probabilistic model is proposed to evaluate the voltage stability of distribution network integrating wind turbine (WT) units. With this intention, a probabilistic voltage stability index (PVSI) of a radial distribution system with wind power generation is presented. This index investigates the probabilistic risk of voltage collapse for all the buses of system considering uncertainty of WTs. Therefore, the most sensitive bus to the voltage collapse can be identified. The problem model is based on the catastrophe theory that can find the bifurcation point of system. Three-point estimation method is employed to calculate the statistical moments of voltage and PVSI of nodes. Moreover, to estimate the cumulative distribution function of output random variables, the Cornish−Fisher series are used. The performance of the probabilistic index is tested on the IEEE 69-bus radial distribution system where different load models are considered. The results demonstrate that the PVSI can accurately predict the voltage instability condition of the system.

Optimal Multi-Indices Application of Distributed Generations in Radial Distribuion Networks Based on Moth-Flame Optimizer

In this paper, a new approach based on the Moth-Flame Optimizer is done to design and operate distribution networks using DGs by determining the optimal choice of location and size of power generated by DG with the aim of losses reduction and improvement of distribution network voltage stability. In this study, the optimal decision variables is including the optimal location and size of DG on the distribution network which is determined by the Moth-Flame Optimizer. The proposed problem has been implemented on IEEE standard 33 and 69 bus distribution networks. In this study, In order to verify the proposed Moth-Flame Optimizer method, the problem is also solved by PSO and the results were compared and analyzed. Optimization results show that the proposed MFO method is the high-power quick way to find the optimal points is compared to PSO Has shown better performance in problem solving. The obtained results have confirmed the capability of the proposed method.

Reactive power operability of distributed energy resources for voltage stability of distribution networks

The penetration level of distributed energy resources (DERs) is increasing and has significant impact on the voltage stability of distribution networks. Based on the various types of DERs with distinct reactive power characteristics (RPC), their different contributions to the system voltage stability require classification. Firstly, the features of DERs are reviewed and classified based on their RPC, to investigate different distributed generation technologies for reactive power support in distribution networks. Then, the concept of a relative available transmission capacity index (RATCI), which is based on power transfer margin of the power-voltage curve considering the non-negligible distribution network resistance, is proposed to quantify and evaluate the voltage stability by integrating DERs with the defined reactive power types. Case studies have been conducted for an IEEE 33-bus distribution network to calculate the system RATCI for the mixed integration of DERs. Results show that the multi-type and multi-locational integration of DERs can improve the voltage stability of a distribution network.