DIgSILENT PowerFactory Research Articles

Dynamic Damping of Power Oscillations in High-Renewable-Penetration Grids with FFT-Enabled POD-P Controllers

The growing integration of renewable energy sources, particularly photovoltaic (PV) and wind power, presents challenges such as reduced system inertia and increased susceptibility to inter-area oscillations. These issues, coupled with stricter regulatory demands for grid stability, highlight the urgent need for effective damping solutions. This study proposes a novel method for detecting and mitigating inter-area oscillations using a power oscillation damping (POD) controller enhanced by applying a Fast Fourier Transform (FFT). The controller’s parameters are optimized through the Nobel Bat Algorithm (NBA) and fully implemented in DIgSILENT PowerFactory (DSPF). Simulations conducted on the New England IEEE-39 power system model under varying levels of renewable energy penetration demonstrate the model’s capability to dynamically detect, mitigate, and deactivate oscillations once stability is achieved. This work addresses emerging regulations requiring oscillation damping systems and offers a framework for certifying POD controllers for real-world implementation, ensuring their adaptability to diverse energy systems and regulatory contexts.

Volt/VAr Regulation of the West Mediterranean Regional Electrical Grids Using SVC/STATCOM Devices With Neural Network Algorithms

ABSTRACTReactive power compensation is now a challenging issue in maintaining adequate power quality and improving the performance of the transmission system. Many researchers have focused on the behavior of voltage in the unbalanced state, and the majority of the studies have been done with STATCOM. In this study, the increasing power demand in power grids and the challenges associated with maintaining power quality and stability are discussed. The power system in the western Mediterranean region of Turkey is modeled with the DigSILENT Power Factory program using real data. It highlights the importance of reactive power compensation and introduces FACTS devices as a solution to control power factors and reactive power in the grid. In the realistic model, voltage and reactive power regulation is achieved by using SVC and STATCOM devices to ensure voltage stability. A load flow and short circuit analysis is performed on the designed transmission system for a number of critical scenarios. The modeled power system is optimized for the size and location of the FACTS devices by applying genetic algorithms (GAs) and particle swarm optimization (PSO) algorithms to the selected busbars of the FACTS devices, a strategy designed to significantly reduce system losses. The load values used in the heuristics differ from those used in other studies in that they use a realistic load profile that varies randomly and instantaneously over the long term, as opposed to a fixed load profile. All the comparative results show that the STATCOM controller can maintain the most significant reduction in technical losses and excellent performance in controlling the reactive power response under various outages. The effectiveness of the proposed methodology has been validated in various outage scenarios, and it has been shown that it will reduce the total cost of electricity generation in the western Mediterranean region on an annual basis. Considering the results of the Turkish National Transmission System, increasing voltage sensitivity and reactive power control can be beneficial in reducing power transmission costs and maintaining the balance between generation and consumption.

A Sustainable Hybrid Off-Grid System Design for Isolated Island Considering Techno-Economic and Frequency Stability Analysis

Electrifying remote islands presents complex challenges. Currently, most remote areas in Indonesia rely on diesel fuel for their electricity supplies, contributing to escalating generation costs and environmental degradation. Aligned with the global net-zero emission goal, this study proposes the design of a hybrid off-grid system for Kabare Village in the Raja Ampat Islands, integrating techno-economic and frequency stability analyses. HOMER Pro was employed to identify the most optimal system configuration, while DIgSILENT PowerFactory was utilized to assess the frequency stability performance of the system. This study unveils that the optimal system combines existing generators, solar panels, and batteries, with a net present cost of $1.37 million. The optimal system delivers an 11.8% reduction in levelized cost of energy to $0.269/kWh, alongside a 25.6% decrease in both fuel consumption and greenhouse gas emissions compared to the existing system. Moreover, the system meets frequency stability metrics, even under extreme operational conditions. This study demonstrates that implementing a hybrid off-grid system in Kabare Village is not only technically and economically feasible but also a practical option. These findings are anticipated to assist the government in promoting the utilization of renewable energy sources, particularly in remote areas such as the islands of eastern Indonesia.

A Novel IoT-Based Controlled Islanding Strategy for Enhanced Power System Stability and Resilience

Intentional controlled islanding (ICI) is a crucial strategy to avert power system collapse and blackouts caused by severe disturbances. This paper introduces an innovative IoT-based ICI strategy that identifies the optimal location for system segmentation during emergencies. Initially, the algorithm transmits essential data from phasor measurement units (PMUs) to the IoT cloud. Subsequently, it calculates the coherency index among all pairs of generators. Leveraging IoT technology increases system accessibility, enabling the real-time detection of changes in network topology post-disturbance and allowing the coherency index to adapt accordingly. A novel algorithm is then employed to group coherent generators based on relative coherency index values, eliminating the need to transfer data points elsewhere. The “where to island” subproblem is formulated as a mixed integer linear programming (MILP) model that aims to boost system transient stability by minimizing power flow interruptions in disconnected lines. The model incorporates constraints on generators’ coherency, island connectivity, and node exclusivity. The subsequent layer determines the optimal generation/load actions for each island to prevent system collapse post-separation. Signals from the IoT cloud are relayed to the circuit breakers at the terminals of the optimal cut-set to establish stable isolated islands. Additionally, controllable loads and generation controllers receive signals from the cloud to execute load and/or generation adjustments. The proposed system’s performance is assessed on the IEEE 39-bus system through time-domain simulations on DIgSILENT PowerFactory connected to the ThingSpeak cloud platform. The simulation results demonstrate the effectiveness of the proposed ICI strategy in boosting power system stability.

Innovative Photovoltaic-Aeration Integration: Enhancing Energy Efficiency and Grid Stability in Wastewater Treatment

Abstract This paper presents a detailed investigation into enhancing the energy efficiency of wastewater treatment plants (WWTPs) by integrating photovoltaic (PV) systems, emphasizing power flow analysis and experimental validation. Recognizing the substantial energy demands of aeration processes in WWTPs, this study proposes an innovative integration of PV panels with aeration tanks. This approach generates renewable energy and optimizes energy use through the thermal interaction between the PV panels and the aeration tanks. Key findings demonstrate a 15% overall increase in energy efficiency and a 5% improvement in PV efficiency due to aeration-induced cooling, along with a reduction in voltage fluctuations by up to 30% during high-demand periods. Additionally, the integration offsets approximately 20% of the WWTP's total energy consumption. The research is structured into two main components: a comprehensive power flow study using DIgSILENT PowerFactory and a laboratory experiment to validate the integration's effectiveness. The power flow analysis evaluates the electrical impact of PV integration on the WWTP's power grid, focusing on scenarios such as load fluctuations, grid disturbances, and the synchronization of PV generation with plant energy needs. The simulation results indicate that the integration significantly enhances the stability and efficiency of the plant's electrical system, reducing reliance on traditional energy sources. Concurrently, a laboratory experiment explored the practical effects of integrating PV systems with aeration tanks. The experiment demonstrated that the cooling effect provided by the aeration tanks leads to increased PV efficiency and notable energy savings. These experimental results align with the simulation findings, confirming the efficacy of this integrated approach. This study introduces a novel methodology for integrating renewable energy technologies into industrial processes, showcasing the potential for significant energy savings and improved operational efficiency in WWTPs. Future research will focus on scaling this integration strategy and assessing its long-term impacts on energy efficiency and wastewater treatment effectiveness.

Stealthy FDI attack to maximize load shedding considering voltage sensitivity analysis

Today, the expansion utilization of telecommunication systems results in the power systems having a physical-cyber structure. Despite the advantages of this structure, one of the main challenges is the impact of cyber on physical and vice versa. This study focuses on False Data Injection (FDI) attacks, where the attacker's aim is to overload a transmission line, leading to load shedding. It is proven that the attacker can bypass Bad Data Detection (BDD) module in DC state estimation (DC-SE) by considering both voltage phase angle and magnitude, even when they only know network parameters and can only inject false data in local area. The proposed method is formulated as a bi-level max-min optimization problem where the load shedding is maximized and minimized from the attacker's and operator's perspectives, respectively. To demonstrate the effectiveness of the proposed method, simulations are carried out on IEEE 39 Bus New England System using DIgSILENT PowerFactory 2021 SP2.

An Open-Source Julia Package for RMS Time-Domain Simulations of Power Systems

This paper presents RMSPowerSims.jl, an open-source Julia package for the time-domain simulation of power systems. The package is designed to be used in conjunction with PowerModels.jl, a widely used Julia package for power system optimization. RMSPowerSims.jl provides a framework for the simulation of power systems in the time domain, allowing for the study of transient stability, frequency stability, and other dynamic phenomena. The package is designed to be intuitive and flexible, allowing users to easily define custom models for network components and disturbances, while also providing a range of pre-constructed models for common power system components. RMSPowerSims.jl simplifies the process of performing RMS simulations on power system models developed using the PowerModels.jl ecosystem, and provides an easy-to-use modeling that reduces the barrier to entry for new users wishing to perform RMS simulations. The accuracy of the package is verified against DIgSILENT PowerFactory for short-circuit and load-increase disturbances, using the New England 39-bus system. The active power generation delivered by several generators in the network, and the voltage magnitudes of selected busbars are analyzed and noted to be in close agreement with those obtained using PowerFactory. The computational performance of the package is compared to that of PowerFactory and is found to be comparable for load-step simulations; however, PowerFactory is found to be considerably faster for short-circuit simulations. As computational performance is not a priority at this stage of development, this is expected, and speed optimization is planned for future work. RMSPowerSims.jl is available under an open-source license and can be downloaded from GitHub.

Controller design and optimal sizing of battery energy storage system for frequency regulation in a multi machine power system

Frequency regulation is one of the key components needed to keep the power grid stable and reliable in the case of an imbalance between generation and load. This study looks at several control techniques for Battery Energy Storage Systems (BESSs) to keep the frequency stable in the power system during generation/load disruptions. This research aims to build several BESS controllers, including the proportional-integral (PI), proportional integral derivative (PID), and Tilt-Integral Derivative (TID) controllers. Also, the BESS controller parameters are optimized and compared by using metaheuristics based particle swarm optimization (PSO) and the BAT algorithm. However, for practical power systems with high MVA ratings, the size of the battery energy storage systems has to be increased considerably to offset frequency deviations. Additionally, by utilizing PSO to reduce the frequency deviations within prescribed limits, this work presents the optimal BESS sizing for multimachine power systems. Furthermore, the research study examines the impact of BESS connected to various voltage levels, such as LV, MV, and HV subgrids. It also examines BESS's role in frequency management, which is an area of expertise that needs further investigation and is anticipated to have a big influence on the frequency stability of the system. Time domain simulations are carried out, which shows that the PSO based controller design is capable of stabilizing the system frequency with superior performance as well as the BESS's capability to participate effectively in frequency regulation. Additionally, this paper also implements the experimental verification through Hardware-in-the-Loop (HIL) simulations to validate the performance and robustness of the proposed control system. The WSCC 9-bus test system is used to demonstrate the BESS's efficacy. The system is modelled and simulated using the DIgSILENT PowerFactory software.

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

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

Power Flow Analysis and Steady State Contingency of IEEE 9-bus System Using DigSilent

Power flow analysis and contingency states of a power system are fundamental tests of finding the real performance of an electrical network during power system planning and operation. Maintaining the system’s security is a challenging issue facing power system engineers. The system will be secure if it can run within system restrictions, such as limits of bus voltage magnitudes, current and power flow through the lines. in the case of a component failure, such as a generator or transmission line, contingency analysis is useful for increasing the power system’s resilience by examining the system’s vulnerability in case of components failure. Using an IEEE 9-bus system as benchmark, the analysis of power flow through contingency analysis is performed to identify the most critical component affected by voltage violation and critical loading condition. Using the one-by-one and two-by-two outages of generators and lines using DIgSILENT Power Factory software. The results of the contingency analysis demonstrate how voltage on busbars can be critically affected when the power system is subject to some sort of unconditional phenomena during the operation of the electrical network.

A multi-layer constrained spectral k-embedded clustering methodology approach for intelligent partitioning of power grid to enhance resiliency in transmission networks

The intentional controlled islanding by intelligent partitioning of the power grid is considered as essential to protect the grid from cascading events, faults, and High Impact Low Probability (HILP) events. To enhance the resilience, stability, and security of the power grid, the proposed model in this paper intentionally divides the affected power network into islands. This paper presents an intelligent partitioning approach to create an islanding solution through multilayer graphs using spectral clustering. The controlled islanding algorithm uses a multi-criteria objective function that considers the correlation coefficients among the frequency of the buses and minimal disturbances in the real and reactive power. The proposed control technique is implemented in two phases. The first phase employs correlation coefficients between frequency of the buses and modularity clustering to identify clusters of coherent buses. During the second stage, all nodes are categorised into groups using Multi-level constrained Spectral Clustering (ML-CSC) to determine the solution for Intentional controlled Islanding that satisfies bus coherency with the minimum level of disruptions to real and reactive power flows across the boundaries. The proposed algorithm for resolving the generator coherency issue and an intelligent islanding solution is demonstrated by simulation experiments conducted on an IEEE 39-bus transmission test system developed in DIGSILENT Powerfactory version 2023. The MATLAB version R2023a is used to construct the ML-CSC control method. The results demonstrated that the proposed ML-CSC algorithm substantially impacts the functioning of the power system, enabling the formation of intelligent islanding during abnormal conditions. Also, the results clearly show that instead of using single-layer spectral clustering, the multi-layer spectral clustering yields a better intentional islanding solution with minimum power flow mismatch which enhances the transient stability of the islands.

Real-Time Simulation and Hardware-in-the-Loop Testing Based on OPAL-RT ePHASORSIM: A Review of Recent Advances and a Simple Validation in EV Charging Management Systems

Phasor-domain (RMS) simulations have become increasingly vital in modern power system analysis, particularly as the complexity and scale of these systems have expanded with the integration of renewable energy sources. ePHASORSIM, an advanced phasor-based simulation tool developed by OPAL-RT, plays a crucial role in this context by enabling real-time phasor-domain simulation and hardware-in-the-loop testing. To keep pace with these evolving needs, continuous efforts are being made to further improve the accuracy, efficiency, and reliability of ePHASORSIM-based simulations. These efforts include automating model conversion processes for enhanced integration with ePHASORSIM, extending ePHASORSIM’s simulation range with custom models, developing hybrid co-simulation techniques involving ePHASORSIM and an EMT simulator, enhancing simulation scalability, and refining HIL testing to achieve more precise validation of control and protection systems. This paper provides a comprehensive review of these recent advances. Additionally, the paper discusses the conversion of models from PowerFactory—a widely used and comprehensive modeling environment—to ePHASORSIM through both automated tools and manual methods using Excel workbooks, which has been discussed little in the literature. Furthermore, as ePHASORSIM is a relatively new tool with limited cross-validation studies, the paper aims to contribute to this area by presenting a comparative validation against DIgSILENT PowerFactory, with a specific emphasis on its application in electric vehicle charging management systems.

Influence of increasing Integration of Solar photovoltaic on Small Signal and Transient stability of Nigeria Power System

Abstract In this paper, the effect of Solar Photovoltaic (SPV) penetration on the damping of critical and inter area modes arising from different penetration level of SPV into the Nigeria national grid has been studied. Also, the possible effects of SPV penetration on Critical Clearing Time (CCT) when a three-phase fault occurs on the grid are studied. The Nigeria 56-bus system was used for the investigation. Sensitivity analyses are carried out to obtain insight into how certain change in parameters affects both the transient and small signal stabilities of the Nigerian power systems. DigSILENT Power Factory was used for the simulation while the analysis was performed in MATLAB. Some of the important findings show that the grid developed increasing amplitude of oscillation from 20 % SPV penetration. There is no steady increase or decrease of CCT with penetration levels. The effect of changes in load on small signal conducted shows that both the real and imaginary load at Kano and Birnin kebbi bus should not exceed 257 MW, 176 MVAR and 171 MW, 134 MVAR, respectively so as to avoid system collapse.

Performance Evaluation of Distance Relay Operation in Distribution Systems with Integrated Distributed Energy Resources

This article presents the evaluation of the performance of the distance relay (ANSI function 21) when integrating Distributed Energy Resources (DERs) in a Local Distribution System (LDS). The aim is to understand the impacts of and the necessary modifications required in the operation of distance relays, considering different levels of DER aggregation, and identifying any threshold levels before issues arise. To achieve this, first, a comprehensive review was carried out to analyze the impacts generated in the protection systems. Second, by using the DigSilent Power Factory software, the implementation of the distance relay using a IEEE 13 Node Test Feeder was validated. The aggregation of the three fundamental types of DG, synchronous machines, solar panels, and wind turbines, was evaluated. The threshold at which distributed generation power injection begins to compromise distance protection performance was identified. This study compares the outcomes of using mho and quadrilateral protection schemes.

Aggregator control of battery energy storage in wind power stations to maximize availability of regulation service

Battery energy storage systems can produce very fast bi-directional power flows, which makes them suitable for providing wind power regulation and frequency control services. Though battery systems can provide fast regulation services, their energy storage capacities are quite low in comparison to other generation sources, so regulation responses from them should be optimized to maximize availability of service. This paper proposes an aggregator that optimizes frequency control responses from battery energy storage systems to maximize service availability. The frequency control response from the aggregated system is defined by a single frequency-droop characteristic. This provides the predictability of response required to comply with grid codes and allows the aggregated system to participate in frequency control markets as a single entity. The method of implementation is fail-safe as failure to receive an optimized order from the aggregator does not prevent the battery energy storage systems from responding to frequency events. This mitigates stability concerns relating to communication delays between the aggregator and battery energy storage systems. Battery systems that provide multiple functions, such as frequency control system services and wind power regulation, can participate in the aggregator scheme by assigning a proportion of the battery’s capacity to the aggregator scheme. Simulations performed in DIgSILENT PowerFactory show that the aggregator successfully extends the duration of full regulation service from the battery systems during frequency excursion events.

Optimal utilization of frequency ancillary services in modern power systems

The widespread global adoption of wind energy sources has established a significant presence in the existing power grid. However, the massive integration of intermittent wind energy poses forecasting errors, prompting the need for supplementary reserves from conventional energy sources with increased operational expenses and carbon emissions. Hence, to facilitate the seamless operation of large-scale wind-integrated power grids, it is imperative to harness the potential of renewable energy sources and leverage flexible loads to deliver power-balancing services. In this research, dynamic real-time power dispatch strategies have been developed for the Automatic Generation Control (AGC) system to integrate the reserve capacities of conventional generation units and wind power plants and utilize the demand response capabilities of flexible loads for power balancing services. A comprehensive power system grid model was developed in DigSilent PowerFactory software, consisting of coal-based energy systems, wind energy systems, gas turbines, and cold storage units as flexible loads. The study is divided into different case studies to assess the impact of each scenario on system operation in mitigating the forecasting errors of wind power plants. Further, a comparative analysis was performed to illustrate the effectiveness of each case study. The analysis showed that Case Study III, where reserves are provided by coal energy systems and cold storage units, yielded the highest reduction in Positive Regulation (PR) and Negative Regulation (NR) errors, at 89.0% and 94.15%, respectively. Conversely, Case Study IV demonstrated the least reduction in errors, with 67.82% in PR and 78.41% in NR. However, it indicates that reserves can be supplied from wind energy systems and flexible loads without the support of conventional power plants.

Analysis of hybrid AC/DC transmission system: A Turkey case study

AbstractThe need to transmit energy in the most effective way arises in parallel with the demand for energy in developing countries. As the amount of transmitted power increases, transmission lines can become overloaded, causing a blackout. This study aims to increase the transmission capacity without experiencing right‐of‐way problems by converting Turkey's existing high voltage AC systems to hybrid AC/DC systems. With such a design, it is aimed at providing more efficient and continuous transmission by using the high‐voltage DC system's low‐loss feature at long distances. Using the 400 kV double circuit line structure, the existing electricity transmission system is modelled using real data in the DigSILENT PowerFactory. The electromagnetic fields that will occur due to the use of AC and DC circuits on the same tower in such a transformation situation are analysed with FEMM 4.2, based on the finite element method. The compliance of the electromagnetic fields that will occur with the use of hybrid 400 kV AC and 500 kV DC was determined in the study. In addition, according to the simulation results, it is predicted that in the case of hybrid AC/DC transmission, the current transmission capacity would increase and the losses would decrease.

Eval_uasi Pemasangan LBSM Loopring untuk Menurunkan SAIDI pada Penyulang PKR 16 dan Riyal di Wilayah Kerja ULP Pulung Kencana

The reliability and continuity of electric power supply are heavily reliant on the maneuverability of existing feeders. To enhance this capability, the installation of LBSM (Load Break Switch Motorized) devices is essential for feeders lacking the ability to maneuver to alternative feeders. This LBSM installation will be implement on the Riyal and PKR 16 feeders at ULP Pulung Kencana. The Riyal feeder receives power from the Mesuji Substation, while the PKR 16 feeder is supplied by the Pakuon Ratu Substation. Both feeders currently lack switches for maneuvering in the event of disturbances or maintenance, which significantly contributes to high SAIDI (System Average Interruption Duration Index) rates. To determine the optimal installation points for the LBSM, a thorough analysis was conducted, prioritizing the closest proximity between the two feeders and incorporating topologic calculations using the Digsilent PowerFactory 15.1 software. This approach ensures optimal performance of the distribution network. The installation of the LBSM loopring is anticipated to significantly improve network maneuverability, thereby reducing the SAIDI rates at ULP Pulung Kencana.

Optimal allocation of distributed energy resources to cater the stochastic E-vehicle loading and natural disruption in low voltage distribution grid

The everyday extreme uncertainties become the new normal for our world. Critical infrastructures like electrical power grid and transportation systems are in dire need of adaptability to dynamic changes. Moreover, stringent policies and strategies towards zero carbon emission require the heavy influx of renewable energy sources (RES) and adoption of electric transportation systems. In addition, the world has seen an increased frequency of extreme natural disasters. These events adversely impact the electrical grid, specifically the less hardened distribution grid. Hence, a resilient electrical network is the demand of the future to fulfill critical loads and charging of emergency electrical vehicles (EV). Therefore, this paper proposes a two-dimensional methodology in planning and operational phase for a resilient electric distribution grid. Initially stochastic modelling of EV load has been performed duly considering the geographical feature and commute pattern to form probability distribution functions. Thenceforth, the impact assessment of extreme natural events like earthquakes using damage state classification has been done to model the impact on distribution grid. The efficacy of the proposed methodology has been tested by simulating an urban Indian distribution grid with mapped EV on DigSILENT PowerFactory integrated with supervised learning tools on Python. Subsequently 24-h load profile before event and after event have been compared to analyze the impact.

Two-Area Automatic Generation Control for Power Systems with Highly Penetrating Renewable Energy Sources

Currently, renewable energy sources (RESs) are gradually replacing traditional power sources that use fossil fuels. In some countries, such as Vietnam, RESs are developed on a massive scale and are concentrated in some key areas. This causes negative impacts on a power system when its transmission system is not deployed synchronously to release their capacity from these new renewable energy plants. An important challenge today is to ensure frequency stability in power systems with high uncertainty in RES output power. Additionally, the system requires solutions to prevent transmission line overloads during periods when RESs make a substantial contribution to the electricity generation capacity. Therefore, this paper builds an automatic generation control (AGC) system for a two-area power system with high penetration of RESs. This AGC system model aims to maintain system frequency stability amid unpredictable changes in RESs while also ensuring that tie-lines transmit the predetermined power levels to mitigate frequent congestion. By continuously monitoring and adjusting the system’s frequency, the challenges posed by the inherent variability of RESs can be effectively mitigated. The AGC model is simulated on DIgSILENT PowerFactory software and tested with a 106-bus system. The simulation results of this study show that the AGC system operates effectively, ensuring that the frequency returns to the rated value and maintaining the exchange capacity on the tie-lines after occurrences of RES power decrease events.