Power Flow Analysis Research Articles

Line-parameter identification of medium-voltage distribution systems based on deep deterministic policy gradients

Accurate line-parameter identification is an important foundation for refined the regulation, protection, and control of distribution systems. Traditional identification models provide accurate modeling, while conventional identification approaches are hindered by the high complexity and low observability of power systems. In this article, a parameter identification method based on the deep deterministic policy gradient is proposed for medium voltage distribution systems. The proposed method starts with objective function constructing, followed by power flow analysis and parameter identification modeling, where the L2 normalization theory is introduced to improve the computation efficiency. On this basis, the parameter identification framework is constructed through designing the Markov decision process of a parameter and using a training mechanism. An adaptive parameter correction method is proposed to improve the accuracy and efficiency of a deep-reinforcement-learning-based agent. The performance of the proposed modal is tested on IEEE 14-node and IEEE 33-node medium-voltage distribution systems. Case simulation results demonstrate that the proposed modal exhibits superior computational capability, while achieving fewer errors compared to traditional methods.

An Optimized Strategy for the Integration of Photovoltaic Systems and Electric Vehicles into the Real Distribution Grid

The increasing spread of photovoltaic systems for private households (PVs) and electric vehicles (EVs) in order to reduce carbon emissions significantly impacts operation conditions in existing distribution networks. Variable and unpredictable PVs can stress distribution network operation, mainly manifested in voltage violations during the day. On the other hand, variable loads such as EV chargers which have battery storage in their configuration have the ability of storying a surplus energy and, if it is necessary, support a distribution network with energy, commonly known as vehicle-to-grid concept (V2G), to help voltage stability network enhancement. This paper proposes an optimal power flow (OPF)-based model for EV charging to minimize power exchange between the superior-10 kV grid and the observed distribution feeder. The optimization procedure is realized using the co-simulation approach that connects power flow analysis software and optimization method. Three different scenarios are observed and analysed. The first scenario is referred to as a base case without optimization. The second and third scenarios include optimal EV charging and discharging patterns under different constraints. To test the optimization model, a 90-bus unbalanced distribution feeder modelled based on real-life examples is used. The obtained results suggest that this optimization model does not only significantly reduce the power exchange between an external network and the distribution feeder but also improves voltage stability and demand curve in the distribution feeder.

Multi-Objective Optimal Power Flow Analysis Incorporating Renewable Energy Sources and FACTS Devices Using Non-Dominated Sorting Kepler Optimization Algorithm

In the rapidly evolving landscape of electrical power systems, optimal power flow (OPF) has become a key factor for efficient energy management, especially with the expanding integration of renewable energy sources (RESs) and Flexible AC Transmission System (FACTS) devices. These elements introduce significant challenges in managing OPF in power grids. Their inherent variability and complexity demand advanced optimization methods to determine the optimal settings that maintain efficient and stable power system operation. This paper introduces a multi-objective version of the Kepler optimization algorithm (KOA) based on the non-dominated sorting (NS) principle referred to as NSKOA to deal with the optimal power flow (OPF) optimization in the IEEE 57-bus power system. The methodology incorporates RES integration alongside multiple types of FACTS devices. The model offers flexibility in determining the size and optimal location of the static var compensator (SVC) and thyristor-controlled series capacitor (TCSC), considering the associated investment costs. Further enhancements were observed when combining the integration of FACTS devices and RESs to the network, achieving a reduction of 6.49% of power production cost and 1.31% from the total cost when considering their investment cost. Moreover, there is a reduction of 9.05% in real power losses (RPLs) and 69.5% in voltage deviations (TVD), while enhancing the voltage stability index (VSI) by approximately 26.80%. In addition to network performance improvement, emissions are reduced by 22.76%. Through extensive simulations and comparative analyses, the findings illustrate that the proposed approach effectively enhances system performance across a variety of operational conditions. The results underscore the significance of employing advanced techniques in modern power systems enhance overall grid resilience and stability.

Physics-Informed Fully Convolutional Network-Based Power Flow Analysis for Multi-Terminal MVDC Distribution Systems

Physics-Informed Fully Convolutional Network-Based Power Flow Analysis for Multi-Terminal MVDC Distribution Systems

Holistic analysis of the dynamic stability of the Southern Cameroon Interconnected grid in contingency situations

The Southern Cameroon Interconnected Network (SIG) is depicted as a large-scale power system that has shown significant instability due to a series of blackouts in recent years. These blackouts are primarily attributed to major disruptions in transmission lines and energy deficits between supply and demand. The imbalance between power supply and demand necessitates the grid to operate near its stability limits, increasing the risk of blackouts. The necessity of investigating the dynamics of SIG behavior in response to observed contingency situations serves as the primary motivation for this study. To achieve this objective, the SIG was modeled using saturated generators with ZIP static loads. Through Newton-Raphson based power flow calculations, voltage magnitude profiles of the grid were obtained for each generation scenario. An N-1 contingency consisting of a standard Newton-based continuation power flow (CPF) analysis has identified line 5–6 as the most frequent worst case of line outage. Additionally, a short-term transient analysis was conducted under three-phase short-circuit, line outage and generator outage scenarios. In the event of a short-circuit, the Mangombe-225 bus experienced the most significant impact. Concerning line outages, line 1–5 had the most adverse effect on the grid's frequency stability. However, generation outages had a lesser impact on frequency stability compared to other disturbances. Lastly, modal analysis revealed that the grid exhibited weak stability with a critical mode identified at a frequency of 4.0267 Hz, exceeding typical values. This underscores the necessity of damping the grid oscillations for enhanced stability.

Power Flow Analysis in Unbalanced Three-Phase Distribution Systems using Backward/Forward Sweep and Current Injection Methods

The electrical power distribution system is a part of the power system that distributes electricity from the transmission network to customers. In the distribution system, imbalances often occur due to the varying load profiles in each phase. This can cause voltage imbalances in the distribution system. This study aims to compare two power flow analysis methods, Backward/Forward Sweep and Current Injection. The study analyses the voltage and power loss conditions on each phase at each bus and line in the three-phase distribution system under unbalanced conditions. Simulations were conducted on two IEEE test buses, IEEE 19-Bus and IEEE 33-Bus with radial configurations. The power flow calculation results using the Backward and Forward Sweep method showed that in the IEEE 19-Bus system, the highest voltage drop percentage occurred on phase b at bus 19, at 3.14%, the highest voltage imbalance percentage occurred at bus 19, at 0.1409%, and the total active and reactive power losses were 7.352 kW and 3.164 kVAR. In the IEEE 33-Bus system, the highest voltage drop percentage occurred on phase c at bus 18, at 5.85%, the highest imbalance percentage occurred at bus 15, at 0.2077%, and the total active and reactive power losses were 19.107 kW and 8.22 kVAR. The percentage difference between the two methods used is less than one percent, indicating that both methods are sufficiently accurate in analyzing power flow in an unbalanced distribution system.

Power Loss Minimization and Voltage Profile Improvement on Nigeria Distribution Network Using Whale Optimization Algorithm

The power grid has significant power losses, unstable voltage, and large voltage drops during high demand due to its high resistance. One way to reduce power loss is by strategically placing and sizing Distributed Generation (DG) within the distribution network. However, improper installation of DG can increase power loss. To address this issue, various optimization techniques have been used, but finding the best solution and dealing with complex issues has been challenging. It is important to make efforts to optimally place and size DG in the distribution network to minimize power loss. To this end, a research study aimed to minimize power loss and improve the voltage profile on the DG network using the Whale Optimization Algorithm (WOA) was done. Objective functions were formulated and integrated into WOA, and power flow analysis on the standard IEEE 33-bus and 33-bus Ilorin industrial distribution feeder with and without DG was conducted using the forward and backward sweep distribution load flow algorithm. The optimal size and location of DG for power network loss reduction using sensitivity analysis (SA) and the whale optimization algorithm were determined. The results of the power flow analysis indicated that the total active losses and reactive power losses were reduced to varying extents with the integration of DG using both SA and WOA. The validation results showed that WOA is more efficient and provides high-quality solutions in terms of system loss reduction and best placement for DG in power systems compared to the application of SA. Additionally, WOA was found to offer accurate and high-quality solutions for power loss reduction compared to other existing techniques such as Loss Sensitivity Analysis (LSA), Grey Wolf Optimizer (GWO), Adaptive Shuffled Frogs Leaping Algorithm (ASFLA), and One Rank Cuckoo Search Algorithm (ORCSA). Keywords: Optimization, Distributed Generation (DG), Whale Optimization Algorithm (WOA), Sensitivity Analysis (SA)

Power flow analysis and volt/var control strategy of the active distribution network based on data-driven method

In order to solve the problems of low power flow calculation accuracy and voltage overcrossing of the distribution network caused by large-scale distributed power supply, a data-driven power flow analysis and volt/var optimization control strategy for distribution network are proposed in this paper. Firstly, a data-driven power flow analysis model for the distribution network is proposed, and the nonlinear mapping relationship between the distribution network state and power flow results is described from the data-driven perspective. Secondly, the paper analyzes the influence of photovoltaic power supply on the voltage of the distribution network, and establishes the volt/var optimization model based on photovoltaic power supply. Then, on the basis of data-driven power flow analysis of the distribution network, the distribution network reactive voltage optimization strategy based on data-driven power flow analysis is proposed to ensure the safe and stable operation of distribution network voltage, reduce the operating network loss of distribution network, and realize the distribution network reactive voltage optimization is not affected by factors such as distribution network line parameters. Finally, IEEE 33 node power distribution system is used to verify the effectiveness of the proposed strategy.

Optimal EV Charging and PV Siting in Prosumers towards Loss Reduction and Voltage Profile Improvement in Distribution Networks

In this paper, the problem of simultaneous charging of Electrical Vehicles (EVs) in distribution networks (DNs) is examined in order to depict congestion issues, increased power losses, and voltage constraint violations. To this end, this paper proposes an optimal EV charging schedule in order to allocate the charging of EVs in non-overlapping time slots, aiming to avoid overloading conditions that could stress the DN operation. The problem is structured as a linear optimization problem in GAMS, and the linear Distflow is utilized for the power flow analysis required. The proposed approach is compared to the one where EV charging is not optimally scheduled and each EV is expected to start charging upon its arrival at the residential charging spot. Moreover, the analysis is extended to examine the optimal siting of small-sized residential Photovoltaic (PV) systems in order to provide further relief to the DN. A mixed-integer quadratic optimization model was formed to integrate the PV siting into the optimization problem as an additional optimization variable and is compared to a heuristic-based approach for determining the sites for PV installation. The proposed methodology has been applied in a typical low-voltage (LV) DN as a case study, including real power demand data for the residences and technical characteristics for the EVs. The results indicate that both the DN power losses and the voltage profile are further improved in regard to the heuristic-based approach, and the simultaneously scheduled penetration of EVs and PVs could yield up to a 66.3% power loss reduction.

Power flow analysis using quantum and digital annealers: a discrete combinatorial optimization approach

Power flow (PF) analysis is a foundational computational method to study the flow of power in an electrical network. This analysis involves solving a set of non-linear and non-convex differential-algebraic equations. State-of-the-art solvers for PF analysis, therefore, face challenges with scalability and convergence, specifically for large-scale and/or ill-conditioned cases characterized by high penetration of renewable energy sources, among others. The adiabatic quantum computing paradigm has been proven to efficiently find solutions for combinatorial problems in the noisy intermediate-scale quantum (NISQ) era, and it can potentially address the limitations posed by state-of-the-art PF solvers. For the first time, we propose a novel adiabatic quantum computing approach for efficient PF analysis. Our key contributions are (i) a combinatorial PF algorithm and a modified version that aligns with the principles of PF analysis, termed the adiabatic quantum PF algorithm (AQPF), both of which use Quadratic Unconstrained Binary Optimization (QUBO) and Ising model formulations; (ii) a scalability study of the AQPF algorithm; and (iii) an extension of the AQPF algorithm to handle larger problem sizes using a partitioned approach. Numerical experiments are conducted using different test system sizes on D-Wave’s Advantage™ quantum annealer, Fujitsu’s digital annealer V3, D-Wave’s quantum-classical hybrid annealer, and two simulated annealers running on classical computer hardware. The reported results demonstrate the effectiveness and high accuracy of the proposed AQPF algorithm and its potential to speed up the PF analysis process while handling ill-conditioned cases using quantum and quantum-inspired algorithms.

Circulating Active Power Flow Analysis in a Hybrid Transformer With the Series Converter Connected to the Primary Side

Circulating Active Power Flow Analysis in a Hybrid Transformer With the Series Converter Connected to the Primary Side

A support vector regression-based interval power flow prediction method for distribution networks with DGs integration

In distribution networks with distributed generators (DGs), power generation and load demand exhibit increased randomness and volatility, and the line parameters also suffer more frequent fluctuations, which may result in significant state shifts. Existing model-driven methods face challenges in efficiently solving uncertain power flow, especially as the size of the system increases, making it difficult to meet the demand for rapid power flow analysis. To address these issues, this paper proposes an SVR-based interval power flow (IPF) prediction method for distribution networks with DGs integration. The method utilizes intervals to describe system uncertainty and employs Support Vector Regression (SVR) for model training. The input feature vector consists of the intervals of active power generation, load demand, and line parameters, while the output feature vector represents the intervals of voltage or line transmission power. Ultimately, the SVR-based IPF prediction model is established, capturing the linear mapping relationship between input data and output IPF variables. Simulation results demonstrate that the proposed method exhibits high prediction accuracy, strong adaptability, and optimal computation efficiency, meeting the requirements for rapid and real-time power flow analysis while considering the uncertainty in distribution networks with DGs integration.

Analysis of Reactive Power Flow in an Electric Power System

Optimal power flow analysis is a calculation to minimize an objective function, namely generation costs or transmission losses by regulating the active power and reactive power generation of each interconnected power system generator by taking into account certain limits. The growth of industrial loads which are dominated by inductive loads requires a fairly large reactive power supply. This reactive power requirement will of course reduce the available power that can be transmitted to the load. Reactive power flow in transmission lines will reduce the active power distribution capacity required by the load. Reactive power flow that is too large can also cause losses. However, this reactive power is also an important component in the stability of the electric power system. For this reason, the flow of active and reactive power in transmission lines needs to be regulated so that the capacity and stability of the electric power transmission system is maintained.

Power flow and harmonics analysis of wind turbine integration into distribution networks

Power flow and harmonics analysis of wind turbine integration into distribution networks

Energy dissipation and power flow analysis based on acoustic black hole laminated beams

To enhance the understanding of the dynamic performance of composite beams, assessing their energy accumulation and dissipation capabilities is crucial. The purpose of this paper is to establish a dynamic analysis model of acoustic black hole (ABH) laminated beams based on the Timoshenko beam theory and isogeometric method and to analyze structural intensity and power flow. The vibration governing equation for the ABH laminated beam is derived by calculating its potential and kinetic energy. The convergence of the results is confirmed through multiple mesh refinements, while the model's accuracy and applicability are substantiated through comparisons with the literature, traditional finite element simulations, and experimental data. This investigation into the power flow and structural intensity under varying parameter conditions elucidates the energy transfer mechanisms within ABH laminated beams, offering valuable insights for the deployment of ABH technologies in practical engineering applications.

Analysis of dynamic modeling and power flow of ABH laminated composite thin beam with elastic boundaries

To investigate the energy distribution characteristics of a laminated structure with an acoustic black hole (ABH), this study introduces the dynamic modeling and power flow analysis of an ABH laminated thin beam (ABH laminated beam) with elastic boundary conditions for the first time. ABH profile is defined by a power function in the dynamic modeling process. Utilizing the Euler-Bernoulli beam theory, the constitutive equation of ABH laminated beams is formulated by using the isogeometric method. Three sets of artificial springs are employed to replicate the elastic boundary conditions, incorporating the potential energy of the springs. Subsequently, the dynamic model of the ABH laminated beam is developed by solving the Lagrange equation concerning the total energy within the uniform region, ABH region, and boundary. Through numerical examples, the convergence and accuracy of the proposed modeling approach are validated by comparing the results with those obtained from COMSOL Multiphysics and experimental data. The analysis of power flow and structural intensity elucidates the energy propagation behavior in ABH laminated beams and the underlying mechanism of the ABH effect. The results demonstrate that the ABH laminated beam displays remarkable absorption and dissipation characteristics, introducing a new perspective for the design and application of ABH structures.

Continuous Power Flow Analysis in the Trigonometric Circle

Continuous Power Flow Analysis in the Trigonometric Circle

Features of planning and managing power flows in distribution grids of megalopolises

The study examines the root causes of disruptions of normal operation of power distribution grids in large cities and metropolitan areas. The existing principles of scheduling and maintaining power flows in power distribution grids as well as ways of ensuring the reliability of their operation are analyzed. The integration of fuel-fired distributed generation facilities and renewable generation plants into distribution networks is shown to affect the ability to ensure transient stability during emergency disturbances. We establish evaluation criteria and provide upward margin values to determine the feasibility of the planned power flows. The study reveals general patterns in the calculation of the upward margin for power distribution grids of large cities and metropolitan areas. Test power flow analysis is performed for a real-world segment of a metropolitan area power distribution grid to identify possible overloads of power grid equipment and develop and implement a list of measures for the power flow to achieve the feasible region. The developed approach makes it possible to minimize load shedding or rule out load shedding altogether, ensuring reliable power supply to consumers in large cities and metropolitan areas in the event of an unexpected load growth.

Evaluation Method for Voltage Regulation Range of Medium-Voltage Substations Based on OLTC Pre-Dispatch

A new energy industry represented by photovoltaic and wind power has been developing rapidly in recent years, and its randomness and volatility will impact the stable operation of the power system. At present, it is proposed to enrich the regulation of the power grid by tapping the regulation potential of load-side resources. This paper evaluates the overall voltage regulation capability of substations under the premise of considering the impact on network voltage security and providing a theoretical basis for the participation of load-side resources of distribution networks in the regulation of the power grid. This paper proposes a Zbus linear power flow model based on Fixed-Point Power Iteration (FFPI) to enhance power flow analysis efficiency and resolve voltage sensitivity expression. Establishing the linear relationship between the voltages of PQ nodes, the voltage of the reference node, and the load power, this paper clarifies the impact of reactive power compensation devices and OLTC (on-load tap changer) tap changes on the voltages of various nodes along the feeder. It provides theoretical support for evaluating the voltage regulation range for substations. The day-ahead focus is on minimizing network losses by pre-optimizing OLTC tap positions, calculating the substation voltage regulation boundaries within the day, and simultaneously optimizing the total reactive power compensation across the entire network. By analyzing the calculated examples, it was found that a pre-scheduled OLTC (on-load tap changer) can effectively reduce network losses in the distribution grid. Compared with traditional methods, the voltage regulation range assessment method proposed in this paper can optimize the adjustment of reactive power compensation devices while ensuring the voltage safety of all nodes in the network.

Studi Aliran Daya pada PT. PLN (Persero) UIWS2JB UP3 Jambi ULP Kotabaru Penyulang Palem dengan Menggunakan Software Electric Transient and Analysis Program (ETAP)

Planning in the use of components in a power system needs to be done correctly. The planning will affect the optimization of the system in distributing power. Suboptimal power distribution will have an impact on the continuity of the power being distributed. The analysis that will be carried out is a power flow analysis. This research was taken using data from ULP Kota Baru Penyulang Palem, the location of this research is located in the distribution system area of Jambi City, Jambi Province, with the connection center at Penyulang Palem which is located in Kota Baru District, Jambi City, Jambi Province. . KVA is used to measure the total power in an electrical system. Total power includes active power and reactive power, so KVA provides a more complete picture of the power requirements of an electrical system. In the KVA measurement, it is assumed that all loads connected on a single line are 85%, 90%, 95%. That the greater the assumed load of the transformer and the farther away from the source, the greater the voltage drop / the smaller the voltage The greater the resistance the smaller the voltage drop, if the smaller the resistance then the drop will be larger. The wider the cross-section, the smaller the strain drop. The highest measurement of all loads is 3918 kv at the base of the source located near the bus in JB1100 assuming all loads of 95%.