scholarly journals A Quasi-Oppositional Heap-Based Optimization Technique for Power Flow Analysis by Considering Large Scale Photovoltaic Generator

Energies ◽  
2021 ◽  
Vol 14 (17) ◽  
pp. 5382
Author(s):  
Vedik Basetti ◽  
Shriram S. Rangarajan ◽  
Chandan Kumar Shiva ◽  
Sumit Verma ◽  
Randolph E. Collins ◽  
...  
Keyword(s):  
Power Systems ◽  
Power Flow ◽  
Large Scale ◽  
Renewable Energy Sources ◽  
Optimization Technique ◽  
Flow Analysis ◽  
Computation Time ◽  
Load Flow ◽  
Critical Conditions ◽  
The Impact

Load flow analysis is an essential tool for the reliable planning and operation of interconnected power systems. The constant increase in power demand, apart from the increased intermittency in power generation due to renewable energy sources without proportionate augmentation in transmission system infrastructure, has driven the power systems to function nearer to their limits. Though the power flow (PF) solution may exist in such circumstances, the traditional Newton–Raphson based PF techniques may fail due to computational difficulties owing to the singularity of the Jacobian Matrix during critical conditions and faces difficulties in solving ill-conditioned systems. To address these problems and to assess the impact of large-scale photovoltaic generator (PVG) integration in power systems on power flow studies, a derivative-free quasi-oppositional heap-based optimization (HBO) (QOHBO) technique is proposed in the present paper. In the proposed approach, the concept of quasi-oppositional learning is applied to HBO to enhance the convergence speed. The efficacy and effectiveness of the proposed QOHBO-PF technique are verified by applying it to the standard IEEE and ill-conditioned systems. The robustness of the algorithm is validated under the maximum loadability limits and high R/X ratios, comparing the results with other well-known methods suggested in the literature. The results thus obtained show that the proposed QOHBO-PF technique has less computation time, further enhancement of reliability in the presence of PVG, and has the ability to provide multiple PF solutions that can be utilized for voltage stability analysis.

Integrated Power Flow Analysis with Large-scale Solar Photovoltaic Power Systems Employing N-R Method

2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Girisha H Navada ◽  
K. N. Shubhanga
Keyword(s):  
Power Systems ◽  
Power System ◽  
Power Flow ◽  
Large Scale ◽  
Control Strategies ◽  
Linear Equations ◽  
Flow Analysis ◽  
Load Flow ◽  
Flow Equations ◽  
Single Machine Infinite Bus

Abstract A method is proposed to modify the conventional load flow programme to accommodate large-scale Solar PhotoVoltaics (SPV) power plant with series power specifications. The programme facilitates easy handling of any number of SPV systems with standard control strategies such as pf-control and voltage-control, considering solar inverter’s power constraints. In this method, the non-linear equations related to SPV systems, located at multiple locations, are solved with the main load flow equations in an integrated fashion, considerably reducing the implementation task. This task is achieved by augmenting the inverter buses to the existing power system network in such a way that the changes required in the conventional programme are minimal. To show the effectiveness of the proposed method, it is compared with the alternate-iteration method popularly followed in the literature. The workability of the proposed method has been demonstrated by using a Single Machine Infinite Bus (SMIB) system and the IEEE14-bus power system with SPV systems. Various test cases pertaining to meteorological variables and control strategies are also presented.

scholarly journals Probabilistic Power Flow Methodology for Large-Scale Power Systems Incorporating Renewable Energy Sources

Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2624 ◽  
Author(s):  
Van Huynh ◽  
Van Ngo ◽  
Dinh Le ◽  
Nhi Nguyen
Keyword(s):  
Power Systems ◽  
Power Flow ◽  
Large Scale ◽  
Clustering Algorithm ◽  
Renewable Energy Sources ◽  
Computation Time ◽  
Principal Component ◽  
Test System ◽  
Clustering Technique ◽  
Probabilistic Power Flow

In this paper, we propose a new scheme for probabilistic power flow in networks with renewable power generation by making use of a data clustering technique. The proposed clustering technique is based on the combination of Principal Component Analysis and Differential Evolution clustering algorithm to deal with input random variables in probabilistic power flow. Extensive testing on the modified IEEE-118 bus test system shows good performance of the proposed approach in terms of significant reduction of computation time compared to the traditional Monte Carlo simulation, while maintaining an appropriate level of accuracy.

scholarly journals Predicting AC Optimal Power Flows: Combining Deep Learning and Lagrangian Dual Methods

2020 ◽  
Vol 34 (01) ◽  
pp. 630-637 ◽  
Author(s):  
Ferdinando Fioretto ◽  
Terrence W.K. Mak ◽  
Pascal Van Hentenryck
Keyword(s):  
Deep Learning ◽  
Power Systems ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Large Scale ◽  
Renewable Energy Sources ◽  
Electrical Power ◽  
Practical Applications ◽  
Fundamental Building Block ◽  
Optimal Power

The Optimal Power Flow (OPF) problem is a fundamental building block for the optimization of electrical power systems. It is nonlinear and nonconvex and computes the generator setpoints for power and voltage, given a set of load demands. It is often solved repeatedly under various conditions, either in real-time or in large-scale studies. This need is further exacerbated by the increasing stochasticity of power systems due to renewable energy sources in front and behind the meter. To address these challenges, this paper presents a deep learning approach to the OPF. The learning model exploits the information available in the similar states of the system (which is commonly available in practical applications), as well as a dual Lagrangian method to satisfy the physical and engineering constraints present in the OPF. The proposed model is evaluated on a large collection of realistic medium-sized power systems. The experimental results show that its predictions are highly accurate with average errors as low as 0.2%. Additionally, the proposed approach is shown to improve the accuracy of the widely adopted linear DC approximation by at least two orders of magnitude.

Power Flow Investigation Using Cubic Spline Function a Case Study

2018 ◽  
Vol 7 (4) ◽  
pp. 1-16 ◽  
Author(s):  
Shabbiruddin ◽  
Karma Sonam Sherpa ◽  
Sandeep Chakravorty ◽  
Amitava Ray
Keyword(s):  
Power Systems ◽  
Power Flow ◽  
Spline Function ◽  
Electrical Power ◽  
Flow Analysis ◽  
Cubic Spline ◽  
Load Flow ◽  
Electrical Power Systems ◽  
Flow Investigation ◽  
Cubic Spline Function

This article presents an approach using cubic spline function to study Load Flow with a view to acquiring a reliable convergence in the Bus System. The solution of the power flow is one of the extreme problems in Electrical Power Systems. The prime objective of power flow analysis is to find the magnitude and phase angle of voltage at each bus. Conventional methods for solving the load flow problems are iterative in nature, and are computed using the Newton-Raphson, Gauss-Seidel and Fast Decoupled method. To build this method, this paper used cubic spline function. This approach can be considered as a ‘two stage' iterative method. To accredit the proposed method load flow study is carried out in IEEE-30 bus systems.

scholarly journals Exploiting Coarse-Grained Parallelism Using Cloud Computing in Massive Power Flow Computation

Energies ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 2268 ◽  
Author(s):  
Dong-Hee Yoon ◽  
Sang-Kyun Kang ◽  
Minseong Kim ◽  
Youngsun Han
Keyword(s):  
Cloud Computing ◽  
Power Systems ◽  
Power System ◽  
Power Flow ◽  
Computation Time ◽  
Coarse Grained ◽  
Contingency Analysis ◽  
Flow Computation ◽  
Cloud Computing System ◽  
The Impact

We present a novel architecture of parallel contingency analysis that accelerates massive power flow computation using cloud computing. It leverages cloud computing to investigate huge power systems of various and potential contingencies. Contingency analysis is undertaken to assess the impact of failure of power system components; thus, extensive contingency analysis is required to ensure that power systems operate safely and reliably. Since many calculations are required to analyze possible contingencies under various conditions, the computation time of contingency analysis increases tremendously if either the power system is large or cascading outage analysis is needed. We also introduce a task management optimization to minimize load imbalances between computing resources while reducing communication and synchronization overheads. Our experiment shows that the proposed architecture exhibits a performance improvement of up to 35.32× on 256 cores in the contingency analysis of a real power system, i.e., KEPCO2015 (the Korean power system), by using a cloud computing system. According to our analysis of the task execution behaviors, we confirmed that the performance can be enhanced further by employing additional computing resources.

An Optimization Framework for Decision Making in Large, Collaborative Energy Supply Systems

2016 ◽  
Vol 138 (5) ◽  
Author(s):  
Bryony DuPont ◽  
Ridwan Azam ◽  
Scott Proper ◽  
Eduardo Cotilla-Sanchez ◽  
Christopher Hoyle ◽  
...  
Keyword(s):  
Decision Making ◽  
Power Systems ◽  
Power Supply ◽  
Power Flow ◽  
Large Scale ◽  
Flow Analysis ◽  
Energy System ◽  
Future Research ◽  
Systems Research ◽  
Supply Systems

As demand for electricity in the U.S. continues to increase, it is necessary to explore the means through which the modern power supply system can accommodate both increasing affluence (which is accompanied by increased per-capita consumption) and the continually growing global population. Though there has been a great deal of research into the theoretical optimization of large-scale power systems, research into the use of an existing power system as a foundation for this growth has yet to be fully explored. Current successful and robust power generation systems that have significant renewable energy penetration—despite not having been optimized a priori—can be used to inform the advancement of modern power systems to accommodate the increasing demand for electricity. This work explores how an accurate and state-of-the-art computational model of a large, regional energy system can be employed as part of an overarching power systems optimization scheme that looks to inform the decision making process for next generation power supply systems. Research scenarios that explore an introductory multi-objective power flow analysis for a case study involving a regional portion of a large grid will be explored, along with a discussion of future research directions.

scholarly journals Load Flow Analysis in Hybrid AC-DC Transmission Network

2021 ◽  
pp. 617-624
Author(s):  
Ajith M ◽  
Dr. R. Rajeswari
Keyword(s):  
Power Systems ◽  
Power System ◽  
Transmission Lines ◽  
Power Flow ◽  
Reactive Power ◽  
Short Circuit ◽  
Flow Analysis ◽  
Load Flow ◽  
System Stability ◽  
And Control

Power-flow studies are of great significance in planning and designing the future expansion of power systems as well as in determining the best operation of existing systems. Technologies such as renewables and power electronics are aiding in power conversion and control, thus making the power system massive, complex, and dynamic. HVDC is being preferred due to limitations in HVAC such as reactive power loss, stability, current carrying capacity, operation and control. The HVDC system is being used for bulk power transmission over long distances with minimum losses using overhead transmission lines or submarine cable crossings. Recent years have witnessed an unprecedented growth in the number of the HVDC projects. Due to the vast size and inaccessibility of transmission systems, real time testing can prove to be difficult. Thus analyzing power system stability through computer modeling and simulation proves to be a viable solution in this case. The motivation of this project is to construct and analyze the load flow and short circuit behavior in an IEEE 14 bus power system with DC link using MATLAB software. This involves determining the parameters for converter transformer, rectifier, inverter and DC cable for modelling the DC link. The line chosen for incorporation of DC link is a weak bus. This project gives the results of load flow and along with comparison of reactive power flow, system losses, voltage in an AC and an AC-DC system.

scholarly journals Electric Vehicles and Biofuels Synergies in the Brazilian Energy System

Energies ◽  
2020 ◽  
Vol 13 (17) ◽  
pp. 4423 ◽  
Author(s):  
Géremi Gilson Dranka ◽  
Paula Ferreira
Keyword(s):  
Power Systems ◽  
Co2 Emissions ◽  
Electric Vehicles ◽  
Large Scale ◽  
Renewable Energy Sources ◽  
Energy System ◽  
Electricity Production ◽  
Transport Sector ◽  
Transportation Sector ◽  
The Impact

Shaping a secure and sustainable energy future may require a set of transformations in the global energy sector. Although several studies have recognized the importance of Electric Vehicles (EVs) for power systems, no large-scale studies have been performed to assess the impact of this technology in energy systems combining a diverse set of renewable energies for electricity production and biofuels in the transportation sector such as the case of Brazil. This research makes several noteworthy contributions to the current literature, including not only the evaluation of the main impacts of EVs’ penetration in a renewable electricity system but also a Life-Cycle Assessment (LCA) that estimates the overall level of CO2 emissions resulted from the EVs integration. Findings of this study indicated a clear positive effect of increasing the share of EVs on reducing the overall level of CO2 emissions. This is, however, highly dependent on the share of Renewable Energy Sources (RES) in the power system and the use of biofuels in the transport sector but also on the credits resulting from the battery recycling materials credit and battery reuse credit. Our conclusions underline the importance of such studies in providing support for the governmental discussions regarding potential synergies in the use of bioresources between transport and electricity sectors.

scholarly journals Blackstart from HVDC-connected Offshore Wind: Hard vs Soft Energization

2020 ◽  
Author(s):  
Anubhav Jain ◽  
Oscar Saborío-Romano ◽  
Jayachandra Naidu Sakamuri ◽  
Nicolaos Antonio Cutululis
Keyword(s):  
Power Systems ◽  
Environmental Sustainability ◽  
Power Plants ◽  
Large Scale ◽  
Renewable Energy Sources ◽  
Offshore Wind ◽  
Sensitivity Analyses ◽  
Power System Restoration ◽  
Soft Start ◽  
The Impact

<div>In recent years, renewable energy sources have been integrated on a large scale in power systems all around the world to address the environmental sustainability concerns. With conventional thermal generators being phased out, large offshore wind power plants present a viable alternative to provide blackstart services for power system restoration. In this paper, by means of simulations, grid-forming wind turbines are shown to successfully energize the offshore transformer and the HVDC export link in a controlled manner, to ultimately supply the onshore grid. Two methods for energizing the offshore network have been compared:</div><div>the prevalent hard-switching approach and the more complex soft-start method. Additionally, control has been implemented to mitigate the significant transients in the export link associated with pre-charging of the onshore converter. It is shown that soft-start can provide faster energization with smaller transients compared to hard-switching. Moreover, the sensitivity analyses performed</div><div>in this study illustrate the impact of pre-insertion resistor design and voltage ramp-up rates on transients during hard-switching and soft-start, respectively. The results presented in the paper also show that a separate controlled pre-charging stage of the onshore converter from its DC terminals is essential for the safe energization and operation of the export link.</div><div><br></div><div>The manuscript has been accepted for publication in IET Renewable Power Generation.</div>

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