Transmission line modeling for the purpose of analog power flow computation of large scale power systems

2021 ◽  
Author(s):  
Aaron St. Leger
Keyword(s):  
Power Systems ◽  
Transmission Line ◽  
Power Flow ◽  
Large Scale ◽  
Flow Computation ◽  
Transmission Line Modeling

scholarly journals A Full-Newton AC-DC Power Flow Methodology for HVDC Multi-Terminal Systems and Generic DC Network Representation

Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1658
Author(s):  
Leandro Almeida Vasconcelos ◽  
João Alberto Passos Filho ◽  
André Luis Marques Marcato ◽  
Giovani Santiago Junqueira
Keyword(s):  
Power Systems ◽  
Direct Current ◽  
Power Flow ◽  
Large Scale ◽  
Flow Problem ◽  
Control Strategies ◽  
Problem Formulation ◽  
Expansion Planning ◽  
Dc Power ◽  
Power Flow Problem

The use of Direct Current (DC) transmission links in power systems is increasing continuously. Thus, it is important to develop new techniques to model the inclusion of these devices in network analysis, in order to allow studies of the operation and expansion planning of large-scale electric power systems. In this context, the main objective of this paper is to present a new methodology for a simultaneous AC-DC power flow for a multi-terminal High Voltage Direct Current (HVDC) system with a generic representation of the DC network. The proposed methodology is based on a full Newton formulation for solving the AC-DC power flow problem. Equations representing the converters and steady-state control strategies are included in a power flow problem formulation, resulting in an expanded Jacobian matrix of the Newton method. Some results are presented based on HVDC test systems to confirm the effectiveness of the proposed approach.

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.

Modeling of Mechanical Systems Using Rigid Bodies and Transmission Line Joints

1999 ◽  
Vol 121 (4) ◽  
pp. 606-611 ◽  
Author(s):  
Petter Krus
Keyword(s):  
Transmission Line ◽  
Hydraulic System ◽  
Large Scale ◽  
Mechanical Systems ◽  
Rigid Bodies ◽  
Large Scale Systems ◽  
Distributed Parameters ◽  
Transmission Line Modeling ◽  
Integration Algorithms ◽  
Transmission Line Models

Dynamic simulation of systems, where the differential equations of the system are solved numerically, is a very important tool for analysis of the detailed behavior of a system. The main problem when dealing with large complex systems is that most simulation packages rely on centralized integration algorithms. For large scale systems, however, it is an advantage if the system can be partitioned in such a way that the parts can be evaluated with only a minimum of interaction. Using transmission line models, with distributed parameters, physically motivated pure time delays are introduced in the communication between components. These models can be used to represent both lines in a hydraulic system and springs in mechanical systems. As a result, components and subsystems can be simulated more independently of each other. In this paper it is shown how flexible joints based on transmission line modeling (TLM) with distributed parameters can be used to simplify modeling of large mechanical link systems interconnected with other physical domains. Furthermore, it provides a straightforward formulation for parallel processing.

scholarly journals A modular parallelization framework for power flow transfer analysis of large-scale power systems

2017 ◽  
Vol 6 (4) ◽  
pp. 679-690
Author(s):  
Chuntian CHENG ◽  
Bin LUO ◽  
Jianjian SHEN ◽  
Shengli LIAO
Keyword(s):  
Power Systems ◽  
Power Flow ◽  
Large Scale ◽  
Flow Transfer

Hierarchical Control of Multi-Domain Power Flow in Mobile Systems: Part II — Aircraft Application

2015 ◽  
Author(s):  
Matthew A. Williams ◽  
Justin P. Koeln ◽  
Andrew G. Alleyne
Keyword(s):  
Power Systems ◽  
Power Flow ◽  
Large Scale ◽  
Control Method ◽  
Hierarchical Control ◽  
Mobile Systems ◽  
Centralized Control ◽  
Modeling Framework ◽  
Control Framework ◽  
Aircraft Application

This two-part paper presents the development of a hierarchical control framework for the control of power flow throughout large-scale systems. Part II presents the application of the graph-based modeling framework and three-level hierarchical control framework to the power systems of an aircraft. The simplified aircraft system includes an engine, electrical, and thermal systems. A graph based approach is used to model the system dynamics, where vertices represent capacitive elements such as fuel tanks, heat exchangers, and batteries with states corresponding to the temperature and state of charge. Edges represent power flows in the form of electricity and heat, which can be actuated using control inputs. The aircraft graph is then partitioned spatially into systems and subsystems, and temporally into fast, medium, and slow dynamics. These partitioned graphs are used to develop models for each of the three levels of the hierarchy. Simulation results show the benefits of hierarchical control compared to a centralized control method.

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.

Scenarios for examination of highly distributed power systems

2008 ◽  
Vol 222 (7) ◽  
pp. 643-655 ◽  
Author(s):  
C N Jardine ◽  
G W Ault
Keyword(s):  
Power Systems ◽  
Carbon Dioxide Emissions ◽  
Power Flow ◽  
Large Scale ◽  
Energy Use ◽  
Housing Stock ◽  
Distributed Power ◽  
Distributed Power Systems ◽  
Network Operation ◽  
The Uk

A set of three scenarios has been created in order to examine the incorporation of extensive penetrations of micro-generators into electricity networks (termed ‘highly distributed power systems’). The scenarios have been created as a synthesis of the Future Network Technologies scenarios and the UK domestic carbon model, and yields energy use and carbon dioxide emissions of the UK housing stock from inputs of household numbers, house type, thermal efficiency, appliance efficiency, as well as the number and efficiency of micro-generators used. The centralized supply mix also varies between scenarios and features extensive penetrations of large-scale renewables. The scenarios illustrate the scale of change required to reduce CO2 emissions by 60 per cent by 2050, which has substantial impacts for electricity network operation. Moving from a centralized system to the one where one-third of electricity comes from distributed sources poses significant challenges including: reverse power flow on networks, load balancing, storage requirements, phase unbalance, harmonics, and ancillary services.

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