A Power Flow Adjustment Planning using Phase Shifting Transformers for Long Term Generation Outages

2014 ◽  
Vol 134 (2) ◽  
pp. 145-152
Author(s):  
Ryuichi Ogahara ◽  
Yuki Kawaura ◽  
Shinichi Iwamoto ◽  
Naohiro Kamikawa ◽  
Masayuki Namba
Keyword(s):  
Power Flow ◽  
Phase Shifting ◽  
Flow Adjustment

Power Flow Adjustment Planning Using Phase Shifting Transformers for Long-Term Generation Outages

2015 ◽  
Vol 192 (2) ◽  
pp. 12-21 ◽  
Author(s):  
Ryuichi Ogahara ◽  
Yuki Kawaura ◽  
Shinichi Iwamoto ◽  
Naohiro Kamikawa ◽  
Masayuki Namba
Keyword(s):  
Power Flow ◽  
Phase Shifting ◽  
Flow Adjustment

Phase-shifting transformer application to power-flow adjustment for large-scale PV penetration

2016 ◽  
Author(s):  
Yuki Kawaura ◽  
Sho Yamanouchi ◽  
Miki Ichihara ◽  
Shinich Iwamoto ◽  
Yo Suetsugu ◽  
...  
Keyword(s):  
Power Flow ◽  
Large Scale ◽  
Phase Shifting ◽  
Flow Adjustment ◽  
Pv Penetration

Power Flow Adjustment for Smart Microgrid Based on Edge Computing and Deep Reinforcement Learning

2021 ◽  
Author(s):  
Tianjiao Pu ◽  
Fei Jiao ◽  
Yifan Cao ◽  
Zhicheng Liu ◽  
Chao Qiu ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Smart Grid ◽  
Power Control ◽  
Power Flow ◽  
Supply And Demand ◽  
Edge Computing ◽  
Stable Operation ◽  
Local Autonomy ◽  
Real Time Control ◽  
Flow Adjustment

Abstract As one of the core components that improve transportation, generation, delivery, and electricity consumption in terms of protection and reliability, smart grid can provide full visibility and universal control of power assets and services, provide resilience to system anomalies and enable new ways to supply and trade resources in a coordinated manner. In current power grids, a large number of power supply and demand components, sensing and control devices generate lots of requirements, e.g., data perception, information transmission, business processing and real-time control, while existing centralized cloud computing paradigm is hard to address issues and challenges such as rapid response and local autonomy. Specifically, the trend of micro grid computing is one of the key challenges in smart grid, because a lot of in the power grid, diverse, adjustable supply components and more complex, optimization of difficulty is also relatively large, whereas traditional, manual, centralized methods are often dependent on expert experience, and requires a lot of manpower. Furthermore, the application of edge intelligence to power flow adjustment in smart grid is still in its infancy. In order to meet this challenge, we propose a power control framework combining edge computing and machine learning, which makes full use of edge nodes to sense network state and power control, so as to achieve the goal of fast response and local autonomy. Furthermore, we design and implement parameters such as state, action and reward by using deep reinforcement learning to make intelligent control decisions, aiming at the problem that flow calculation often does not converge. The simulation results demonstrate the effectiveness of our method with successful dynamic power flow calculating and stable operation under various power conditions.

Joint Regulation of Power Flow and Short Circuit Current Limitations with the Aid of a Phase-Shifting Transformer

2018 ◽  
Vol 51 (5) ◽  
pp. 584-592 ◽  
Author(s):  
A. S. Brilinskii ◽  
G. A. Evdokunin ◽  
R. I. Mingazov ◽  
N. N. Petrov ◽  
V. S. Chudnyi
Keyword(s):  
Power Flow ◽  
Short Circuit ◽  
Short Circuit Current ◽  
Phase Shifting

scholarly journals Defining Transmission System Operators’ Investment Shares for Phase-Shifting Transformers Used for Coordinated Redispatch

Energies ◽  
2020 ◽  
Vol 13 (15) ◽  
pp. 4019
Author(s):  
Michał Kłos ◽  
Endika Urresti-Padrón ◽  
Przemysław Krzyk ◽  
Wojciech Jaworski ◽  
Marcin Jakubek
Keyword(s):  
Cost Sharing ◽  
Daily Basis ◽  
Transmission System ◽  
Phase Shifting ◽  
Optimal Result ◽  
Procedure Cost ◽  
Capacity Calculation ◽  
Remedial Actions ◽  
Special Priority

The implementation of network codes within the framework of European Transmission System Operators (TSOs), involves redesigning the process of executing remedial actions aimed at maintaining the power system on a daily basis. One of the key elements of this redesign is the co-optimisation of all accessible measures, bringing a cost-optimal result and providing network security for the entire Capacity Calculation Region (CCR). This specifically means that the currently installed Phase Shifting Transformers (PSTs) are expected to be utilised for the benefit of the whole CCR, with no special priority to any issues incurred by the owner. Therefore, this paper addresses any questions regarding the rules of financing (investment shares per TSO) to be applied for future PST installations. The investment shares are calculated based on the exemplary implementation of a new European procedure – cost-sharing of remedial actions. Consequently, another long-term application of this process is postulated. In order to support the claims with numerical evidence, two scenarios with new PST investments are analysed. The conclusions drawn show that the largest investment burden can be imposed upon zones different from the area of which the new PST installation has taken place. As a result, joint TSOs’ investments may be a potential solution to financing new devices used for future coordination of remedial actions.

A Combined Three-Port LLC Structure for Adaptive Power Flow Adjustment of PV Systems

2020 ◽  
Vol 35 (10) ◽  
pp. 10413-10422
Author(s):  
Ting Qian ◽  
Kai Guo ◽  
Chenghui Qian
Keyword(s):  
Power Flow ◽  
Pv Systems ◽  
Flow Adjustment ◽  
Adaptive Power
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