scholarly journals A review: Smart Distribution Grid Management using Agents

2020 ◽  
Vol 19 ◽  

This paper focuses on the main features of the smart distribution grid (grid management using agents). The fault management is consisting of three stages including faulted section identification, faulted section isolation, and restoration. The probable control strategies utilized in the smart grid are either centralized, decentralized, or autonomous control. Multi-Agent System (MAS) based model uses both centralized and decentralized strategies. The fault management process is usually carried out based on MAS. A literature survey on fault management control schemes is investigated. Furthermore, the reliability is estimated for both centralized, decentralized, autonomous, and modified centralized control strategies. This paper presents reliability modeling and analysis of all considered control strategies. In this paper, comprehensive detailed reliability models of considered control strategies are developed. Using this equivalent reliability model, various reliability indices are calculated.

Author(s):  
Kamil Korotkiewicz ◽  
Philippe Steinbusch ◽  
Marcel Ludwig ◽  
Felix Dorsemagen ◽  
Marcus Stotzel ◽  
...  

Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 593
Author(s):  
Moiz Muhammad ◽  
Holger Behrends ◽  
Stefan Geißendörfer ◽  
Karsten von Maydell ◽  
Carsten Agert

With increasing changes in the contemporary energy system, it becomes essential to test the autonomous control strategies for distributed energy resources in a controlled environment to investigate power grid stability. Power hardware-in-the-loop (PHIL) concept is an efficient approach for such evaluations in which a virtually simulated power grid is interfaced to a real hardware device. This strongly coupled software-hardware system introduces obstacles that need attention for smooth operation of the laboratory setup to validate robust control algorithms for decentralized grids. This paper presents a novel methodology and its implementation to develop a test-bench for a real-time PHIL simulation of a typical power distribution grid to study the dynamic behavior of the real power components in connection with the simulated grid. The application of hybrid simulation in a single software environment is realized to model the power grid which obviates the need to simulate the complete grid with a lower discretized sample-time. As an outcome, an environment is established interconnecting the virtual model to the real-world devices. The inaccuracies linked to the power components are examined at length and consequently a suitable compensation strategy is devised to improve the performance of the hardware under test (HUT). Finally, the compensation strategy is also validated through a simulation scenario.


2021 ◽  
Vol 1754 (1) ◽  
pp. 012059
Author(s):  
Dongliang Zhang ◽  
Kaiwen Zhang ◽  
Liufeng Wang ◽  
Qinqin Hong

2013 ◽  
Vol 341-342 ◽  
pp. 1229-1234
Author(s):  
Guang Yang ◽  
Li Ping Su ◽  
Ru Lin Zhao ◽  
Jun Sheng Wu

Distribution network supervisory terminal unit is widely used in the smart distribution grid construction. To solve the problem that the means of communication is short, a multi-mode communication distribution network supervisory terminal is proposed which can be contactless operated and can collect and transfer local data remotely.


2013 ◽  
Vol 347-350 ◽  
pp. 2590-2595 ◽  
Author(s):  
Sheng Zhai ◽  
Shu Zhong Lin

Aiming at the limitations of traditional reliability analysis theory in multi-state system, a method for reliability modeling and assessment of a multi-state system based on Bayesian Network (BN) is proposed with the advantages of uncertain reasoning and describing multi-state of event. Through the case of cell production line system, in this paper we will discuss how to establish and construct a multi-state system model based on Bayesian network, and how to apply the prior probability and posterior probability to do the bidirectional inference analysis, and directly calculate the reliability indices of the system by means of prior probability and Conditional Probability Table (CPT) . Thereby we can do the qualitative and quantitative analysis of the multi-state system reliability, identify the weak links of the system, and achieve assessment of system reliability.


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