Reactive multi-agent system applied to self-healing in Smart Grids

Campos, Italo Ramon da Costa; Saraiva, Filipe

doi:10.22456/2175-2745.97479

Cited by 1 publication

(10 citation statements)

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“…Figure 25 illustrated the comparison of the reconfiguration times as required by the multiagent‐based self‐healing (SHMAS), the theoretical upper bound of the required reconfiguration time (SHGHS T ) of the proposed self‐healing implementation as well as the experimental recovery time of the latter (SHGHS E ). Note that, in this case, the theoretical upper bound of the recovery time is 825 ms, which is actually always lower that the recovery time achieved by the multiagent‐based implementation presented in Reference 24.…”

Section: Performance Comparisonmentioning

confidence: 74%

“…It is also noteworthy to observe that both compared methodologies achieved successful recovery for the failure commuting the same power lines. However, the proposed implementation is twice faster to reach the recovery state thank the implementation proposed in Reference 24. The average speedup is about 2.05.…”

Section: Performance Comparisonmentioning

confidence: 87%

“…The performance of the proposed method is compared with the reactive multiagent parallel methodology applied to self-healing in smart grid. 24 The essence and main contribution of the approach are presented in section 3.3. As the IEEE 33-bus power grid is used in Reference 24 as a case study, we first introduce the main characteristics of the grid.…”

Section: Performance Comparisonmentioning

confidence: 99%

“…For comparison with the work presented in Reference 24, we consider seven possible line failures. The considered scenarios are regarding simple failure and are presented in Table 11.…”

Section: Performance Comparisonmentioning

confidence: 99%

“…In Reference 24, the authors present a decentralized algorithm for smart grids self‐healing, at the distribution level. The algorithm implementation is developed using a reactive multiagent system that models the power grid with the help of autonomous agents, responsible for performing the basic operations in a distributed and parallel way.…”

Section: Related Workmentioning

confidence: 99%

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An efficient distributed approach for aself‐healingsmart grid using minimal spanning tree

Nedjah

Cardoso

Mourelle

2021

Intl J of Energy Research

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In the event of a network failure that compromises energy supply, the characteristic of smart grid self-healing consists of finding a proposal for reconfiguration of the grid, aiming at restoring the power, partially or completely to supply all network nodes. The search for a satisfactory reconfiguration is a combinatorial problem whose complexity is proportional to the network size. An exhaustive search-based method is time-consuming and often computationally non-viable. To overcome this difficulty, techniques for generating minimal spanning trees (MSTs) of the graph that represents the smart grid, are exploited. However, existing studies provide centralized implementations. In this work, we propose a distributed implementation, where each of the network switch collaborates in developing of the recovery solution. The proposed decentralized approach seeks a reduction of reconfiguration time requirements, thus increasing network intelligence. For this purpose, a distributed algorithm for building the MST is embedded in the processing elements available at the commutation nodes. The evaluated case studies show that, whenever possible, the proposed solution allows for a successful reconfiguration, regardless of the number of simultaneous failures. Moreover, the network reconfiguration time is not significantly impacted by the number of buses and included lines. The implementation presents results of communication cost and reconfiguration time significantly lower than the expected upper bounds. Notably, for the case studies, the proposed implementation achieves 70% and 69% speedup regarding the reconfiguration time from simple and multiple failures, respectively, when compared to the expected theoretical performance. Furthermore, when compared to existing multiagentbased self-healing systems, the proposed implementation recovers from failures twice as fast, making it more desirable in a smart-grid real implementation.

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Section: Performance Comparisonmentioning

confidence: 74%

Section: Performance Comparisonmentioning

confidence: 87%

Section: Performance Comparisonmentioning

confidence: 99%

“…For comparison with the work presented in Reference 24, we consider seven possible line failures. The considered scenarios are regarding simple failure and are presented in Table 11.…”

Section: Performance Comparisonmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 3 more Smart Citations