Expert system requirements for power system restoration

Adibi, M. M.; Kafka, L.R.J.; Milanicz, D.P.

doi:10.1109/59.336099

Cited by 80 publications

(30 citation statements)

References 14 publications

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“…The result of Equation (18), which can be adjusted by controlling the loads of node i, should be 0 to maintain stable frequency of system. In Equation (19), the Q i equals the output active power of DG i minus reactive power of load on node i. The result of Equation (19), which can be adjusted by using inductive compensation equipment, should be 0 to maintain stable voltage of the system.…”

Section: Constraint Conditionmentioning

confidence: 99%

“…The variation coefficient [19], as an objective weighting method, assesses the weight of each index by calculating the index data. According to the variation coefficient method, indexes with a large difference can indicate the quality of the evaluated objects and reflect objective information of the change of index data, so the index is given more weight.…”

Section: Black Start Capability Evaluation Model Of Dgs Based On Varimentioning

confidence: 99%

“…Step 6: In the restoration process, it is necessary to supply a proper number of loads to ensure the stable operation of the network; in addition, it is necessary to test whether the DGs' output constraints (14) and (15), node voltage constraint (16), line constraint (17), and node power balance constraints (18) and (19) are satisfied. If a line operation fails in the restoration process, return to step 5 on the basis of the restored lines and nodes and select a new recovery path.…”

Section: Parallel Restoration Strategy For Microgrid Reconfigurationmentioning

confidence: 99%

See 2 more Smart Citations

A Parallel Restoration for Black Start of Microgrids Considering Characteristics of Distributed Generations

et al. 2017

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Abstract:The black start capability is vital for microgrids, which can potentially improve the reliability of the power grid. This paper proposes a black start strategy for microgrids based on a parallel restoration strategy. Considering the characteristics of distributed generations (DGs), an evaluation model, which is used to assess the black start capability of DGs, is established by adopting the variation coefficient method. Thus, the DGs with good black start capability, which are selected by a diversity sequence method, are restored first in parallel under the constraints of DGs and network. During the selection process of recovery paths, line weight and node importance degree are proposed under the consideration of the node topological importance and the load importance as well as the backbone network restoration time. Therefore, the whole optimization of the reconstructed network is realized. Finally, the simulation results verify the feasibility and effectiveness of the strategy.

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Section: Constraint Conditionmentioning

confidence: 99%

Section: Black Start Capability Evaluation Model Of Dgs Based On Varimentioning

confidence: 99%

Section: Parallel Restoration Strategy For Microgrid Reconfigurationmentioning

confidence: 99%

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A Parallel Restoration for Black Start of Microgrids Considering Characteristics of Distributed Generations

et al. 2017

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“…Some work has hybridized both strategies by designing Expert Systems that solves a series of approximate problems optimally [14,9]. Interestingly, most of the work in planning PSR has focused on the details of scheduling power system restoration [2,3]. More specifically, what is the best order of restoration and how should system components be reconfigured during restoration?…”

Section: Dynamic Behaviormentioning

confidence: 99%

“…power engineer intuition) to guide an incomplete search of the solution space. These incomplete search methods include Knowledge Based Systems [16], Expert Systems [10,3,5], and Local Search [12,13]. The second strategy is to approximate the power system with a linear model and solve the approximate problem optimally [17].…”

Section: Dynamic Behaviormentioning

confidence: 99%

Strategic Planning for Power System Restoration

Coffrin

Hentenryck

Bent

2011

Vulnerability, Uncertainty, and Risk

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This paper considers the power system restoration planning problem (PSRPP) for disaster recovery, a fundamental problem faced by all populated areas. PSRPPs are complex stochastic optimization problems that combine resource allocation, warehouse location, and vehicle routing considerations. Furthermore, electrical power systems are complex systems whose behavior can only be determined by physics simulations. Moreover, these problems must be solved under tight runtime constraints to be practical in real-world disaster situations. This work is threefold; It formalizes the specification of PSRPPs, introduces a simple optimization-simulation hybridization necessary for solving PSRPPs, and presents a complete restoration algorithm that utilizes the strengths of mixed integer programming, constraint programming, and large neighborhood search.

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The Concordance Index C and the Mann–Whitney Parameter Pr(X>Y) with Randomly Censored Data

Koziol

Jia

2009

Biometrical J

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Harrell's c-index or concordance C has been widely used as a measure of separation of two survival distributions. In the absence of censored data, the c-index estimates the Mann-Whitney parameter Pr(X>Y), which has been repeatedly utilized in various statistical contexts. In the presence of randomly censored data, the c-index no longer estimates Pr(X>Y); rather, a parameter that involves the underlying censoring distributions. This is in contrast to Efron's maximum likelihood estimator of the Mann-Whitney parameter, which is recommended in the setting of random censorship.

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Expert system requirements for power system restoration

Cited by 80 publications

References 14 publications

A Parallel Restoration for Black Start of Microgrids Considering Characteristics of Distributed Generations

A Parallel Restoration for Black Start of Microgrids Considering Characteristics of Distributed Generations

Strategic Planning for Power System Restoration

The Concordance Index C and the Mann–Whitney Parameter Pr(X>Y) with Randomly Censored Data

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