A novel node ordering approach for parallel load flow analysis

Chen, S.-D.; Chen, J.-F.

doi:10.1002/etep.4450110408

Cited by 1 publication

(1 citation statement)

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“…Distributed approaches can utilize local data by partitioning the network according to such factors as the electrical properties of the network and the forecast power flow [28][29][30]. For example, in [31] epsilon decomposition is used to determine the range of influence of the network's DG, which is then utilized to control voltages should they exceed operating limits.…”

Section: Introductionmentioning

confidence: 99%

Constrained coordinated distributed control of smart grid with asynchronous information exchange

Millar

Jiang

Haque

2015

J. Mod. Power Syst. Clean Energy

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Smart grid constrained optimal control is a complex issue due to the constant growth of grid complexity and the large volume of data available as input to smart device control. In this context, traditional centralized control paradigms may suffer in terms of the timeliness of optimization results due to the volume of data to be processed and the delayed asynchronous nature of the data transmission. To address these limits of centralized control, this paper presents a coordinated, distributed algorithm based on distributed, local controllers and a central coordinator for exchanging summarized global state information. The proposed model for exchanging global state information is resistant to fluctuations caused by the inherent interdependence between local controllers, and is robust to delays in information exchange. In addition, the algorithm features iterative refinement of local state estimations that is able to improve local controller ability to operate within network constraints. Application of the proposed coordinated, distributed algorithm through simulation shows its effectiveness in optimizing a global goal within a complex distribution system operating under constraints, while ensuring network operation stability under varying levels of information exchange delay, and with a range of network sizes.

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