2017 IEEE Energy Conversion Congress and Exposition (ECCE) 2017
DOI: 10.1109/ecce.2017.8096876
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Power electronics intelligence at the network edge (PINE)

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Cited by 8 publications
(4 citation statements)
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“…The base case with 30% PV penetration contains an equal share of autonomous and legacy inverters. Since the likelihood of experiencing voltage issues is location-dependent [9], we randomly select 40 different PV locations. This set includes an instance with a PV cluster with the minimum electric distance from the secondary transformer and another with a cluster at the maximum distance.…”
Section: Model Setup and Evaluationmentioning
confidence: 99%
“…The base case with 30% PV penetration contains an equal share of autonomous and legacy inverters. Since the likelihood of experiencing voltage issues is location-dependent [9], we randomly select 40 different PV locations. This set includes an instance with a PV cluster with the minimum electric distance from the secondary transformer and another with a cluster at the maximum distance.…”
Section: Model Setup and Evaluationmentioning
confidence: 99%
“…Two inverter control strategies for mitigating sudden changes in load or solar PV output relying on a single-loop P −Q regulation method and double loop control method were demonstrated in [29]. Voltage regulation based on network clustering and two-stage inverter output optimisation was presented in [30], but line losses were ignored; we show that reducing line losses is the biggest benefit of OID.…”
Section: Introductionmentioning
confidence: 98%
“…Simulations in [10] demonstrate that increasing inverter reactive power compensation further from the distribution feeder improves the voltage profiles relative to fixed compensation schemes that ignore the size and location of PV inverter. A scalable, decentralized method for voltage regulation using power electronic converters able to support a high amount of PV and electric vehicles at the distribution grid is presented in [11]. An ability to provide reactive power compensation on demand requires each customer in the network to install additional converters increasing the costs of the proposed solution.…”
Section: Introductionmentioning
confidence: 99%