Placement and sizing of DG for distribution system by using a novel algorithm

Viswanatharao, J.; Praveena, E.; Srinivasarao, R.

doi:10.1109/icicct.2017.7975222

Cited by 2 publications

(2 citation statements)

References 7 publications

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“…Thus in order to keep the losses to a minimum value, the DG size is fixed to an optimum value. Analytical approach is used for optimum DG size selection [11]. The method is easy to implement and computationally efficient.…”

Section: Placement and Sizing Of Dgmentioning

confidence: 99%

“…Ref [10] explains optimal placement of DG in radial distribution network using evolutionary algorithms like Genetic Algorithm and Particle Swam Optimisation. A multi-objective performance index-based sizing and placement of DG in distribution systems is studied in [11]. Load is considered to be varying by considering the effect of industrial, residential and commercial loads.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Linear Distribution System State Estimation with Integration of DG

Bindu¹,

Ushakumari²,

Savier³

2021

Technol Econ Smart Grids Sustain Energy

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Monitoring of a power system is essential for maintaining it in a secure operating condition. Electric distribution management system (DMS) should possess a monitoring mechanism addressing the entire operating conditions of the system. Distribution System State Estimation (DSSE) is an integral building block of the DMS. Because of new technologies integrated into the power distribution system, new opportunities, problems and challenges related to control and management are being explored. To make efficient and reliable control actions, an accurate knowledge of the system states is required. This paper presents Linear State Estimator based DSSE which can handle the challenges mentioned above. The estimator studied and reported in the paper allows to include synchronized phasor measurements provided by Phasor Measurement Units (PMUs). With the increasing integration of DG in distribution system, the state estimation scheme needs be reworked to address the complexities introduced by power exchange of DG. To address this, Linear State Estimation (LSE) is reformulated and its performance is analysed with DG integrated in the sample network under study.

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Section: Placement and Sizing Of Dgmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%