A stochastic search algorithm for voltage and reactive power control with switching costs and ZIP load model
•A new random search algorithm for voltage and reactive power control is proposed.•Both switching costs and voltage-dependent loads are incorporated in the models.•Performance of the algorithm is compared and discussed under different scenarios.•Increasing voltage may increase energy consumption und...
Saved in:
Published in | Electric power systems research Vol. 133; no. C; pp. 328 - 337 |
---|---|
Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Switzerland
Elsevier B.V
01.04.2016
Elsevier |
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | •A new random search algorithm for voltage and reactive power control is proposed.•Both switching costs and voltage-dependent loads are incorporated in the models.•Performance of the algorithm is compared and discussed under different scenarios.•Increasing voltage may increase energy consumption under voltage-dependent loads.
This paper considers voltage and reactive power control models that take into account the operational costs of switching devices and the correlation between loads and voltage profiles. In addition to maintaining acceptable voltage at all points along the distribution feeder, the aim is to determine the proper settings of shunt capacitors and transformer load tap changers in order to minimize the energy loss or the energy consumption over a selected planning horizon. A random search algorithm is proposed for optimizing these models. The algorithm searches the optimal control schedule by randomly sampling from a sequence of probability distributions over the space of all possible settings of tap changers and shunt capacitors. The algorithm is shown to be globally convergent and its effectiveness is illustrated by comparing its performance with that of three other commonly used procedures on a 69-bus distribution system and a 24-bus system with distributed generation. |
---|---|
Bibliography: | OE0000220 USDOE |
ISSN: | 0378-7796 1873-2046 |
DOI: | 10.1016/j.epsr.2015.12.025 |