期刊
ELECTRIC POWER SYSTEMS RESEARCH
卷 182, 期 -, 页码 -出版社
ELSEVIER SCIENCE SA
DOI: 10.1016/j.epsr.2020.106233
关键词
Biased Random-Key Genetic Algorithm; Multi-objective optimization; Meter placement; State estimation; Network Reconfiguration; Energy losses
This paper proposes a methodology to allocate meters in distribution networks oriented to state estimation. The proposed approach considers that the meter placement is carried out simultaneously with the Distribution Network Reconfiguration (DNR) for annual energy loss reduction. This formulation of the allocation problem prevents the State Estimator Accuracy (SEA) from being degraded when the topology is changed and that an excessive number of meters is installed to obtain acceptable accuracy. These objectives were achieved using a multi-objective formulation that minimizes resistive losses, the risk of violating SEA and the number of meters installed in the network. The problem of meter placement formulated in this paper is solved through the Multi-Objective Biased Random-Key Genetic Algorithm (MOBRKGA). The tests results demonstrate that MOBRKGA can generate high quality solutions with significant reduction in annual energy losses and metering system with good accuracy and low installation cost.
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