Incremental Heuristic Approach for Meter Placement in Radial Distribution Systems

Abstract

The evolution of modern power distribution systems into smart grids requires the development of dedicated state estimation (SE) algorithms for real-time identification of the overall system state variables. This paper proposes a strategy to evaluate the minimum number and best position of power injection meters in radial distribution systems for SE purposes. Measurement points are identified with the aim of reducing uncertainty in branch power flow estimations. An incremental heuristic meter placement (IHMP) approach is proposed to select the locations and total number of power measurements. The meter placement procedure was implemented for a backward/forward load flow algorithm proposed by the authors, which allows the evaluation of medium-voltage power flows starting from low-voltage load measurements. This allows the reduction of the overall costs of measurement equipment and setup. The IHMP method was tested in the real 25-bus medium-voltage (MV) radial distribution network of the Island of Ustica (Mediterranean Sea). The proposed method is useful both for finding the best measurement configuration in a new distribution network and also for implementing an incremental enhancement of an existing measurement configuration, reaching a good tradeoff between instrumentation costs and measurement uncertainty.

Bibliometric study of distribution system state estimation: advances and challenges

“…In addition, there are proposals related with noise of non-Gaussian measurements [18], chaos simulation and/or Monte Carlo [10,19], Genetics Algorithm [20], Heuristic Methods, Combined or Hybrid [9,21] Integer Linear Programming (ILP) [22], Mixed Integer Semi-Definite Programming (MISDP) [23], Information Entropy Evaluation and multiobjective optimization [24].…”

Meter placement algorithms to enhance distribution systems state estimation: Review, challenges and future research directions

“…Probabilistic methods are the most appropriate way to incorporate the measurement error uncertainties into the solution procedure. The most widely used probabilistic method in the analysis of state estimator accuracy and specifically in the meter placement problem is MCS [25,34,46,59]. MCS is a simple and powerful technique for performing uncertainty propagation analysis and evaluating probabilistic indices.…”

PQ and Harmonic Assessment Issues on Low-Cost Smart Metering Platforms: A Case Study

“…In [18], an enhanced solution for distribution system state estimation is presented, based on PMUs measurements and the cloud-based Internet of Things (IoT) paradigm. In [19][20][21], PQAs exploitation for power flows analysis at the distribution level is investigated, proposing properly distributed measurement systems and related power flows estimation algorithms able to also deal with partial data availability. In [22], PQ meters are integrated into a heterogeneous communication infrastructure to allow for the analysis of voltage dips in distribution networks.…”