Optimized positioning of measurements in distribution grids

Echternacht, David; Linnemann, Christian; Moser, Albert

doi:10.1109/isgteurope.2012.6465628

Cited by 14 publications

(3 citation statements)

References 4 publications

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“…In order to avoid grid operation limit violations such as congestion and over-voltages in the network, advanced control actions at the mediumvoltage (MV) network level need to be carried out by the Distribution System Operators (DSOs) [1], requiring an accurate estimate of the actual system state. State Estimation (SE) algorithms are widely applied in transmission systems and now find their way to distribution systems, processing (pseudo-)measurements and their error variances to calculate the highest likelihood values for a set of variables that uniquely represent the system state [4].…”

Section: A Motivationmentioning

confidence: 99%

Assessment of Dynamic Measurement Intervals for State Estimation in Future Distribution Systems

Sirige

Blaauwbroek²,

Rueda

et al. 2021

2021 IEEE Madrid PowerTech

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The ongoing energy transition introduces new load and generation units like photovoltaic generation in the mediumvoltage systems network. These generation units increase the variance of the power injections, resulting in increased stochasticity of the power flow values. For confident assessment of the system's operating condition, a measurement scheme is essential for accurate state estimation at every minute of the day. This paper presents a performance assessment of the Weighted Least Square (WLS) distribution system state estimation algorithm with respect to the measurement intervals, and proposes a measurement scheme considering the measurement locations and intervals that satisfy a required error limit. The scheme is tested on a synthetic test model of a Dutch MV network, which takes into account projected (year 2040) and highly stochastic power flow profiles. Numerical results show that the proposed algorithm for the measurement scheme determination successfully satisfies the chosen error limit.

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Section: A Motivationmentioning

confidence: 99%

Assessment of Dynamic Measurement Intervals for State Estimation in Future Distribution Systems

Sirige

Blaauwbroek²,

Rueda

et al. 2021

2021 IEEE Madrid PowerTech

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show abstract

“…Research has been carried for obtaining improved accuracy of the estimation in low voltage grids where, in case of improved state estimation, the relative estimation error distribution for state variables is used as the initial measure of the estimator's accuracy [45]. Furthermore, the estimation error can be reduced economically by incorporating more real-time measuring devices at the secondary substations by choosing appropriate network nodes to be measured to ensure the observability of the entire system [46].…”

Section: Optimal Smart Meter Placementmentioning

confidence: 99%

Meter Placement in Power System Network—A Comprehensive Review, Analysis and Methodology

et al. 2018

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The blackout in North India due to the failure of the central grid has led to the need for intelligent power system state estimation, where optimal location is necessary to understand. State estimation meter placement plays a major role in the smart operation of a modern distributed power system. A literature review of the different algorithms incorporated for the determination of minimal number of meters required for the measurement of real time measurements is presented for the power system and distribution system state estimation, including smart meter location.

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“…A new and presumably more economic approach is the use of smart meters which may provide data of power injections and loads and even voltage magnitudes at customer sites if selected and parameterized accordingly. The collected data is then typically used for classic SE algorithms, which due to the measurement topology works more or less only in radial LV grids [3,4]. In these approaches possible topology faults are identified within the SE process.…”

Section: Introductionmentioning

confidence: 99%

Identification of topology faults by smart meter data in meshed low voltage grids

Wellßow

Waeresch

2014

2014 Power Systems Computation Conference

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The integration of distributed generation causes an increase of the voltage magnitude in low voltage grids. In addition to classical grid expansion distribution system operators have various options at their hands to reduce the voltage rise, e.g. by installing distribution transformers with on-load tap changers or voltage regulators. For efficient control the network operator need information on relevant operational system parameters. The classical approach of using measurement and monitoring devices from SCADA systems is comparatively too expansive and complex. In future, smart meters can provide information about the relevant operational data. In addition these data can enable the identification of topology faults in meshed low voltage grids. This paper proposes a simple approach for the identification of topology faults including some analysis on the probability of detecting such faults even in case of a scarce population with smart meters. The presented approach includes the preprocessing and plausibility checks of smart meter data, a comparative analysis of measured and calculated voltages and evaluating functions. Despite the simplicity of the process, the results gathered from a field test are promising, provided that line lengths are not too short and currents not too small.

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Optimized positioning of measurements in distribution grids

Cited by 14 publications

References 4 publications

Assessment of Dynamic Measurement Intervals for State Estimation in Future Distribution Systems

Assessment of Dynamic Measurement Intervals for State Estimation in Future Distribution Systems

Meter Placement in Power System Network—A Comprehensive Review, Analysis and Methodology

Identification of topology faults by smart meter data in meshed low voltage grids

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