Power Quality Monitoring and Classification

Cobben, Sjef

doi:10.5772/14467

Cited by 3 publications

(5 citation statements)

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“…The reporting of "how well" a network perform in terms of voltage sag events, requires knowledge on the affects thereof, of which the cost implications as proposed in the classification scheme of Cobben et al [2], can be used. A reporting tool, which integrates voltage sag events and voltage waveform quality parameters relating, is under consideration.…”

Section: Discussionmentioning

confidence: 99%

“…A wider audience, both technical and non-technical, can be informed on "how good" the PQ is as proposed in [1], [2] and [3].…”

Section: Discussionmentioning

confidence: 99%

“…al. in [1], [2] and [3] contributes to reporting on QoS. The application on voltage magnitude demonstrated in [3], makes use of limit levels, where the demonstration in this paper makes use of compatibility levels.…”

Section: A Classification and Reporting Methods For Pqmentioning

confidence: 98%

“…Useful contributions to the above by innovative approaches in reporting PQ can be found in [1], [2] and [3]. An alternative approach is introduced in this paper and applied to voltage magnitude data recorded over an extended period of time at singular sites and for groups of sites.…”

Section: Introductionmentioning

confidence: 99%

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On the reporting of power quality

Rens

Stander

2011

11th International Conference on Electrical Power Quality and Utilisation

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The reporting of power quality (PQ) requires consideration as different users of information on Quality of Supply (QoS) have different needs. Reporting on the compliancy of voltage regulation in terms of a PQ standard can be done without detail knowledge of such standard as demonstrated in this paper. This concept is claimed to be useful for the operators of the network as the parameters under their control are used in this reporting approach.

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Section: Discussionmentioning

confidence: 99%

“…A wider audience, both technical and non-technical, can be informed on "how good" the PQ is as proposed in [1], [2] and [3].…”

Section: Discussionmentioning

confidence: 99%

Section: A Classification and Reporting Methods For Pqmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

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On the reporting of power quality

Rens

Stander

2011

11th International Conference on Electrical Power Quality and Utilisation

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“…Up to recently, distribution system operators (DSO's) have few to no measurements available in the low-voltage network for assessing the power quality (Abur & Expósito, 2004) (Zarco & Expósito, 2000) and are only informed of issues when end-users file a complaint with their grid operator. This lack of measurements from actual grids poses a challenge to the academic community as well, frequently limiting the scope of research to idealized, lab-condition grids, or labour-intensive small-scale case studies (Cobben, Gaiddon, & Laukamp, 2008). The large-scale deployment of advanced metering infrastructure (AMI, or 'smart meters') provides detailed data at an unprecedented scale (U.S. International Trade Commission, 2014), thereby creating opportunities to study and understand low voltage grid issues assiduously.…”

Section: Introductionmentioning

confidence: 99%

Every ray counts! : Enabling large-scale solar PV integration by smart-grid applications combining fine-resolution meteorology and grid management

Kreuwel

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Chapter 6 evaluates a year-long case study of operational congestion management on a city area scale, where congestion occurs when there is an excess of solar generation. An open-source machine learning framework is provided to Summary iv systematically analyse the predictability of load on a contingency. Grid operators have only recently started to apply day-ahead congestion management to locally balance the grid. While accurate forecasts of the net-load are required to stay costeffective and ensure grid-safety, the operational achievability of this accuracy must be proven. The net-load in this case study is a combination of energy consumption primarily households and small, medium businesses) and solar-and wind generation. This ML framework is applied to attribute of inaccuracies in the net-load forecast to errors in the forecasted weather parameters related to wind-and solar energy generation. Overall, the largest part of the errors in the net-load forecast can be attributed to errors in the wind forecast. However, we show that when the load approaches the grid safety limits, errors in the solar forecasts have the biggest impact on the accuracy of the net-load forecast.The results of this thesis, as summarized in Chapter 7, contribute to connecting the fields of meteorology and grid management. Specifically high-resolution irradiance forecasting and integration of solar PV by active grid balancing. These findings have led the grid operator involved in this work to adapt their worst-case scenarios of PV generation to include extreme values found under broken-cloud conditions. Moreover, a predictability analysis using the framework detailed in this work is performed for areas where congestion management is considered. Moving forward, we recognize the growing importance of weather forecasts in facilitating the energy transition. To bridge the temporal gap towards the next generation of highresolution, cloud-resolving weather models, we suggest the providers of weather forecasts to include post-processed results in a comparable way to the current model output, using proven models form the academic forecasting community. Most importantly, we recommend formulating joint projects between the fields of meteorology and grid management, to facilitate the collaboration between experts of these fields, which is desperately required for an efficient transition to a renewable-based society.v System operators recognize that in addition to reinforcement of the grid, they also need to make better use of the grids capacity by balancing local supply and demand (Schittekatte & Meeus, 2020). For the distribution grid, this balancing on a local level needs to occur at three distinct spatial scales (Figure 1.1, right). The smallest scale is the street scale (~20 households, ~0.1 x 0.1 km 2 ), which concerns a single low-voltage cable. The intermediate scale is the neighbourhood scale (~150 households, ~0.5 x 0.5 km 2 ), where the key challenges lie in serving several street scale areas using a single distribution transformer. The la...

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