Development of a probabilistic tool using Monte Carlo simulation and smart meters measurements for the long term analysis of low voltage distribution grids with photovoltaic generation

Vallée, François; Klonari, Vasiliki; Lisiecki, T.; Durieux, Olgan; Moiny, Francis; Lobry, Jacques

doi:10.1016/j.ijepes.2013.05.029

Cited by 46 publications

(53 citation statements)

References 12 publications

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“…To that end, a sampling of an uniformly distributed number on the interval [0, 1] is performed and the active power corresponding to that number is inferred from the associated CDF [4]. In order to obtain a good convergence threshold (< 0.1%) on the results, it is shown that 10,000…”

Section: Developed Methodologymentioning

confidence: 99%

“…Today, most of the smart meters are thus installed in some selected area characterized by a high penetration rate of DGs (around 25%). For those clients with PV units, two smart meters are installed in order to discern contributions of load and generation and to determine useful information for the DSO such as the auto-consumption rate of the prosumer (consumer with its own PV installation) [4]. The installation diagram is presented in Fig.…”

Section: Exploitation Of the Smart Meter Datamentioning

confidence: 99%

“…Such a study is vital for the DSO in order to avoid unexpected investments due to a premature aging of the network facilities. The methodology relies on a probabilistic model based on quarterly energy flows coming from smart meters installed at some customers [4]- [5]. Although these smart meters are expected to be widely deployed in the future, this data gathering is still limited to some sparse areas of the distribution grids.…”

Section: Introductionmentioning

confidence: 99%

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Probabilistic Study of the Impact on the Network Equipment of Changing Load Profiles in Modern Low Voltage Grids

Toubeau¹,

Klonari²,

Grève³

et al. 2024

RE&PQJ

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Abstract. The paper proposes a measurement-based method for the long-term analysis of the low-voltage (LV) distribution network. This work focuses on line power flows susceptible to cause a premature deterioration of cables and on power exchanged at the MV/LV transformer that can potentially induce adverse repercussions on its lifetime. Such estimations are indeed essential as the distribution systems are more and more frequently subject to stress conditions due to the increase of photovoltaic (PV) installations and significant loads such as electric vehicles. In this context, using a probabilistic approach is more beneficial than worst-case scenarios that yield much more restrictive conclusions. The approach is implemented in a pseudo-sequential Monte-Carlo environment and is based on quarter-hourly energy flows recorded by smart meters installed at some LV customers of the Belgian distribution network. These devices are currently located in some scarce selected areas but the penetration rate is expected to massively grow in the future. With the increase of collected measurements, this analysis tool will therefore allow Distribution System Operators (DSOs) to accurately assess important parameters for a secure and efficient operation of the network.

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Section: Developed Methodologymentioning

confidence: 99%

Section: Exploitation Of the Smart Meter Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Probabilistic Study of the Impact on the Network Equipment of Changing Load Profiles in Modern Low Voltage Grids

Toubeau¹,

Klonari²,

Grève³

et al. 2024

RE&PQJ

Self Cite

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“…12b. From (10) and (11), the equivalent impedance for the line section shown in Fig. 12b is expressed as:…”

Section: Appendixmentioning

confidence: 99%

“…Monte Carlo is a technique that develops repeated random sampling to get statistical results and is commonly used to address uncertainties in power systems [11]. Monte Carlo as a statistical method has been used to validate the probabilities of overloads that may cause faults in [12].…”

Section: Introductionmentioning

confidence: 99%

Monte Carlo-based Stochastic Analysis Results for Coordination of Single-Phase Rooftop PVs in Low Voltage Residential Networks

2015

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Installation of single-phase rooftop photovoltaic (PV) systems in low voltage (LV) residential feeders without controlling their ratings and locations may deteriorate the overall grid performance including reversed power flows, high losses and unacceptable voltage profiles. Therefore, in recent years the utilities have adopted limitations on the maximum allowable number of PVs in LV networks. To overcome these issues, this paper investigates the performance of a communication-based and intelligent voltage profile regulating technique under a Monte Carlo-based stochastic framework. This technique is applicable for LV residential feeders with single-phase rooftop PVs and relies on the availability of smart meters along the LV feeder to transmit phase voltage measurements to the controllers of the PV inverters. The objective of the voltage regulation technique is to minimize voltage unbalance along the feeder. The effectiveness of the voltage regulation technique are investigated in this paper by the help of MATLAB-based simulation studies.

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SARMA Time Series for Microscopic Electrical Load Modeling

Hupez

Toubeau

Grève

et al. 2017

Contributions to Statistics

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Development of a probabilistic tool using Monte Carlo simulation and smart meters measurements for the long term analysis of low voltage distribution grids with photovoltaic generation

Cited by 46 publications

References 12 publications

Probabilistic Study of the Impact on the Network Equipment of Changing Load Profiles in Modern Low Voltage Grids

Probabilistic Study of the Impact on the Network Equipment of Changing Load Profiles in Modern Low Voltage Grids

Monte Carlo-based Stochastic Analysis Results for Coordination of Single-Phase Rooftop PVs in Low Voltage Residential Networks

SARMA Time Series for Microscopic Electrical Load Modeling

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