Understanding Distribution Grid Congestion Caused by Electricity Generation from Renewables

Schermeyer, Hans; Studer, Michael Hans-Peter; Ruppert, Manuel; Fïchtner, Wolf

doi:10.1007/978-3-319-66553-5_6

Cited by 12 publications

(8 citation statements)

References 1 publication

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“…A study on congestion events in the distribution systems caused due to RES in Germany is presented in ref. [6]. The study further presents that due to increasing RES penetration the total amount of energy curtailment in 2014 was the same as the aggregated amount from 2009 to 2013 and it is growing further.…”

Section: Introductionmentioning

confidence: 86%

Development of a DSO support tool for congestion forecast

Srivastava

Steen

Tuấn

et al. 2021

IET Generation Trans & Dist

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This paper presents a novel DSO support tool with visualisation capability for forecasting network congestion in distribution systems with a high level of renewables. To incorporate the uncertainties in the distribution systems, the probabilistic power flow framework has been utilised. An advanced photovoltaic production forecast based on sky images and a load forecast using an artificial neural network is used as the input to the tool. In addition, advanced load models and operating modes of photovoltaic inverters have been incorporated into the tool. The tool has been applied in case studies to perform congestion forecasts for two real distribution systems to validate its usability and scalability. The results from case studies demonstrated that the tool performs satisfactorily for both small and large networks and is able to visualise the cumulative probabilities of nodes voltage deviation and network components (branches and transformers) congestion for a variety of forecast horizons as desired by the DSO. The results have also shown that explicit inclusion of load-voltage dependency models would improve the accuracy of the congestion forecast. For demonstrating the applicability of the tool, it has been integrated into an existing distribution management system via the IoT platform of a DMS vendor, Atos Worldgrid.

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Section: Introductionmentioning

confidence: 86%

Development of a DSO support tool for congestion forecast

Srivastava

Steen

Tuấn

et al. 2021

IET Generation Trans & Dist

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“…The above cost term penalises the power interaction with the grid (p grid ). As a result, if (1) is to be minimised the EM scheme will try to keep the values of p grid as low as possible. This will ensure that grid feed-in is reduced.…”

Section: B Mpc Based Scheduling Unitmentioning

confidence: 99%

“…R ENEWABLE sources (RES) in electric grids are environment friendly but tend to not be grid friendly. The intermittent nature of this generation has led to grid congestions , voltage regulation problems and instabilities [1]. Energy storage systems (ESS) are increasingly utilised to overcome these issues and facilitate the RES integration [2].…”

Section: Introductionmentioning

confidence: 99%

An Analysis of Multi Objective Energy Scheduling in PV-BESS System Under Prediction Uncertainty

Nair

Sandelić

Sangwongwanich

et al. 2021

IEEE Trans. Energy Convers.

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Energy storage systems (ESS) are being considered to overcome issues in modern grids, caused by increasing penetration of renewable generation. Nevertheless, integration of ESS should also be supplemented with an optimal energy management framework to ensure maximum benefits from ESS. Conventional energy management of battery, used with PV system, maximises self-consumption but does not mitigate grid congestion or address battery degradation. Model predictive control (MPC) can alleviate congestion and degradation while ensuring maximum self-consumption. Studies will be carried out to highlight the improvement with MPC based energy management over conventional method using simulations of oneyear system behaviour. As MPC uses forecast information in decision making, the impact of forecast uncertainties will be assessed and a method to address them through a constraint tightening will be presented.

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“…The last decade has seen more than doubling of renewable generation capacity, mainly driven by photovoltaic (PV) and wind power systems integrated in power grids [1]. This increased penetration of load-decoupled intermittent renewable sources has caused grid congestions, voltage regulation and stability issues [2][3][4] in power networks.…”

Section: Introductionmentioning

confidence: 99%

Grid Congestion Mitigation and Battery Degradation Minimisation Using Model Predictive Control in PV-Based Microgrid

Nair

Sandelić

Sangwongwanich

et al. 2021

IEEE Trans. Energy Convers.

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Increasing integration of photovoltaic (PV) system in electric grids cause congestion during peak power feed-in. Battery storage in PV systems increases self-consumption, for consumer's benefit. However with conventional maximising self consumption (MSC) control for battery scheduling, the issue of grid congestion is not addressed. The batteries tend to be fully charged early in the day and peak power is still fed-in to grid. This also increases battery degradation due to increased dwell time at high state of charge (SOC) levels. To address this issue, this work uses a model predictive control (MPC) for scheduling in PV system with battery storage to achieve multiple objectives of minimising battery degradation, grid congestion, while maximising self consumption. In order to demonstrate the improvement, this work compares the performances of MPC and MSC schemes when used in battery scheduling. The improvement is quantified through performance indices like self consumption ratio, peak power reduction and battery capacity fade for one-year operation. An analysis on computation burden and maximum deterioration in MPC performance under prediction error is also carried out. It is concluded that, compared to MSC, MPC achieves similar self consumption in PV systems while also reducing grid congestion and battery degradation.

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Understanding Distribution Grid Congestion Caused by Electricity Generation from Renewables

Cited by 12 publications

References 1 publication

Development of a DSO support tool for congestion forecast

Development of a DSO support tool for congestion forecast

An Analysis of Multi Objective Energy Scheduling in PV-BESS System Under Prediction Uncertainty

Grid Congestion Mitigation and Battery Degradation Minimisation Using Model Predictive Control in PV-Based Microgrid

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