Increasing PV hosting capacity in LV grids with a probabilistic planning approach

Niederhuemer, Walter; Schwalbe, Roman

doi:10.1109/sedst.2015.7315266

Cited by 10 publications

(13 citation statements)

References 2 publications

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“…1% of transformer capacity) is allocated at a bus n, and it is increased in steps until it violates the defined conditions as given in Eqs. (2)(3)(4)(5)(6)(7). In this paper, the network behavior is analyzed for the entire day (24 h) and mainly covers two circumstances: (i) voltage rise problems due to low load demand (1) and high PV generation, and (ii) loading problems due to high demand and high generation.…”

Section: Methodology For Estimating Pv Hosting Capacitymentioning

confidence: 99%

“…An approach for enhancing PV HC based on a reactive power control strategy was presented by Atmaja et al [3], but it did not include load flow analysis with simultaneous penetration of PV capacity at different nodes. A probabilistic approach-based method for PV HC was presented by Niederhuemer and Schwalbe [4] considering the worst-case scenario (i.e. maximum PV and low load), but network operational parameters were not analyzed.…”

Section: Introductionmentioning

confidence: 99%

“…The reliability of the stand-alone system was validated with applied algorithms and effectiveness, but the suitability of the design system was not tested with the grid [8]. Most of the reviewed literatures [3][4][5][6][7][8] have not covered a comparative assessment of hosting capacity considering various operational constraints. Therefore, it is essential to analyze PV HC within the distribution network at different nodes with simultaneous PV and load profiles.…”

Section: Introductionmentioning

confidence: 99%

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Solar photovoltaic-based microgrid hosting capacity evaluation in electrical energy distribution network with voltage quality analysis

et al. 2021

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In this paper, solar photovoltaic hosting capacity within the electrical distribution network is estimated for different buses, and the impacts of high PV penetration are evaluated using power hardware-in-loop testing methods. It is observed that the considered operational constraints (i.e. voltage and loadings) and their operational limits have a significant impact on the hosting capacity results. However, with increasing photovoltaic penetration, some of the network buses reach maximum hosting capacity, which affects the network operation (e.g. bus voltages, line loading). The results show that even distributing the maximum hosting capacity among different buses can increase the bus voltage rise to 9%. To maintain the network bus voltages within acceptable limits, reactive power voltage-based droop control is implemented in the photovoltaic conditioning devices to test the dynamics of the network operation. The results show that implementation of the droop control technique can reduce the maximum voltage rise from 9% to 4% in the considered case. This paper also presents the impact of forming a mesh type network (i.e. from radial network) on the voltage profile during PV penetration, and a comparative analysis of the operational performance of a mesh type and radial type electrical network is performed. It is observed that the cumulative effect of forming a mesh type network along with a droop control strategy can further improve the voltage profile and contribute to increase photovoltaic penetration. The results are verified using an experimental setup of digital real-time simulator and power hardware-in-loop test methods. The results from this work will be useful for estimating the appropriate photovoltaic hosting capacity within a distribution network and implementation of a droop control strategy in power conditioning devices to maintain the network operational parameters within the specified limits. Highlights Voltage and line loading constraints’ combination can reduce PV hosting capacity by 50% as compared to only voltage as a constraint. Implementation of reactive power versus voltage droop control in PV power conditioning device can reduce voltage variation from 9% to 4%. In a PV integrated electrical energy network, line loading can be reduced by 20% if the network is configured from radial to mesh type.

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Section: Methodology For Estimating Pv Hosting Capacitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Solar photovoltaic-based microgrid hosting capacity evaluation in electrical energy distribution network with voltage quality analysis

et al. 2021

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“…The authors of ( [28,30,37,60,65,83,[88][89][90]) and ( [23,75,76]) considered EN-50160(±10% Un) and BS EN-50160 (−6/+10%Un) standard for voltage limits, respectively. The research conducted in [30] investigated HC of Danish LV network by taking phase voltage magnitude (±10% Un), voltage unbalance factor (2% Un), neutral potential and system losses as limiting factors complying to EN-50160 while considering the first two criteria as the most important.…”

Section: Voltage Levelmentioning

confidence: 99%

Review on the PV Hosting Capacity in Distribution Networks

2020

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The increasing penetration of Photovoltaic (PV) generation results in challenges regarding network operation, management and planning. Correspondingly, Distribution Network Operators (DNOs) are in the need of totally new understanding. The establishment of comprehensive standards for maximum PV integration into the network, without adversely impacting the normal operating conditions, is also needed. This review article provides an extensive review of the Hosting Capacity (HC) definitions based on different references and estimated HC with actual figures in different geographical areas and network conditions. Moreover, a comprehensive review of limiting factors and improvement methods for HC is presented along with voltage rise limits of different countries under PV integration. Peak load is the major reference used for HC definition and the prime limiting constraint for PV HC is the voltage violations. However, the varying definitions in different references lead to the conclusion that, neither the reference values nor the limiting factors are unique values and HC can alter depending on the reference, network conditions, topology, location, and PV deployment scenario.

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“…Indeed, these models may be adapted to this new paradigm, with the help of present innovative solutions such as LV network-monitoring technologies and MV/LV state estimation algorithms [22]. Particularly, hosting capacity approaches are strongly conditioned by the nominal admissible limits on the network element of study [21] or the number and characteristics of scenarios considered [23], while demand side management requires the development of models oriented to facilitate end users' decision-making [24] and read locational market signals in order to boost participation in LV networks [20].…”

Section: Introductionmentioning

confidence: 99%

Data Analytics-Based Multi-Objective Particle Swarm Optimization for Determination of Congestion Thresholds in LV Networks

2019

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A growing presence of distributed energy resources (DER) and the increasingly diverse nature of end users at low-voltage (LV) networks make the operation of these grids more and more challenging. Particularly, congestion and voltage management strategies for LV grids have usually been limited to some elemental criteria based on human experience, asset oversizing, or grid reinforcement. However, with the current massive deployment of sensors in modern LV grids, new approaches are feasible for distribution network assets operation. This article proposes a multi-objective particle swarm optimization (MOPSO) approach, combined with data analytics through affinity propagation clustering, for congestion threshold determination in LV grids. A real case study from the smart grid of Smartcity Malaga Living Lab is used to illustrate the proposed approach. Within this approach, distribution system operators (DSOs) can take decisions in order to prevent situations of risk or potential failure at LV grids.

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Increasing PV hosting capacity in LV grids with a probabilistic planning approach

Cited by 10 publications

References 2 publications

Solar photovoltaic-based microgrid hosting capacity evaluation in electrical energy distribution network with voltage quality analysis

Solar photovoltaic-based microgrid hosting capacity evaluation in electrical energy distribution network with voltage quality analysis

Review on the PV Hosting Capacity in Distribution Networks

Data Analytics-Based Multi-Objective Particle Swarm Optimization for Determination of Congestion Thresholds in LV Networks

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