A flexible stochastic PV hosting capacity framework considering network over-voltage tolerance

Esau, Zulu; Hara, Ryoichi; Kita, Hidetoshi

doi:10.1016/j.egyr.2022.11.101

Cited by 7 publications

(5 citation statements)

References 8 publications

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“…Unlike the gradient-based PSO, the proposed approach only applies the GD component to the particle velocity component given in ( 2). This modification is shown in equation (13).…”

Section: Proposed Hybrid Pso-gd Algorithmmentioning

confidence: 99%

“…The PVHC estimation problem is formulated as a maximization problem in the form of mixed integer, non-linear programming (MINLP), shown in Equations ( 16)-( 22) [13,15,[20][21][22]24,39].…”

Section: Problem Formulationmentioning

confidence: 99%

“…There are two distinct methods used for PVHC estimation: the stochastic or probabilistic approach and the deterministic approach [11,13]. The stochastic approach is widely used, especially in the case of many small-scale PVs.…”

Section: Introductionmentioning

confidence: 99%

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An Efficient Hybrid Particle Swarm and Gradient Descent Method for the Estimation of the Hosting Capacity of Photovoltaics by Distribution Networks

2023

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With many distribution networks adopting photovoltaic (PV) generation systems in their networks, there is a significant risk of over-voltages, reverse power flow, line congestion, and increased harmonics. Therefore, there is a need to estimate the amount of PV that can be injected into the distribution network without pushing the network towards these threats. The largest amount of PV a distribution system can accommodate is the PV hosting capacity (PVHC). The paper proposes an efficient method for estimating the PVHC of distribution networks that combines particle swarm optimization (PSO) and the gradient descent algorithm (GD). PSO has a powerful exploration of the solution space but poor exploitation of the local search. On the other hand, GD has great exploitation of local search to obtain local optima but needs better global search capabilities. The proposed method aims to harness the advantages of both PSO and GD while alleviating the ills of each. The numerical case studies show that the proposed method is more efficient, stable, and superior to the other meta-heuristic approaches.

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“…Unlike the gradient-based PSO, the proposed approach only applies the GD component to the particle velocity component given in ( 2). This modification is shown in equation (13).…”

Section: Proposed Hybrid Pso-gd Algorithmmentioning

confidence: 99%

“…The PVHC estimation problem is formulated as a maximization problem in the form of mixed integer, non-linear programming (MINLP), shown in Equations ( 16)-( 22) [13,15,[20][21][22]24,39].…”

Section: Problem Formulationmentioning

confidence: 99%

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An Efficient Hybrid Particle Swarm and Gradient Descent Method for the Estimation of the Hosting Capacity of Photovoltaics by Distribution Networks

2023

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“…In the coming years, distributed generation systems will increase the energy's potential of those countries that are taking appropriate measures to change the energy matrix and introducing renewable energies as an alternative, especially solar energy, as a global trend (Esau et al, 2023).…”

Section: Introductionmentioning

confidence: 99%

Data-driven Model-free Hosting Capacity Estimation in a Low Voltage Prosumer

Andagoya Alba,

Jara,

Catota

et al. 2024

Conectividad

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Currently, distributed generation systems have been proposed as a way to increase the energy potential of the countries introducing them, however, the entry of this new form of energy generation can cause some negative effects on the correct operation of the distribution network, one of these negative effects are the overvoltages that can exceed the levels allowed by the local operator. For this reason, it is necessary to limit in some way the injection of distributed generation into the grid. This parameter has been called Hosting Capacity, which is a new parameter developed to limit the power coming from distributed sources while maintaining the proper functioning of the grid. Many studies have been developed to define and calculate the Hosting Capacity, mainly based on scenario simulations, however, these need detailed and accurate network models which at low voltage levels is very difficult to have. The present work focuses on determining a Hosting Capacity value in a node at low voltage using values taken from a smart meter, the methodology uses a regression model considering voltage and power consumption values at the point. The results show a good approximation of Hosting Capacity validated through a network model of the connection node obtaining voltage values close to the limit, but lower than it, which allows the conclusion that the planted methodology is useful for the calculation of Hosting Capacity without the need for having a network model.

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“…A rapid increase in PV capacity will cause negative effects on the grid, such as overvoltage, and potential reserve power flow (which can damage/affect the operation of the protection system) from line congestion which leads to additional heat in the conductors and cables. This makes it important to determine the limit of PV that can be injected into the grid, without forcing the operating performance indicators in extreme failure conditions (Esau et al, 2023). The limit of PV systems that can be integrated into the electricity network can be defined as the PV Hosting Capacity (PVHC).…”

Section: Introductionmentioning

confidence: 99%

Effect of PLTS power factor settings on power losses and voltage conditions in 20 kV medium voltage networks

Savira,

Sudiarto

2023

JPTK

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As technology develops, the rapid increase in PV capacity will affect the grid. This makes it important to determine the PV limit that can be injected into the grid defined as the PV Hosting Capacity (PVHC). In this paper, the author evaluates and analyses the impact of PV connections on medium voltage distribution lines (20kv) using ETAP 19.01 simulation. A medium voltage Grid with a capacity of 30MVA, has an industrial load varies from 650 kVA to 25 kVA with the total load capacity of 2225 KVA. The loads are supplied from two sources, grid and PV system. The simulation results state that the best of grid performance which provide the best losses and voltage condition when connecting 100% capacity of PV to the existing grid network is by setting the inverter power factor to 0.9. This setting will provide lowest power losses of 0,7 kW and improve the voltage value.

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A flexible stochastic PV hosting capacity framework considering network over-voltage tolerance

Cited by 7 publications

References 8 publications

An Efficient Hybrid Particle Swarm and Gradient Descent Method for the Estimation of the Hosting Capacity of Photovoltaics by Distribution Networks

An Efficient Hybrid Particle Swarm and Gradient Descent Method for the Estimation of the Hosting Capacity of Photovoltaics by Distribution Networks

Data-driven Model-free Hosting Capacity Estimation in a Low Voltage Prosumer

Effect of PLTS power factor settings on power losses and voltage conditions in 20 kV medium voltage networks

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