Comparison of Different References When Assessing PV HC in Distribution Networks

Fatima, Samar; Püvi, Verner; Lehtonen, Matti

doi:10.3390/cleantechnol3010008

Cited by 4 publications

(2 citation statements)

References 15 publications

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“…This is because the customers in an area have different loading profiles based on different percentage contributions of heating modes as shown in Table 3. The heating modes and their significance in the context of Finnish low voltage networks have been discussed in [31]. The information regarding the cost parameters of transformers and cables is based on data by Finnish Energy Authority [32].…”

Section: Methodsmentioning

confidence: 99%

Comparison of Economical and Technical Photovoltaic Hosting Capacity Limits in Distribution Networks

et al. 2021

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Power distribution networks are transitioning from passive towards active networks considering the incorporation of distributed generation. Traditional energy networks require possible system upgrades due to the exponential growth of non-conventional energy resources. Thus, the cost concerns of the electric utilities regarding financial models of renewable energy sources (RES) call for the cost and benefit analysis of the networks prone to unprecedented RES integration. This paper provides an evaluation of photovoltaic (PV) hosting capacity (HC) subject to economical constraint by a probabilistic analysis based on Monte Carlo (MC) simulations to consider the stochastic nature of loads. The losses carry significance in terms of cost parameters, and this article focuses on HC investigation in terms of losses and their associated cost. The network losses followed a U-shaped trajectory with increasing PV penetration in the distribution network. In the investigated case networks, increased PV penetration reduced network costs up to around 40%, defined as a ratio to the feeding secondary transformer rating. Above 40%, the losses started to increase again and at 76–87% level, the network costs were the same as in the base cases of no PVs. This point was defined as the economical PV HC of the network. In the case of networks, this level of PV penetration did not yet lead to violations of network technical limits.

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Section: Methodsmentioning

confidence: 99%

Comparison of Economical and Technical Photovoltaic Hosting Capacity Limits in Distribution Networks

et al. 2021

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“…Their studies show that relying only on software tools may mislead investors during the decision-making process, as in most of these tools, installation costs, maintenance costs, net metering options, and taxation schemes are not included. The focus in [20] is on assessing the threshold of PV penetration, known as hosting capacity (HC) of PV integration, in low-voltage distribution systems. To this end, the HC values of three types of networks in rural, suburban, and urban regions for different HC reference definitions were compared.…”

Section: A Short Review Of the Contributions In This Issuementioning

confidence: 99%

Integration and Control of Distributed Renewable Energy Resources

Nazaripouya

2022

Clean Technol.

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Solar PV Stochastic Hosting Capacity Assessment Considering Epistemic (E) Probability Distribution Function (PDF)

Mulenga

2022

Electricity

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This paper presents a stochastic approach to assessing the hosting capacity for solar PV. The method is part of the optimal techniques for the integration of renewables. There are two types of uncertainties, namely aleatory and epistemic uncertainties. The epistemic and aleatory uncertainties influence distribution networks’ hosting capacity differently. The combination of the two uncertainties influences the planning of distribution networks. The study introduces and considers the epistemic probability distribution function (pdf). DSO does take levels of risk for a parameter violation when planning. Epistemic pdf is a range of values of the planning risk margin for quantifying the hosting capacity. The planning risk acknowledges that overvoltages may occur at weaker conceivable locations in a distribution network. In the paper, it has been shown that the number of customers who will be able to connect solar PV in future is influenced by the DSO’s planning risk margin. The DSO can be stricter or less strict in planning risk margin. It has been concluded that fewer customers can connect solar PV to a distribution network when a DSO takes a stricter planning risk. Alternatively, more customers can connect solar PV units for a less strict planning risk. How stricter or less strict the DSO is with the planning risk margin determines the investment needed for mitigation measures. The mitigation measures in the future will lead to not exceeding the overvoltage limit when solar PV is connected to the weaker conceivable points of the distribution network.

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Comparison of Different References When Assessing PV HC in Distribution Networks

Cited by 4 publications

References 15 publications

Comparison of Economical and Technical Photovoltaic Hosting Capacity Limits in Distribution Networks

Comparison of Economical and Technical Photovoltaic Hosting Capacity Limits in Distribution Networks

Integration and Control of Distributed Renewable Energy Resources

Solar PV Stochastic Hosting Capacity Assessment Considering Epistemic (E) Probability Distribution Function (PDF)

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