Solar PV Stochastic Hosting Capacity Assessment Considering Epistemic (E) Probability Distribution Function (PDF)
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 influe...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-12-01
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| Series: | Electricity |
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| Online Access: | https://www.mdpi.com/2673-4826/3/4/29 |
| _version_ | 1827640604305129472 |
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| author | Enock Mulenga |
| author_facet | Enock Mulenga |
| author_sort | Enock Mulenga |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-09T17:01:59Z |
| format | Article |
| id | doaj.art-dca900803f9a463c9dcc529d6d8d042f |
| institution | Directory Open Access Journal |
| issn | 2673-4826 |
| language | English |
| last_indexed | 2024-03-09T17:01:59Z |
| publishDate | 2022-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electricity |
| spelling | doaj.art-dca900803f9a463c9dcc529d6d8d042f2023-11-24T14:29:07ZengMDPI AGElectricity2673-48262022-12-013458659910.3390/electricity3040029Solar PV Stochastic Hosting Capacity Assessment Considering Epistemic (E) Probability Distribution Function (PDF)Enock Mulenga0Electric Power Engineering, Division of Energy Science, Department of Engineering Sciences and Mathematics (TVM), Luleå University of Technology, 93187 Skellefteå, SwedenThis 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.https://www.mdpi.com/2673-4826/3/4/29hosting capacityMonte Carlo methodssolar powerstochastic assessmentuncertainty |
| spellingShingle | Enock Mulenga Solar PV Stochastic Hosting Capacity Assessment Considering Epistemic (E) Probability Distribution Function (PDF) Electricity hosting capacity Monte Carlo methods solar power stochastic assessment uncertainty |
| title | Solar PV Stochastic Hosting Capacity Assessment Considering Epistemic (E) Probability Distribution Function (PDF) |
| title_full | Solar PV Stochastic Hosting Capacity Assessment Considering Epistemic (E) Probability Distribution Function (PDF) |
| title_fullStr | Solar PV Stochastic Hosting Capacity Assessment Considering Epistemic (E) Probability Distribution Function (PDF) |
| title_full_unstemmed | Solar PV Stochastic Hosting Capacity Assessment Considering Epistemic (E) Probability Distribution Function (PDF) |
| title_short | Solar PV Stochastic Hosting Capacity Assessment Considering Epistemic (E) Probability Distribution Function (PDF) |
| title_sort | solar pv stochastic hosting capacity assessment considering epistemic e probability distribution function pdf |
| topic | hosting capacity Monte Carlo methods solar power stochastic assessment uncertainty |
| url | https://www.mdpi.com/2673-4826/3/4/29 |
| work_keys_str_mv | AT enockmulenga solarpvstochastichostingcapacityassessmentconsideringepistemiceprobabilitydistributionfunctionpdf |