Abstract
The hosting capacity determines the grid ability to host integrated installations, where mutual-limitations among points of connection (POCs) are important and formulate a combinational feasible region. Intended to assess such interdependence for defining the region, this article proposes a multidimensional hosting capacity region derivation scheme in a radial grid. As this scheme can be designed conservative, from a risk-averse viewpoint, it gains significant acceptance in the industrial sector. This multidimensional region not only exploits grid power delivery potential, but also aids in making grid congestion management decisions. A typical 10.5 kV Dutch grid case has been tested accordingly, and corresponding results have confirmed the conservative property preservation of the region. The case study demonstrates that compared to the original hosting capacity concept, the region hypervolume gain ratio remains higher than 1.94. With proper measure selection, the estimated region occupation ratio can keep up to 92.50%. The congestion management decision computation time can also be reduced by 58.0% compared to that using the monolithic model. The effectiveness of the proposed scheme and its advantages in grid congestion management have been successfully confirmed.
| Original language | English |
|---|---|
| Article number | 10283913 |
| Pages (from-to) | 5024 - 5035 |
| Number of pages | 12 |
| Journal | IEEE Transactions on Power Systems |
| Volume | 39 |
| Issue number | 3 |
| Early online date | 12 Oct 2023 |
| DOIs | |
| Publication status | Published - 1 May 2024 |
Funding
This work was supported in part by the New Energy and mobility Outlook for the Netherlands (NEON) through Project 17628 and in part by NWO (the Dutch Research Council).
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- hosting capacity
- power quality
- feasible region
- multidimensional geometry
- Reactive power
- Power cables
- Voltage
- Impedance
- Solar panels
- Load modeling
- Testing
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