offshore wind;
meso-scale models;
hybrid AC-DC optimal power flow;
wind power variability;
DC offshore grid;
D O I:
10.3390/resources3020454
中图分类号:
X [环境科学、安全科学];
学科分类号:
08 ;
0830 ;
摘要:
This paper evaluates, for a 2030 scenario, the impact on onshore power systems in terms of the variability of the power generated by 81 GW of offshore wind farms installed in the North Sea. Meso-scale reanalysis data are used as input for computing the hourly power production for offshore wind farms, and this total production is analyzed to identify the largest aggregated hourly power variations. Based on publicly available information, a simplified representation of the coastal power grid is built for the countries bordering the North Sea. Wind farms less than 60 km from shore are connected radially to the mainland, while the rest are connected to a hypothetical offshore HVDC (High-Voltage Direct Current) power grid, designed such that wind curtailment does not exceed 1% of production. Loads and conventional power plants by technology and associated cost curves are computed for the various national power systems, based on 2030 projections. Using the MATLAB-based MATPOWER toolbox, the hourly optimal power flow for this regional hybrid AC/DC grid is computed for high, low and medium years from the meso-scale database. The largest net load variations are evaluated per market area and related to the extra load-following reserves that may be needed from conventional generators.
机构:
Tech Univ Berlin, Inst Energy Technol, Dept Digital Transformat Energy Syst, D-10623 Berlin, GermanyTech Univ Berlin, Inst Energy Technol, Dept Digital Transformat Energy Syst, D-10623 Berlin, Germany
Neumann, Fabian
Brown, Tom
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机构:
Tech Univ Berlin, Inst Energy Technol, Dept Digital Transformat Energy Syst, D-10623 Berlin, GermanyTech Univ Berlin, Inst Energy Technol, Dept Digital Transformat Energy Syst, D-10623 Berlin, Germany
机构:
Univ Groningen, Groningen Ctr Energy Law & Sustainabil, Groningen, NetherlandsUniv Groningen, Groningen Ctr Energy Law & Sustainabil, Groningen, Netherlands