Fostering Offshore Wind Integration in Europe through Grid Connection Impact Assessment

被引:7
作者
Amaro, Nuno [1 ]
Egorov, Aleksandr [1 ]
Gloria, Goncalo [1 ]
机构
[1] Ctr Invest Energia REN State Grid, R&D NESTER, P-2835659 Sacavem, Portugal
关键词
nodal capacity; offshore wind; RES integration; ARCWIND; OPTIMAL POWER-FLOW; DISTRIBUTED GENERATION; NETWORK CAPACITY; SYSTEMS;
D O I
10.3390/jmse10040463
中图分类号
U6 [水路运输]; P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
Floating offshore wind energy is one of the solutions that can foster the ongoing climate transition in Europe. The ARCWIND project aims to contribute to this topic by considering multiple research activities designed to contribute to the development of multiple floating technologies, identifying high-potential deployment areas while considering their economic viability and the impact that these would have in existing power systems. Regarding the latter activity, a two-step methodology was implemented to first calculate the nodal capacity that existing electricity networks have to absorb energy from these potential new wind farms and secondly to assess the impact at the point of connection. This assessment is performed by identifying grid reinforcement needs, verifying the impact on short circuit current levels and measuring the impact on the existing energy mix at countrywide level. This article includes the description of this methodology as well as its application to six different use cases covering five European countries: Portugal, Spain, France, the United Kingdom, and Ireland. Results obtained seem to indicate that, in most cases, the current power systems have enough capacity for the possible connection of new floating offshore wind farms without major reinforcement needs and that these wind farms can have a major contribution to the countries' energy mix and to the achievement of established climate targets.
引用
收藏
页数:13
相关论文
共 20 条
[1]  
Amaro e N., 2018, Em: 2018 International Conference on Smart Energy Systems and Technologies (SEST), P1, DOI [DOI 10.1109/SEST.2018.8495676, 10.1109/SEST.2018.8495676]
[2]  
Amaro N., 2020, DEV RENEWABLE ENERGI, V1st, P6, DOI [10.1201/9781003134572, DOI 10.1201/9781003134572]
[3]   Optimizing nodal capacity allocation using risk assessment of element failure rate [J].
Amaro, Nuno ;
Carrola, Francisco ;
Reis, Francisco .
2020 IEEE 14TH INTERNATIONAL CONFERENCE ON COMPATIBILITY, POWER ELECTRONICS AND POWER ENGINEERING (CPE-POWERENG), VOL 1, 2020, :44-49
[4]  
[Anonymous], 2021, Plano de Desenvolvimento e Investimento da RNTIAT 2022-31
[5]  
ENTSO-E, 2018, ENTSO-E Grid Model for TYNDP 2018
[6]  
Gupta P., 2014, Int. Conf. Recent Adv. Innov. Eng.', Jaipur, P1, DOI 10.1109/POWERI.2014.7117648
[7]   Optimal power flow evaluation of distribution network capacity for the connection of distributed generation [J].
Harrison, GP ;
Wallace, AR .
IEE PROCEEDINGS-GENERATION TRANSMISSION AND DISTRIBUTION, 2005, 152 (01) :115-122
[8]  
IEA, 2021, IEA GLOB EN CO 2 STA
[9]   Optimal distributed generation allocation in radial distribution systems considering customer-wise dedicated feeders and load patterns [J].
Kanwar, Neeraj ;
Gupta, Nikhil ;
Niazi, K. R. ;
Swarnkar, Anil .
JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY, 2015, 3 (04) :475-484
[10]   State-of-the-Art Techniques and Challenges Ahead for Distributed Generation Planning and Optimization [J].
Keane, Andrew ;
Ochoa, Luis F. ;
Borges, Carmen L. T. ;
Ault, Graham W. ;
Alarcon-Rodriguez, Arturo D. ;
Currie, Robert A. F. ;
Pilo, Fabrizio ;
Dent, Chris ;
Harrison, Gareth P. .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2013, 28 (02) :1493-1502