Market-pull policies to promote renewable energy: A quantitative assessment of tendering implementation

被引:32
作者
Bento, Nuno [1 ]
Borello, Mattia [2 ]
Gianfrate, Gianfranco [3 ]
机构
[1] IUL, ISCTE, DINAMIACET, Av Forcas Armadas, P-1649026 Lisbon, Portugal
[2] Bocconi Univ, Via Roberto Sarfatti 25, I-20136 Milan, Italy
[3] EDHEC Business Sch, 393 Promenade Anglais 393,BP3116, F-06202 Nice 3, France
关键词
Policy assessment; Synthetic control; Investment; Tendering; Renewable energy; FEED-IN TARIFFS; ELECTRICITY; SUPPORT; AUCTIONS; EFFICIENCY; LESSONS; GROWTH;
D O I
10.1016/j.jclepro.2019.119209
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Policymakers ideally select the support mechanism that better foments renewable energy production at the lowest cost to comply with international climate agreements. Currently, tendering is the fastest rising scheme. Yet a quantitative assessment of its performance in the literature is missing. We assess the effect of the introduction of auctions in accelerating the addition of renewable capacity through three econometric models: fixed-effects multivariate regression, statistical matching and synthetic control. The dataset includes 20 developed countries, spanning from 2004 to 2014, and both macroeconomic and policy drivers. Results show that tendering has the strongest effects to promote net renewable capacity comparing to other mechanisms like feed-in tariffs. Countries implementing tendering on average have a higher addition of net capacity of renewables in the order of 1000-2000MW annually. The positive effect of tenders is clearer when analyzing with synthetic controls the case of Italy: while tendering enhances the deployment of renewables, policy instability jeopardizes the sustainability of tendering's impact. (c) 2019 Elsevier Ltd. All rights reserved.
引用
收藏
页数:13
相关论文
共 45 条
[41]   A Market Assessment of Distributed Battery Energy Storage to Facilitate Higher Renewable Penetration in an Isolated Power System [J].
McIlwaine, Neil ;
Foley, Aoife M. ;
Al Kez, Dlzar ;
Best, Robert ;
Lu, Xi ;
Zhang, Chongyu .
IEEE ACCESS, 2022, 10 :2382-2398
[42]   Quantitative assessment of sustainable renewable energy through soft computing: Fuzzy AHP-TOPSIS method [J].
Alghassab, Mohammed .
ENERGY REPORTS, 2022, 8 :12139-12152
[43]   Competitiveness of renewable energies for heat production in individual housing: A multicriteria assessment in a low-carbon energy market [J].
Fito, J. ;
Dimri, N. ;
Ramousse, J. .
ENERGY AND BUILDINGS, 2021, 242
[44]   Opportunity Assessment of Virtual Power Plant Implementation for Sustainable Renewable Energy Development in Indonesia Power System Network [J].
Setiawan, Agus ;
Jufri, Fauzan Hanif ;
Dzulfiqar, Fatih ;
Samual, Muhammad Gillfran ;
Arifin, Zainal ;
Angkasa, Fahmi Firdaus ;
Aryani, Dwi Riana ;
Garniwa, Iwa ;
Sudiarto, Budi .
SUSTAINABILITY, 2024, 16 (05)
[45]   Assessment of renewable energy alternatives for sustainable resource policies with knowledge-based expert prioritized quantum picture fuzzy rough modelling [J].
Dincer, Hasan ;
Yuksel, Serhat ;
Pedrycz, Witold .
EXPERT SYSTEMS WITH APPLICATIONS, 2025, 273