Knowledge Agora



Similar Articles

Title Drivers of Effective Renewable Energy Policies
ID_Doc 76450
Authors Treki, A; Urban, B
Title Drivers of Effective Renewable Energy Policies
Year 2015
Published Inzinerine Ekonomika-Engineering Economics, 26, 3
Abstract Sustainability and green issues are becoming an integral part of business and management. Large gird connected renewable energy (RE) facilities form a subset of sustainability and the clean technology sector. From a business perspective, it is important to understand what policies are available and what factors (drivers) play a key role. This study identifies five main RE policy mechanisms (Feed-In Tariffs (FITs); Tradable Green Certificates; Renewable Portfolio Standards; Bidding/Tendering and Fiscal) of which the FIT has experienced the most success in establishing a RE sector. Using Fuzzy Cognitive Mapping (FCM), the study relates the policies to the drivers to identify which drivers are most effective within a RE sector. The development and analysis of the model is based on an iterative process, where the draft FCM was adapted to fit a representative model and then further validated by applying country specific examples. Results indicate that all simulations reached an equilibrium state in the FCM model. The four drivers, observed as the most influential drivers, as set out in the propositions are: big players (category: local conditions), non-RE sector (category: economics), cost competitiveness (category: financial) and risk (category: financial). These four drivers seem to play the most influential part of a RE sector when a FIT policy mechanism is deployed. It is proposed that these four drivers are best suited to model a FIT system. This study is one of the first to empirically examine how various drivers emerge and how they need to be managed when designing a RE policy mechanism. Managing the four key drivers - as identified in this study - is pivotal in establishing a sustainable RE sector.
PDF https://inzeko.ktu.lt/index.php/EE/article/download/4884/6897

Similar Articles

ID Score Article
77846 Rieksta, M; Bazbauers, G; Blumberga, A; Blumberga, D Mapping of New Business Models in Domains of Technologies and Energy for Modelling of Dynamics of Clean Energy Transition(2021)Environmental And Climate Technologies, 25, 1
Scroll