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Building renovation is embedded into several EU directives as a means to achieve the EU climate and energy targets, having a key role both for climate mitigation and adaptation, and the topic of several projects IEECP is working on.
“Split incentives” refer to any situation where the benefits of a transaction do not accrue to the actor who pays for the transaction. In the context of energy efficiency in buildings, split incentives are linked with cost recovery issues related to energy efficiency upgrade investments due to the failure of distributing effectively financial obligations and rewards of these investments between concerned actors [1]. Especially, when it comes to the PRS, existing literature identifies “split incentives” among landlords and tenants, as one of the main barriers when implementing energy efficiency policies to tackle energy poverty [2]. Moreover, in most European Union (EU) countries, there is significant lack of studies or estimations on the extent of the “split incentives” issue, which leads to the design of renovation policies with a subsidy rate that is not often adequate or optimised as it cannot capture the impact of “split incentives”. In this context, contributions that aim to address this gap are planned. The presentations will focus on methodologies and tools that seek to better understand the issue and enhance the uptake of energy efficiency investments in the PRS. The ENPOR Split Incentive Quantification Tool – allocates the costs and benefits of energy efficiency interventions for landlords and tenants. The tool contributes to a deeper understanding about how to tackle energy efficiency in the private rented sector. A tool that mainly aims to identify the share of the triggered benefits from the implementation of energy efficiency interventions between landlords and tenants in order to quantify the appropriate allocation of costs or subsidy rates for both sides, towards specific energy efficiency scenarios in several geographical/national contexts.
A next generation energy efficiency meter named eensight was created by SENSEI. The eensight tool is based on machine learning and will contribute to the much-needed advancement of the automated measurement and verification (M&V) methods for portfolios of buildings’ energy efficiency and provide essential insights for investors, legislators, building owners and energy companies to realise their goals. eensight is essentially an automated meter for energy savings. A key ingredient for the digitalisation of the energy efficiency-related activities.
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