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When new energy efficient products are struggling with their commercialisation and diffusion into widespread applications you would typically expect policy-makers and green lead-users to guide the way. This paper examines the case of the hot water circulator pump industry in Europe, where parts of the industry envisioned and worked for a voluntary energy label, bringing technological innovation, new business and energy savings of approx. 85% for each new circulator pump. The case study explores the complexities of innovation processes where technology, market, actors and policy co-evolve over time to transform an existing socio-technical regime. The paper highlights the importance of policies to reduce barriers towards innovation and energy efficiency and shows that it is not always policy-makers that establish the crucial policies that change the innovation dynamics for the benefit of the environment and the industry. [ABSTRACT FROM AUTHOR]

This paper summarises the results of a study to identify and quantify the potential impact of measures and policies to reduce the energy consumption of air conditioning in European countries over a 10-year period. The market penetration of air conditioning in Europe has increased steadily over several decades. On a “business as usual” basis, its energy consumption would increase by over 50% by 2020. Measures to restrict this increase are therefore important, but the savings potential straddles several overlapping areas which are subject to different constraints including those imposed by the replacement rates of systems and products, and the refurbishment rates of existing buildings. This work reported in this paper is based on the use of information from a variety of sources in a highly disaggregated model to assess the “realisable” savings over a 10-year period, taking into account relevant constraints. The paper summarises results at a European level, focussing on those cases that generate the greatest realisable savings. Savings are possible in three areas: improved equipment and system efficiency, reduced cooling loads, and more effective operation. The cases that offer the largest savings provide the basis for recommendations for policy measures, often using existing policy instruments. In addition, areas where further work is needed are identified. More detailed results and information about the study and additional recommendations can be found at http://www.bre.co.uk/searchresults.jsp?category=5&q=energy+management [1] . [ABSTRACT FROM AUTHOR]

The European Energy Efficiency Directive requests the application of high quality and cost effective energy audits across Europe. The potential of up to 20% of energy savings shall be realized to follow the strategy of smart, sustainable, and inclusive growth. A number of barriers must be tackled to implement the Directive, especially among small and medium sized enterprises (SMEs). A large number of cost effective energy efficiency measures remains unimplemented because of financial reasons, a lack of information, and limited in-house skills. Information measures, audits, capacity buildings are suggested as potentially effective measures to support implementation of energy efficiency measures. Within the work described in this paper, an auditing approach was developed, focusing on modelling the energy consumption of an SME. The model of the energy consumption is built using simple MS Excel tools, dividing the process into unit operations and attributing annual consumption to these units, from measurements or by calculation. Consumption is linked to drivers of consumption and corresponding losses, thus developing an understanding of the origin of energy consumption, priorities, and the potential for reduction. The approach simultaneously addresses the needs for the identification of measures, capacity building, information and awareness raising. The auditing approach was tested with 280 companies in Austria, Bulgaria, Cyprus, Italy, Romania, Slovakia and Spain. A wide range of energy efficiency measures was identified and implemented, partly consisting of no-cost options, but partly also innovative technical solutions. Over EUR 10 million investments with a simple payback time of less than three years were triggered. 6500 toe per year of primary energy savings were realized, as well as greenhouse gas emission reductions of 13,500 tonnes per year. [ABSTRACT FROM AUTHOR]

Increasing the energy efficiency of the built environment has become a priority worldwide and especially in Europe. Because of the relatively low turnover rate of the existing built environment, energy efficiency retrofitting appears to be a fundamental step in reducing its energy consumption. Last experiences have shown that there is a vast energy efficiency potential lying in the building stock, and it is mainly untapped. One of the reasons is a lack of robust methodologies able to evaluate the effect of applied energy efficiency measures and inform about the expected impact of potential retrofitting strategies. Nowadays, dynamic measured data coming from automated metering infrastructure provides valuable information to evaluate the effect of energy conservation strategies. For this reason, energy performance modeling and assessment methods based on this data are starting to play a major role. In this paper, several methodologies for the measurement and verification of energy savings, and for the prediction and recommendation of energy retrofitting strategies, are analysed in detail. Practitioners looking at different options for these two processes, will find in this review a thorough and detailed overview of the different methods that can be used. Guidance is also provided to determine which method could work best depending on the specific case under analysis. The reviewed approaches include statistical learning models, machine learning models, Bayesian methods, deterministic approaches, and hybrid techniques that combine deterministic and data-driven modeling. Existing research gaps are identified and prospects for future investigation are presented within the main conclusions of this research work. • Novel techniques to estimate energy efficiency savings in buildings were reviewed. • Techniques to plan energy retrofitting strategies in buildings were reviewed. • The focus is on data-driven methods (statistical, machine learning, Bayesian). • Strengths and weaknesses of every method are analysed. • Research gaps and prospects for future investigation are presented. [ABSTRACT FROM AUTHOR]