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Increasing energy prices and market volatilities force energy intensive industries to implement energy management systems in order to ensure competitiveness. In this paper, we focus on the strategic level of energy management, specifically, on the analysis of the internal and external conditions that form the basis for strategic development. For this, we selected the case of the Austrian paper and pulp industry. We applied a hybrid method by combining an analysis of strengths, weaknesses, opportunities and threats with an analytic hierarchy process which was based on a survey of expert opinion. The results show that cost-related factors predominate. According to our analysis, the four most important factors are all directly linked to energy costs, energy efficiency, and the energy market. Experts pay little attention to environmental issues or to energy market volatilities. Apart from that, the combination of an analysis of strengths, weaknesses, opportunities and threats with an analytic hierarchy process promises to be a valuable tool for strategic energy management. This is especially true for energy intensive companies and/or sectors, since it enables decision makers to take strategic decisions based on a systematic understanding of the main issues. [ABSTRACT FROM AUTHOR]

Globally, small and medium-sized enterprises (SMEs) constitute a significant industrial segment. However, their energy-efficiency potential has remained largely untapped due to several barriers. The prevailing approaches on energy optimization in the energy-intensive SMEs are focused on the technological improvements at the operational level and lack a strategic approach. This study developed an energy management system (EnMS) for SMEs by integrating technical and managerial energy saving activities (ESAs), suggested in energy management literature. The proposed EnMS adopted a PDCA (Plan-Do-Check-Act) process approach for consistent energy efficiency and cleaner production. For the validation of the proposed EnMS, a case of small-sized Indian paper mill was selected. The case exhibited the ramp of continuous improvement in the energy efficiency at the mill by illustrating two PDCA cycles. Step I (Plan) involved creating energy management roles with management support, energy auditing, identifying energy-saving opportunities and developing action plan; step II (Do) was about creating communication, awareness and motivation before the implementation of the action plan; step III (Check) involved periodic monitoring, analysis and reporting of the energy key performance indicators (KPIs), and benchmarking enterprise energy performance. The case analysis showed a 35% reduction in specific energy consumption (SEC) of one of the Paper Machine's (PM) vacuum system by the implementation of ESAs for vacuum optimization, generating an annual energy-saving of 0.3 GJ/t. In step IV, the subsequent PDCA cycle was triggered by the biannual management review for exploring the new energy saving opportunities at the enterprise. The next improvement cycle targeted at steam and condensate system optimization in another PM resulted in an additional energy cost saving of USD 26,900. [ABSTRACT FROM AUTHOR]

In today's manufacturing scenario, rising energy prices, increasing ecological awareness, and changing consumer behaviors are driving decision-makers to prioritize green manufacturing. The Internet of Things paradigm promises to increase the visibility and awareness of energy consumption, thanks to smart sensors and smart meters at the machine and production line level. Consequently, real-time energy consumption data from manufacturing processes can be collected easily, and then analyzed, to improve energy-aware decision-making. Relying on a comprehensive literature review and on experts' insight, this paper contributes to the understanding of energy-efficient production management practices that are enhanced and enabled by the Internet of Things technology. In addition, it discusses the benefits that can be obtained thanks to adopting such management practices. Eventually, a framework is presented to support the integration of gathered energy data into a company's information technology tools and platforms. This is done with the ultimate goal of highlighting how operational and tactical decision-making processes could leverage on such data in order to improve energy efficiency, and therefore competitiveness, of manufacturing companies. With the outcomes of this paper, energy managers can approach the Internet of Things adoption in a benefit-driven manner, addressing those energy management practices that are more aligned with company maturity, measurable data and available information systems and tools. [ABSTRACT FROM AUTHOR]

Abstract: The EU has established so-called 20–20–20 targets, which in relation to energy mean that each Member State shall improve energy intensity levels by 3.3% annually, leading to a reduced primary energy use of 20% by the year 2020, calculated from a projected level based on the primary energy use in 2005. Sweden has established a less ambitious target of 1.7% annual energy intensity improvement through 2020. The aim of this paper is to evaluate, ex-ante, the EU 2020 primary energy target for the Swedish industrial sector. An applied backcasting methodology is used. The assessment made in this paper is that actions that lead to between 31.6 and 33.2 TWh/year reductions in energy end-use are needed if the EU target is to be achieved. Results from this paper shows that the current energy policy instruments are not sufficient to the EU or Swedish targets. Estimations in this paper are that a primary energy target of about 22.3 TWh/year is reasonable. The paper concludes by presenting a roadmap on how the Swedish 2020 target can be achieved through: i) energy management; ii) energy-efficient technology; and iii) energy supply measures, with an approximate cost of 280–300 MEUR or 75–80 kWh per public EUR. Three major additional policy measures are needed compared with the current policy: including all energy carriers, not just electricity, in the Swedish long-term agreements program PFE; setting up networks; and making it possible for third parties, i.e., industry, to deliver excess heat into the monopolized Swedish district heating grids. [Copyright &y& Elsevier]

Fuel poverty is a recognized and increasing problem in several European countries. A growing body of literature covers this topic, but dedicated analysis for Portugal are scarce despite the high perception of this condition. This paper contributes to fill this knowledge gap focusing on a European southern city while bringing new datasets and analysis to the assessment of this topic; consumer groups identification and to policy discussion. Daily electricity smart meters' registries were combined with socio-economic data, collected from door-to-door surveys, to understand the extent and the determinants of energy consumption for two contrasting consumer groups (herein called fuel poverty and fuel obesity groups). The analysis is based on the amount and annual profile of electricity consumption and was complemented with building energy simulations for relevant building typologies in those groups, to identify heating and cooling thermal performance gaps. The existence of these gaps allowed confirming and/or discarding the initial hypothesis of the poverty or obesity conditions. Results disclose socio-economic variables, as income, and consumers' behavior as key determinants of electricity consumption. It was identified a severe lack of thermal comfort levels inside households of both groups, either in cooling (98% for fuel poverty and 87% for fuel obesity) and heating seasons (98% for fuel poverty and 94% for fuel obesity). Major conclusion refers that electricity consumption cannot be used alone to segment consumer groups. This assessment may serve to support energy policy measures and instruments targeted to different consumers' groups. For example, distinct campaigns and differentiated incentives may apply to achieve energy efficiency and reduction while keep or improve indoor comfort levels. [ABSTRACT FROM AUTHOR]

Energy management has been considered in the global agenda as a way to improve energy performance and greenhouse gas reduction in organizations. Industries account for a significant part of energy use worldwide and present opportunities for energy efficiency improvements. Within the industry, energy management is a complex task, regarding scenarios with variables related to the following perspectives: economics, contingency, technological change and behavioural. This paper aims at analyzing the influencing factors on energy management in industries from these perspectives. A survey with 40 variables was carried out with middle managers from different industrial sectors in Brazil. The variables were divided into three groups: drivers for investments in energy efficiency; organizational processes and actions in energy management; involvement of middle managers. Initially, an exploratory factor analysis technique was employed aiming at specifying the main factors influencing energy management. In the sequence , a confirmatory factor analysis was used to associate the variables to the main factors as well as to know how the factors relate to each other. The study showed a positive correlation among all the factors identified. Statistical tests suggested that the factors could not be explained separately. Hypotheses tests were applied to verify the influence of the factors among the groups surveyed. The final model comprised eight factors into the three groups: organizational (strategic , operational), involvement (motivation, support), drivers (production, economics , competitiveness, environment). The results and the main implications of the study are discussed in the paper. • The main factors on energy management presented a positive correlation among them. • Middle managers' involvement influenced strategy and operation on energy management. • Middle managers' involvement depended on the support and motivation from superiors. • Operational factor on energy management influenced drivers for energy efficiency. • Production process was a driver for energy efficiency influencing energy management. [ABSTRACT FROM AUTHOR]