Energy Performance of Italian Oil Refineries Based on Mandatory Energy Audits

Petroleum products account for the 32.3% of worldwide primary energy. There are more than 100 oil refineries in Europe that directly employ 119,000 people with a turnover of EUR 600 billion and around 1.2% to the total value added in manufacturing. Therefore, the petroleum refining sector is very important in the European economy, and its decarbonization is crucial in the energy transition. Refineries present a high degree of complexity and integration, and the continuous increase of their energy efficiency is a key topic for the sector. In this work an analysis of the energy efficiency in ten Italian refineries based on mandatory energy audits and public data is presented. The primary (0.0963 ± 0.0341 toe/t), thermal (3421.71 ± 1316.84 MJ/t), and electrical (68.20 ± 19.34 kWh/t) specific energy consumptions have been evaluated. Some insights about the impact of refined products mix (mainly driven by production of diesel fuel) and Nelson Complexity Index in energy consumption are presented. Lastly, an overview of energy performance improvement actions (EPIAs) information extracted from energy audits is presented. This work presents a first step for the benchmark of Italian refineries that should be subsequently improved.

A Methodology for the Identification and Characterization of Low-Temperature Waste Heat Sources and Sinks in Industrial Processes: Application in the Italian Dairy Sector

Waste heat recovery is considered as one of the most promising options to improve the efficiency and sustainability of industrial processes. Even though industrial waste heat is abundantly available and its utilization is not a new concept, the implementation rate of waste-heat recovery interventions in industrial facilities is still low, due to several real or perceived barriers. Foremost challenges are represented by technical, economic, financial and regulatory factors. An additional prominent barrier lies in the lack or incompleteness of information concerning the material and energy flows within the factories, and the types and characteristics of waste heat sources and possible sinks for their internal or external reuse. With the aim to overcome some of the information barriers and increase the willingness of companies to approach waste heat recovery and reuse, a methodology to map waste heat sources and sinks in industrial processes is proposed in this study. The approach here presented combines information from the most relevant publications on the subject and data gathered from the analysis of energy audits carried out by large and energy-intensive enterprises. In order to demonstrate its feasibility, the methodology was applied to the Italian dairy sector, because of its large energy consumption and its enormous potential for the utilization of low-temperature waste heat sources.

Energy-Saving Technology Opportunities and Investments of the Italian Foundry Industry

The foundry industry is regarded as one of the most energy-intensive industrial sector due to its energy consumption up to 9 MWh/ton of produced metal. As a result, many companies are trying to increase the energy efficiency of their foundry plants. Since many energy-saving technologies are proposed by manufacturers and the literature, choosing the most appropriate one is a difficult task. Moreover, being updated with the available energy-saving solutions is complicated because of the quick technology advances. Consequently, this paper aims at investigating the recent and future opportunities and investments for reducing the energy consumptions of the technologies of Italian foundry companies. Additionally, it aims at presenting a list of available technological solutions validated by Italian experts. To this end, the Energy Audits developed by 231 plants were analyzed to extract the implemented and planned interventions. Furthermore, the economic data available within the Energy Audits were studied to determine the advantages of a given technological solutions compared to the others. It emerged that the companies are strongly investing in increasing the efficiency of the auxiliary systems such as compressors and motors. The outcomes of this study can assist both researchers and energy managers in choosing the most appropriate energy-saving solutions.

From Energy Audit to Energy Performance Indicators (EnPI): A Methodology to Characterize Productive Sectors. The Italian Cement Industry Case Study

In this work, a novel methodology to assess energy performance indicators of productive and economic sectors trough the analysis of the Italian mandatory energy audits database is presented. The updating of sectoral reference energy performance indicators is fundamental for both companies and policy makers—for the formers to evaluate and compare their energy performance with competitors in order to achieve improvements and for the latter to effectively monitor the impact of energy policies. This methodology could be potentially applied to all production sectors, providing key information needed to characterize various production processes from an energy point of view. Awareness of energy efficiency and sectorial benchmarking represent the first necessary steps for companies moving towards energy transition. This paper provides details of the statistical method developed and its application to the NACE 23 division “Manufacturing of other non-metallic mineral products”, with a focus on the cement industry. For this sector, results are presented in terms of specific indicators based on energy source. General results, methodological insights, and validation of the proposed case study are discussed.

Techno-economic impact assessments of energy efficiency improvements in the industrial combustion systems

Industrial energy efficiency assessments not only provide benefits to manufacturers, but also generate significant economic and environmental benefits to localities, states, and the nation through indirect and induced benefits. Quantifying these benefits requires a systematic economic framework for capturing these interactions. This article employs methodologies for improving the energy efficiency of small and medium-size industry through their combustion systems. Combustion systems offer large opportunities to enhance energy efficiency through adopting advanced technologies and better-informed operations. The case studies presented illuminate the potential savings and impacts from implementing energy-efficient combustion recommendations and the importance of energy audits and energy efficiency in the fight against climate change. This study describes and quantifies the cascading economic and environmental impacts of implementing the industrial energy efficiency recommendations offered by an energy auditing program by participating facilities over a ten-year period. Results showed that it is expected that a total of $185M would be saved in energy costs and 2.3 million metric tons of carbon dioxide emissions would be avoided annually, and about 972 jobs could be created in the studied region if all the combustion recommendations would be implemented. The broader view afforded by the proposed study can be used to support better energy efficient practices in manufacturing facilities, communities, and states.

Opportunities in Otaki for Improved Energy Efficiency in Retail Lighting and Its Offsetting through Renewable Resources

<p>In 2010 the town of Otaki decided to go "Off the Grid", obtaining all its electricity supply from renewable resources. To support this goal, this thesis documents and quantifies the electricity demand for the Otaki retail stores along State Highway 1. It was found the majority of the load in these 33 stores was for lighting. To minimise the renewable electricity generation capital requirements, the load was optimised by exploring energy efficiency opportunities. Energy audits to AS/NZS 3598:2000 Energy Audit Level 2 were undertaken in 23 of the stores. These created a consistent set of data on the lighting load and energy consumption. Potential energy savings opportunities were then identified to reduce the lighting load by 26% through lamp replacement and removal. When combined with improved lighting management, these could reduce annual electricity consumption by 34% to 248,321 kWh. An investigation of available renewable resources (Photovoltaic (PV), wind and hydroelectric) found that PV generation was the most suitable for this urban setting. PV generation using 53 by 4 kW panels, at a capital cost of $1.3 million, which would generate 250,425 kWh per year. This would meet the annual electricity demand, but there would be a summer surplus and winter deficit. The absence of net metering provision makes this option uneconomic, although the creation of an Otaki mini-grid may be a viable alternative.</p>

Opportunities in Otaki for Improved Energy Efficiency in Retail Lighting and Its Offsetting through Renewable Resources

<p>In 2010 the town of Otaki decided to go "Off the Grid", obtaining all its electricity supply from renewable resources. To support this goal, this thesis documents and quantifies the electricity demand for the Otaki retail stores along State Highway 1. It was found the majority of the load in these 33 stores was for lighting. To minimise the renewable electricity generation capital requirements, the load was optimised by exploring energy efficiency opportunities. Energy audits to AS/NZS 3598:2000 Energy Audit Level 2 were undertaken in 23 of the stores. These created a consistent set of data on the lighting load and energy consumption. Potential energy savings opportunities were then identified to reduce the lighting load by 26% through lamp replacement and removal. When combined with improved lighting management, these could reduce annual electricity consumption by 34% to 248,321 kWh. An investigation of available renewable resources (Photovoltaic (PV), wind and hydroelectric) found that PV generation was the most suitable for this urban setting. PV generation using 53 by 4 kW panels, at a capital cost of $1.3 million, which would generate 250,425 kWh per year. This would meet the annual electricity demand, but there would be a summer surplus and winter deficit. The absence of net metering provision makes this option uneconomic, although the creation of an Otaki mini-grid may be a viable alternative.</p>

Validation and calibration of dynamic energy models: energy audit of a public building

Detailed buildings energy audits require dynamic simulation models based on hourly input data. This paper presents the calibration and validation of an office building energy model for the heating and cooling services. Simulation are carried out by DesignBuilder software. Measured hourly heating and cooling energy supplied by the generation system are used for the calibration of the model. Employee behaviour with reference to occupancy profiles and indoor temperature settings is also considered. A good agreement between measured and simulated data is obtained for both heating and cooling seasons.

An Approach to Semantically Segmenting Building Components and Outdoor Scenes Based on Multichannel Aerial Imagery Datasets

As-is building modeling plays an important role in energy audits and retrofits. However, in order to understand the source(s) of energy loss, researchers must know the semantic information of the buildings and outdoor scenes. Thermal information can potentially be used to distinguish objects that have similar surface colors but are composed of different materials. To utilize both the red–green–blue (RGB) color model and thermal information for the semantic segmentation of buildings and outdoor scenes, we deployed and adapted various pioneering deep convolutional neural network (DCNN) tools that combine RGB information with thermal information to improve the semantic and instance segmentation processes. When both types of information are available, the resulting DCNN models allow us to achieve better segmentation performance. By deploying three case studies, we experimented with our proposed DCNN framework, deploying datasets of building components and outdoor scenes, and testing the models to determine whether the segmentation performance had improved or not. In our observation, the fusion of RGB and thermal information can help the segmentation task in specific cases, but it might also make the neural networks hard to train or deteriorate their prediction performance in some cases. Additionally, different algorithms perform differently in semantic and instance segmentation.