Energy Procedia最新文献

The poultry industry generates a large quantity of litter, which consists of a mixture of manure, waste bedding and feathers, and can be used for recovery of energy. Recent studies suggest that gasification is a promising technology for an effective conversion of poultry litter to energy. This paper aims to assess the environmental impacts of generating electricity from the gasification of poultry litter in a small-scale integrated gasification combined cycle (IGCC) plant. Gasification of poultry litter has been simulated with ASPEN Plus® software and life cycle assessment has been used to determine the carbon footprint and primary energy demand of the system. The following life cycle stages have been considered: collection and storage of poultry litter, its gasification, syngas cleaning, production of electricity and co-production of ash as a fertiliser. The carbon footprint and primary energy demand of generating 1 kWh of energy by poultry litter gasification plant are estimated at 42 g CO2 eq./kWh and 0.14 MJ/kWh, respectively. Compared to electricity from fossil fuels, this system has 91%-96% smaller carbon footprint and 98%-99% lower primary energy demand. The energy payback period is estimated at 1.5 years.

This study evaluates the life cycle environmental sustainability of cheddar cheese with energy recovery from cheese whey via anaerobic digestion. Environmental hotspots and improvement opportunities along the supply chain are also identified. The cheddar cheese production process has been simulated by using Aspen Plus. The environmental impacts have been estimated through life cycle assessment (LCA) using the outputs from process simulation. The LCA data for the rest of the life cycle have been sourced from databases and literature. The results reveal that the total primary energy consumed in the whole life cycle of cheddar cheese is 347 MJ, with the carbon footprint equal to 14 kg CO₂ eq. per kg of cheddar. Energy recovered from anaerobic digestion of whey reduces the total life cycle primary energy demand and the carbon footprint by only 2%. Much greater reductions could be achieved by targeting milk production and storage of cheese. However, anaerobic digestion of whey makes the cheese production process energy self-sufficient and reduces the production costs. It also makes the production process carbon negative, reducing its carbon footprint from 0.12 to -0.12 kg CO₂ eq./kg due to the credits for electricity and heat produced from biogas.

The energy performance of emerging food pasteurisation technologies (high pressure processing, microwave volumetric heating, ohmic heating) are evaluated to establish whether they can offer significant reductions in energy consumption and overall carbon emissions, relative to conventional processes, while delivering equivalent microbiological lethality, nutritional and organoleptic quality under commercially-representative processing conditions. Product quality (vitamin C and flavour compounds) data have been collected using established analytical and instrumental methods to benchmark achievable product quality improvements. The results show that for maintaining the raw product quality, the emerging electro-technologies are more energy- and primary resource-efficient, subject to identified operating parameters.

Cleaning of process plants is important to ensure product purity and safety. Cleaning is however expensive with respect to energy, waste and time. It is important to be able to minimise losses from cleaning, by maximising product recovery and reducing waste. Viscous food and personal care products can form thick layers on process surfaces. Cleaning of a surface by a water jet has been studied here. Two modes of cleaning are identified experimentally; for thin films, cleaning is by formation of a crater that expands with time, whilst for thick films a ‘blister’ forms in which water spreads underneath the deposit. The blister eventually cleans, but over a much longer timescale than for the thinner film. The cleaned area after 10 seconds is comparable in size to the blister area after less than half a second of cleaning. This behaviour has implications for the cleaning of real systems.

Characterising rehydration kinetics is key to understand the effect of microstructure on the quality of rehydrated products. Well-connected porous networks, like the ones created by freeze-drying processes, can enhance water absorption and transport, leading to higher final quality rehydrated products. Such products present the basis for a novel distribution scenario for (freeze-)dried products that are rehydrated closer to the consumption point. In this work, fresh tomatoes were first freeze-dried and subsequently rehydrated at different temperatures. Four rehydration models were fitted to the experimental data using regression analysis. The goodness-of-fit was evaluated according to (i) Root Mean Squared Error (ii) adjusted R-square (iii) Akaike Information Criterion (iv) Bayesian Information Criterion. The Exponential and Weibull models provided the most accurate descriptions of the rehydration kinetics. The effect of temperature on rehydration kinetics was also evaluated, with rehydration capacities and equilibrium moisture contents of the rehydrated tomatoes increasing with temperature. In addition, activation energy values for rehydration, which were in accordance with the existing literature values, were also obtained from the fitted rehydration rate parameters.

The dairy processing and slaughterhouse industries consume large volumes of water and their waste effluents often contain high levels of chemical oxygen demand (COD), biochemical/biological oxygen demand (BOD) and fertilising nutrients. Therefore, water treatment is necessary to reduce the levels of these contaminants prior to discharge or reuse of the water. In this short review paper we provide a brief overview of electrocoagulation (EC) technology and summarise the current literature relating to the use of EC treatment to clean dairy processing and slaughterhouse wastewaters.

The purpose of this paper (parts I and II) is to examine the socio-technical factors that affect urban food production and associated energy, water and waste services. Part I introduced the growing role of prosumers, discussed the context of the human relationship with food and demonstrated how citizens’ choices and actions regarding food consumption and production in urban settings are shaped by the economic, cultural and infrastructure systems in which they live. A residential estate on the urban fringe of Australia’s subtropical Gold Coast was described, setting the context for a mixed methods analysis of quantitative and qualitative data gathered through estate maps, development planning documents, visual observations, interviews and surveys. Part II presents the results, analysed around the themes of food production, consumption and development infrastructure (physical and social). An integrated approach to land-use, energy, water and waste was instrumental in enabling ubiquitous high biodiversity food production, highlighting planning decisions that affect the ability of urban prosumers to incorporate sustainability into their food practices. The case study demonstrates that an integrated approach to urban infrastructure can support and enable urban prosumer food practices. A framework to evaluate urban neighbourhoods in terms of potential for creating synergies between land use, water, waste and energy infrastructure is presented and an initial performance indicator framework is proposed, to understand, develop and manage prosumer-driven urban agriculture in the context of integrated energy, water, waste and food services.

The paper presents the development of an experimental research facility based on a transcritical single stage vapour compression refrigeration cycle with CO₂ as the working fluid. The experimental setup includes instrumentation and controls which enable tests in a broad range of operating conditions. The measurements presented refer to external temperatures between 21.0°C and 33.5°C; in this latter operating point, energy and exergy analysis allowed the breakdown of irreversibilities. In particular, the gas cooler contributes to the 42.6% of the total exergy losses while the share due to the high-pressure expansion valve is 27.2%. In order to improve the performance of the refrigeration system, a theoretical model was developed including an ejector as the replacement of the expansion valve. The results show that the Coefficient of Performance (COP) is strongly dependent on the entrainment ratio; a value of greater than 0.6 seem to lead to higher COP values, even at low external temperatures.

This paper presents systematic design procedure and features of a sun simulator developed for testing low concentrating linearly focusing solar photovoltaic concentrators. The designed solar simulator comprises of a xenon short arc lamp and paraboloidal reflector for uniform radiative flux distribution on focal plane at desired radiation intensity. Initial inputs to the design process include reflector geometry (shape and size), surface properties of the reflector surface (reflectivity), distance of the reflector aperture from the illuminated area, rated lamp power, lamp geometry and orientation. These specifications were inputted in a ray tracing analyzer using COMSOL Multiphysics. The angular distribution of radiative intensity from the lamp was also accounted for. The proposed design is able to deliver a radiative intensity of 500 W/m² to test photovoltaic concentrators with aperture of up to 140 mm x 50 mm with a spatial non-uniformity of 4.5%.

Predicting the electricity demand of new supermarkets will help with design, planning, and future energy management. Instead of creating complex site-specific thermal engineering models, simplified statistical energy prediction models as we propose can be useful to energy managers. We have designed and implemented a data-driven method to predict the ‘electricity daily load profile’ (EDLP) for new stores. Our preliminary work exploits a data-set of hourly electricity meter readings for 196 UK supermarkets from 2012 to 2015. Our method combines the most similar stores on a feature space (floor area split by usage such as general merchandise, food retail and offices and geographical location) to obtain a prediction of the EDLP of a new store. Computational experiments were performed separately for subsets of supermarkets that consume only electricity, both electricity and gas, and by season. The best results were obtained when predicting Summer EDLPs with stores using electricity only. In this case, the average Manhattan difference and the percentage difference are 234 kWh and 16%, respectively. We aim to develop an application tool for supermarket energy managers to automatically generate EDLP for potential new stores.