Zero carbon manufacturing facility - Towards integrating material, energy, and waste process flows

The increasing pressure on material availability, energy prices, as well as emerging environmental legislation is leading manufacturers to adopt solutions to reduce their material and energy consumption as well as their carbon footprint, thereby becoming more sustainable. Ultimately manufacturers could potentially become zero carbon by having zero net energy demand and zero waste across the supply chain. The literature on zero carbon manufacturing and the technologies that underpin it are growing, but there is little available on how a manufacturer undertakes the transition. Additionally, the work in this area is fragmented and clustered around technologies rather than around processes that link the technologies together. There is a need to better understand material, energy, and waste process flows in a manufacturing facility from a holistic viewpoint. With knowledge of the potential flows, design methodologies can be developed to enable zero carbon manufacturing facility creation. This paper explores the challenges faced when attempting to design a zero carbon manufacturing facility. A broad scope is adopted from legislation to technology and from low waste to consuming waste. A generic material, energy, and waste flow model is developed and presented to show the material, energy, and waste inputs and outputs for the manufacturing system and the supporting facility and, importantly, how they can potentially interact. Finally the application of the flow model in industrial applications is demonstrated to select appropriate technologies and configure them in an integrated way. © 2009 IMechE.

Energy efficiency, resilience to future climates and long-term sustainability: the role of the built environment

Just under half of all energy consumption in the UK today takes place indoors, and over a quarter within our homes. The challenges associated with energy security, climate change and sustainable consumption will be overcome or lost in existing buildings. A background analysis, and the scale of the engineering challenge for the next three to four decades, is described in this paper.

Energy efficiency, resilience to future climates and long-term sustainability: the role of the built environment.

Just under half of all energy consumption in the UK today takes place indoors, and over a quarter within our homes. The challenges associated with energy security, climate change and sustainable consumption will be overcome or lost in our existing buildings. A background analysis, and the scale of the engineering challenge for the next three to four decades, is described in this paper.

A probabilistic energy model for non-domestic building sectors applied to analysis of school buildings in greater London

The diversity of non-domestic buildings at urban scale poses a number of difficulties to develop models for large scale analysis of the stock. This research proposes a probabilistic, engineering-based, bottom-up model to address these issues. In a recent study we classified London's non-domestic buildings based on the service they provide, such as offices, retail premise, and schools, and proposed the creation of one probabilistic representational model per building type. This paper investigates techniques for the development of such models. The representational model is a statistical surrogate of a dynamic energy simulation (ES) model. We first identify the main parameters affecting energy consumption in a particular building sector/type by using sampling-based global sensitivity analysis methods, and then generate statistical surrogate models of the dynamic ES model within the dominant model parameters. Given a sample of actual energy consumption for that sector, we use the surrogate model to infer the distribution of model parameters by inverse analysis. The inferred distributions of input parameters are able to quantify the relative benefits of alternative energy saving measures on an entire building sector with requisite quantification of uncertainties. Secondary school buildings are used for illustrating the application of this probabilistic method. © 2012 Elsevier B.V. All rights reserved.

Future-proofed energy design for dwellings: Case studies from England and application to the Code for Sustainable Homes

This paper investigates 'future-proofing' as an unexplored yet all-important aspect in the design of low-energy dwellings. It refers particularly to adopting lifecycle thinking and accommodating risks and uncertainties in the selection of fabric energy efficiency measures and low or zero-carbon technologies. Based on a conceptual framework for future-proofed design, the paper first presents results from the analysis of two 'best practice' housing developments in England; i.e., North West Cambridge in Cambridge and West Carclaze and Baal in St. Austell, Cornwall. Second, it examines the 'Energy and CO2 Emissions' part of the Code for Sustainable Homes to reveal which design criteria and assessment methods can be practically integrated into this established building certification scheme so that it can become more dynamic and future-oriented.Practical application: Future-proofed construction is promoted implicitly within the increasingly stringent building regulations; however, there is no comprehensive method to readily incorporate futures thinking into the energy design of buildings. This study has a three-fold objective of relevance to the building industry:Illuminating the two key categories of long-term impacts in buildings, which are often erroneously treated interchangeably:- The environmental impact of buildings due to their long lifecycles.- The environment's impacts on buildings due to risks and uncertainties affecting the energy consumption by at least 2050. This refers to social, technological, economic, environmental and regulatory (predictable or unknown) trends and drivers of change, such as climate uncertainty, home-working, technology readiness etc.Encouraging future-proofing from an early planning stage to reduce the likelihood of a prematurely obsolete building design.Enhancing established building energy assessment methods (certification, modelling or audit tools) by integrating a set of future-oriented criteria into their methodologies. © 2012 The Chartered Institution of Building Services Engineers.

A conceptual framework for future-proofing the energy performance of buildings

This paper presents a review undertaken to understand the concept of 'future-proofing' the energy performance of buildings. The long lifecycles of the building stock, the impacts of climate change and the requirements for low carbon development underline the need for long-term thinking from the early design stages. 'Future-proofing' is an emerging research agenda with currently no widely accepted definition amongst scholars and building professionals. In this paper, it refers to design processes that accommodate explicitly full lifecycle perspectives and energy trends and drivers by at least 2050, when selecting energy efficient measures and low carbon technologies. A knowledge map is introduced, which explores the key axes (or attributes) for achieving a 'future-proofed' energy design; namely, coverage of sustainability issues, lifecycle thinking, and accommodating risks and uncertainties that affect the energy consumption. It is concluded that further research is needed so that established building energy assessment methods are refined to better incorporate future-proofing. The study follows an interdisciplinary approach and is targeted at design teams with aspirations to achieve resilient and flexible low-energy buildings over the long-term. © 2012 Elsevier Ltd.

Energy recycling from multigigahertz clocks using fully integrated switching converters

Large digital chips use a significant amount of energy to broadcast a low-skew, multigigahertz clock to millions of latches located throughout the chip. Every clock cycle, the large aggregate capacitance of the clock network is charged from the supply and then discharged to ground. Instead of wasting this stored energy, it is possible to recycle the energy by controlling its delivery to another part of the chip using an on-chip dc-dc converter. The clock driver and switching converter circuits share many compatible characteristics that allow them to be merged into a single design and fully integrated on-chip. Our buck converter prototype, manufactured in 90-nm CMOS, provides a proof-of-concept that clock network energy can be recycled to other parts of the chip, thus lowering overall energy consumption. It also confirms that monolithic multigigahertz switching converters utilizing zero-voltage switching can be implemented in deep-submicrometer CMOS. With multigigahertz operation, fully integrated inductors and capacitors use a small amount of chip area with low losses. Combining the clock driver with the power converter can share the large MOSFET drivers necessary as well as being energy and space efficient. We present an analysis of the losses which we confirm by experimentally comparing the merged circuit with a conventional clock driver. © 2012 IEEE.

Accelerating Bayesian hierarchical clustering of time series data with a randomised algorithm.

We live in an era of abundant data. This has necessitated the development of new and innovative statistical algorithms to get the most from experimental data. For example, faster algorithms make practical the analysis of larger genomic data sets, allowing us to extend the utility of cutting-edge statistical methods. We present a randomised algorithm that accelerates the clustering of time series data using the Bayesian Hierarchical Clustering (BHC) statistical method. BHC is a general method for clustering any discretely sampled time series data. In this paper we focus on a particular application to microarray gene expression data. We define and analyse the randomised algorithm, before presenting results on both synthetic and real biological data sets. We show that the randomised algorithm leads to substantial gains in speed with minimal loss in clustering quality. The randomised time series BHC algorithm is available as part of the R package BHC, which is available for download from Bioconductor (version 2.10 and above) via http://bioconductor.org/packages/2.10/bioc/html/BHC.html. We have also made available a set of R scripts which can be used to reproduce the analyses carried out in this paper. These are available from the following URL. https://sites.google.com/site/randomisedbhc/.

Investigating the link between well-being and energy use; an explorative case study between passive and active domestic energy management systems

The aim of this study was to explore how the remote control of appliances/lights (active energy management system) affected household well-being, compared to in-home displays (passive energy management system). A six-week exploratory study was conducted with 14 participants divided into the following three groups: active; passive; and no equipment. The effect on well-being was measured through thematic analysis of two semi-structured interviews for each participant, administered at the start and end of the study. The well-being themes were based on existing measures of Satisfaction and Affect. The energy demand for each participant was also measured for two weeks without intervention, and then compared after four weeks with either the passive or active energy management systems. These measurements were used to complement the well-being analysis. Overall, the measure of Affect increased in the passive group but Satisfaction decreased; however, all three measures on average decreased in the active group. The measured energy demand also highlighted a disconnect between well-being and domestic energy consumption. The results point to a need for further investigation in this field; otherwise, there is a risk that nationally implemented energy management solutions may negatively affect our happiness and well-being. © 2013 Elsevier Ltd.

A bottom-up energy analysis across a diverse urban building portfolio: Retrofits for the buildings at the Royal Botanic Gardens, Kew, UK

A methodology for the analysis of building energy retrofits has been developed for a diverse set of buildings at the Royal Botanic Gardens (RBG), Kew in southwest London, UK. The methodology requires selection of appropriate building simulation tools dependent on the nature of the principal energy demand. This has involved the development of a stand-alone model to simulate the heat flow in botanical glasshouses, as well as stochastic simulation of electricity demand for buildings with high equipment density and occupancy-led operation. Application of the methodology to the buildings at RBG Kew illustrates the potential reduction in energy consumption at the building scale achievable from the application of retrofit measures deemed appropriate for heritage buildings and the potential benefit to be gained from onsite generation and supply of energy. © 2014 Elsevier Ltd.

Effects of longer heavy vehicles on traffic congestion

Two-lane, "microscopic" (vehicle-by-vehicle) simulations of motorway traffic are developed using existing models and validated using measured data from the M25 motorway. An energy consumption model is also built in, which takes the logged trajectories of simulated vehicles as drive-cycles. The simulations are used to investigate the effects on motorway congestion and fuel consumption if "longer and/or heavier vehicles" (LHVs) were to be permitted in the UK. Baseline scenarios are simulated with traffic composed of cars, light goods vehicles and standard heavy goods vehicles (HGVs). A proportion of conventional articulated HGVs is then replaced by a smaller number of LHVs carrying the same total payload mass and volume. Four LHV configurations are investigated: an 18.75 m, 46 t longer semi-trailer (LST); 25.25 m, 50 t and 60 t B-doubles and a 34 m, 82 t A-double. Metrics for congestion, freight fleet energy consumption and car energy consumption are defined for comparing the scenarios. Finally, variation of take-up level and LHV engine power for the LST and A-double are investigated. It is concluded that: (a) LHVs should reduce congestion particularly in dense traffic, however, a low mean proportion of freight traffic on UK roads and low take-up levels will limit this effect to be almost negligible; (b) LHVs can significantly improve the energy efficiency of freight fleets, giving up to a 23% reduction in fleet energy consumption at high take-up levels; (c) the small reduction in congestion caused by LHVs could improve the fuel consumption of other road users by up to 3% in dense traffic, however in free-flowing traffic an opposite effect occurs due to higher vehicle speeds and aerodynamic losses; and (d) underpowered LHVs have potential to generate severe congestion, however current manufacturers' recommendations appear suitable. © 2013 IMechE.