•We modelled integrated land use change and sustainability for Australia to 2050.•Unparalleled detail scope, and temporal and spatial resolution at continental scale.•Substantial land-use and ...sustainability impacts of global change and domestic policy.•Type, magnitude, timing, and location of change was sensitive to scenario parameters.•Wide-ranging implications for strategic policy for Australia and elsewhere.
Understanding potential future influence of environmental, economic, and social drivers on land-use and sustainability is critical for guiding strategic decisions that can help nations adapt to change, anticipate opportunities, and cope with surprises. Using the Land-Use Trade-Offs (LUTO) model, we undertook a comprehensive, detailed, integrated, and quantitative scenario analysis of land-use and sustainability for Australia’s agricultural land from 2013–2050, under interacting global change and domestic policies, and considering key uncertainties. We assessed land use competition between multiple land-uses and assessed the sustainability of economic returns and ecosystem services at high spatial (1.1km grid cells) and temporal (annual) resolution. We found substantial potential for land-use transition from agriculture to carbon plantings, environmental plantings, and biofuels cropping under certain scenarios, with impacts on the sustainability of economic returns and ecosystem services including food/fibre production, emissions abatement, water resource use, biodiversity services, and energy production. However, the type, magnitude, timing, and location of land-use responses and their impacts were highly dependent on scenario parameter assumptions including global outlook and emissions abatement effort, domestic land-use policy settings, land-use change adoption behaviour, productivity growth, and capacity constraints. With strong global abatement incentives complemented by biodiversity-focussed domestic land-use policy, land-use responses can substantially increase and diversify economic returns to land and produce a much wider range of ecosystem services such as emissions abatement, biodiversity, and energy, without major impacts on agricultural production. However, better governance is needed for managing potentially significant water resource impacts. The results have wide-ranging implications for land-use and sustainability policy and governance at global and domestic scales and can inform strategic thinking and decision-making about land-use and sustainability in Australia. A comprehensive and freely available 26 GB data pack (http://doi.org/10.4225/08/5604A2E8A00CC) provides a unique resource for further research. As similarly nuanced transformational change is also possible elsewhere, our template for comprehensive, integrated, quantitative, and high resolution scenario analysis can support other nations in strategic thinking and decision-making to prepare for an uncertain future.
There has been an increased interest in cost and energy efficiency for heating, ventilation, and air conditioning systems for buildings since these are responsible for between 25% and 40% of total ...building energy demand. Solar assisted ground source heat pump systems which combine solar and geothermal energy are gaining attention due to their higher efficiency and greater functional diversity when compared with conventional systems. This paper presents a mixed integer linear programming approach to minimize the operational cost of a solar assisted ground source heat pump system, considering time-of-use electricity price (peak, off peak). Two types of system configurations are investigated in order to examine the effect of thermal storage in the system. Two different objectives are explored: minimizing electricity consumption and operational cost. The results indicate that the system having integrated thermal storage leads to improved peak shaving, which reduces the need for expensive peak electricity production for the grid, and has a reduction of operating cost by 7.8% when it is optimized for minimal cost.
•Model Predictive Control is proposed for the intermittent operation of a solar assisted ground source heat pump system.•Time-of-use electricity price is considered to reduce the electricity consumption of the system during peak hours.•The effect of adding a thermal storage on performance of a solar assisted heat pump system is investigated.
Ground source heat pump systems (GSHP) for residential building heating, cooling, and hot water are highly energy efficient but capital intensive when sized for peak demands. The use of supplemental ...sources of energy with GSHP systems enables improved life-cycle economics through the reduction in the size and cost of the GSHP components. This paper investigates the life-cycle economics of hybrid solar-assisted ground source heat pump systems (SAGSHP) using simulations validated from field data. The economics and optimal sizing of SAGSHP systems for heating dominant climates in four locations in Australia and ten locations elsewhere are evaluated in order to explore the suitability and relative merits of SAGSHP systems in a range of heating dominant climates. In locations having high or moderate levels of solar irradiation, high electricity prices, and high or moderate gas prices, SAGSHP systems are shown to have the lowest life cycle cost amongst alternatives, with predicted savings of up to 30%.
•A comprehensive investigation of the design and performance of hybrid GHSPs.•A comparison of hybrid GSHPs and conventional systems on cost and CO2 emissions.•Effects of local climatic and economic conditions are evaluated for 14 global cities.•Hybrid GSHPs have shown to be the most economical system for 10 out of 14 locations.•Local energy price is a key factor that influences the feasibility of hybrid GSHPs.
•Compares occurrence of fires in elevated fire danger conditions from different causes across the state of Victoria, Australia.•Fires caused by faults in electricity distribution infrastructure are ...more prevalent at elevated fire dangers.•Fires caused by electricity infrastructure burn larger areas, on average, than those from all other causes, except lightning.
Electricity distribution infrastructure causes fewer wildfires than most other sources of ignition. However, these fires have been associated with more severe consequences than those from other causes. This paper examines whether fires caused by faults in electricity distribution infrastructure occur more often during periods of elevated fire danger, thereby increasing their consequence. The occurrence of wildfires caused by electricity distribution infrastructure were compared to those attributed to other causes during periods of elevated fire danger across the State of Victoria, Australia, where historically such fires have had significant impact on lives and assets of value. The results provided strong evidence that fires caused by electrical faults are more prevalent during elevated fire danger conditions and that they burn larger areas than fires ignited by most other causes. As a result the consequences of fires caused by electricity infrastructure are worse than fires from other causes. This knowledge highlights the importance of mitigating ignition-causing faults in the electricity network, particularly on days of elevated fire danger.
•Incorporation of an animal migration model into optimal road design is proposed.•Computational tractability is achieved via a surrogate model.•Problem dimensionality is reduced via a novel ...reduced-order parameter.•The model allows finding low cost roads that maintain a minimum animal population.
With increasing land transportation requirements in both urban and rural areas, roads are encroaching ever more on animal habitats, where collisions with vehicles are a leading contributor to wildlife mortality. While road designers recognise the importance of accounting for such impacts at the design level, existing approaches simply either ignore viable habitat or avoid such regions entirely. Respectively, this can result in road alignments that are overly damaging to vulnerable species or prohibitively expensive to build and operate. The research presented in this paper investigates the effects of explicitly accounting for animal mortality on the design of a road through an ecologically sensitive area. The model presented achieves this by incorporating a spatially-explicit animal migration and road mortality model into an accepted optimal road alignment algorithm to propose low-cost roads that maintain the animal population above a minimum threshold by the end of a specified design horizon. The new method was applied to an example scenario to demonstrate the effect of setting a minimum required animal population on the road design. This model was able to consistently produce a road that met a minimum required species conservation benefit. This reflected a major improvement over the model that ignored animal habitats while only requiring a minor increase in construction and operating costs compared to the model that avoids habitat.
The construction and operation of linear infrastructure has major impacts on biodiversity through loss of habitat, increased mortality and loss of connectivity. In particular, minimising the impact ...of roads which pass through ecologically sensitive areas on surrounding species at the construction and operational phases is critical for conservation. However, potential impacts are rarely known perfectly at the construction phase and early in the operational phase. To address this problem, a company could build flexibility into road operation so that it can respond rapidly to future ecological impacts if necessary. In this paper we analyse the value of this flexibility using stochastic dynamic programming and use the results to guide a global search algorithm to find high value roads in the region. We consider flexibility in terms of the proportion of traffic volume routed along the road, with the remainder passing along an existing higher-cost, lower-impact road. We applied this to an example scenario where a road must be routed through a region with a vulnerable species present. By incorporating flexibility, the proposed model was able to find a road that met a desired ending population of animals and was more valuable than roads found under existing design alternatives.
In a globalised world, land use change outlooks are influenced by both locally heterogeneous land attributes and world markets. We demonstrate the importance of high resolution land heterogeneity ...representation in understanding local impacts of future global scenarios with carbon markets and land competition influencing food prices. A methodologically unique Australian continental model is presented with bottom-up parcel scale granularity in land use change, food, carbon, water, and biodiversity ecosystem service supply determination, and partial equilibrium food price impacts of land competition. We show that food price feedbacks produce modest aggregate national land use and ecosystem service supply changes. However, high resolution results show amplified land use change and ecosystem service impact in some places and muted impacts in other areas relative to national averages. We conclude that fine granularity modelling of geographic diversity produces local land use change and ecosystem service impact insights not discernible with other approaches.
•We modeled Australian land use change and ecosystem service responses to global scenarios.•The model features a novel approach to very high resolution land heterogeneity representation.•To demonstrate, we model how food price feedbacks of land competition differ spatially.•Modest land use change and ecosystem service impacts are observed in aggregate for Australia.•High resolution impacts vary from large to minuscule depending on local land heterogeneity.
Purpose
The food processing industry is growing with retail and catering supply chains. With the rising complexity of food products and the need to address food customization expectations, food ...processing systems are progressively shifting from production line to job-shops that are characterized by high flexibility and high complexity. A food job-shop system processes multiple items (i.e. raw ingredients, toppings, dressings) according to their working cycles in a typical resource and capacity constrained environment. Given the complexity of such systems, there are divergent goals of process cost optimization and of food quality and safety preservation. These goals deserve integration at both an operational and a strategic decisional perspective. The twofold purpose of this paper is to design a simulation model for food job-shop processing and to build understanding of the extant relationships between food flows and processing equipment through a real case study from the catering industry.
Design/methodology/approach
The authors designed a simulation tool enabling the analysis of food job-shop processing systems. A methodology based on discrete event simulation is developed to study the dynamics and behaviour of the processing systems according to an event-driven approach. The proposed conceptual model builds upon a comprehensive set of variables and key performance indicators (KPIs) that describe and measure the dynamics of the food job-shop according to a multi-disciplinary perspective.
Findings
This simulation identifies the job-shop bottlenecks and investigates the utilization of the working centres and product queuing through the system. This approach helps to characterize how costs are allocated in a flow-driven approach and identifies the trade-off between investments in equipment and operative costs.
Originality/value
The primary purpose of the proposed model relies on the definition of standard resources and operating patterns that can meet the behaviour of a wide variety of food processing equipment and tasks, thereby addressing the complexity of a food job-shop. The proposed methodology enables the integration of strategic and operative decisions between several company departments. The KPIs enable identification of the benchmark system, tracking the system performance via multi-scenario what-if simulations, and suggesting improvements through short-term (e.g. tasks scheduling, dispatching rules), mid-term (e.g. recipes review), or long-term (e.g. re-layout, working centres number) levers.
Purpose
The food processing industry is growing with retail and catering supply chains. With the rising complexity of food products and the need to address food customization expectations, food ...processing systems are progressively shifting from production line to job-shops that are characterized by high flexibility and high complexity. A food job-shop system processes multiple items (i.e. raw ingredients, toppings, dressings) according to their working cycles in a typical resource and capacity constrained environment. Given the complexity of such systems, there are divergent goals of process cost optimization and of food quality and safety preservation. These goals deserve integration at both an operational and a strategic decisional perspective. The twofold purpose of this paper is to design a simulation model for food job-shop processing and to build understanding of the extant relationships between food flows and processing equipment through a real case study from the catering industry.
Design/methodology/approach
The authors designed a simulation tool enabling the analysis of food job-shop processing systems. A methodology based on discrete event simulation is developed to study the dynamics and behaviour of the processing systems according to an event-driven approach. The proposed conceptual model builds upon a comprehensive set of variables and key performance indicators (KPIs) that describe and measure the dynamics of the food job-shop according to a multi-disciplinary perspective.
Findings
This simulation identifies the job-shop bottlenecks and investigates the utilization of the working centres and product queuing through the system. This approach helps to characterize how costs are allocated in a flow-driven approach and identifies the trade-off between investments in equipment and operative costs.
Originality/value
The primary purpose of the proposed model relies on the definition of standard resources and operating patterns that can meet the behaviour of a wide variety of food processing equipment and tasks, thereby addressing the complexity of a food job-shop. The proposed methodology enables the integration of strategic and operative decisions between several company departments. The KPIs enable identification of the benchmark system, tracking the system performance via multi-scenario what-if simulations, and suggesting improvements through short-term (e.g. tasks scheduling, dispatching rules), mid-term (e.g. recipes review), or long-term (e.g. re-layout, working centres number) levers.
Unit Commitment (UC) is a computationally intensive problem, which has been solved sufficiently well for day ahead scheduling and single scenario simulations. However, the introduction of renewable ...energy sources and storage exposes new challenges in computation time due to the need for large-scale multi-scenario modeling while preserving inter-temporal constraints. To address this, we introduce a novel approach with adaptive time resolution that increases simulation speed and preserves accuracy. We reduce the size of the problem by grouping successive time intervals with similar net demand levels, forming a new longer interval. In comparison with the conventional UC solutions, the proposed approach is computationally more efficient, as it avoids repeated optimization for similar intervals. We analyze the quality of the solutions using the 6-bus, and IEEE 118-bus test systems as the two case-studies. The numerical results demonstrate that high quality solutions can be obtained with significant gains in computational speed, especially for the more difficult IEEE 118-bus case which is 115 times faster with a maximum error of less than ±1%.
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