39,535 research outputs found
Emission-aware Energy Storage Scheduling for a Greener Grid
Reducing our reliance on carbon-intensive energy sources is vital for
reducing the carbon footprint of the electric grid. Although the grid is seeing
increasing deployments of clean, renewable sources of energy, a significant
portion of the grid demand is still met using traditional carbon-intensive
energy sources. In this paper, we study the problem of using energy storage
deployed in the grid to reduce the grid's carbon emissions. While energy
storage has previously been used for grid optimizations such as peak shaving
and smoothing intermittent sources, our insight is to use distributed storage
to enable utilities to reduce their reliance on their less efficient and most
carbon-intensive power plants and thereby reduce their overall emission
footprint. We formulate the problem of emission-aware scheduling of distributed
energy storage as an optimization problem, and use a robust optimization
approach that is well-suited for handling the uncertainty in load predictions,
especially in the presence of intermittent renewables such as solar and wind.
We evaluate our approach using a state of the art neural network load
forecasting technique and real load traces from a distribution grid with 1,341
homes. Our results show a reduction of >0.5 million kg in annual carbon
emissions -- equivalent to a drop of 23.3% in our electric grid emissions.Comment: 11 pages, 7 figure, This paper will appear in the Proceedings of the
ACM International Conference on Future Energy Systems (e-Energy 20) June
2020, Australi
CSA Practices for Sustainable Cocoa Farming Systems
Climate change will shape the future production of cocoa and requires mutual cooperation amongst sector stakeholders to tailor responses to its differentiated impacts. Identifying and prioritizing climate smart agriculture (CSA) responses requires integration of multiple objectives and managing trade-offs between food security, adaptation and mitigation. Impact of future climates on growing regions is needed to select locally appropriate CSA practices. Zones of adaptation needs in Indonesia are identified and the âwhy?â and âhow?â of tailored CSA practices are illustrated in an accessible guidebook format
Human Swarm Interaction: An Experimental Study of Two Types of Interaction with Foraging Swarms
In this paper we present the first study of human-swarm interaction comparing two fundamental types of interaction, coined intermittent and environmental. These types are exemplified by two control methods, selection and beacon control, made available to a human operator to control a foraging swarm of robots. Selection and beacon control differ with respect to their temporal and spatial influence on the swarm and enable an operator to generate different strategies from the basic behaviors of the swarm. Selection control requires an active selection of groups of robots while beacon control exerts an influence on nearby robots within a set range. Both control methods are implemented in a testbed in which operators solve an information foraging problem by utilizing a set of swarm behaviors. The robotic swarm has only local communication and sensing capabilities. The number of robots in the swarm range from 50 to 200. Operator performance for each control method is compared in a series of missions in different environments with no obstacles up to cluttered and structured obstacles. In addition, performance is compared to simple and advanced autonomous swarms. Thirty-two participants were recruited for participation in the study. Autonomous swarm algorithms were tested in repeated simulations. Our results showed that selection control scales better to larger swarms and generally outperforms beacon control. Operators utilized different swarm behaviors with different frequency across control methods, suggesting an adaptation to different strategies induced by choice of control method. Simple autonomous swarms outperformed human operators in open environments, but operators adapted better to complex environments with obstacles. Human controlled swarms fell short of task-specific benchmarks under all conditions. Our results reinforce the importance of understanding and choosing appropriate types of human-swarm interaction when designing swarm systems, in addition to choosing appropriate swarm behaviors
Optimizing Urban Distribution Routes for Perishable Foods Considering Carbon Emission Reduction
The increasing demand for urban distribution increases the number of transportation vehicles which intensifies the congestion of urban traffic and leads to a lot of carbon emissions. This paper focuses on carbon emission reduction in urban distribution, taking perishable foods as the object. It carries out optimization analysis of urban distribution routes to explore the impact of low carbon policy on urban distribution routes planning. On the base of analysis of the cost components and corresponding constraints of urban distribution, two optimization models of urban distribution route with and without carbon emissions cost are constructed, and fuel quantity related to cost and carbon emissions in the model is calculated based on traffic speed, vehicle fuel quantity and passable time period of distribution. Then an improved algorithm which combines genetic algorithm and tabu search algorithm is designed to solve models. Moreover, an analysis of the influence of carbon tax price is also carried out. It is concluded that in the process of urban distribution based on the actual network information, the path optimization considering the low carbon factor can effectively reduce the distribution process of CO2, and reduce the total cost of the enterprise and society, thus achieving greater social benefits at a lower cost. In addition, the government can encourage low-carbon distribution by rationally adjusting the price of carbon tax to achieve a higher social benefit
Feasibility Study: Vertical Farm EDEN
Hundreds of millions of people around the world do not have access to sufficient food. With the
global population continuing to increase, the global food output will need to drastically increase
to meet demands. At the same time, the amount of land suitable for agriculture is finite, so it is
not possibly to meet the growing demand by simply increasing the use of land. Thus, to be able
to feed the entire global population, and continue to do so in the future, it will be necessary to
drastically increase the food output per land area.
One idea which has been recently discussed in the scientific community is called Vertical Farming
(VF), which cultivates food crops on vertically stacked levels in (high-rise) buildings. The Vertical
Farm, so it is said, would allow for more food production in a smaller area. Additionally, a
Vertical Farm could be situated in any place (e.g. Taiga- or desert regions, cities), which would
make it possible to reduce the amount of transportation needed to deliver the crops to the
supermarkets.
The technologies required for the Vertical Farm are well-known and already being used in
conventional terrestrial greenhouses, as well as in the designs of bioregenerative Life Support
Systems for space missions. However, the economic feasibility of the Vertical Farm, which will
determine whether this concept will be developed or not, has not yet been adequately assessed.
Through a Concurrent Engineering (CE) process, the DLR Institute for Space Systems (RY) in
Bremen, aims to apply its know-how of Controlled Environment Agriculture (CEA) Technologies
in space systems to provide valuable spin-off projects on Earth and to provide the first
engineering study of a Vertical Farm to assess its economic feasibility
Fine Grained Component Engineering of Adaptive Overlays: Experiences and Perspectives
Recent years have seen significant research being carried out into peer-to-peer (P2P) systems. This work has focused on the styles and applications of P2P computing, from grid computation to content distribution; however, little investigation has been performed into how these systems are built. Component based engineering is an approach that has seen successful deployment in the field of middleware development; functionality is encapsulated in âbuilding blocksâ that can be dynamically plugged together to form complete systems. This allows efficient, flexible and adaptable systems to be built with lower overhead and development complexity. This paper presents an investigation into the potential of using component based engineering in the design and construction of peer-to-peer overlays. It is highlighted that the quality of these properties is dictated by the component architecture used to implement the system. Three reusable decomposition architectures are designed and evaluated using Chord and Pastry case studies. These demonstrate that significant improvements can be made over traditional design approaches resulting in much more reusable, (re)configurable and extensible systems
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