From Packet to Power Switching: Digital Direct Load Scheduling

At present, the power grid has tight control over its dispatchable generation capacity but a very coarse control on the demand. Energy consumers are shielded from making price-aware decisions, which degrades the efficiency of the market. This state of affairs tends to favor fossil fuel generation over renewable sources. Because of the technological difficulties of storing electric energy, the quest for mechanisms that would make the demand for electricity controllable on a day-to-day basis is gaining prominence. The goal of this paper is to provide one such mechanisms, which we call Digital Direct Load Scheduling (DDLS). DDLS is a direct load control mechanism in which we unbundle individual requests for energy and digitize them so that they can be automatically scheduled in a cellular architecture. Specifically, rather than storing energy or interrupting the job of appliances, we choose to hold requests for energy in queues and optimize the service time of individual appliances belonging to a broad class which we refer to as "deferrable loads". The function of each neighborhood scheduler is to optimize the time at which these appliances start to function. This process is intended to shape the aggregate load profile of the neighborhood so as to optimize an objective function which incorporates the spot price of energy, and also allows distributed energy resources to supply part of the generation dynamically.Comment: Accepted by the IEEE journal of Selected Areas in Communications (JSAC): Smart Grid Communications series, to appea

Grid-Enabled Non-Invasive Blood Glucose Measurement

Abstract. Earth and life sciences are at the forefront to successfully include computational simulations and modeling. Medical applications are often mentioned as the killer applications for the Grid. The complex methodology and models of Traditional Chinese Medicine offer different approaches to diagnose and treat a persons health condition than typical Western medicine. A possibility to make this often hidden knowledge ex-plicit and available to a broader audience will result in mutual synergies for Western and Chinese medicine as well as improved patient care. This paper proposes the design and implementation of a method to accurately estimate blood glucose values using a novel non-invasive method based on electro-transformation measures in human body meridians. The frame-work used for this scientific computing collaboration, namely the China-Austria Data Grid (CADGrid) framework, provides an Intelligence Base offering commonly used models and algorithms as Web/Grid-Services. The controlled execution of the Non-Invasive Blood Glucose Measure-ment Service and the management of scientific data that arise from model execution can be seen as the first application on top of the CADGrid