GridAPPS-D Distributed App Architecture and API for Modular and Distributed Grid Operations
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Demand response (DR) of building HVAC load can provide crucial demand-side flexibility for the future smart grid. Compared to direct load control, price-based control can respect the customers’ autonomy and privacy. However, it is challenging for price-based control to attain provable performance guarantees under future uncertainty. In this paper, we propose a framework for a utility to perform price-based control of flexible building load within the utility’s service area, in order to attain competitive performance guarantees in terms of controlling the system peak demand under future uncertainty. By adopting a two-step approach, our online price-based control solution can attain a provable competitive ratio for all possible realizations within a given uncertainty set. Simulation experiments demonstrate that, with a robustification procedure, our solution can perform well not only for worst-case inputs, but also for average-case inputs.
This grant funded a Market and Technology Assessment project which included 1) an analysis of the total addressable market (TAM) for the RT-OPF technology; 2) a segmented assessment of North American utility business models and barriers to adoption of the RT-OPF technology for those models; 3) a validation of DER customer needs and barriers to participation in utility programs; and 4) a forward-looking analysis of utility regulatory innovation and changes that may impact utility business models and ability for utilities to adopt this technology.
In this presentation, we will describe how the system uses CIRs in terms of subscriptions, filters and priorities, and how client interests are propagated throughout the system, and we will describe the novel information flows that result from this CIR propagation.
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The relative dispersion of cloud and fog droplets has significant impacts on aerosol indirect effects, radiative transfer, and microphysical processes. However, previous studies have been mostly concerned with clouds, with limited studies on fog, particularly those that examine the combined influences of all key physical processes and their roles during fog evolution. As such, this study aims to conduct a comprehensive investigation by examining the relationships between relative dispersion and other microphysical variables, as well as the underlying microphysical and dynamic processes, based on field fog campaigns in polluted and clean conditions. In polluted fog, droplet concentrations are higher, leading to smaller droplets and increased dispersion. The correlation between dispersion and droplet volume-mean radius is positive in the polluted fog, but shifts to negative in clean fog. Here, we attribute the difference to various microphysical processes like aerosol activation, condensation, collision-coalescence, and entrainment-mixing. In polluted fog, high aerosol concentrations, low supersaturations, and strong turbulence (entrainment-mixing) provide suitable conditions for the simultaneous occurrence of droplet condensation and aerosol activation, resulting in a positive correlation between dispersion and volume-mean radius, especially during the fog formation stage. In contrast, during the mature stage in clean fog, condensation is dominant with weak aerosol activation leading to a negative correlation between relative dispersion and volume-mean radius. The collision-coalescence process is more active in the mature stage, increasing radii and leading to the negative correlation between dispersion and volume-mean radius. This result sheds new light on understanding the relative dispersion and mechanisms in fog under different aerosol backgrounds.
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The impact of an external electric field on the concerted behavior of oxygen over a multi-faceted catalytic Fe grain is determined via the interpolation of ab initio models of oxygen adsorption on Fe(100), Fe(110), and Fe(111) in the presence of an external electric field. The application of both negative and positive electric fields weaken the adsorption strength for oxygen on all three surface facets, with Fe(110) experiencing the greatest effect. Kinetic models of a multi-faceted catalytic Fe grain show that the average oxygen coverage over the grain surface is reduced under the influence of both a negative and positive electric field, which are consistent with phase diagram results at comparable pressures. Furthermore, we show that there is a weak synergistic effect between a Pd promoter and a positive electric field on the oxygen adsorption energy, i.e. the Pd promoter and electric field combination weaken the oxygen adsorption energy to a greater degree than the simple addition of both components separately. Overall, the work shows that the application of an applied external electric field may be a useful tool in fine-tuning chemical properties of Fe-based catalysts in hydrodeoxygenation applications.