• Energy Research

As we extend the reach of the Internet through sensing and automation, networked interactions become more critical and safety and security require improved means for designing and testing system components, platforms and services. A tremendous amount of messy, heterogeneous data passes through such networks; integrating and applying that data so that it can be used for seamless interoperability and higher level reasoning requires conversion into some higher abstraction. This necessitates a new foundation for information modeling and model management, broadly construed. Such a foundation must support model construction in a wide range of formalism as well as capabilities for integrating models across different formalisms. We must also allow for easy model evolution, simplifying both iterative design and long-term maintenance. In this paper, we argue that category theory, a branch of abstract mathematics, provides a firm conceptual foundation for information modeling which already meets most of these criteria. We close with a discussion of some challenges for exploiting category theory in applied contexts.

Abstract Despite frequent blackouts and brownouts, extension of the central grid remains the Indian government׳s preferred strategy for the country׳s rural electrification policy. This study reports an assessment that compares grid extension with distributed generation (DG) alternatives, based on the subsidies they will necessitate, and costs of service interruptions that are appropriate in the rural Indian context. Using cross-sectional household expenditure data and region fixed-effects models, average household demand is estimated. The price elasticity of demand is found to be in the range of −0.3 to −0.4. Interruption costs are estimated based on the loss of consumer surplus due to reduced consumption of electric lighting energy that results from intermittent power supply. Different grid reliability scenarios are simulated. Despite the inclusion of interruption costs, standalone DG does not appear to be competitive with grid extension at distances of less than 17 km. However, backing up unreliable grid service with local DG plants is attractive when reliability is very poor, even in previously electrified villages. Introduction of energy efficient lighting changes these economics, and the threshold for acceptable grid unreliability significantly reduces. A variety of polices to promote accelerated deployment and the wider adoption of improved end-use efficiency, warrant serious consideration.

The problem of integrating multiple overlapping models and data is pervasive in engineering, though often implicit. We consider this issue of model management in the context of the electrical power grid as it transitions towards a modern 'Smart Grid.' We present a methodology for specifying, managing, and reasoning within multiple models of distributed energy resources (DERs), entities which produce, consume, or store power, using categorical databases and symmetric monoidal categories. Considering the problem of distributing power on the grid in the presence of DERs, we show how to connect a generic problem specification with implementation-specific numerical solvers using the paradigm of categorical databases. In Proceedings ACT 2019, arXiv:2009.06334