Srinivasan Iyengar

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A new methodology to perform hybrid empirical/ab-initio molecular dynamics is presented. The method combines the well-established hybrid ONIOM scheme with the recently developed ADMP (Atom-Centered Density Matrix Propagation) approach, where the one electron density matrix expanded in an atom-centered Gaussian basis set is propagated as electronic variables(More)
The popularity of rooftop solar for individual homes continues to rise rapidly. However, techniques for accurately forecasting solar generation are critical to fully exploiting the benefits of such locally-generated solar energy. In this paper, we present SolarCast, a cloud-based web service, which automatically generates models that provide customized(More)
Heating, ventilation, and air conditioning (HVAC) accounts for over 50% of a typical home's energy usage. A thermostat generally controls HVAC usage in a home to ensure user comfort. In this paper, we focus on making existing "dumb" programmable thermostats smart by applying energy analytics on smart meter data to infer home occupancy patterns and compute(More)
Despite the persistent need for appropriate volume of high utility data across all TCS projects, there was no economical, efficient, flexible, person-independent and reusable methodology for data generation and supporting tool available to satisfy this need. In this paper, we propose a novel, flexible methodology called Xplod for generation of any volume of(More)
We discuss hybrid quantum-mechanics/molecular-mechanics (QM/MM) and quantum mechanics/quantum mechanics (QM/QM) generalizations to our recently developed quantum wavepacket ab initio molecular dynamics methodology for simultaneous dynamics of electrons and nuclei. The approach is a synergy between a quantum wavepacket dynamics, ab initio molecular dynamics,(More)
Understanding the energy usage of buildings is crucial for policy-making, energy planning, and achieving sustainable development. Unfortunately, instrumenting buildings to collect energy usage data is difficult and all publicly available datasets typically include only a few hundred homes within a region. Due to their relatively small size, these datasets(More)
—Electric vehicles (EV) are growing in popularity as a credible alternative to gas-powered vehicles. These vehicles require their batteries to be " fueled up " for operation. While EV charging has traditionally been grid-based, use of solar powered chargers has emerged as an interesting opportunity. These chargers provide clean electricity to(More)
A variety of energy management and analytics techniques rely on models of the power usage of a device over time. Unfortunately, the models employed by these techniques are often highly simplistic, such as modeling devices as simply being on with a fixed power usage or off and consuming little power. As we show, even the power usage of relatively simple(More)
Homeowners are increasingly deploying grid-tied solar systems due to the rapid decline in solar module prices. The energy produced by these solar-powered homes is monitored by utilities and third parties using networked energy meters, which record and transmit energy data at fine-grained intervals. Such energy data is considered anonymous if it is not(More)
As the cost of photovoltaic (PV) solar panels decreases, their use among homeowners is becoming increasingly popular. However, due to the intermittent and uncontrollable nature of solar power generation, there is a need for tools that help consumers and utilities forecast future solar generation at individual homes throughout the grid. Thus, we present(More)