Teja Kuruganti

Small- and Medium-Sized Commercial Building Monitoring and Controls Needs: A Scoping Study

Buildings consume over 40% of the total energy consumption in the U.S. A significant portion of the energy consumed in buildings is wasted because of the lack of controls or the inability to use existing building automation systems (BASs) properly. Much of the waste occurs because of our inability to manage and controls buildings efficiently. Over 90% of the buildings are either small-size ( 100,000 sf). Lawrence Berkeley National Laboratory (LBNL), Oak Ridge National Laboratory (ORNL) and Pacific Northwest National Laboratory (PNNL) were asked by the U.S. Department of Energy’s (DOE’s) Building Technologies Program (BTP) to identify monitoring and control needs for small- and medium-sized commercial buildings and recommend possible solutions. This study documents the needs and solutions for small- and medium-sized buildings.

Control and estimation through cognitive radio with distributed and dynamic spectral activity

Cognitive radio systems are currently a popular topic and are a good prospect for research when combined with control technology. In this paper, we consider the control and estimation via a two switch model which can represent a cognitive radio system. We provide an optimal estimator for this model and demonstrate that the optimal LQG controller is not a linear gain of the estimate of the states, as well as showing how the separation principle does not hold. Several conditions of stability are also discussed. Numerical examples are provided to verify the results.

Cost-effective retrofit technology for reducing peak power demand in small and medium commercial buildings

This article describes a cost-effective retrofit technology that uses collective control of multiple rooftop air-conditioning units to reduce the peak power consumption of small and medium commercial buildings. The proposed control uses a model of the building and air-conditioning units to select an operating schedule for the air-conditioning units that maintains a temperature set-point subject to a constraint on the number of units that may operate simultaneously. A prototype of this new control system was built and deployed in a large gymnasium to coordinate four rooftop air-conditioning units. Based on data collected while operating this prototype, it is estimated that the cost savings achieved by reducing peak power consumption is sufficient to repay the cost of the prototype within a year.

Real-time prediction of power system frequency in FNET: A state space approach

This paper proposes a novel approach to predict power frequency by applying a state-space model to describe the time-varying nature of power systems. It introduces the Expectation maximization (EM) and prediction error minimization (PEM) algorithms to dynamically estimate the parameters of the model. In this paper, we discuss how the proposed models can be used to ensure the efficiency and reliability of power systems in Frequency Monitoring Network (FNET), if serious frequency fluctuation or measurement failure occur at some nodes; this is achieved without requiring the exact model of complex power systems. Our approach leads to an easy online implementation with high precision and short response time that are key to effective frequency control. We randomly pick a set of frequency data for one power station in FNET and use it to estimate and predict the power frequency based on past measurements. Several computer simulations are provided to evaluate the method. Numerical results showed that the proposed technique could achieve good performance regarding the frequency monitoring with very limited measurement input information.

Optimal estimation over unreliable communication links with application to cognitive radio

This paper considers state estimation of linear stochastic discrete-time systems through an unreliable network. Packet losses from the sensor to the estimator are assumed to follow a Bernoulli distribution, while information loss is not assumed to be available at the receiver at any time. The optimal estimator provides a satisfactory estimate under unreliable communications as the estimator is used successfully in a Linear Quadratic Gaussian (LQG) controller to stabilize an inverted pendulum system, and comparison with an optimal estimator for which information loss at the receiver is available. The optimal estimator for a cognitive radio system is derived. Cognitive radio is an emerging technology with many promising applications. Cognitive radio can be considered as a combination of packet loss with and without acknowledgement in the dynamical model. An illustrative example shows that the optimal estimator improves the performance largely.

Vacuum-Assisted Low-Temperature Synthesis of Reduced Graphene Oxide Thin-Film Electrodes for High-Performance Transparent and Flexible All-Solid-State Supercapacitors

Simple and easily integrated design of flexible and transparent electrode materials affixed to polymer-based substrates hold great promise to have a revolutionary impact on the functionality and performance of energy storage devices for many future consumer electronics. Among these applications are touch sensors, roll-up displays, photovoltaic cells, health monitors, wireless sensors, and wearable communication devices. Here, we report an environmentally friendly, simple, and versatile approach to produce optically transparent and mechanically flexible all-solid-state supercapacitor devices. These supercapacitors were constructed on tin-doped indium oxide coated polyethylene terephthalate substrates by intercalation of a polymer-based gel electrolyte between two reduced graphene oxide (rGO) thin-film electrodes. The rGO electrodes were fabricated simply by drop-casting of graphene oxide (GO) films, followed by a novel low-temperature (≤250 °C) vacuum-assisted annealing approach for the in situ reduction of GO to rGO. A trade-off between the optical transparency and electrochemical performance is determined by the concentration of the GO in the initial dispersion, whereby the highest capacitance (∼650 μF cm-2) occurs at a relatively lower optical transmittance (24%). Notably, the all-solid-state supercapacitors demonstrated excellent mechanical flexibility with a capacity retention rate above 90% under various bending angles and cycles. These attributes underscore the potential of the present approach to provide a path toward the realization of thin-film-based supercapacitors as flexible and transparent energy storage devices for a variety of practical applications.

Non-intrusive load monitoring of HVAC components using signal unmixing

Heating, Ventilating and Air Conditioning units (HVAC) are a major electrical energy consumer in buildings. Monitoring of the operation and energy consumption of HVAC would increase the awareness of building owners and maintenance service providers of the condition and quality of performance of these units, enabling conditioned-based maintenance which would help achieving high efficiency in energy consumption. In this paper, a novel non-intrusive method based on constrained non-negative matrix factorization is proposed for monitoring the different components of HVAC unit by only having access to the whole building aggregated power signal. At the first level of this hierarchical approach, power consumption of the building is decomposed to energy consumption of the HVAC unit and all the other electrical devices operating in the building such as lighting and plug loads. Then, the estimated power signal of the HVAC is used to estimate the power consumption profile of the HVAC major electrical loads such as compressors, condenser fans and indoor blower. Experiments conducted on real data collected from a building testbed maintained at the Oak Ridge National Laboratory (ORNL) demonstrate high accuracy on disaggregation task.

Analysis, optimization, and implementation of a hybrid DS/FFH spread-spectrum technique for smart grid communications

In recent years, there has been great interest in using hybrid spread-spectrum (HSS) techniques for commercial applications, particularly in the Smart Grid, in addition to their inherent uses in military communications. This is because HSS can accommodate high data rates with high link integrity, even in the presence of significant multipath effects and interfering signals. A highly useful form of this transmission technique for many types of command, control, and sensing applications is the specific code-related combination of standard direct sequence modulation with ‘fast’ frequency hopping, denoted hybrid DS/FFH, wherein multiple frequency hops occur within a single data-bit time. In this paper, error-probability analyses are performed for a hybrid DS/FFH system over standard Gaussian and fading-type channels, progressively including the effects from wide- and partial-band jamming, multi-user interference, and varying degrees of Rayleigh and Rician fading. In addition, an optimization approach is formulated that minimizes the bit-error performance of a hybrid DS/FFH communication system and solves for the resulting system design parameters. The optimization objective function is non-convex and can be solved by applying the Karush-Kuhn-Tucker conditions. We also present our efforts toward exploring the design, implementation, and evaluation of a hybrid DS/FFH radio transceiver using a single field-programmable gate array (FPGA). Numerical and experimental results are presented under widely varying design parameters to demonstrate the adaptability of the waveform for varied harsh smart grid RF signal environments.

Performance study of hybrid DS/FFH spread-spectrum systems in the presence of frequency-selective fading and multiple-access interference

Hybrid spread-spectrum (HSS) systems have recently received considerable interest in commercial, Smart Grid, and military communication systems because they accommodate high data rates with high link integrity, even in the presence of significant multipath effects and interfering signals. A highly useful form of this modulation scheme is the specific code-related combination of standard direct-sequence spread spectrum (DSSS) with fast frequency-hopping (FFH) spread spectrum, denoted hybrid DS/FFH, wherein multiple frequency hops occur within a single data-bit time. In this paper we perform a simulation-based study of the DS/FFH performance as compared to the existing standard DSSS and FHSS wireless networks. The performance metrics are biterror probability and multiple-access capability. The parameter space of DS/FFH, including the DS spreading rate, frequency hopping rate, carrier frequencies, and numbers of users, is explored to show its performance under frequency-selective Rayleigh fading environments and multiuser interference. Direct digital synthesizers to achieve fast hopping speeds are also considered in our study.

Model-free load control for high penetration of solar photovoltaic generation

This paper presents a new model-free control (MFC) mechanism that enables the local distribution level circuit consumption of the photovoltaic (PV) generation by local building loads, in particular, distributed heating, ventilation and air conditioning (HVAC) units. The local consumption of PV generation will help minimize the impact of PV generation on the distribution grid, reduce the required battery storage capacity for PV penetration, and increase solar PV generation penetration levels. The proposed MFC approach with its corresponding intelligent controllers does not require any precise model for buildings, where a reliable modeling is a demanding task. Even when assuming the availability of a good model, the various building architectures would compromise the performance objectives of any model-based control strategy. The objective is to consume most of the PV generation locally while maintaining occupants comfort and physical constraints of HVAC units. That is, by enabling proper scheduling of responsive loads temporally and spatially to minimize the difference between demand and PV production, it would be possible to reduce voltage variations and two-way power flow. Computer simulations show promising results where a significant proportion of the PV generation can be consumed by building HVAC units with the help of intelligent control.