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Demand control for maintaining grid frequency without affecting consumers’ quality of service through decentralized bandwidth-constrained MPC (2017)

We propose a decentralized algorithm to help reduce demand-supply imbalance in a power grid by varying the demand from loads, just like charging and discharging a battery. The algorithm ensures strict bounds on the consumers’ quality of service (QoS) by putting constraints on the bandwidth of demand variation. A model-predictive control (MPC) formulation is adopted to compute local decisions at the loads. The algorithm is decentralized in the sense that loads do not communicate with one another. Instead, loads use local measurements of the grid-frequency, which provide information about global demand-supply imbalance, to coordinate their actions. It is envisioned that consumers will be recruited through long-term contracts, aided by the QoS guarantees provided by the proposed scheme. Simulation results show that loads are successfully able to reduce frequency deviations while maintaining QoS constraints and that the performance of the algorithm scales well with the number of loads. Closed-loop stability is established under some assumptions.

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The role of values, moral norms, and descriptive norms in building occupant responses to an energy-efficiency pilot program and to framing of related messages (2015)

This study examined building occupants’ responses associated with an occupant-based energy-efficiency pilot in a university building. The influence of occupants’ values and norms as well as effects of two educational message frames (descriptive vs. moral norms cues) on program support were tested. Occupants’ personal moral norm to conserve energy predicted willingness to dress differently; perceptions that other occupants tried to conserve energy were related to increased intention to complain about the program. Those who received the descriptive-norms message were somewhat more likely to say they might complain about the program. Implications for communicating about similar energy-saving interventions in large organizations are discussed.

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Identification of control-oriented thermal models of rooms in multi-room buildings (2013)

Model-based control for improving energy efficiency of buildings has been a popular topic of late. Smart control requires a predictive model of the building’s thermal dynamics. Due to the complexity of the underlying physical processes, usually system identification techniques are used to identify parameters of a physicsbased grey-box model. We investigate questions of required model structure and identification techniques for parameter estimation of a single zone model through a combination of analysis and experiments. Our results indicate that a secondorder model can reproduce the input-output behavior of a full-scale model with 13 states. We also show that data collected during usual operation leads to poor parameter estimates that may nevertheless appear to predict the temperature well. The error becomes apparent when there is sufficient difference among various inputs and the output. We propose an algorithm to overcome these issues that involve specific forced-response tests. The results of this investigation are expected to provide guidelines on do’s and don’t’s in modeling and identification of buildings for control.

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