Role of control, communication, and markets in smart building operation
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This thesis explores the role of control, communication, and markets in the operation of smart buildings and microgrids. It develops models to study demand response (DR) alternatives in smart buildings using different communication and control protocols in building management systems. Moreover, it aims at understanding the extent to which smart buildings can provide regulation service reserves (RSR) by real time direct load control (DLC) or price-based indirect control approaches. In conducting a formal study of these problems, we first investigate the optimal operational performance of smart buildings using a control protocol called packetized direct load control (PDLC). This is based on the notion of the energy packet which is a temporal quantization of energy supplied to an appliance or appliance pool by a smart building operator (SBO). This control protocol is built on top of two communication protocols that carry either complete or binary information regarding the operation status of the appliances in the pool. We discuss the optimal demand side operation for both protocols and analytically derive the performance differences between them. We analyze the costs of renewable penetration to the system's real time operation. In order to strike a balance between excessive day-ahead energy reservation costs and stochastic real time operation costs, we propose an optimal reservation strategy for traditional and renewable energy for the PDLC in both the day-ahead and the real time markets to hedge the uncertainty of real time energy prices and renewable energy realization. The second part of the thesis proposes systematic approaches for smart buildings to reliably participate in power reserve markets. The problem is decomposed into two parts in the first of which the SBO starts by estimating its prior capacity of reserve provision based on characteristics of the building, the loads, and consumer preferences. We show that the building's reserve capacity is governed by a few parameters and that there is a trade off for smart buildings to provide either sustained reserve or ramping reserve. Based on the estimated capacity, we propose two real time control mechanisms to provide reliable RSR. The first is a DLC framework wherein consumers allow the SBO to directly modulate their appliances' set points within allowable ranges. We develop a feedback controller to guarantee asymptotic tracking performance of the smart building's aggregated response to the RSR signal. The second is a price controlled framework that allows consumers to voluntarily connect and consume electricity based on their instantaneous utility needs. Consumers' time varying dynamic preferences in providing RSR are studied by Monte Carlo simulation, in which such preferences are characterized by sufficient statistics that can be used in a stochastic dynamic programming (DP) formulation to solve for the optimal pricing policy.