Indoor climate control in multi-unit grid-interactive efficient buildings

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Naqvi, Syed Ahsan Raza
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Electronic thesis
Electrical engineering
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In this work, we develop a number of energy management policies for building heating,ventilation and cooling (HVAC) systems for satisfying various objectives. Control policies whose objective is to improve building operations are primarily aimed at economizing indoor climate control operations. On the other hand, occupant-centric control strategies prioritize the comfort of individual occupants. In this dissertation, we evaluate the performance of some of these policies in both simulated and physical setups. The thermal inertia of buildings, along with the flexibility associated with thermostatically controlled loads (TCLs) allows HVAC systems to be used for grid demand response (DR). The initial few chapters of this report develop control strategies aimed at minimizing the operational costs of a building’s HVAC system. We first consider a hydronic HVAC system that serves multiple units in a residential building to meet their space heating requirements. We determine the optimal power flow to each unit that minimizes the energy costs (EC) incurred by the building while keeping in consideration the occupants’ thermal comfort. The building is assumed to participate in a DR program which allows the building temperatures to deviate from the set-points up to a maximum limit. Despite the complex, non-linear structure of the problem, we show how the optimal solutions can be obtained efficiently using quadratic programming. Since HVAC systems can run on either electricity or natural gas, we study the efficacy of the DR regime for both hourly electricity prices and flat gas prices over the course of 24 hours. We also study the optimal thermal power and the evolution of unit temperatures for various energy pricing schemes. Subsequently, we expand the scope of our work to include TCLs in large commercial buildings. The load profiles of most commercial and industrial consumers are characterized by brief periods of very high power consumption followed by intervals of lower demand. To encourage such consumers to flatten their load profiles, power utilities in around the world often levy a monthly demand charge (DC) on the peak demand measured over brief intervals. It was seen in the preceding study that a control policy that minimizes EC while being agnostic to instantaneous power consumption can introduce significant spikes in the building’s demand patterns. Therefore, we expand our study on hydronic HVAC systems to consider the joint optimization of EC and the instantaneous peak power of a multi-unit building that participates in a DR program. We study the power demand patterns resulting from our proposed control strategy for TCLs, and evaluate its performance for various climate zones in the US, under both typical and atypical weather conditions. The results show that depending on the ambient conditions and the tariff structure, our control policy can result in utility bill savings of up to nearly 19% compared to the baseline. Our power control strategy was also seen to significantly reduce the instantaneous peak power consumption in commercial TCLs. The work summarized hitherto is primarily centered around developing theoretical control frameworks for building HVAC systems as desired by building operators (BOs). However, the next part of the research presented in this report develops multiple control strategies for heating and cooling operations in buildings for meeting the objectives of both the BO and the building occupants. Moreover, this part of our report develops a prototype for autonomous temperature management schemes that can be readily deployed in a real-life shared workspace. Specifically, we study the problem of indoor zone temperature control in shared workspaces equipped with heterogeneous heating and cooling sources with the goal of increased energy savings and environment personalization. Shared workspaces typically witness distinct intervals when they are occupied or are unoccupied. Moreover, these intervals generally follow a fixed schedule which may be known in advance. In this work, we develop control strategies for space heating and cooling operations to achieve the various indoor conditioning objectives for each of these distinct intervals. Specifically, we consider two contiguous intervals of equal duration where a shared workspace remains unoccupied prior to hosting a scheduled event, such as a work meeting. For the first interval, when the workspace is unoccupied, we propose multiple time-bound pre-cooling/pre-heating control strategies for conditioning the workspace in preparation for a scheduled activity (Phase I). For the second interval, when the workspace is occupied, we propose a separate control strategy which enhances the thermal comfort of the occupants by harnessing the spatial differentiation of the thermal environment to satisfy the different temperature preferences of the individuals (Phase II). Utilizing a physical test-bed, we use data-driven model learning to establish a relationship between the HVAC control inputs of the indoor space, and the zone temperatures. Next, we present a simple control strategy to achieve the pre-conditioning objective in Phase I and show that it is less computationally expensive than conventional model predictive control (MPC). For Phase II, we then use a simple, low complexity, quadratic program to minimize the thermal discomfort experienced by individuals based on their temperature preferences. The experimental results show that for Phase I, the proposed control policies can save a significant amount of energy and achieve the desired mean temperature in the space fairly accurately. We further note that for Phase II, the control scheme can achieve a significant spatial differentiation in temperature towards satisfying the occupants’ thermal preferences. Occupant well-being requires not only efficient indoor thermal management but also indoor air quality (IAQ) management. Control strategies aimed at improving the efficiency of HVAC systems while enhancing occupant wellness must jointly optimize ventilation as well as heating and cooling operations. The final direction of this work studies the problem of minimizing the energy consumption of the HVAC system in a multi-unit building, while meeting thermal comfort and IAQ requirements. Here, we use zonal carbon dioxide (CO2) to be an indicator for IAQ in individual zones. We first perform a steady state analysis of the zonal CO2 concentration and the temperature dynamics. The resulting expressions are convex in the zonal mass flow rates and zonal temperatures. Guided by the steady state solutions for meeting the thermal comfort constraints, we develop two control policies for improving the energy efficiency of building HVAC systems while jointly satisfying indoor temperature and IAQ constraints. We compare the performance of our proposed approaches with those of multiple baseline approaches which implement separate regimes for managing zonal temperature and IAQ for a typical work-day in a multi-zone campus building. We have evaluated the performance of our proposed approaches under varying levels of flexibility in zonal temperatures. Our proposed approaches were seen to offer potential savings of nearly 29% compared to the baseline. In the closing chapter of this report, we offer some remarks pertaining to the results obtained from the aforementioned studies. We conclude this report by proposing possible extensions to this work.
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Rensselaer Polytechnic Institute, Troy, NY
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