5,312 research outputs found
Modeling and control of complex building energy systems
Building energy sector is one of the important sources of energy consumption and especially
in the United States, it accounts for approximately 40% of the total energy consumption.
Besides energy consumption, it also contributes to CO2 emissions due to the combustion of
fossil fuels for building operation. Preventive measures have to be taken in order to limit the
greenhouse gas emission and meet the increasing load demand, energy efficiency and savings
have been the primary objective globally. Heating, Ventilation, and air-conditioning (HVAC)
system is a major source of energy consumption in buildings and is the principal building system
of interest. These energy systems comprising of many subsystems with local information
and heterogeneous preferences demand the need for coordination in order to perform optimally.
The performance required by a typical airside HVAC system involving a large number of zones
are multifaceted, involves attainment of various objectives (such as optimal supply air temperature)
which requires coordination among zones. The required performance demands the need
for accurate models (especially zones), control design at the individual (local-VAV (Variable Air
Volume)) subsystems and a supervisory control (AHU (Air Handling Unit) level) to coordinate
the individual controllers.
In this thesis, an airside HVAC system is studied and the following considerations are addressed:
a) A comparative evaluation among representative methods of different classes of
models, such as physics-based (e.g., lumped parameter autoregressive models using simple
physical relationships), data-driven (e.g., artificial neural networks, Gaussian processes) and
hybrid (e.g., semi-parametric) methods for different physical zone locations; b) A framework
for control of building HVAC systems using a methodology based on power shaping paradigm
that exploits the passivity property of a system. The system dynamics are expressed in the
Brayton-Moser (BM) form which exhibits a gradient structure with the mixed-potential function,
which has the units of power. The power shaping technique is used to synthesize the controller by assigning a desired power function to the closed loop dynamics so as to make the equilibrium point asymptotically stable, and c) The BM framework and the passivity tool are
further utilized for stability analysis of constrained optimization dynamics using the compositional
property of passivity, illustrated with energy management problem in buildings. Also,
distributed optimization (such as subgradient) techniques are used to generate the optimal setpoints
for the individual local controllers and this framework is realized on a distributed control
platform VOLTTRON, developed by the Pacific Northwest National Laboratory (PNNL)
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High-Performance Integrated Window and Façade Solutions for California
The researchers developed a new generation of high-performance façade systems and supporting design and management tools to support industry in meeting California’s greenhouse gas reduction targets, reduce energy consumption, and enable an adaptable response to minimize real-time demands on the electricity grid. The project resulted in five outcomes: (1) The research team developed an R-5, 1-inch thick, triplepane, insulating glass unit with a novel low-conductance aluminum frame. This technology can help significantly reduce residential cooling and heating loads, particularly during the evening. (2) The team developed a prototype of a windowintegrated local ventilation and energy recovery device that provides clean, dry fresh air through the façade with minimal energy requirements. (3) A daylight-redirecting louver system was prototyped to redirect sunlight 15–40 feet from the window. Simulations estimated that lighting energy use could be reduced by 35–54 percent without glare. (4) A control system incorporating physics-based equations and a mathematical solver was prototyped and field tested to demonstrate feasibility. Simulations estimated that total electricity costs could be reduced by 9-28 percent on sunny summer days through adaptive control of operable shading and daylighting components and the thermostat compared to state-of-the-art automatic façade controls in commercial building perimeter zones. (5) Supporting models and tools needed by industry for technology R&D and market transformation activities were validated. Attaining California’s clean energy goals require making a fundamental shift from today’s ad-hoc assemblages of static components to turnkey, intelligent, responsive, integrated building façade systems. These systems offered significant reductions in energy use, peak demand, and operating cost in California
Ten questions concerning integrating smart buildings into the smart grid
Recent advances in information and communications technology (ICT) have initiated development of a smart electrical grid and smart buildings. Buildings consume a large portion of the total electricity production worldwide, and to fully develop a smart grid they must be integrated with that grid. Buildings can now be ‘prosumers’ on the grid (both producers and consumers), and the continued growth of distributed renewable energy generation is raising new challenges in terms of grid stability over various time scales. Buildings can contribute to grid stability by managing their overall electrical demand in response to current conditions. Facility managers must balance demand response requests by grid operators with energy needed to maintain smooth building operations. For example, maintaining thermal comfort within an occupied building requires energy and, thus an optimized solution balancing energy use with indoor environmental quality (adequate thermal comfort, lighting, etc.) is needed. Successful integration of buildings and their systems with the grid also requires interoperable data exchange. However, the adoption and integration of newer control and communication technologies into buildings can be problematic with older legacy HVAC and building control systems. Public policy and economic structures have not kept up with the technical developments that have given rise to the budding smart grid, and further developments are needed in both technical and non-technical areas
Customer Engagement Plans for Peak Load Reduction in Residential Smart Grids
In this paper, we propose and study the effectiveness of customer engagement
plans that clearly specify the amount of intervention in customer's load
settings by the grid operator for peak load reduction. We suggest two different
types of plans, including Constant Deviation Plans (CDPs) and Proportional
Deviation Plans (PDPs). We define an adjustable reference temperature for both
CDPs and PDPs to limit the output temperature of each thermostat load and to
control the number of devices eligible to participate in Demand Response
Program (DRP). We model thermostat loads as power throttling devices and design
algorithms to evaluate the impact of power throttling states and plan
parameters on peak load reduction. Based on the simulation results, we
recommend PDPs to the customers of a residential community with variable
thermostat set point preferences, while CDPs are suitable for customers with
similar thermostat set point preferences. If thermostat loads have multiple
power throttling states, customer engagement plans with less temperature
deviations from thermostat set points are recommended. Contrary to classical
ON/OFF control, higher temperature deviations are required to achieve similar
amount of peak load reduction. Several other interesting tradeoffs and useful
guidelines for designing mutually beneficial incentives for both the grid
operator and customers can also be identified
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