Power electronics implementation of dynamic thermal storage as effective inertia in large energy systems

Cao, Yue

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https://hdl.handle.net/2142/98350 Copy

Description

Title

Power electronics implementation of dynamic thermal storage as effective inertia in large energy systems

Author(s)

Cao, Yue

Issue Date

2017-07-10

Director of Research (if dissertation) or Advisor (if thesis)

Krein, Philip T.

Doctoral Committee Chair(s)

Krein, Philip T.

Committee Member(s)

• Alleyne, Andrew G.
• Haran, Kiruba S.
• Pilawa-Podgurski, Robert C.N.

Department of Study

Electrical & Computer Eng

Discipline

Electrical & Computer Engr

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

• Power electronic and drives
• Power systems
• Energy storage
• Complex system energy management
• Thermal storage
• Grid-level energy storage
• Stochastic energy resources
• Energy efficient buildings
• Heating, ventilation, and air conditioning (HVAC) systems
• Solar energy
• Thermal modeling
• Maximum power point tracking (MPPT)
• High frequency solar data
• More electric aircraft (MEA)
• Electric vehicles
• Environmental control systems (ECS)
• Lithium-ion battery
• Modeling and simulation
• Loss modeling
• Battery modeling
• Vehicle dynamic simulator

Abstract

Modern large energy systems such as electricity grids and electrified transportation encounter increasing processed power in multi-physics domains, such as electrical, mechanical, thermal, and chemical. Although many systems are becoming predominantly electrical dependent, an integrated multi-physics energy approach creates additional avenues to higher power density, system efficiency, and reliability. Power electronics, serving as power conversion mechanisms, are key linking subsystems consisting of electronic devices, electro-mechanical units, energy storage, etc. This dissertation first studies the use of power electronic drives to implement dynamic thermal storage as effective inertia in solar-interfaced grid-connected low-energy buildings, as an example of a stationary large energy system. Dynamic management of energy components is used to offset variability of stochastic solar resources. Emphasis is on power electronic HVAC (heating, ventilation, and air-conditioning) drives, which can act as an effective electric swing bus to mitigate solar power variability. In doing so, grid power flows become substantially more constant, reducing the need for fast grid resources or dedicated energy storage such as batteries. The work defines a bandwidth over which such HVAC drives can operate. A practical band-pass filter is realized with a lower frequency bound such that the building maintains consistent temperature, and an upper frequency bound to ensure that commanded HVAC fan speeds do not update arbitrarily fast, avoid acoustic discomfort to occupants, and prevent undue hardware wear and tear. The dissertation then moves onto investigation of a mobile energy system, specifically more electric aircraft (MEA), with the purpose of evaluating thermal inertia’s efficacy in a microgrid-like inertia-lacking electrical system. Thermal energy inherent in the cabin air and aircraft fuel serves as a dynamic management solution to offset stochastic load power in the MEA power system. Power electronic controlled environmental control system (ECS) drives, emulating dynamic thermal inertia, showcase a more constant generator output power, allowing potential to downsize required generator ratings. An operating bandwidth is proposed similar to that of building HVAC systems, subject to additional degrees of constraints unique on MEA. A more sensitive virtual synchronous machine control boosts desirable inertia in sub-seconds scales in the MEA power system. To validate the thermal storage as effective inertia in both stationary and mobile energy systems, comprehensive simulation studies and experimental work are conducted at multiple levels. For the energy-efficient building research platform, building electrical and thermal energy systems modeling is addressed, including solar and HVAC systems as well as batteries and large-scale thermal storage. A lab-scale power system features various update rates of a variable frequency fan drive over stochastic solar data. A full-scale multiple-day case study provides insight on potential grid-side and storage-related benefits. The simulation and experimental studies are supported by 18 months of solar data collected on sub-millisecond time scales as a basis to evaluate efficacy, determine solar frequency-domain content, and analyze mitigation of variability. For the MEA research platform, steady-state and dynamic behaviors of electrical components in the Boeing 787 power systems, including electric machines, power converters, batteries, transformers, and loads, are modeled. In particular, in-depth discussions cover a multi-timescale parametric electrical battery model for use in dynamic electric transportation simulations. An integrated thermal model within electrical components and electrical systems captures temperature variations and ECS thermal dynamics. Simulation studies based on realistic load power demand over a 5-hour mission profile show mitigation of generator power transients while maintaining relatively comfortable cabin temperature bounds. Finally a scaled-down lab power system is implemented on a microcontroller-tied industrial drive to demonstrate feasibility in a potential commercial system.

Graduation Semester

2017-08

Type of Resource

text

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http://hdl.handle.net/2142/98350

Copyright and License Information

Copyright 2017 Yue Cao

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