Thermodynamics-based optimization and control of integrated energy systems

Jain, Neera

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Description

Title

Thermodynamics-based optimization and control of integrated energy systems

Author(s)

Jain, Neera

Issue Date

2013-05-24T22:05:31Z

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

Alleyne, Andrew G.

Doctoral Committee Chair(s)

Alleyne, Andrew G.

Committee Member(s)

• Kyritsis, Dimitrios C.
• Salapaka, Srinivasa M.
• Domínguez-García, Alejandro D.
• Stoustrup, Jakob

Department of Study

Mechanical Sci & Engineering

Discipline

Mechanical Engineering

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

• optimization and control
• thermal energy systems
• second-law analysis
• exergy analysis
• integrated energy systems

Abstract

With increasing worldwide demand for energy comes the need to both generate and consume energy more efficiently. Integrated energy systems (IESs) combine power generation technologies, such as internal combustion engines or fuel cells, with other technologies which directly utilize the power produced by the generator and/or utilize the thermal energy otherwise wasted in the production of power. IESs are becoming more prevalent because of their environmental, economic, and reliability benefits. However, to fully realize these benefits, effective optimization and control of IESs is required. In turn, this requires a function which can accurately capture the objectives (performance, efficiency, etc.) for the system in terms of desired decision variables. The aim of this research is to develop a systematic methodology for developing objective functions to be used in conjunction with optimal control algorithms for improving operational efficiency and performance of IESs. This is accomplished through the use of a thermodynamics-based minimization metric, exergy destruction, which is used as the foundation for deriving objective functions which are 1) physics-based, 2) generalizable to a wide class of IESs, and 3) modular with the ability to characterize not only an entire IES but also specific subsystems of a larger IES. Exergy destruction can be used to characterize irreversibilities across multiple energy domains (chemical, electrical, mechanical, and thermal) making it a particularly suitable metric for IESs. The generalizability and modularity of the optimization framework is demonstrated through static setpoint optimization of a combined heating, cooling, and power (CCHP) system with time-varying performance demands. It was shown that minimizing exergy destruction increases exergetic efficiency at some expense of energy consumption, but that the decrease in exergy destruction can possibly outweigh the increases in energy consumption. An additional layer of flexibility was introduced as the “interchangeability” between power minimization and exergy destruction rate minimization for those subsystems in which the reversible power is constant with respect to the decision variables. Interchangeability allows the user to only derive the exergy destruction rate for those systems in which the equivalence does not hold and construct an objective function which would result in the same solution as minimizing the rate of exergy destruction in every subsystem. Exergy analyses have long been used to better understand the behavior of a variety of thermodynamic systems, primarily from a static design and operation point of view. However, as the complexity of integrated energy systems grows, for example as a result of intermittent grid power from renewable energy technologies such as wind and solar, an understanding of transient behavior is needed. As a case study, the dynamic exergy destruction rate was derived for the refrigerant-side dynamics of a vapor-compression cycle system and then used in formulating an exergy destruction minimization (EDM) optimal control problem for the system with full actuation capabilities. The results highlighted how time-varying control decisions can affect the distribution of irreversibilities throughout the overall system. Moreover, it was shown that EDM has the potential to uncover a different set of solutions than those produced by an energy or power minimization and is therefore a valuable tool for operational optimization of IESs.

Graduation Semester

2013-05

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Copyright and License Information

Copyright 2013 Neera Jain

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