rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    non sort: A
    title: methodology to measure retrofit energy savings in commercial buildings
  name:
    name part: Kissock, John Kelly
    name part: 1958-
    role:
      role term: creator
  name:
    name part: Anand, N. K.
    role:
      role term: degree committee member.
  name:
    name part: Claridge, David E.
    role:
      role term: degree supervisor.
  name:
    name part: Haberl, Jeff S.
    role:
      role term: degree committee member.
  name:
    name part: Pendleton, Olga
    role:
      role term: degree committee member.
  name:
    name part: Reddy, T. Agami
    role:
      role term: degree committee member.
  name:
    name part: Texas A & M University
    role:
      role term: degree granting institution.
  type of resource: text
  genre: bibliography
  genre: Academic theses
  origin info:
    place:
      place term: xx
    date issued: 1993
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: print
    extent: xxiv, 205 leaves : illustrations ; 28 cm
  abstract: Measured energy savings promote and sustain energy conservation retrofits by verifying the success of retrofits, determining pay-back schedules, guiding the selection of future retrofits and identifying opportunities for further savings. This dissertation develops a methodology to measure retrofit energy savings and the uncertainty of the savings in commercial buildings. The functional forms of empirical models of cooling and heating energy use in commercial buildings are derived from an engineering analysis of constant-air-volume and variable-air-volume HVAC systems. One, two, three and four parameter, temperature-dependent regression models are proposed to model baseline energy use. Retrofit savings are measured as the difference between the baseline energy use projected by the models and the measured post-retrofit energy use. A hybrid ordinary least squares/autoregressive method is developed to determine the uncertainty of the predicted energy use and savings. The annual predictive ability of models based on pre-retrofit data sets of less than a full year is investigated. The energy delivery efficiency is introduced to measure the efficiency of air-side systems at meeting the net building load. A preliminary investigation of the use of artificial neural network models to measure savings is presented. The methodology is demonstrated on case study examples using software specifically developed for the analysis of commercial building energy use.
  note: "Major subject: Mechanical Engineering."
  note: Vita.
  note: Ph. D. Texas A & M University 1993
  note: Includes bibliographical references.
  subject:
    topic: Major mechanical engineering
  identifier: http://proxy.library.tamu.edu/login
  identifier: https://hdl.handle.net/1969.1/DISSERTATIONS-1529833
  identifier: http://gateway.proquest.com/openurl
  related item:
    location:
      url: http://proxy.library.tamu.edu/login
  related item:
    location:
      url: https://hdl.handle.net/1969.1/DISSERTATIONS-1529833
  related item:
    location:
      url: http://gateway.proquest.com/openurl
  record info:
    record content source: TXA
    record creation date: 960404
    record change date: 20220103134924.0
    record identifier: in00001284260
    language of cataloging:
      language term: eng