Rapid multi-objective optimization with multi-year future weather condition and decision-making support for building retrofit

Pengyuan Shen, William Braham, Yun Kyu Yi, Eric Eaton

Research output: Contribution to journalArticle

Abstract

A method of fast multi-objective optimization and decision-making support for building retrofit planning is developed, and lifecycle cost analysis method taking into account of future climate condition is used in evaluating the retrofit performance. In order to resolve the optimization problem in a fast manner with recourse to non-dominate sorting differential evolution algorithm, the simplified hourly dynamic simulation modeling tool SimBldPy is used as the simulator for objective function evaluation. Moreover, the generated non-dominated solutions are treated and rendered by a layered scheme using agglomerative hierarchical clustering technique to make it more intuitive and sense making during the decision-making process as well as to be better presented. The suggested optimization method is implemented to the retrofit planning of a campus building in UPenn with various energy conservation measures (ECM) and costs, and more than one thousand Pareto fronts are obtained and being analyzed according to the proposed decision-making framework. Twenty ECM combinations are eventually selected from all generated Pareto fronts. It is manifested that the developed decision-making support scheme shows robustness in dealing with retrofit optimization problem and is able to provide support for brainstorming and enumerating various possibilities during the decision-making process.

Original languageEnglish (US)
Pages (from-to)892-912
Number of pages21
JournalEnergy
Volume172
DOIs
StatePublished - Apr 1 2019

Keywords

  • Building retrofit
  • Climate change
  • Heuristic method
  • Hierarchical clustering
  • Optimization
  • Pareto fronts

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Building and Construction
  • Pollution
  • Mechanical Engineering
  • Industrial and Manufacturing Engineering
  • Electrical and Electronic Engineering

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