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Optimizing Power, Heating, and Cooling Capacity on a Decision-Guided Energy Investment Framework

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Enterprise Information Systems (ICEIS 2013)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 190))

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Abstract

We propose a Decision-Guided Energy Investment (DGEI) Framework to optimize power, heating, and cooling capacity. The DGEI framework is designed to support energy managers to (1) use the analytical and graphical methodology to determine the best investment option that satisfies the designed evaluation parameters, such as return on investment (ROI) and greenhouse gas (GHG) emissions; (2) develop a DGEI optimization model to solve energy investment problems that the operating expenses are minimal in each considered investment option; (3) implement the DGEI optimization model using the IBM Optimization Programming Language (OPL) with historical and projected energy demand data, i.e., electricity, heating, and cooling, to solve energy investment optimization problems; and (4) conduct an experimental case study for a university campus microgrid and utilize the DGEI optimization model and its OPL implementations, as well as the analytical and graphical methodology to make an investment decision and to measure trade-offs among cost savings, investment costs, maintenance expenditures, replacement charges, operating expenses, GHG emissions, and ROI for all the considered options.

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Author information

Authors and Affiliations

  1. Department of Computer Science, George Mason University, 4400 University Drive, Fairfax, VA, 22030, USA

    Chun-Kit Ngan, Alexander Brodsky & Nathan Egge

  2. Facilities Management Department, George Mason University, 4400 University Drive, Fairfax, VA, 22030, USA

    Erik Backus

Authors
  1. Chun-Kit Ngan
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  2. Alexander Brodsky
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  3. Nathan Egge
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  4. Erik Backus
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Corresponding author

Correspondence to Chun-Kit Ngan .

Editor information

Editors and Affiliations

  1. Groupe ESEO, Angers, France

    Slimane Hammoudi

  2. Polytechnic Institute of Setúbal, Setúbal, Portugal & INSTICC, Setúbal, Portugal

    José Cordeiro

  3. Wroclaw University of Economics, Wroclaw, Poland & Macquarie University, Sydney, NSW, Australia

    Leszek A. Maciaszek

  4. Polytechnic Institute of Setúbal, Setúbal, Portugal & INSTICC, Setúbal, Poland

    Joaquim Filipe

Appendix: Abbreviation

Appendix: Abbreviation

Abbreviation

Full Name

Abbreviation

Full Name

CHCP

Centralized Heating and Cooling Plant

ES

Electricity Supply

CO2

Carbon Dioxide

FCWA

Fairfax County Water Authority

CoGen

Cogeneration

FMD

Facilities Management Department

DGEI

Decision-Guided Energy Investment

GHG

Greenhouse Gas

DVPC

Dominion Virginia Power Company

MILP

Mixed Integer Linear Programming

EC

EnergyConnect

MINLP

Mixed Integer Non-Linear Programming

ECU

Energy Contractual Utility

NOx

Mono-Nitrogen Oxide

EFD

Energy Future Demand

OPL

Optimization Programming Language

EFE

Energy Facility Expansion

QoS

Quality of Service

EGP

Energy Generation Process

ROI

Return On Investment

EHD

Energy Historical Demand

WGLC

Washington Gas Light Company

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Ngan, CK., Brodsky, A., Egge, N., Backus, E. (2014). Optimizing Power, Heating, and Cooling Capacity on a Decision-Guided Energy Investment Framework. In: Hammoudi, S., Cordeiro, J., Maciaszek, L., Filipe, J. (eds) Enterprise Information Systems. ICEIS 2013. Lecture Notes in Business Information Processing, vol 190. Springer, Cham. https://doi.org/10.1007/978-3-319-09492-2_10

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  • DOI: https://doi.org/10.1007/978-3-319-09492-2_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-09491-5

  • Online ISBN: 978-3-319-09492-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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