Published February 1, 2017 | Version v1
Journal article

Mathematical modelling and optimization of a large-scale combined cooling, heat, and power system that incorporates unit changeover and time-of-use electricity price

  • 1. School of Material and Energy, Guangdong University of Technology, No. 100 Waihuan Xi Road, Guangzhou Higher Education Mega Center, Panyu District, Guangzhou 510006 (China)
  • 2. Soft Matter Center, Guangdong Province Key Laboratory on Functional Soft Matter, No. 100 Waihuan Xi Road, Guangzhou Higher Education Mega Center, Panyu District, Guangzhou 510006 (China)
  • 3. School of Chemistry and Chemical Engineering, Key Lab of Low-carbon Chemistry & Energy Conservation of Guangdong Province, Sun Yat-Sen University, No. 135, Xingang West Road, Guangzhou 510275 (China)

Description

Highlights: • We propose a novel superstructure for the design and optimization of LSCCHP. • A multi-objective multi-period MINLP model is formulated. • The unit start-up cost and time-of-use electricity prices are involved. • Unit size discretization strategy is proposed to linearize the original MINLP model. • A case study is elaborated to demonstrate the effectiveness of the proposed method. - Abstract: Building energy systems, particularly large public ones, are major energy consumers and pollutant emission contributors. In this study, a superstructure of large-scale combined cooling, heat, and power system is constructed. The off-design unit, economic cost, and CO2 emission models are also formulated. Moreover, a multi-objective mixed integer nonlinear programming model is formulated for the simultaneous system synthesis, technology selection, unit sizing, and operation optimization of large-scale combined cooling, heat, and power system. Time-of-use electricity price and unit changeover cost are incorporated into the problem model. The economic objective is to minimize the total annual cost, which comprises the operation and investment costs of large-scale combined cooling, heat, and power system. The environmental objective is to minimize the annual global CO2 emission of large-scale combined cooling, heat, and power system. The augmented ε–constraint method is applied to achieve the Pareto frontier of the design configuration, thereby reflecting the set of solutions that represent optimal trade-offs between the economic and environmental objectives. Sensitivity analysis is conducted to reflect the impact of natural gas price on the combined cooling, heat, and power system. The synthesis and design of combined cooling, heat, and power system for an airport in China is studied to test the proposed synthesis and design methodology. The Pareto curve of multi-objective optimization shows that the total annual cost varies from 102.53 to 94.59 M$ and the annual CO2 emission varies from 407390.4 to 328632.3 ton. The total annual cost of the scheme without simultaneously incorporating unit start-up cost is 1.23% higher than that of the scheme simultaneously incorporating unit start-up cost. The natural gas price sensitivity analysis results show that the natural gas-based combined cooling, heat and power system is superior to power importation in both economic and environmental performance when the natural gas price is lower than 500 $/t.

Availability note (English)

Available from http://dx.doi.org/10.1016/j.enconman.2016.10.056

Additional details

Identifiers

DOI
10.1016/j.enconman.2016.10.056;
PII
S0196-8904(16)30970-0;

Publishing Information

Journal Title
Energy Conversion and Management
Journal Volume
133
Journal Page Range
p. 385-398
ISSN
0196-8904
CODEN
ECMADL

Optional Information

Copyright
Copyright (c) 2016 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.