Optimization of three power and desalination plants and exergy-based economic and CO2 emission cost allocation and comparison

Abstract

In this work, a multi-effect distillation with thermal vapor compression desalination unit is proposed to satisfy the freshwater demand of São Mateus, Espírito Santo, Brazil. The desalination unit is driven by saturated vapor produced by boiler or heat recovery steam generator. The goal and main contribution of this work are, respectively, to compare and evaluate the most feasible configuration among a steam power cycle, gas turbine and combined cycle power plant. To accomplish this objective, the first and second laws of thermodynamics are used, and economic analyses are carried out for each option. In consequence, an optimization using a genetic algorithm shows the optimal results. The usage of an exergy-based approach for cost allocation assists in the best judgment. For instance, the combined cycle power plant driving a desalination unit presents the highest net power generation of 51.7 MW and a total cost rate of 24,811 US$ h−1, which means a Leveled Cost of Energy of around 0.132 US$ kWh−1. In addition, it has the lowest exergetic and monetary costs of net power (2.316 kJ kJ−1 and 0.132 US$ kWh−1) and freshwater (17.9 kJ kJ−1 and 2.684 US$ kWh−1). However, it also has the highest environmental cost for net power (22.451 kgCO2 kWh−1) and the second highest one for freshwater (196.120 × 10−3 kgCO2 m−3).

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Abbreviations

c:

Monetary unit cost [US$ kWh−1]

CRF:

Annual capital recovery factor

DTML:

Logarithmic mean temperature difference [°C]

E:

Exergy [kW]

h:

Specific enthalpy [kJ kg−1]

k:

Exergetic unit cost [kW kW−1]

\({\dot{m}}\) :

Mass flow rate [kg s−1]

N:

Hour of plant operation per year [h]

OF:

Objective function

P:

Pressure [kPa]

\({\dot{Q}}\) :

Heat transfer rate [kW]

RP:

Pressure relation

T:

Temperature [°C]

TCI:

Total cost of investment

\({\dot{W}}\) :

Power [kW]

x:

Mass fraction

Ż:

Cost rate [$ s−1]

AC:

Air compressor

APP:

Economizer approach

BO:

Boiler

br:

Brine

CC:

Combustion chamber

ec:

Economizer

ev:

Evaporator

F:

Fuel

fw:

Freshwater

GT:

Gas turbine

in:

Inlet

NET:

Net output

out:

Outlet

PM:

Pump and motor

PP:

Pinch point

rw:

Return water

SA:

Superheating

sh:

Superheater

ST:

Steam turbine

sw:

Sea water

TOT:

Total

α:

External fuel unit cost

η:

Isentropic efficiency

λ:

Specific CO2 emission [kgCO2 kWh−1]

φ:

Maintenance factor [–]

ΔT:

Temperature difference [°C]

AC:

Air compressor

BO:

Boiler

CC:

Combustion chamber

CCI:

Construction cost index

CCPP:

Combined cycle power plant

CEPCI:

Chemical engineering plant cost index

ENR:

Engineering News-Record

FI:

Installation factor

GOR:

Gain output ration

GT:

Gas turbine

HRS:

Heat recovery steam generator

MED:

Multi-effect distillation

MSF:

Multi stage flash

OF:

Objective function

PEC:

Purchase equipment cost

PM:

Pump and motor

RO:

Reverse osmosis

ST:

Steam turbine

TVC:

Thermal vapor compression

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Acknowledgements

The authors would like to thank Professor Márcio Coelho de Mattos, Head of DEM/Ufes, for his support.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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Correspondence to A. B. Lourenço.

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Chun, A., Barone, M.A. & Lourenço, A.B. Optimization of three power and desalination plants and exergy-based economic and CO2 emission cost allocation and comparison. Int J Energ Water Res 4, 13–25 (2020). https://doi.org/10.1007/s42108-019-00047-3

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Keywords

  • Combined cycle
  • Exergoeconomics
  • Gas turbine
  • Genetic algorithm
  • Multi-effect distillation
  • Steam cycle