Environmental influence prediction of discharged waterfrom ocean thermal energy conversion plantin Kume-Island by numerical simulations
Zhe WangMarine Environmental System Lab.
Department of Ocean Technology, Policy, and Environment
Graduate School of Frontier Science
The University of Tokyo
Supervisor:
Professor Shigeru TABETA
January 30, 2017

Outline
1. Introduction

3. Results & Discussion

OTEC plant

100MW offshore plant

Environmental issues
Study cases
Previous work
Objectives

2. Methodology
Computational models
Model validation
Computational conditions
Grid system verification

4. Effect of difference indischarge scheme
Discharge depthProportion of surface water anddeep seawater

5. Conclusion

Introduction

Introduction: OTEC plant
What is OTEC :A renewable energy technology that exploits the thermal difference between surface seawaterand deep seawater to generate electric power.

Suitable area :Tropical and subtropical oceans.

Categorization :Closed-cycle, open-cycle and hybrid cycle.

Principle of Closed-cycle :→ vaporized into vapor by surface water→ drive the turbine to work
→ cooled by the deep ocean water→ recycled in the system→ used surface water and DOW will be discharged.

Fig.1. Schematic diagram of closedcycle OTEC power plant [1].

Introduction: environmental issues
Properties of Deep Ocean Water (DOW):• Cleanness, uniformity, enormous reservation, fast renewability.
• Low temperature, high nutrient concentrations.

Environmental influence :Enhance primary productivity

Benefit Create fish ground.
IssuesAlter local marine environment
Cause a phytoplankton bloom.
Perturb natural population of marine organisms.

Project of OTEC plant:

Fig.2. 50 kW OTEC plant on
Kume-Island [2].

In 1974, OTEC study in Japan started with launch of Sunshine Project.
In 2013, a 50 kW OTEC pilot plant was constructed on Kume-Island and performing stable.
Now, commercial scales of 1MW~100MW OTEC plants are in the plans.

Introduction: study cases
100 MW offshore OTEC plant

1 MW onshore OTEC plant

9km away from northeast coast.

northeast of Kume-Island

Discharge depth

15 m

50 m, 200 m

Discharge amount

1,480,000 t/h

22,100 t/h

Water temperature

16.9°C

18.7°C

Nitrate concentration

9.541×10#$ µmol/L

8.44×10#$ µmol/L

Location

Introduction: previous work
Marine Environmental influence :Construction, presence, operation of the OTEC plant;
Discharge and withdraw of the seawater.
Quinbyhunt (1987)

One of the most prominent environmental concern isthe potential for upwelled nutrients.

1MW OTEC plant in Tarawa, Kiribati :EFDC and CFD was adopted toidentified the dispersion characteristics
of discharged water.
Hwang-Ki Lee (2016)

Binger (2003)

Numerical simulations :Most of the paper focuses on
Physical Field.

100 MW OTEC plant in Hawaii :EFDC model was adopted to simulate the discharged
plume and clarified the nitrate concentration around
OTEC plant.
Patrick Grandelli (2011)

Few papers concerns about
Ecosystem Response.

Introduction: objectives
This research focuses on
Environmental influence prediction of the discharged water fromthe 100MW offshore OTEC plant and the 1MW onshore OTEC plantin Kume-Island.
This research aims at :• Clarifying the behavior of discharged water;• Predicting the distribution of the water qualities and planktons;• Investigating possible ways to control the environmental influence.

Methodology

Methodology: MEC-NEST model
Model
1. Calculation of hydrodynamic process [3]Navier-Stokes equation:••!"!#!6!#+%+%• 0=−!"!&!6!&!"+'+'- !0. !*!(!6!(−g+)!"!*!6+)!*=−=−- !0+ f' + A 3./ !(- !0./ !(!4 "!4 "!&!(44 +!4 8− fu + A 3!&4+!4 8!(4++!
!*!
!*!;!&+!8!(+!<!*••!#!A+u!=!&!A+v!(!A+w!=!*!A= A@+ u !& + v !( + w !* = A @!#Density equation:• B = B ∗ D, F, G!8!*

(1)
(2)

ttime;

ggravitational acceleration;(7)

Coriolis parameter;

AM Horizontal eddy viscosity coefficient;= 0 (4)!=!*f

KM Vertical eddy viscosity coefficient;

Advection-diffusion equations of the temperature and salinity:!=K3!"

ρ0 standard value of seawater density;(3)

Continuity equation:•K3!4 =!&4!4 A!&4+!4 =!(4!4 A+!
!*!

K@!=!*!A+ !(4 + !* K @ !*

(5)
(6)

AC Horizontal eddy diffusivity coefficient;
KC Vertical eddy diffusivity coefficients.

Methodology: Low-trophic ecosystem model
2. Calculation of low-trophic ecosystem model
Table.1. Compartments in the low-trophic ecosystem modelFig.4 Low-trophic ecosystem model [4].

SymbolCompartment
PS
Small Phytoplankton
PLLarge Phytoplankton
ZS
Small Zooplankton
ZL
Large Zooplankton
ZP
Predatory Zooplankton
NitrateNO3
Ammonium
NH4
Si(OH)4
Silicate
PON
Particulate Organic Nitrogen
DON
Dissolved Organic Nitrogen
Opal
Particulate Silicon
SQNS Cell Quota of Small Phytoplankton Nitrogen
SQNL Cell Quota of Large Phytoplankton Nitrogen
SQSiL
Cell Quota of Large Phytoplankton Silicon

UnitµmolN/LµmolN/LµmolN/LµmolN/LµmolN/LµmolN/LµmolN/LµmolSi/LµmolN/LµmolN/LµmolSi/LµmolN/LµmolN/LµmolSi/L

Methodology: Low-trophic ecosystem model
Suppose B as the variable of each compartment in the ecosystem model.
#!$ represents the biological & chemical process concerning each compartment.
∂ !" ∂ !" ∂ !"∂!
∂ 2 !" ∂ 2 !"∂∂ !"K+u+v+w " = Ac+#!$++c∂t∂x∂y∂z∂z∂z∂x2 ∂y2(8)Q &'( = GppPLn − ResPLn − MorPLn − ExcPLn − GraPL2ZLn − GraPL2ZPn(9)<== represents the production rate due to photosynthesis.
Mor represents mortality rate.
Exc represents extracellular secretion rate.
Res represents respiration rate.
GppPLn NO@ , NHC , Si OH C , Temp, I, PLn = VJKLM minW

exp k RSSM Temp ∫UVX
XYZ[\exp 1 −SQNL
SQSiL,/RSiNSQNL + QNL0 SQSiL + QSiL0X
XYZ[\dz ` PLn(10)Parameters in the model were picked up from Shiokari (2012), the experiment about theeffect of DOW on fertilization in sea area around Oshima.

Model validation
Introduction :Observational data source:

Due to the shortage of local data around area of OTEC
plant, I chose the data available in other sea area.

Experiment on the effect of Takumi
was carried out in 2006.

In the experiment, uranine solution
was used as the tracer to track theApplied density current generator for artificial upwelling.
hydrodynamic motion of sea wateraround Takumi facility.
Mechanism :Pump in deep ocean water and surface ocean water, mix Results of the tracer concentrationand discharge in surrounding sea area.
at the observational spots wasacquired and reported byEffect :Marinoforum21.
Enhancing marine primary productivity by taking
advantages of DOW.

Takumi facility:

Location :Sagami bay, Kanagawa Prefecture

Results were used to validate
MEC-NEST model.

Model validation
Computational Domain:

Grid :
Length : 1000m
Number : 26×21×26

Data source:
Meteorological data : JMA
Water quality data: JODC, WOA13
Topographic data : Sasaki (2005)
Experiment data : Marinoforum (2007)
Fig.5. Location and computational domain ofTakumi facility.

• Red box is computational domain.
• Black dots are the places where theobservation experiment was conducted.

Comparable Approach :1. Observational data which has clear
values are chosen.
2. Tracer concentration of each spots waspicked up from the calculation andobservation data.

Model validation

Fig.7. Comparison between observation data and computational data.

In farther area, computational data agree with the observation data.
In closer area, some incorrespondence occurs.
Local current is not completely taken into consideration.
Fig.6. Uranine observation line.

Validation of MEC-NEST model is accomplished to some extend.

Methodology: conditions
Computational domain :In the horizontal plane :Meteorological condition
Japan Meteorological
Agency (JMA)
Oceanographic condition

Fig.8. 100MW offshore
OTEC plant.

Grid arrangement :Finer grid system→ Enhance the resolution
and precision of results.

Fig.9. Grid system of the 100MW offshore
OTEC plant.

In the vertical plane :Multi-level layers (z-coordinate)• Tide :Tide Model NAO99b• Water quality:
Japan Oceanographic
Data Center (JODC)World Ocean Atlas 2013

Grid system verification
Necessity :Verification of the finer grid system is also necessary to ensure the precision of the results.

Approach :Calculation on nesting3 grid system was conducted and compared with the nesting2 and nesting1.

Fig.9. Grid system of nesting 3

Grid system verification
Results :The amount of water mass of which water temperature drops 0.1℃ ~ 1℃ was calculated.

Fig.10. Amount of water mass of which the water temperature drops.

The results verify that the precision of the nesting2 is enough for the analysis and prediction.

Results & Discussion

Results & Discussion
Results of 100MW offshore OTEC plant :• Results of 60 days in calculation period areused when the variation of water quality(temperature, nutrients, salinity), andphytoplankton are stable.
• From the figure, only a little difference can beidentified.

Subtraction :After OTEC
installation_Before OTEC
installation=

Change due toOTEC installation
Fig.11. Horizontal plane of temperature
distribution at each depths.

Results & Discussion

Water temperature

Nitrate concentration

Fig.12. Changes of temperature distribution and nitrate concentration distribution in horizontal plain
due to discharged water from 100MW OTEC plant.

Water temperature, Nutrient concentration (NO#) :• Depth of 35m is not affected very much.
• Depth where affected most is around the depth of 55m.

Results & Discussion
Large Phytoplankton :• Phytoplankton concentration increases
at the depth around 75m .
• Phytoplankton concentration does notchange in vicinity of OTEC plant but
increases a little far.
Fig.13. Changes of phytoplankton distribution in horizontal
plain due to discharged water from 100MW OTEC plant.

Discussion :• Instead of dispersing at the depth where the discharged water is released, discharged water
will first flow downward, while the density changes at the same time. When it reaches thedepth where the density is the same with itself, it disperses horizontally.
• Phytoplankton increases under the influence of water temperature and nutrients concentration.

Effect of difference in discharge scheme

Effect of difference in discharge scheme
Different depth :Calculation on 4 different discharge
depth is attempted.
Table.2. water temperature and density of thebackground.

Fig.14. Distribution of temperature and phytoplankton concentration
change of different discharge depth.

Schemes of discharge depth 7.5m, 15m, 25m have little changes.
Scheme of discharge depth 55m, affected area is smaller.
Scheme of discharge depth 205m, affected area is limited.

Effect of difference in discharge scheme
Different proportion of the deep sea water and surface water :Amount of the DOW was not changed to maintain theefficiency of the OTEC plant.
By increasing the surface water, the proportion is changed.
Table.2. water temperature and density of the different proportion.

Fig.14. Distribution of phytoplankton concentration
change of different water proportion.

Changing the proportion of the discharged water will noteffectively change the influence.

Adjustment of the discharge depth is an effective way to control the water quality factors.

Conclusion

Conclusion
Accomplished achievement :• Behavioral characteristics of the discharged water from 100MW offshore OTEC plant and1MW onshore OTEC plant were analyzed by using the three-dimensional numerical model
MEC-NEST. The discharged water will spread at the equilibrium depth horizontally insteadof spreading right after released.
• The variation of the nutrients and phytoplanktons is predicted by combining the lowtrophic ecosystem model.
• Changing discharge depth can be an effective way of controlling the environmental influence.

Future tasks :• In the present calculation, I did not take the ocean currents into consideration. But in reality,
there are still some ocean currents around Kume-Island.
• Ecosystem model and parameters that I used in the present model are applicable to the middle
latitude of North Pacific Ocean. Since Kume-Island is located in subtropical area, the modeland parameters need to be adjusted according to the observational data.

Thanks for your attention !