In this project, I designed, simulated and optimized an Ocean Thermal Energy Conversion system (OTEC) using MATLAB. I also studied the effect of 4 different working fluids on the system performance.
Concept
Natural thermal gradient is present in oceans.
Ocean Thermal Energy Conversion system (OTEC) utilizes this temperature difference to produce power.
Relatively less temperature difference: a major challenge
To overcome: a solar collector is proposed to be incorporated into the system
Problem Definition
Design an OTEC system to maximize the net power output and study the effect of working fluid, subject to certain resources/constraints.
System Schematic
Closed Rankine cycle
Thermal system consists of:
Evaporator
Condenser
Working fluid pump
Sea water pumps
Piping system and valves
Solar collector unit (Modelling is out of present scope)
Information Flow Diagrams
Pinch Point Analysis
Mass flow rates in HEx cannot be arbitrary.
A certain minimum mass flow rate of sea water is required to meet the pinch constraints.
System Design & Simulation
Each component is modeled as a function in MATLAB.
Each function is successively called and the output of one is fed as an input to the next.
Sample Simulation Result
Optimization
The optimization problem is defined as follows:
Maximize Efficiency = f (Evaporator pressure, r)
subject to,
Q = 35 MW
Twsi = 50 degC
Tcsi = 7 degC
Tc = 20 degC
Pinch = 5 degC
This problem is solved individually for the following fluids:
R1234ze(E)
R1234yf
R123
R134a
Optimization Procedure
To understand the effect of the independent variables on the objective function, above plot was used.
Conclusions
For a given evaporator pressure, the maximum efficiency occurs at r = r-critical (critical corresponds to pinch being just hit)
As the evaporator pressure is increased, the maximum efficiency that can be achieved, first increases and then decreases
From the two conclusions, the two variable optimization can be solved by the following strategy:
Step 1:
Evaluate r-critical as a function of evaporator pressure using the pinch point analysis.
Step 2:
Since it is known that the maximum efficiency for a given evaporator pressure occurs at r = r-critical, the system is simulated at this r-critical (from step 1) for different evaporator pressures.
Then a simple exhaustive search is performed to find the optimum evaporator pressure where the efficiency is maximum. The r-critical corresponding to this pressure is the optimum r.
Optimization Results
Conclusion
There does exist an optimum evaporator pressure where the efficiency peaks.
Pinch point analysis plays an important role in the determination of optimum evaporator pressure.
All the 4 working fluids show a similar maximum efficiency of ~4%. This seems natural, since the Carnot efficiency for all the 4 fluids is ~6.3%.
However, the evaporator pressure where the maxima occurs, varies significantly for the 4 fluids from a minimum of 1.520bar (R123) to a maximum of 10.100bar (R1234yf).
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