This chapter analyzes a Distributed Collector system implementing a parabolic trough solar collector field for fluid heating, thermal energy storage, and electricity generation [8].
2.1 Distributed collector system
The complete system comprising the collector field, temperature storage and energy conversion system is shown in fig. 3. once the temperature through the collector field is obtained by the "Combined Charging System (CCS)" estimated at 280°C as the working temperature, it is necessary to analyze the performance of the thermal energy storage system [9].
The stratified tank is divided into ten segments for analysis, in which the highest temperature is at the top in the segment called "Upper segment" and the lowest temperature at the bottom in the "Lower segment" [10]. From the upper segment, the fluid with the working temperature is conducted to the steam generation system. In the steam generator, the steam produced reaches a pressure of 25 bar so that the turbine can reach the working power of 500 kW. The inlet pressures for the tests are assigned by a controller that evaluates the load [11].
The “Iterative Feedback Controller (IFC)" Type 22 is designed to maintain the set points of oil temperature and pressure flow. "Iterative Feedback Controller (IFC)" tracks the tracking error 𝑥𝑘 (𝑥𝑘 = 𝑦 - 𝑦𝑠𝑒𝑡) with the secant method. Where 𝑥𝑘 is the tracking error, 𝑦 is a controlled variable and 𝑦𝑠𝑒𝑡 is the set point. The secant method [12] calculates the output signal 𝑓(𝑥𝑘) of a controller to minimize the tracking error. The method is defined by "(1)" [12].
Where 𝑥𝑘+1 is the approximation of the root of (𝑥)=0; 𝑥0, 𝑥1 are the initial values of the secant method. In numerical analysis, the secant method is a root-finding algorithm that uses a succession of secant line roots to best approximate the root of a function 𝑓(𝑥) [13].
According to the principles of operation of the steam system, it is necessary to introduce the thermodynamic variables; these variables are presented in Table 1. Through the steam pressure and temperature, it is possible to find the specific values of enthalpy and steam volume through tables given by the manufacturers specializing in steam systems [14].
Table 1. Values implemented in the steam generator.
Property
|
Value
|
Unit
|
Vapor enthalpy
|
25000
|
Kj×Kg-1
|
Steam pressure
|
25
|
Bar
|
Steam exhaust pressure
|
16
|
Bar
|
Steam mass flow rate
|
36000
|
Kj×Kg-1
|
Steam temperature
|
280
|
℃
|
Maximum temperature difference
|
7
|
℃
|
In Fig. 4. the input values are presented in the solar field for a sunny, cloudless day in the summer. The samples were taken from 09:00 to 15:30. The “Fluid input temperature (TCCS,in)” in the collector field remains constant at 186,3°C. Ambient temperature (Ta) ranges from 30°C to 32°C.
Solar irradiance (I) shows a minimum value of 421 (W×m-2) at 09:00 and a maximum value of 975 (W×m-2) at 13:38. The inflow (QCCS) of oil to the collector field is provided by the set point delivered by a controller with minimum values of 3600 (Kg×h-1) and a maximum of 9832 (Kg×h-1). As can be seen, the pump flow from the collector field on a sunny day follows solar irradiance. The “Fluid output temperature (𝑇CCS,out)” shows the temperature at the outlet of the collector field with a maximum value of 280°C.
In Fig. 5. corresponds to a loading operation in the storage tank, the "Heat transfer fluid (HTF)" is heated in the collector field and enters the upper part of the tank. Due to the stratification in the tank, there are different temperatures. The oil volumes are significantly different. As the thermocouples are placed at intervals, the temperature changes are very pronounced.
When the steam turbine is operating, the values of the inlet temperature to the energy conversion system and its respective outlet are shown in Fig. 6. The input temperature (TPCS,in) has a minimum value of 180°C and reaches 280°C. This temperature is provided by the storage tank.
The output temperature (TPCS,out) has a minimum value and 99°C and reaches 220°C, the output temperature (TPCS,out) becomes the inlet temperature of the storage tank. As can be seen, the outlet temperature (TPCS,out) presents a linear behavior, starting at 10:45 due to the continuous consumption of the steam turbine.
In the following experiment, it will be shown how the operation of the turbine depends on several factors such as weather conditions and electricity consumption, which makes necessary other types of controls that interpret the requirements of the work during a whole day.
The "Steam flow (QPCS)" works at a value of 5277,8 W and the electrical power obtained by the generator (Power) reaches the value of 500 kW. The presented experiment is considered ideal for a "Distributed Collector System (DCS)" where it can work optimally.
2.2 Case study
The study system feeds the estimated demand of 7475 inhabitants of the island of San Cristóbal, in the Galapagos archipelago, whose consumption is estimated at 1.4 (kW.h-1) per family [15]. The proposed hybrid system is composed of a group of seven combustion generators with a total capacity of 9.8 MW, a group of three wind turbines with a total power of 2.4 MW, a photovoltaic system of 0.95 MW, a solar thermal field with a capacity of 1 MW and a "Battery Energy Storage System (BESS)" of 6.5 MW [16]. The power ratings given for each system were obtained from the optimization study in which the objective was to reduce emissions and diesel consumption in the combustion generators. Fig. 7. shows the energy and power demand for the province of Galapagos until 2027, with values of 100.068 MWh [17].
Table 2. Values implemented in the steam generator.
Wind turbine
|
Diesel-GENSET
|
Model
|
Made A-59
|
Model
|
CAT-3512 DITA
|
Type
|
IV-Full
converter
|
Type
|
-
|
Power rating
|
800 kW
|
Power rating
|
650 kW
|
Generator speed range
|
750-1650 RPM
|
Capacity
|
813 KVA
|
Gearbox ratio
|
1:66.185
|
Output voltage
|
480 V±
|
Synchronization speed
|
1500 RPM
|
Frequency
|
60 Hz
|
Converter output voltage
|
1000 V± 10%
|
Synchronization speed
|
1200 RPM
|
Converter output frequency
|
60 Hz
|
Equivalent inertia constant (Base 3×813 KVA)
|
1200 RPM 0.4208 Seg
|
The stratified tank is divided into ten segments for analysis, in which the highest temperature is at the top in the segment called "Upper segment" and the lowest temperature at the bottom in the "Lower segment" [19]. From the upper segment, the fluid with the working temperature is conducted to the steam generation system. In the steam generator, the steam produced reaches a pressure of 25 bar so that the turbine can reach the working power of 500 kW. The inlet pressures for the tests are assigned by a controller that evaluates the load [20].
2.3 Energy management strategies with fuzzy logic and neural networks
Within the topology of the energy generation and storage system, as presented above, a fuzzy logic controller-based energy management supervision system is suggested, as presented in Fig. 9. In a previous work [21], a classical "all or nothing" logic control of switches (relays), resulted in requesting one source at a time.
A multi-input multi-output fuzzy logic smart controller is developed using the fuzzy tools of the Matlab software environment. The "Fuzzy Logic Smart Controller (FLSC)", is constructed with five inputs, i.e., the five energy flows of the system, which are load demand, photovoltaic, solar thermal, wind, storage battery system and five outputs, i.e., the command signals from the electronic switches to supply the load demand, batteries and electrolyzer system the load [22].
- Renewable energy from the photovoltaic system, wind turbine and solar thermal are the input sources to feed the load, then the "Battery Energy Storage (BESS)" and finally the combustion generators.
- Only when the renewable energies are in low energy states, the "Battery Energy Storage (BESS)" will be charged by the combustion generators.
- The combustion generators only supply energy to the load when the other sources are at zero.
These initial operating states are presented in the simplified flow diagram in Fig. 10. and generate a set of 27 rules to be considered in the "Fuzzy Logic Smart Controller (FLSC)" [23].
The formulated rules, which ensure the optimal operation of the intelligent controller, are implemented for simulation in Matlab using its fuzzy logic tools. The rules are established by making dozens of combinations with the three levels ''A: high, M: medium and B: low'' of the five inputs, and then, the ''Fuzzy Logic Smart Controller (FLSC)'' is imposed. Table III shows the input combinations and the imposed duty cycle levels of the electronic switches [24].
The basic idea of fuzzy set theory is that an element belongs to a fuzzy set with a certain degree of membership. Thus, a proposition is not true or false but can be partially true (or partially false) to any degree. This degree is usually taken as a real number in the interval (0,1), as presented in references [25]. The x-axes in Fig. 11. a and b represent the universe of discourse and the range of all possible values applicable to the chosen variables, i.e., the power inputs and the levels of the duty cycle command signals, respectively. Both axes represent the membership values of the fuzzy set [26]. The coverings, as a linguistic variable, carry with them the concept of qualifiers and forms of fuzzy sets. Three adverbs of fuzzy subsets are chosen as low, medium and high, which allows to establish precise rules without making the system extremely complex [27].
Once the linguistic and fuzzy variables are specified, the complete inference system can be defined as the development of a "Fuzzy Inference System (FIS)" and the control of a problem.
The form of the adopted membership function is triangular. The composition operation is the method by which the controlled outputs are generated. The Max-Min method is used, and the output membership function of each rule is given by the Min output of each rule [28].
Table 3. Values implemented in the steam generator.
Inputs: Power level states
|
Output: Electronic switches duty cycle levels
|
Rules
|
PL
2.2MW
|
PReno 5.35MW
|
PBat 6.5MW
|
DGal
|
RenoaL
|
BaL
|
DGaB
|
RenoaB
|
1
|
L
|
H
|
L
|
L
|
M
|
L
|
L
|
H
|
2
|
L
|
M
|
M
|
L
|
M
|
L
|
L
|
M
|
:
|
:
|
:
|
:
|
:
|
:
|
:
|
:
|
:
|
26
|
H
|
M
|
M
|
L
|
M
|
L
|
L
|
L
|
27
|
H
|
M
|
H
|
L
|
M
|
M
|
L
|
L
|