ISSN 0003-701X, Applied Solar Energy, 2017, Vol. 53, No. 1, pp. 45–52. © Allerton Press, Inc., 2017.
SOLAR ENERGY CONCENTRATORS
Performance of Parabolic Through Solar Power Plant under Weather Conditions of the Oujda City in Morocco1 H. Ait Lahoussine Oualia, R. Guechchatia, M. A. Moussaouia, b, and A. Mezrhaba, * a
Laboratoire de Mécanique and Energétique, Faculté des sciences, Département de Physique, Oujda, Maroc b Ecole Nationale des Sciences Appliquées Al-Hoceima, Université Mohamed Premier, Maroc *e-mail:
[email protected] Received June 11, 2015
Abstract⎯A numerical simulation of Concentrating Solar Power (CSP) plant based on an Organic Rankine Cycle (ORC) power generation unit integrated with parabolic trough collectors is carried out. For the study we refer to the Solar Electric Generating System VI (SEGS VI), installed in the Mojave desert-California (USA), whose solar field which is constituted by LS2 parabolic trough collectors and we consider the same plant implementation in the region of Oujda city (Morocco). To predict the energy performance, the simulations are carried out using TRNSYS 16 simulation program known for its modularity and flexibility and the external library known as the Solar Thermal Electric Components (STEC) library. The meteorological parameters including Direct Normal Irradiation (DNI), ambient temperature and other weather conditions are taken from meteorological year database provided by a high precision MHP station located in Mohamed Premier University. The obtained results show that the region of East offers great potential in general for implementing this type of plant. In fact, the value of 30 MWe is reached during the strongest sunshine day and the operating time can go from 7 AM until 19 PM for a summer day. DOI: 10.3103/S0003701X17010121
model using EASY simulation software. Similar PTC solar field model was presented and created in the TRNSYS simulation environment using the Solar Thermal Electric Component model library by Jones et al. [21]. Patnode [22] developed a model for the SEGS VI solar collector field using the TRNSYS simulation program where the Rankine power cycle was separately modeled with a simultaneous equation solving software (EES). Kolb [23] has applied TRNSYS software to investigate the annual performance comparison of the 50 MWe Andasol solar power station where are used either a 2-tank or a single tank molten salt as thermal storage system. A nonlinear model of the 30 MWe SEGS VI parabolic trough plant has been established by Stuetzle [24]. Where the collector field was treated dynamically and the power plant by a steady state model. Badran and Eck [25] conducted a numerical investigation with the simulation package IPSEpro to study the use of parabolic trough solar thermal power plants for electricity production under Jordanian climate. Two different cites are compared, the first one is Amman in the middle region and the second one is Ma’an in the southern region. Rheinlander et al. [27] studied technical and economic performance of PTC power plant model. All plant components were modeled in steady state. Daniel et al. [28] applied a numerical technique of the heat transfer
INTRODUCTION In recent years, the production of energy from clean and renewable sources like wind, solar, geothermal and hydro power has become an issue of great importance. Solar energy can be captured and transformed into other forms of energy, such as heat and electricity. The exploitation of this energy may be direct as with photovoltaic’s (PV) [1, 2] or indirectly with concentrated solar power (CSP). In this last case, one several technologies have been developed, namely parabolic trough systems, linear Fresnel reflectors, solar power tower and dish Stirling [3–10]. Considered as one of the most promising and mature systems, the parabolic trough solar collector has many industrial applications like CSP plant, industrial process heat (IHP), domestic hot water and space heating, air-conditioning and refrigeration, pumping irrigation water, desalination, solar chemistry and other [11–19]. Many researches studying the performances of solar thermal power plants are available in literature [20–36]. For instance, Lippke [20] studied the performance of a typical 30-MWe SEGS plant located at Kramer Junction (California) and developed a new 1 The article is published in the original.
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Solar collector field LP–
HP–
Generator HTF Pump
Expansion vessel
Reheater
Condenser Preheater
Deaerator Condensafe pump
Steam generator
Superheader
HP– Feedwatwr heater
LP– Feedwater heater Feedwater pump
Fig. 1. Flow Diagram of the 30 MWe SEGS VI Plant [24].
in the vacuum shell of a parabolic trough collector and compared non evacuated and evacuated glass tubes. In the present work, we propose to study and simulate a solar power CSP parabolic trough technology (SEGS VI) under the Oujda weather data. To assess its energy performance, a numerical model was established using the TRNSYS 16 software. This paper is structured as follows: Section 2 defines a simple model for the SEGS VI solar collector; Section 3 presents the model validation and discusses results; and finally, conclusions are provided in Section 4. 2. THE SEGS VI MODEL 2.1. The SEGS VI The 30 MWe SEGS VI plant is located in the Mojave Desert of southern California. Flow Diagram is presented in Fig. 1. The solar trough collector field is constituted by 50 loops of solar collectors divided into three quadrants with 12 each and one quadrant with 14. Each collector loop consists of 16 solar collector assemblies (SCA), arranged in two parallel rows of 8 SCA each. The heat transfer fluid (HTF) leaves the supply (cold) header through one row of the collector loop and after being heated up by the absorbed energy of the sun, the HTF back toward the return (hot) header through the other row and thereafter merges in the return headers and is pumped back to the central power plant. In the power plant, the hot HTF is piped
through a series of heat exchangers and transfers its thermal energy to a working fluid (water or steam) which will in turn, used in a conventional Rankine cycle power. The HTF leaves the power plant being cold in a central header that feeds the 50 collectors. The total collector area is 188000 m2. The collectors are single-axis tracking and aligned on a northsouth line, thus tracking the sun from east to west. The direct radiation provided from sun is focused by the parabolic curved mirrors onto a heat collection element (HCE) that runs through the focal line of each trough. Generally, the gross HTF temperature rise across the solar field during peak summer periods is about 100°C, from a cold inlet temperature of 293°C toward a hot outlet temperature around 390°C [22]. During cloudy days and off-summer periods, the temperature rise will be lower for a constant flow rate. The actual temperature achieved at the solar field outlet is varied due to many parameters like the HTF flow rate, the solar field inlet temperature, the incident solar radiation, cleanliness of the collectors, the tracking precision, the thermal losses and the surface properties of the collector field materials [22]. Overall, the plant is formed by solar field and power cycle. The elements of the solar field are: parabolic trough collectors, expansion tank, control unit and pumps, while those of the power cycle are: steam turbine, pumps, closed feed water heaters (heat exchangers), deaerator, economizer, boiler, superheater and reheater. APPLIED SOLAR ENERGY
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Weather Tupe65d Type4a
Trough
FRA-SPL Pompe
ElecGe_2 GV LP turbine
X→h
Turbine power
X2H Eco_sh Stage-7
H2X_1 X→h
X2H-2
HP turbine
LP feed water heater
Saltpu_1-2
HP feed water heater Deaerator
Saltpu_1
Fig. 2. SEGS VI TRNSYS model.
The partial differential equation for the HTF temperature is [24]:
∂ THTF ( z, t ) ∂t (1) V HTF ∂ THTF ( z, t ) = − ρ HTF cHTF + q gained ( z, t ) , nCollectors ∂z ρ HTF cHTF AABS,i
where: VHTF is the overall HTF volume flow rate, ρHTF, cHTF, THTF as the HTF density, specific heat and temperature where the first two depend on the latter, AABS,i is the cross-sectional area of the inside tube of the absorber. 2.2. Computer Simulation Program TRNSYS is powerful dynamic simulation tool developed since 1975 at The University of Wisconsin for the behavior of complex systems which include solar systems (solar thermal and PV), Buildings, HVAC, Renewable energy systems, etc [37–39] Among advantages of this modular approach one can cite: a complex problem can be divided into several less complex problems allowing theirs resolutions and work in an “open” environment, allowing adding new components. The model components are graphically connected in the Simulation Studio to built the TRNSYS project [33]. Each type of component is described by a mathematical model in the TRNSYS simulation engine and has a set of matching proforma’s in the simulation studio. The proforma has a black-box description of a APPLIED SOLAR ENERGY
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component: inputs, outputs, parameters, etc. TRNSYS components are often referred to as Types [40]. TRNSYS is decomposed in two parts, the kernel and the library of components. The standard library includes approximately 150 models but the users can add others libraries like Thermal Energy System Specialists (TESS) or Solar Thermal Electric Components (STEC). STEC library is developed by German Aerospace Centre (DLR) and Sandia National Laboratory and consists of models suitable for Rankine and Brayton cycles, concentrating solar thermal systems (central receiver, heliostat field, and parabolic trough models), and storage [41]. In this work a model of a solar thermal electric generating system using parabolic trough collector was created using components from the STEC library. The model scheme implemented in the TRNSYS simulation studio is presented in Fig. 2. Both high pressure (HP) and low pressure (LP) turbines are Efficiency and pressures for turbine sections [30] Turbine Inlet Pressure, bar Exit Pressure, bar Efficiency HP1 HP2 LP1 LP2 LP3 LP4 LP5
100 33.61 17.1 7.98 2.73 0.96 0.29
33.61 18.58 7.98 2.73 0.96 0.29 0.08
0.8376 0.8463 0.8623 0.917 0.9352 0.88 0.64
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Fig. 3. Weather conditions on 18/7/1991 [21].
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Fig. 6. Comparison gross power output results on 18/7/1991.
Fig. 5. Outlet HTF temperature on 18/7/1991.
modeled using several components which are grouped into a single macro. The table resumes the efficiency and pressures for turbine sections. 3. RESULTS AND DISCUSSION 3.1. Validation
Ambient temperature, °C
The validation of the numerical simulation is obtained by comparing our results with those obtained
in Jones et al. [21]. Figure 3 shows the weather data in form of the DNI, temperature and wind speed measured during a clear sunny day on 18/7/1991 in California [21]. Figure 4 shows results from the TRNSYS model for the same location and data. Comparison of TRNSYS results with predictions reported in [21] shows that the DNI, wind and ambient temperature results are close to each other.
Time, h Fig. 7. Annual hourly variation of ambient temperature in 2012. APPLIED SOLAR ENERGY
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Ja nu Fe ary br ua ry M ar ch Ap ril M ay Ju ne Ju l Au y Se gus pt t em b O er cto b N ov er em D b ec er em be r
Average DNI of Oujda city, W/m2
Fig. 8. Annual hourly variation of DNI in 2012.
Fig. 9. Daily average of DNI in 2012.
3.2. Results and Discussions Figure 7 shows the evolution of the annual hourly variation of ambient temperature at Oujda city in 2012. The climate of Oujda, distinctly Mediterranean semiarid, is characterized by relatively cold winters and hot summers. The minimum temperature reached is 1°C, while the maximum temperature is 43.8°C. Following these variations, August is the warmest month of this year with an average temperature of 30.26°C, while January is the coldest month with an average temperature of 9.5°C. The average annual temperature is about 18.67°C. These measurements were taken from our meteorological station (MHP) located at the Faculty APPLIED SOLAR ENERGY
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of Sciences of the Mohammed First University in Oujda. Figures 8 and 9 present the annual hourly of direct normale insolation and his monthly average mesured by the same station. They give us a good idea of what the standard shape of DNI curve looks like. 40 Ambient temperature, °C et wind velocity, m/s
The temporal outlet HTF temperature on 18/7/91 is seen in Fig. 5. Slight mismatch is observed between our results and those of Jones [21]. Figure 6 presents measured and predicted gross power output results on July 18, 1991 from 6 AM to 8 PM as reported in Jones et al. [21] and the predictions from the current model. The maximum difference is less than 5%. Thus, the present TRNSYS simulation results are in good agreement with those of Jones et al. [21].
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Ambiant temperature Wind velocity DNI
30 25 20 15 10 5 0
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10 15 Time, h
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Fig. 10. Weather Condition of Oujda in 20/07/ 2012.
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Fig. 14. Winter week power output results.
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Fig. 13. Clear week power output results.
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Fig. 11. Weather condition of Oujda in 4/01/2012.
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Fig. 15. System, cycle and collector efficiencies versus time Oujda for July 20, 2012.
Fig. 16. System, cycle and collector efficiencies versus time Oujda for January 4, 2012.
Figures 10 and 11 present the DNI, wind velocity and ambient temperature for two representative days, July 20 and January 4, 2012 selected to observe the system’s behavior. The curve of the Fig. 10 is clear with a
temperature generally raised. On the other hand, we remark disturbances in Fig. 11 with low temperatures. Figure 12 presents a comparaison of the Gross electric power between the two representative days. As APPLIED SOLAR ENERGY
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expected the electric output is much higher on the summer day where the solar radiation is maximum and the day time is long(more duration of operation for the day of summer is 9 h against 6 h in winter). In the summer day, the maximal electric generation reaches 28 MWe, whereas it does not exceed 13 MWe in January 4, 2012. Figure 13 presents simulation results for summer conditions during one week. From these predictions, it can be seen that the peak daily power which is generated all week nearly reaches 30 MW. But some variation between days does exist due to differences in cloud cover and therefore insulation. Figure 14 shows a typical partly cloudy week power output results for the winter conditions. By comparing these predictions to those for the clear summer week, one can see significantly larger fluctuations. Figure 15 presents, the efficiency for a summer day (July 20, 2012). As can be shown, the efficiency of collector, cycle and the system are approximately of 51%, 27% and 16%. For a winter day efficiency (January 4, 2012), shown in Fig. 16, collector, cycle and system efficiencies decrease from 10 a.m. This is due to cloudy passage (after the curve DNI) and systeme efficiency is approximately 6%. 4. CONCLUSIONS In the present paper, a model of 30-MW SEGS-VI solar power plant was created in the TRNSYS simulation environment using the Solar Thermal Electric Component (STEC) model library. The model has served as a tool for understanding the plant’s operating characteristics. After being successfully validated by measured data under the same weather conditions, the model has been used to evaluate the daily and weekly performance of such plant under Oujda climate. The main obtained results show that the maximum summer power is about 30 MW but the maximum winter power is about 17 MW. These results of simulation are very encouraging and they can give an idea to investors and policy-makers in Morocco to invest in this promoting technology in the Eastern region of Morocco.
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