Forecasting the performance of a district solar thermal smart network in desert climate – A case study

Energy Conversion and Management 207 (2020) 112521

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Forecasting the performance of a district solar thermal smart network in desert climate – A case study

T

⁎

Mohamed Hmadia,b, Adel Mourtadaa, , Remi Daoub a

Doctoral School of Science and Technology (EDST), Lebanese University, B.P. 11-2806 Beirut, Lebanon Higher School of Engineering in Beirut (École supérieure d'ingénieurs de Beyrouth – ESIB), Saint Joseph University, B.P. 17-5208 Mar Mikhael, Beirut 1104 2020, Lebanon

b

A R T I C LE I N FO

A B S T R A C T

Keywords: Solar cooling District plants Smart thermal network Hot phase change material Evacuated tube solar collectors Absorption chillers

The present paper investigates the performance of a district solar thermal smart network capable of providing the cooling, heating, and domestic hot water needs for a group of 100 villas in the desert climate of Riyadh, Saudi Arabia. Evacuated tube solar collectors are distributed over the villas’ roofs, while the hot water Lithium Bromide absorption chillers and hot phase change material thermal storage tanks are located in a centralized plant. Electrical heating elements embedded in the thermal storage tanks are considered as back up auxiliary sources in case of shortages. Using the “Design Builder” energy simulation program, a typical villa constructed as per the local thermal standard has been modeled to calculate the hourly thermal loads. These hourly profiles are the initial inputs for a Transient System Simulation (TRNSYS) model integrated with the Generic Optimization Program (GenOpt). The interaction between these two programs is used to find the optimized sizing of the solar collectors’ area and the hot thermal storage volume which could achieve the maximum thermo-economic performance with a 100% solar fraction. The hourly transient simulations over a one-year period show that this system can achieve up to 82.67% reduction in the annual electrical consumption as well as carbon dioxide emissions if compared to conventional district thermal plants. Furthermore, the smart network benefits have been revealed from three different aspects: generation source, transmission loop network, and end-user consumer. The feasibility analysis performed shows that adopting the smart network can enhance the profitability of the project by 34.89% if compared to central solar plants. Also, it gives the end-user the opportunity to participate in energy production through buying the solar collectors installed on their roofs, and thus further enhancing the reduction in their annual thermal bills from 23.13% to 82.88% in a payback period of 4 years and 11 months.

1. Introduction The way we are using our global natural resources to provide the high increase demand for energy consumption is increasing the CO2 levels, raising the global temperature, polluting our environment, and endangering our survival on earth. Based on the fact that cities are responsible for more than 70% of this consumption [1], researches have been conducted towards providing the cooling and heating loads of cities from solar district thermal plants. Horn et al. [2] developed an optimized methodology for testing the performance of a hybrid district solar heating and cooling systems in Itzling, in the city of Salzburg, Austria. The system model designed in TRNSYS and Dymola5 was mathematically implemented in MATLAB to simulate the system behaviour. Positive results have been reported for the potential gains of buildings’ energy exchange and load sifting strategies. Arabkoohsar ⁎

et al. [3] supported a bi-functional solar assisted absorption chiller in district heating and cooling networks. Perdichizzi et al. [4] validated the improvement of a concentrated solar power plant's overall efficiency. This plant was capable of producing cooling in island-mode. Carotenuto et al. [5] provided a dynamic simulation and energy-economic analysis of a combined solar-geothermal district heating, cooling, and domestic hot water system. Based on the United Nations Environment Program (UNEP) report about unlocking the potential of energy efficiency and renewable energy in district plants in cities [1], the new future tendency is toward the 4th generation low-temperature district energy networks. Guelpa et al. [6] predicted the optimized management of building thermal load towards 4th generation district heating plant. A thermo-economic study and optimization was performed on low-temperature district heating and cooling system by Im Y-H et al. [7] using bi-lateral heat trades

Corresponding author. E-mail address: [email protected] (A. Mourtada).

https://doi.org/10.1016/j.enconman.2020.112521 Received 12 November 2019; Received in revised form 16 January 2020; Accepted 18 January 2020 0196-8904/ © 2020 Elsevier Ltd. All rights reserved.

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Nomenclature

Q̇ Ti Aa collectors’ absorber area (m2) ATB annual thermal bill (USD) a0 collector efficiency coefficient (%) a1 1st order collectors’ loss coefficients a2 2nd order collectors loss coefficients CHWS chilled water supply CHWR chilled water return CF cost function (USD) CH hot water thermal tariff (USD/kWh) Cc chilled water thermal tariff (USD/kWh) CpHW specific heat of hot water (kWh/(kg.K)) CpCHW specific heat of chilled water (kWh/(kg.K)) COP coefficient of performance eff rated efficiency of absorption chiller (%) fi,DesignLoad chiller’s hourly design load fraction fi, Full chiller’s full load capacity fraction fi, Nom chiller’s nominal capacity fraction fi,DEI chiller’s design energy input fraction fri PCM liquid fraction at i hours H1 mixing header HWS Hot water supply HWR Hot water return HWG Hot water generates i time hour index Ii hourly global solar irradiance(kW/m2) IDNit hourly direct normal solar irradiance (kW/m2) IdiffH,i hourly diffuse horizontal solar irradiance (kW/m2) Lf latent energy of phase change from solid to liquid (kWh/ kg) PCM phase change material PS photoelectric sensor P1 water pump hourly heating and domestic hot water thermal energy Q̇Hi rate (kW) QĊ i hourly cooling energy rate (kW) ̇ hourly thermal energy rate of chilled water flow (kW) QCHW i chiller’s rated capacity (kW) Q̇rated QȦ i hourly thermal energy rate of chiller’s generator hot water

QĠ i

̇ i QCh Q̇Di Q̇Lossi ̇ i Qaux. QH QC QT QG QPCM qHWi qCHWi THWS THWRi TCHWS TCHWRi TPCM THWGi T1 Ti Tai Tout V1 VPCM β θZi θAi γ ρ Δt ηSi

flow (kW) Hourly thermal energy rate of total needed hot water flow (kW) hourly rate of thermal energy generated by solar collectors (kW) hourly thermal energy rate that could be charged inside the tank (kW) hourly thermal energy rate that could be discharged from the PCM tank (kW) hourly rate of thermal loss (kW) hourly auxiliary energy rate (kW) total annual heating and domestic hot water thermal energy (kWh) total annual cooling energy (kWh) total annual needed hot water thermal energy (kWh) total annual energy generated by solar collectors (kWh) maximum charging capacity of PCM tank (kWh) hot water flow (kg/h) chilled water flow (kg/h) Hot water supply temperature (°C) Hot water return temperature (°C) chilled water supply temperature (°C) chilled water return temperature (°C) PCM melting temperature (°C) hot water generated temperature (°C) temperature sensor hourly mean temperature inside solar collectors (°C) hourly ambient temperature (°C) temperature of hot water leaving the thermal storage (°C) motorized valve PCM storage volume (m3) tilt angle of the panels (rad) hourly zenith angle between the vertical and the line of the sun (rad) hourly azimuth horizontal angle clockwise from the South (rad) azimuth of the normal to the tilted plane (rad) density of the PCM material (kg/m3) time step difference (h) solar collector’s efficiency (%)

comparative experimental analysis of thermal performance between a standard glazed flat plate collector and an evacuated tube collector installed under the same working conditions. Results obtained have shown the higher performance of the evacuated tube collectors in terms of daily efficiency and stationary standard conditions. One of the main triggers for solar district cooling plants is the absorption chillers: the cogeneration and tri-generation integrated for district heating/cooling scenarios was studied by Ameri and Besharati [14]. A mathematical model of an absorption chiller was experimentally verified by Jayasekara et al. [15] including three-dimensional temperature and concentration distributions. ESAKI et al. [16] investigated lower temperature limitation characteristics of hot water fired absorption chiller. Li et al. [17] provided a transient model to simulate the performance of a hot water lithium bromide absorption chiller under the weather conditions of Singapore. The maximum coefficient of performance evaluated was at a heat source temperature of around 95 °C. In addition, Sabbagh et al. [18] established an optimal control strategy of a single stage lithium bromide absorption chiller since derived by a low grade heat source. Results obtained from the dynamic model developed using the interior point optimization (IPOPT) solver have shown a significant enhancement in the coefficient of performance and thus in the economic study due to the reduced operational costs.

model, and by Park B-S et al. [8] on low-temperature district heating network under local conditions of South Korea. Vetterli et al. [9] monitored the energy performance of a low-temperature district heating and cooling network “Suurstoffi”. The main results were confined in calculating the real efficiency of the thermal network, identifying the design mistakes, developing planning guidelines, improving the energy efficiency through system operation optimization, and quantifying its influence on the user. Evacuated tube solar collectors were capable of providing the needed hot water for the generator of a single-stage LiBr absorption chiller as predicted by Franchini et al. [10]. This system reached an efficiency of 72.3% with an operating temperature between 85 and 100 °C under the conditions of Riyadh, Saudi Arabia. Paradis P-L et al. [11] presented a one dimensional thermal model of evacuated tube solar collectors and compared its predictive outcomes to an experimental setup. Results achieved showed a good agreement between the simulated and experimental outlet measures and highlighted the major influence of solar radiation compared to other environmental parameters like the wind and ambient temperatures on the performance of the solar collectors. Saxena et al. [12] studied the effect of mass flow rate, temperature gradient, inlet and outlet temperature on the exergy and efficiency of the evacuated tube collectors based on the presented mathematical modelling and experimental data provided. Moreover, Zambolin et al. [13] provided a

2

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determined the optimal size of the different components providing the minimal system’s life cycle cost. Van der Heijde et al. [38] simulated a detailed computer dynamic equation-based thermo-hydraulic pipe model serving district heating and cooling system. In line with this literature review, the potential benefits from the contribution of a thermal smart network in high solar fraction district cooling and heating plants have not been revealed yet. Based on previous researches investigating the optimization approaches and methods of such networks done by Zeng et al. [39] and Sameti et al. [40], the main novelty of the work is to investigate the optimal design model, and performance of a smart network configuration for a 100% solar fraction district thermal plant serving a residential compound in desert climate. This novelty is tackled from three different aspects: the smart features, the 100% solar fraction optimal design, and the lowtemperature network benefits. First of all, the smart system configuration, control strategy, and the operating conditions were proposed at three different levels: energy generation source, transmission loop pipeline network, and the end-user consumers. The generation source solar collectors are distributed over the hundred villas’ inclined roofs. This distribution has increased the reliability of the system due to diversifying the point sources and has enhanced the profitability due to eliminating the cost of land from the CAPEX if compared to the central solar plants adopted by similar researches. It also decreased the project’s footprint and thus saved more land for other investments. Moreover, the proposed transmission network is of the loop type. Thus in case of failure in any of the connection pipes, the water flow can be rerouted to ensure the continuous supply of the different thermal loads to all zones. Besides, the end-user consumers have the chance to transform from passive consumers to active participants in energy production through investing in the solar collectors installed on their roofs and thus further reducing their annual energy bills. Secondly, the optimal thermo-economic design was achieved by the interaction between the TRNSYS model and the GenOpt program using the Hooke and Jeeves optimization algorithm which is considered one of the most significant solutions as shown by Calise et al. [41]. This interaction is also followed by Franchini et al. [10] by predicting the performance of a solar district cooling system in Riyadh, Saudi Arabia. Kirgat and Surde [42] provided an explained review of the Hooke and Jeeves’ direct search methodology and its application on mechanical engineering design. The minimal capital cost sizes of the system’s components have been found between the different combinations of solar collector’s area and the PCM hot storage volume with the constraint of providing a 100% solar energy fraction to feed the system. Thirdly, following the new tendency toward the 4th generation lowtemperature (less than 100°) district energy networks explained in the literature before, using evacuated tube solar collectors with a generating temperature of 98 °C will achieve a higher profitability if compared to a higher temperature systems using concentrating panels due to the lower specification pipes installed, lower maintenance required, and lower network’s thermal losses due to minimizing the temperature difference between inside and outside pipes. Furthermore, adopting a low-temperature network will reduce the high risk of damages in case of pipes’ failures especially that solar collectors are installed on the roofs of occupied residences. In accordance with its high solar irradiance, the Kingdom of Saudi Arabia's new vision is focusing on renewable solar technologies to overcome the great increase in its annual electrical consumption. Based on the fact that more than 15% of this consumption is from residential compounds [43], a group of 100 villas located in the desert climate of Riyadh, Kingdom of Saudi Arabia was taken as a case study. Firstly, a baseline conventional villa designed as per the thermal local standards was modeled using the “Design Builder” simulation program. This program provided the needed annual hourly cooling, heating, and domestic hot water profiles. These profiles together with the site data were the input to the interaction optimization model between TRNSYS and GenOpt programs. Although the work presented in this paper can

Furthermore, seasonal and diurnal thermal storage methodologies studied by Schmidt et al. [19] are increasingly integrated into district thermal plants to optimize its performance as achieved by Romanchenko et al. [20]. Thermal energy storages could be recognized in three different types: sensible, latent and thermochemical [21]. Because of its high energy storage densities and narrow operating temperatures, the scientific community nowadays is highly focusing on the latent heat thermal energy storage which involves a phase change process of the storage material [22]. Between the different available phase change materials, the solid–liquid type is considered the most appropriate one because of its smaller and compact storage volume if compared to sensible heat storage types [23]. For low-temperature thermal energy storage applications, the transient behavior of phase change material was simulated by Jradi et al. [24], and its thermal conductivity was enhanced by Singh et al. [25]. Kumar et al. [26] designed, developed and analyzed the thermal performance of fatty acids/1-dodecanol binary eutectic phase change materials for low temperature solar applications. Good agreement between the computed and measured results was achieved which proves the suitability of phase change materials in building’s heating and cooling applications. Kanimozhi et al. [27] provided a DOE model for integrating the paraffin waxes phase change material in solar water heating applications. While Brancato et al. [28] identified the characterization of inorganic salt hydrates as phase change material operating in the temperature range between 80 °C and 100 °C. Results obtained confirm the applicability and stability of such phase change materials in practical low temperature solar cooling systems. Many other papers focus on improving the system at the network level. Oppelt et al. [29] analyzed the network operation of district cooling plants by performing a dynamic thermo-hydraulic model. Wang et al. [30] developed a detailed numerical model based on a quasi-static approach for the transient hydraulic behavior for a multi-source district heating network. Lund et al. [31] defined the concept of the future 4th generation low temperature district heating network and investigated the integration of the smart thermal grid including individual contributions in energy production from the connected buildings. These smart thermal networks are predicted to be involved widely in district plants as reviewed by Stănişteanu [32]. Gao et al. [33] introduced and evaluated the different technologies of intelligent systems integrated into a smart district heating network. Results have shown that adopting the smart thermal network concept will save manpower, materials, as well as financial resources and changes the users’ rule of just consuming into saving and even participating in energy production. Li et al. [34] optimized and enhanced the performance of district cooling and heating network integrated with a smart thermal grid, energy storage, and renewable energy. Results have shown extraordinary benefits in terms of reducing fossil fuel consumption, CO2 emission, heat losses, and feasibility. An innovative smart dual building thermal substation concept, which allows a bidirectional heat exchange of the buildings with the thermal network were investigated by Sánchez et al. [35]. Based on that approach, end-users became partners in thermal energy production which increase the reliability of the network. Challenges facing these systems are the source variability, the optimal component sizes, and the sequence of operations, connections and controls. To overcome these challenges, there is a need to design advanced models to predict the optimized thermo-economic performance component sizes, and thermal load management integrated with the diurnal and seasonal storage tanks. The performance of more than 70% solar fraction model of district heating systems taking Denmark as a case study has been studied by Daniel Trier [36] and results obtained have shown that the cost of heat from a solar district plant is competitive compared to that of a conventional Danish district heating plant. As for the combined district cooling and heating networks, Nurzia et al. [37] designed and simulated a detailed model using TRNSYS. A typical Northern Italy town (Alpine climate) and a typical Southern Italy town (Mediterranean climate) were taken as case studies. Simulations 3

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plant. Chilled water supply pipe (CHWS) provides chilled water needed for cooling from the absorption chiller to the air handling unit in each villa at an operating temperature of 7 °C. Chilled water return pipe (CHWR) delivers the chilled water back from the villas to the absorption chiller at an operating temperature of 12 °C. Hot water supply pipe (HWS) provides the hot water needed for the generator of the absorption chiller, heating and domestic hot water for the different villas at operating temperature of 87 °C. Hot water return pipe (HWR) delivers the hot water back from the villas to the central plant at an operating temperature of 80 °C. Hot water generated pipe (HWG) collects the generated hot water (temperature ranges from 91 °C to 98 °C) from the different evacuated tube collectors and delivers it to the central plant to be either stored in the thermal storage or supplied back to the different loads. The operating temperature of the hot water supply THWS and return THWRi are determined based on the generator requirements of the hot water Lithium Bromide (LiBr) absorption chiller capable of providing needed chilled water supply temperature TCHWS and return TCHWRi as illustrated by Jakob [51]. To maintain these operating temperatures from a phase change material (PCM) thermal storage, a Magnesium Nitrate Hexahydrate material studied by Ding et al. [52] is needed with a melting temperature TPCM. To charge this energy in a latent form, the evacuated tube solar collectors equipped with an overheat protection mechanism can generate the needed hot water temperature THWGi even in case of stagnation as presented by Orosz and Dickes [53]. All the pumps in this system are equipped with variable frequency drives controlled by the two-way valves distributed and installed on each branch. When the load changes, the operating temperatures start to fluctuate and accordingly the two-way valves close and open, thus varying the pressure inside the main piping network. As pressure changes, the variable speed pumps vary the water flow, thus reducing the operating energy consumed by these pumps. Table 2 summarizes the set point temperatures of the hot water THWS and chilled water TCHWS supplied to the different villas. The design control strategy adopted is based on sizing the solar collectors and the hot storage tank volume to provide the thermal loads of cooling, heating, and domestic hot water fully from solar energy through a typical year. Thus the supply temperatures are considered to be constant during operation hours. In the case of solar irradiance availability, the solar collectors will ensure to reach these fixed values. While, in case of shortage irradiation conditions such as cloudy conditions, the charged energy from the solar collectors in the hot PCM storage tank will interfere to maintain the operating temperatures. In case of failure or long unexpected shortages periods where the set point inside the tank dropped

be considered as a theoretical predictive model, the villas’ architectural plans were based on real villas’ project in Riyadh area and the thermoeconomic performance analysis performed has shown that adopting the smart network system will provide an extraordinary reduction in the annual electrical energy consumption, the operational primary energy consumption (tons of oil equivalent TOE) and the carbon dioxide emissions if compared to conventional district thermal plants. As a conclusion, results achieved can encourage district thermal plants’ owners to invest in such systems if the vision of the country is implemented. It will also encourage the government to involve such systems in the country’s energy efficiency policy. Furthermore, generalizing the results obtained can form a design guideline tool for district solar thermal smart networks in similar site locations (with high levels of beam solar radiation and dry climate). 2. Modeling and optimization 2.1. Residential compound model The residential compound taken as a case study is a group of 100 villas located in Riyadh, the capital city of Saudi Arabia. Each villa is designed according to local typical architecture adopted in the country with an inclined roof to handle the solar collectors as rendered in Fig. 1. The villa is a two-floor residence with a total surface of 400 m2 and a global volume of 1425 m3. Using “Design Builder” simulation program, a 3D model for the villa is designed to simulate the building behavior under actual operating conditions. The thermal transmittance characteristics of the walls, roofs, and glazing are determined from the values of low rise residential buildings adopted after January 2017 by the Saudi Standards Organization (SASO) [44], as shown in Table 1. The fresh air requirements, external infiltration, occupancies, lighting, and appliances associated with their schedules for each room are based on the ASHRAE standards 90.2 [45] and 62.1 [46]. After importing all these values into the simulation program, the “Design Builder” will evaluate all the thermal gains from external ventilation, the heat transmission through building envelope, glazing, shading effect, and radiation for the multi-zones. The program simulates the model using real hourly ambient weather conditions derived from the International Weather for Energy Calculations (IWEC) [47]. The hourly heating and cooling loads are then calculated for a oneyear period based on the ASHRAE heat balance method used by “Energy Plus” which is implemented in the simulation program. According to an evaluation performed by Yang et al. [48], the Combined Heat and Moisture Finite Element (HAMT) method is used as the solution simulation algorithm. Indoor conditions obtained are in full compliance ASHRAE 55 [49] comfort zone criteria. Furthermore, the simulation program provides the hourly domestic hot water (DHW) by using hot water consumption rates based on the activity in each zone. The mains supply water temperature delivered to the building is estimated to the monthly average outside air temperature. The operational schedule of the different hot water fixtures is derived from the ASHRAE 90.1 library [50]. After that the total hourly thermal loads are calculated for the whole residential compound without considering any diversity factor between the 100 villas since assumed having similar activities, and schedules. The ambient conditions together with the thermal load profiles are fully detailed in Section 3.1. 2.2. Thermal network configuration Fig. 2 shows a schematic diagram of the smart district thermal network. The evacuated tube solar collectors are distributed over the inclined roofs of the 100 villas, while the central plant will contain the absorption chillers, its cooling towers, and the hot phase change material (PCM) thermal storage. Fig. 3 illustrates a rendering of the residential compound showing the loop network. This network consists of the five pipes connecting the distributed collectors and the centralized

Fig. 1. Villa Architecture. 4

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Table 1 Envelope Thermal Properties. Comfort and Gains Indoor set point temperature Indoor Relative humidity Infiltration Lighting (peak) Internal gains (peak) Average/Maximum Occupancy Maximum dry bulb ambient temperature Coincident wet bulb temperature Minimum dry bulb ambient temperature

Thermal Characteristics °C % Vol/h W/m2 kW People °C °C °C

24 50 0.3 20 3 5/10 44.7 19.2 5.8

Wall Thermal Transmittance Wall thickness Wall solar absorptance Roof Thermal Transmittance Roof Thickness Roof Solar absorptance Glazing Thermal Transmittance Solar Heat Gain Coefficient Visible Transmittance

under the designed one (89 °C equals to the melting point of PCM), embedded auxiliary electrical elements inside the tank will be used to raise the temperature inside the tank and maintain the workability of the system. Table 2 also sets the limitations and boundaries within which the returned chilled water TCHWRi, returned hot water THWRi, and hot water generated temperatures THWGi are allowed to vary. Due to thermal losses, the returned hot water temperature upper boundary (87 °C) and the chilled water temperature lower boundary (7)°C will not be reached. In addition, Fig. 4 illustrates the charging and discharging water temperatures distribution of the PCM storage taking into consideration an operating temperature difference between inlets and outlets of 7 °C. Reducing the heat losses in the network pipes is one of the most important factors to enhance the efficiency and operation of the whole system. Masatin et al. [54] evaluate the different factors influencing district heat losses which include the operating water temperature, heat transmittance insulation coefficient, pipes diameters, and lengths. These factors were analyzed to minimize the thermal losses which will be considered during the simulation progress. First of all, the thermal losses depend on the difference between the ambient and the operating water temperatures inside pipes. Thus following the new future approach toward the 4th generation low-temperature (less than 100°)

W/(m2·K) Mm – W/(m2·K) mm – W/(m2·K) – –

0.34 285 0.3 0.2 300 0.2 2.67 0.25 0.25

Fig. 3. Residential Compound and Network Loop.

district energy networks adopted by the United Nations Environment Program (UNEP) report about unlocking the potential of energy efficiency and renewable energy in district plants in cities [1], the temperature difference and thus the thermal losses will be reduced. Secondly, all pipes are insulated thus increasing the thermal resistance between the water inside pipes and the ambient temperatures and

Fig. 2. Smart Network Schematic Diagram. 5

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Table 2 Temperature Limitations in Different Pipes. Hot water supply temperature Hot water return temperature range Generated water temperature range

°C °C °C

THWS = 87 80 ≤ THWRi < 87 91 ≤ THWGi ≤ 98

Chilled water supply temperature Chilled water return temperature range PCM melting temperature range

°C °C °C

TCHWS = 7 7 < TCHWRi ≤ 12 TPCM = 89 ± 1

thermal energy load is just equal to the energy collected by the panels. In this case, the mixed water from header H1 will move towards header H2 to be either consumed by the different loads or regenerated again in the solar collectors in each villa. Secondly, if sensor T2 indicates a temperature greater than 91 °C, then the energy collected is greater than that needed by the different thermal loads and it is possible to charge the excess in the PCM storage. In this case, the motorized valve V3 will deviate a portion of the generated flow towards the thermal storage tank having phase change material (PCM) at a melting point of 89 °C ± 1 °C. The rest of the flow will continue its path towards H2 and then the network. Thirdly, if T2 indicates a temperature lower than 87 °C, then the energy collected is lower than that needed by the different thermal loads or there is no solar radiation. In this case, the motorized thermal storage will interfere to maintain the stability of the system and provide the deficit in energy. The motorized valve V4 will deviate the flow towards the tank to raise the water temperature to a minimum value of 87 °C measured by sensor T3. The temperature sensor T4 will assure that the temperature inside the PCM storage is maintained at 89 °C ± 1 °C. In case of failure or if T4 measures a temperature less than 89 °C ± 1 °C, the auxiliary electrical elements embedded installed inside the PCM storage will operate to maintain the deficit in energy and retain the redundancy of the system. Following this control strategy, a “TRNSYS” model combining all the different system’s components was developed. “TRNSYS” is a modular structure program used for the transient simulation of systems. It is widely used to validate the new building’s energetic evaluation as studied by Eddib et al. [57], or to predict the simulation results of the new solar energy system as studied by Feng et al. [58]. The annual hourly thermal loads obtained by the “Design Builder” are the input files of this model. The “TRNSYS” deck shown in Fig. 5 simulates the hourly operation performance of the proposed system year-round. The different components are obtained from the TESS and software databases, while others are explained hereafter. In line with Fig. 2, the evacuated tube solar collectors generate hot water highlighted in red towards the header H1 where it mixes with the return hot water highlighted in orange to provide the supply hot water highlighted in magenta. The light and dark blue are respectively the chilled water supply and return, while the green connection designates the cooling water circuit between the chiller’s condenser unit and the evaporative cooling tower. The hourly thermal heating and domestic hot water energy rates for the residential compound have been computed then added together to find Q̇Hi for the 100 villas without taking any diversity factor since villas share the same consumption rates and schedules. In the same manner, the hourly thermal cooling rates QĊ i have been computed and added to hourly heat losses rates Q̇Loss(CHWS,CHWR)i in the chilled water ̇ supply and return pipes to calculate QCHW i as shown in Eq. (1):

Fig. 4. Schematic Graph for Charging and Discharging Temperatures of PCM Storage.

reducing the thermal losses. Based on the distribution and service pipes’ optimal design characteristics provided by Halldor and Bøhm [55], the pipes’ insulation thickness is considered to be 50 mm and other heat transmittance insulation coefficient parameters are summarized in Table 3. Thirdly, in compliance with the Engineering Association and the pipe manufacturers [56], a maximum water speed of 2.5 m/s in main branches and 1.5 m/s in smaller ones are considered to calculate the optimized pipes’ sizes. This approach will decrease the surface of heat exchange and thus reduces heat transfer losses between inside and outside pipes. Fourthly, the centralized plant location is planned to be in the center of the residential compound thus reducing pipes’ sizes and runs which will also reduce the thermal losses surface transfer areas. The total length of each of the different used pipes is 4.7 km. Finally, the hourly heat loss rates along the network are calculated. 2.3. Optimization model The optimized capacity is designed to provide all the thermal needs of the residential compound from solar energy collected by the evacuated tube solar panels. Fig. 2 illustrates the control strategy of the system. When the photoelectric sensor (PS) detects the presence of solar radiation, the pump P1 starts circulating the water inside the solar collectors until it reaches the desired operating temperature. When the temperature sensor T1 indicates 91 °C, the motorized valve V1 closes, while V2 opens. In this case, the hot water supplied from the central plant at temperature 87 °C will enter the solar collectors in each villa to be generated to a higher temperature ranging from 91 °C till 98 °C. Then this generated hot water moves towards the central plant to be mixed with the hot water returned at temperature 80 °C from the villas and the absorption chiller. After mixing in header H1, three possible scenarios are considered. First of all, if the temperature sensor T2 indicates a temperature between 87 °C and 91 °C, then the needed

Table 3 Pipeline Heat losses Parameters.

6

Diameter (mm)

Total Pipes Length (m)

Linear Heat Loss (W/m)

Surface per Unit Length (m2/m)

Heat Loss Coefficient (W/ (m2·K))

50 80 100 120 150

4 8 5 4 1

0.701 0.792 0.883 0.975 1.066

0.157 0.251 0.314 0.376 0.471

1.729 1.221 1.090 1.002 0.877

350 400 050 600 100

1 5 9 4 9

08 33 16 99 24

56 80 30 60 32

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Fig. 5. TRNSYS Deck of the Solar Smart Network.

̇ ̇ ̇ QCHW i = QCi + Q Loss(CHWS,CHWR)i = qCHWi · CpCHW ·(TCHWRi − TCHWS )

temperature, cooling water inlet temperature, and chilled water set point temperature, the TRNSYS model reads the data file extracted from manufacturer and adopted by [10] to find on hourly basis the full load capacity fraction fi,Full, the nominal capacity fraction fi,Nom, and the design energy input fraction fi,DEI currently required by the absorption chiller under the hourly conditions. Thus, the hourly hot water energy rate QȦ i needed for the absorption chiller’s generator is calculated as shown in Eq. (3):

(1)

where i is the hourly index year through and varies between 1 and 8 ̇ 760. QCHW i is the hourly thermal energy rate that must be removed from the chilled water return stream having the hourly temperature TCHWRi to reach the chilled water supply set point temperature TCHWS at the hour i of the year. The variable speed pumps will maintain the needed hourly mass flow qCHWi in kg/h. CpCHW is the specific heat of chilled water stream fluid in kWh/(kg·K). Using the calculated data from the “Design Builder” and manufactures datasheet, the rated capacity Q̇rated of the chiller operating in on–off modes was determined with all its characteristics as shown in Table 4. The single-effect hot-water Lithium Bromide absorption chiller mathematical model (Type107 in “TRNSYS”) adopts a normalized catalog data lookup approach to predict its performance. It firstly calculates the hourly design load fraction fi,DesignLoad as shown in Eq. (2):

fi .DesignLoad =

̇ QCHW i Q̇rated

QȦ i =

̇ QCHW i ·f eff ·fi,Full ·fi,Nom i,DEI

(3)

where eff is the rated efficiency of the absorption chiller. The condenser water from the absorption chiller will reject its heat through a cooling tower which will maintain its temperature within the accepted ranges stated in Table 4. Adding QȦ i to Q̇Hi and taking into consideration the hourly heat losses rates Q̇Loss(HWS,HWR)i in the hot water pipes, the hourly total needed hot water energy rate Q̇ Ti is calculated in Eq. (4):

Q̇ Ti = QȦ i + Q̇Hi + Q̇Loss(HWS,HWR)i = qHWi ·CpHW ·(THWS − THWRi )

(2)

(4)

where THWS and THWRi are respectively the hot water supply and the

Using this hourly fraction with the specified hot water supply Table 4 Single-Effect Hot Water Absorption Chiller Properties. Total Rated Cooling Capacity (Commercial) Chilled Water Inlet Temperature Chilled Water Outlet Temperature Chilled Water Circuit Inner Pressure Loss Cooling Water Inlet Temperature Cooling Water Outlet Temperature

kW °C °C mLC °C °C

3 370 12 7 4.9 29.4 36.4

Cooling Water Circuit Inner Pressure Loss Hot Water Inlet Temperature Hot Water Outlet Temperature Hot Water Circuit Inner Pressure Loss Rated COP Total Power Consumption

7

mLC °C °C mLC – kVA

9.2 87 80 3.6 0.8 15

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thermal cooling loads of the villa (the effect of the inclined roof shading was considered in the thermal load calculation). In order for the system to work with a solar fraction nearly one and to complete the mismatch between the availability of generated energy and the needed demand, a phase change material thermal storage tank modeled by developing TRNSYS Type 60 for stratified fluid tanks to be capable of considering the PCM properties and parameters. This approach was adopted by Bony and Citherlet [60]. Two operation modes were considered: charging mode and discharging mode. During the charging mode, the hourly thermal energy rate generated by the solar collectors QĠ i is greater than that needed by the different loads Q̇ Ti . In ̇ i this case, the hourly thermal energy rates that could be charged QCh

hourly return water temperatures. The evacuated tube solar collectors’ mathematical model (Type71 in “TRNSYS”) installed on the inclined roof of each villa are used to find the hourly energy rates QĠ i that could be generated based on current hourly irradiance and taking into consideration the hourly heat losses rates Q̇ Loss(HWG)i in the hot water generated pipes as shown in Eq. (5):

QĠ i = ηSi ·Aa ·Ii − Q̇ Loss(HWG)i = qHWi ·CpHW ·(THWGi − THWS)

(5)

2

where Aa is the collectors’ absorber area in m . The solar collector’s efficiency ηSi is calculated in Eq. (6):

ηSi = a0 − a1

(Ti − Tai ) (T − Tai )2 − a2 i Ii Ii

(6)

inside the tank is calculated in Eq. (8):

̇ i = QĠ i − Q̇ Ti = qHWi ·CpHW ·(THWGi − Tout ) QCh

where a0 is the collector optical efficiency coefficient. a1 and a2 are respectively the 1st and 2nd order loss coefficients of the chosen solar collectors. These coefficients together with the other characteristics parameters are taken from the manufacturer datasheet and summarized in Table 5. Ti is the hourly mean temperature between the hourly hot water generated THWGi and supplied THWS, while Tai is the hourly ambient temperature. Ii is the global hourly irradiance incident on the tilted solar collectors’ surface and calculated in Eq. (7):

where Tout is the temperature of hot water leaving the thermal storage towards the mixing header H2. The maximum energy that could be stored in the PCM storage QPCM is calculate as per Eq. (9):

QPCM = ρ ·VPCM·L f

(9)

where ρ is the density of the PCM material. VPCM is its PCM storage volume. Lf is the latent energy of phase change from solid to liquid. To benefit from the latent energy, it is considered that the PCM stays within the solid–liquid phase change by applying an upper limit equals to one on the liquid fraction. After this limit, the thermal storage will not be permitted to charge. The hourly liquid fraction is calculated in Eq. (10):

Ii = IDNi ·[cos(θZi )·cos(β ) + sin(θZi )·sin(β )·cos(θAi − γ )] + IdiffHi 1 + cos(β ) ] [ 2

(8)

(7)

fri = fr(i − 1) +

where IDNi and IdiffHi are respectively the hourly direct normal and diffuse horizontal incident solar irradiance collected from site data. θZi is the hourly zenith angle between the vertical and the line of the sun given from site data. γ is the azimuth of the normal to the tilted plane. θAi is the hourly azimuth horizontal angle measured clockwise from the South (greater than0 westward). All of the different parameters are read on an hourly basis from the Metronome data mentioned in Section 2.1, together with the ambient temperature and relative humidity. Due to its tubular shape and having an azimuth angle equals to zero (south oriented since Riyadh is in the northern hemisphere of the earth), the panels could collect the solar radiation from east to west directly without the need of any east–west tracking system. Furthermore, in accordance with the results achieved by Corrada et al. [59], varying the tilted angle of the evacuated tubes β using a tracking system will provide a thermal performance similar to those fixed at the annual optimal tilted angle. In order to find its optimal value, a simulation using the TRNSYS program is performed to find the annual energy generated from one solar panel under the hourly solar irradiance conditions of Riyadh at different tilted angles. The tilt angle value is set to vary from 0 to 90° with a step of 5°. Results show that the maximum annual energy generated from one solar thermal panel is at 20°’ tilt angle. Thus the solar collectors are fixed directly parallel on the inclined roofs. These roofs were designed based on their performance to be south oriented with a tilt angle equals the optimal tilted angle of the panels (20°). This will eliminate the shading effect of one panel over the other, provide more area to install the panels, preserves the horizontal roof area under the inclined one that could be used as storage room or for other purposes, and provides shading to below ceiling thus reducing the

̇ i − Q̇Loss(PCM Tank) i )·Δt (QCh QPCM

(10)

where fri and fr(i-1) are respectively the liquid fraction at i and (i-1) hours. Δt is the time step difference. Q̇Loss(PCM Tank)i is the hourly thermal heat losses rates from the PCM tank. The different characteristics collected from manufacturers of the PCM material is summarized in Table 6. The other mode is the discharging mode which occurs when the hourly thermal energy rate generated by the solar collectors QĠ i is less than that needed by the different loads Q̇ Ti , or in case there is no solar radiation available. In this case, the hourly thermal energy rates Q̇Di that could be discharged from the tank are calculated in Eq. (11):

Q̇Di = Q̇ Ti − QĠ i = qHWi ·CpHW ·(THWS − THWRi )

(11)

Having the same consideration of maintaining the PCM within the solid–liquid phase change, the liquid fraction has a lower limit equals to zero. After this limit, the thermal storage will not be permitted to be discharged anymore. The hourly liquid fraction is calculated in Eq. (12):

fri = fr(i − 1) −

(Q̇Di + Q̇Loss(PCM Tank)i )·Δt QPCM

(12)

In case the lower limit of the liquid fraction is reached or the temperature inside the thermal tanks drops below the melting temperature of the PCM, auxiliary heating elements will activate to provide the ̇ i deficit in the system. In this case, the hourly auxiliary energy rate Qaux. needed will be equal to that of the total needed loads as shown in Eq. (13):

Table 5 Evacuated Tube Solar Collectors Properties. One panel’s gross area One panel’s aperture area Length Width Thickness Weight Tube Quantity

m2 m3 mm mm mm kg Tubes

4.9 4.4 2 250 2 200 120 67.5 30

Absorption Emission Maximum Operating Pressure Optical efficiency coefficient a0 1st order heat loss coefficient a1 2nd order heat loss coefficient a2 Maximum cut off temperature

8

– – bar – W/(m2·K) W/(m2·K2) °C

0.96 0.04 10 0.752 1.12 0.004 98

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Table 6 Mg(NO3)2·6H2O Phase Change Material Properties. Melting temperature Latent heat of fusion Lf

°C kWh/kg

̇ i = Q̇ Ti Qaux.

89 ± 1 0.05

Thermal conductivity Density

0.49 1 550

number of panels is determined by the number of panels that could be installed over the maximum gross inclined roof areas of the 100 villas (200 m2 gross area each). The incremental step of the solar collectors is the area of one panel. As for the PCM storage volume, the minimum value was set to zero, while the maximum value was set to be the total average weekly needed thermal energy (QT divided by 52 the number of weeks in one year). The incremental step in energy was set to be the amount of energy that could be stored in 1 m3 of the PCM material. Table 7 provides the minimum, maximum, incremental step, the unit cost for the different components collected from manufacturers or published papers [10,61,62], and the optimal values of the variables found at the end of the optimization process.

(13)

The intent of this work is to find the optimal minimum cost combination between the solar collectors’ area and the thermal PCM storage volume capable of operating the system year-round with all hourly ̇ equals to zero. “TRNSYS” program is auxiliary energy rate values Qaux characterized by the ability to easily connect with the generic multidimensional optimization program “GenOpt”. Similar to what was adopted by Franchini et al. [10], the present paper uses this interaction as shown in Fig. 6 to find the optimal values. The optimization methodology is based on the Hooke and Jeeves algorithm which starts from the minimum initial values of the two variables, then incrementing each variable by the research step value in both directions. These values are entered each time to TRNSYS which simulates the annual performance. The search procedure takes place in two stages. The first stage is to find the configuration having a total annual auxiliary energy Qaux equals to zero. The second stage is based on minimizing the cost function CF of the solar collectors and PCM volume calculated in Eq. (14):

CF = Aa ·Cos tpanel + VPCM·Cos tPCM + Penalty(aux > 0)

W/(m·K) kg/m3

3. Desert climate case study 3.1. Simulation results Based on Koppen and Geiger climate classification, Riyadh has a dry desert climate with an average annual temperature of 25.4 °C and average annual relative humidity of 27.34%. Fig. 7 illustrates the hourly ambient dry bulb temperature and the coincident relative humidity. It is noticed that there exist daily and seasonal fluctuations in temperature which can reach as high as 45 °C and as low as 0 °C, while the relative humidity is relatively low at an average of 20%. Based on this data, both cooling and heating are needed. Riyadh is also characterized by high solar radiations as shown in Fig. 8. The annual direct normal irradiance is equal to 2 344 kWh/m2 and the annual diffuse horizontal irradiance is equal to 735 kWh/m2. The conterminous between solar irradiance, extreme ambient temperatures, and the need for

(14)

where Costpanel is the unit price of solar collectors USD/m2, CostPCM is the unit price of PCM storage USD/m3 . A penalty value Penalty(aux > 0) is added to discard the combinations which need auxiliary energy. Since the main intent of this paper is to provide all the needed thermal loads from solar energy, the minimum number of panels was determined by dividing the total annual needed thermal energy QT by the total annual energy QG generated (6 084 kWh per panel) using the area of one panel only at the optimal tilted angle (20°). The maximum

Fig. 6. Optimization Program Interaction. 9

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Table 7 Optimization Parameters. Evacuated Tube Solar Collectors Minimum Aperture Value Maximum Aperture Value Incremental step Incremental step Aperture area Unit cost per Aperture area Optimal Aperture area Optimal number of panels

PCM Hot Thermal Storage 2

m m2 Panels m2 USD/m2 m2 Panels

9 108 17 960 1 4.4 270 10 978 2 495

Minimum Value Maximum Value Incremental step value Incremental step value Unit cost Optimal Value Optimal Energy Stored

m3 m3 m3 kWh USD/m3 m3 kWh

0 3 170 1 70 1 150 1 940 135 800

this optimized sized system is capable of providing the yearly thermal needs without operating any auxiliary electrical elements. Besides, the 72 h’ variation in the network temperatures is provided for winter and summer conditions in Fig. 14, proving that the variations stay within the limitations stated in Table 2. Using the quasi-static approach of the Darcy equation and taking into account the real hourly water velocity and pipe characteristics, the actual hourly thermal losses in all network branches were computed and represent around 6.48%. As stated before, the variable frequency drive pumps to control the water flow inside the hot and chilled water network to meet the real energy needs and temperature limitations. The maximum water velocity inside the main pipes is less than 2.5 m/s even in peak hours. To evaluate the performance of the new system, a baseline conventional district thermal system was simulated. This system consists of water-cooled centrifugal chillers used to provide the chilled water loads, and electric hot water storage tanks used to provide the hot water needed for heating and domestic hot water. Similar to the model presented for the solar system, the conventional baseline system was also simulated using TRNSYS where the different parameters were collected from manufacturers and already existing district plants. Electricity is considered imported from the grid. The peak electrical power is 2 140 kW and 293 kW for the conventional and solar new system. Fig. 15 summarizes the monthly electrical energy consumption for the two systems. The electrical energy includes the chillers, pumps, cooling towers, and electrical equipment. According to the World Energy Council website [64], the average efficiency of the Saudi power generation Systems was used to estimate the rate of the primary energy consumption (based on tons of oil equivalent) and the CO2 production. Tables 9 and 10 summarize the energy, economic, and environmental performance analysis of the baseline and renewable energy systems respectively. Results show that the solar smart district plant reduces the annual electrical energy consumption as well as the operational primary energy consumption (tons of oil equivalent TOE) and the carbon dioxide emissions by 82.67%. An important parameter to be studied is the coefficient of performance COP which is defined by the total annual thermal energy needed by the

cooling and heating makes the solar thermal system the best choice that combines the needs with the available resources. As explained in Section 2.1, the Design Builders program provides the hourly cooling, heating, and domestic hot water loads for one villa over one year as shown in Figs. 9–11 respectively. The seasonal variations in the monthly thermal demands designated in bars are superimposed onto the instantaneous hourly load fluctuations influenced by solar radiation, ambient temperature and internal loads. The peak power load and the annual energy needed are summarized in Table 8, then compared per unit area with similar researches studying the thermal loads for villas in Riyadh [10,63]. No diversity factor was taken between the villas since they share the same loads’ schedule. Fig. 12 shows a comparison between the total monthly thermal energy that could be generated by the solar panels (QG), the monthly total needed thermal energy (QT), the monthly energy needed for the hot water of the absorption chiller (QA), and the monthly energy needed for the combined heating and domestic hot water loads (QH). Since the cooling load is the dominant thermal need, from May to September all the energy that could be generated by the solar panels was consumed by the different thermal needs, while during the rest of the year there is an excess in the energy generated. This excess is controlled through the self-cutoff spring embedded inside the evacuated tubes when the generated temperature exceeds 98 °C. The 72 h simulation for the energy generated QĠ i , the energy needed Q̇ Ti , the charged ̇ i and discharged energy Q̇Di within the thermal storage is illustrated QCh for winter and summer conditions in Fig. 13 respectively. During winter, most of the load is during night time due to the low ambient temperatures and the need for heating. Thus, most of the generated energy during the daytime period is charged in the hot PCM tank to be then discharged at night. During the summer period, the needed load doesn’t significantly change day-through due to the high ambient temperatures during the daytime and high occupancy scheduled at night. Thus, the generated energy during the daytime period is divided into two parts: the first part will be directly consumed by the absorption chillers while the second part will be charged in the hot PCM tank to be then discharged at night by the chillers. These simulations prove that

Fig. 7. Ambient Dry bulb Temperature and Relative Humidity. 10

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Fig. 8. Direct Normal and Diffuse Horizontal Irradiance.

Fig. 9. Cooling Hourly and Monthly Thermal Load.

Fig. 10. Heating Hourly and Monthly Thermal Load.

3.2. Cost benefit analysis

end-user (QH and QC) divided by the annual electrical energy consumed. As a conclusion, the performance of the solar system (COP = 10.96) is found to be 5.77 times more than that of the baseline system (COP = 1.9).

The electrical tariffs in the Kingdom of Saudi Arabia are highly subsidized. The residential tariff reaches 0.05 USD/kWh for the first 6 000 kWh per month and 0.081 USD/kWh for the rest. Based on its new 11

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Fig. 11. Domestic Hot Water Hourly and Monthly Thermal Load.

consideration the time value of money. It is noticed that the discounted payback period using 2019 electrical tariffs is more than 26 years compared to the baseline conventional district thermal plant, while if the new tariff is adopted the discounted payback period will be 9 years and 4 months with a net present value of 12.145 Million USD. Thus the new policy followed by the kingdom will encourage the operators to adopt such solar systems which have an extraordinary benefit on reducing electrical energy consumption, unnecessary subsidies paid on electricity production, and pollution.

Table 8 Villa’s Thermal Loads. Peak Load Cooling Load Heating Load Domestic Hot Water Load

Annual Thermal Energy Consumed kW kW kW

33 26 4

Cooling Load Heating Load Domestic Hot Water Load

kWh kWh kWh

71 315 7 072 4 708

vision towards reducing the electrical consumption, and according to the Electricity and Cogeneration Regulatory Authority (ECRA) in Saudi Arabia, the new electrical tariff will be the same as the production cost estimated to 0.216 USD/kWh by 2025. RETScreen program was used to conduct the financial analysis. It is a management software used to analyze the feasibility of solar power plants [65], geothermal power plants [66], and other systems [67]. The methodology adopted is based on finding the optimized combination with the minimal capital cost. The initial price of the different components together with the maintenance costs are provided by market operators and manufacturers. The initial investment cost is the difference between the initial cost of the new solar system and the conventional baseline system that would be used instead. The earnings are the difference between the electrical bills paid in the conventional system and that that would be paid using the new solar system. Table 11 provides all the financial inputs parameters and results are calculated using present discounted cash inflows which takes into

4. Smart network features The smart network features are embodied in three different aspects: generation source, transmission network, and end-user consumer. First of all, the benefits of using a low-temperature generation source distributed over the roofs of the hundred villas were revealed by performing two different economical comparisons. The first comparison has been performed to find the advantages of using the evacuated tubes instead of the parabolic trough solar concentrating collectors. The evacuated tubes will generate a lower hot water temperature than the parabolic troughs. This lower temperature has proven to be sufficient for operating the smart network continuously year-round with a 100% solar fraction as shown in Section 3.1. Adopting the lower operating temperature has eliminated the use of expensive high specification pipes and heat exchangers needed in case the concentrated solar

Fig. 12. Monthly Thermal Energy Generated Compared to the Total Needed Thermal Loads. 12

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Fig. 13. 72 h Thermal Simulation Results: a) Winter b) Summer.

Fig. 14. 72 h Temperature Simulation Results: a) Winter b) Summer.

Fig. 15. Monthly Electrical Consumption of the Conventional and New Solar System. 13

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Table 9 Conventional Baseline System Properties. Conventional District Cooling Plant Rated COP Chilled Water Temperature range (in-out) Cooling Water Temperature range (in-out) Total Conventional Electrical Energy

kW – °C °C MWh

3 300 5.65 12–7 30–35 4 571

Total Selling Electrical Bill Total Production Electrical Bill Total Subsidies on Electrical Bill Primary energy consumption Annual CO2 emissions

USD USD USD TOE Tons

367 899 987 284 619 385 1 149 3 217

residential compound using this smart solar network instead of the conventional type for two main reasons: lower annual thermal loads and the active participation in energy production. Based on data collected from existing district thermal plants, the internal rate of return for the thermal production is 8%. Taking the production price of electricity explained in Section 3.2, a financial analysis was conducted to find the total annual thermal bill that must be collected by the operator to reach the IRR of 8%. This analysis was performed for the conventional system and the new solar system as shown in Table 13. Results obtained show that the end-users’ annual thermal bill (ATB) based on the smart solar network is 23.13% less than that using the conventional system, without affecting the internal rate of return or the profitability index of the operator. In order to find the hot water tariff CH(USD/ kWh), the same analysis was performed for the solar hot water production system, by removing the absorption chillers’ price from the initial investment, and taking the total hot water produced as the sold energy as shown in Table 13. The hot water thermal unit tariff is calculated in Eq. (15):

collectors are used. It also has reduced the thermal losses due to the decreasing the temperature difference between the ambient and water inside pipes. Furthermore, the evacuated solar collectors consist of tubes working independently, so in case of failure or maintenance, only the damaged tube will be replaced and not the whole panel as in the case of the parabolic trough mirrors. Also, it is easier to clean and needs no solar tracking system since it could collect solar irradiances from different directions. Furthermore, although the concentrating solar collectors have higher efficiency, the evacuated tubes could collect the diffuse solar irradiances (which represents a good portion of the global solar irradiance) if compared to the concentrating collectors which depend only on direct irradiances. Moreover, and in order to quantify the comparison, a simulation using the interaction between the TRNSYS model and the GenOpt program has been conducted to find the needed aperture area of concentrated solar collectors capable of operating the smart network with the same PCM storage volume. Table 12 summarizes the different parameters of the parabolic trough concentrated solar collectors taken from the manufacturer datasheet and presents the results from the economic study performed. Although the concentrated solar collectors could provide the same thermal performance with a lower aperture area than the evacuated tubes (8016 m2 compared to 10978 m2 in case of evacuated tubes), the payback period in case of concentrated collectors (10 years and 10 months) is longer than that of the evacuated tube (9 years and 4 months) due to its higher capital and operational costs. As a conclusion, adopting the low generation temperature evacuated tubes will enhance the profitability of the smart system by 15.86% (from 2.315 to 2.678) compared to concentrating collectors and will increase the safety level by limiting the risks of damages associated from high-temperature pipes’ failures especially that solar collectors are installed on the roofs of occupied residences. The second comparison has been performed to reveal the benefits of distributing the evacuated tubes solar collectors on the roofs of the 100 villas instead of installing them in a central solar plant. This distribution increases the reliability of the smart network through diversifying the point sources. It also enhances the profitability index of the system by 34.89% (from 1.985 to 2.678) through eliminating the cost of land from the CAPEX. The payback period in case the evacuated tube collectors are centralized on a horizontal land would increase to 12 years and 7 months instead of 9 years and 4 months in case of distribution. This aspect also decreases the footprint of the project and thus saving more land for future investments. Secondly, the transmission network explained in Section 2.2 is of the loop type. Thus in case of failure in any of the connection pipes, the water flow can be re-routed to ensure the continuous supply of the different thermal loads to all zones. This will further enhance the reliability of the system. Thirdly, the end-user consumers are encouraged to buy a villa in the

CH =

ATBhot = 0.055 QT

(15)

where ATBhot is the annual thermal bill need to be collected by the operator to reach an IRR = 8% in case QT hot thermal loads are only produced. The total annual thermal cooling energy QC and hot water energy QH are used together with the annual thermal bill ATBsolar based on the total solar thermal system to find the chilled water tariff Cc as shown in Eq. (16):

CC =

ATBsolar − CH·QH = 0.107 QC

(16)

Furthermore, and in line with these thermal tariffs, distributing the evacuated tubes over the villas’ roofs gives the end-user the opportunity to buy the solar panels installed on his roof (25 Panels with a capital cost of 30 641 USD) and transforms from being a passive consumer to be an active participator in energy production. Following this approach, the end-user could sell the hot water thermal loads collected by their evacuated tubes (117 090 kWh) to the network based on the hot water thermal tariff (annual earnings 6 440 USD). This will further enhance the reduction in the annual thermal bill to 82.88% compared to the conventional system thermal bill. The conducted feasibility study results in a payback period of 4 years and 11 months with a 126 431 USD net present value and IRR = 23.32%. This strategy will also help the operator reduces the capital cost of the thermal plant thus further enhancing its feasibility.

Table 10 New Solar Smart District Thermal Network Properties. Combined DHW & Heating Energy QH Total Cooling Energy QC Total Chilled Water Energy QCHW Hot water Absorption Energy QA Total Hot Water Network Energy QT Total Hot Water Generated Energy QG Total Global Irradiance Energy Aa.I

MWh MWh MWh MWh MWh MWh MWh

1 178 7 131 7 507 10 357 11 709 15 180 25 385

Total Peak Load Total annual Electrical Energy Total Selling Electrical Bill Total Production Electrical Bill Total Subsidies on Electrical Bill Primary energy consumption Annual CO2 emissions

14

kW MWh USD USD USD USD Tons

293 792 61 837 171 120 109 283 74 206

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Table 11 Financial Parameters. ETC Solar Field Pumping Stations Absorption Chiller Hot PCM Storage Tank Cooling Towers Infrastructure and Piping Conventional District Plant Total Initial Investment Cost Yearly Earnings Based on 2019 Electrical Tariffs

Mio Mio Mio Mio Mio Mio Mio Mio Mio

USD USD USD USD USD USD USD USD USD

2.964 0.1 1.348 2.231 0.104 1.69 1.2 7.237 0.306

Yearly Earnings Based on 2025 Electrical Tariff Operation and maintenance expenses Discount rate per period Inflation rate Life time period Discounted Payback Period based on 2019 Tariff Discounted Payback Period based on 2025 Tariff Net Present Value after Incentives Internal rate of Return after Incentives

Mio USD Mio USD % % Years Years Years Mio USD %

0.816 0.022 2.5 2.5 25 26.08 9.33 12.145 12.39%

Table 12 Parabolic Trough Concentrating Solar Collectors Properties. Gross area of one panel Aperture area of one panel Length Width Concentration Ratio Weight Optical efficiency coefficient a0 1st order heat loss coefficient a1 2nd order heat loss coefficient a2 Maximum cut off temperature

m2 m3 m m – kg – W/(m2·K) W/(m2·K2) °C

14.1 13.7 12.19 1.16 60 264 0.772 0.180 0.026 170

Optimal Aperture area needed Unit cost per Aperture area including the high thermal fluid needed Parabolic trough solar Field Additional price of heat exchanger and high pressure rated pipes Operation and maintenance expenses Total Initial Investment Cost Yearly Earnings Based on 2025 Electrical Tariff Discounted Payback Period based on 2025 Tariff Net Present Value Internal rate of Return

m2 USD/m2 Mio USD Mio USD Mio USD Mio USD Mio USD Years Mio USD %

8016 385 3.086 0.922 0.030 8.281 0.816 10.83 10.891 10.57%

Table 13 Annual Thermal Bill Calculation. Financial Parameters

Units

Conventional

New System

Solar Hot Water Production

Investment= Earnings from the total annual thermal bills collected= Expenses= Net Present Value NPV= Internal Rate of Return Return on Investment Total Hot Water Energy Sold: Total Chilled Water Energy Sold:

Mio USD Mio USD Mio USD Mio USD % – kWh kWh

1.200 1.078 0.987 1.006 8.00% 1.84 1 178 037 7 131 487

8.437 0.828 0.193 7.071 8.00% 1.84 1 178 037 7 131 487

7.089 0.638 0.104 5.938 8.00% 1.84 11 708 986 0

5. Conclusion

generation temperatures concentrated solar collectors. Moreover, the villa owners can have the opportunity to participate in energy production by buying the solar collectors existing on their roofs and thus achieving up to 82.88% reduction in their annual thermal bills. In conclusion, the new vision of Saudi Arabia’s government characterized by removing unnecessary subsidies on grey energy resources is increasing the tendency towards adopting systems similar to the solar smart thermal networks which prove extraordinary benefits in terms of energy, economy, and environment.

In this paper, a design guideline model for forecasting the performance of a 100% solar fraction smart low-temperature thermal network was simulated for desert climate conditions. The hourly cooling, heating and domestic hot water for the 100 villas residential compound in Riyadh were evaluated as a case study. An optimization methodology was developed to find the best thermo-economical combination between the evacuated tube solar collectors’ area and the thermal PCM hot storage volume based on the smart system configuration, control strategy, and the operating conditions. Results obtained from the hourly transient simulations over a oneyear period and the cost-benefit analysis performed have revealed the benefits of this system from the end-user consumer, operator, government, and the world. If compared to the conventional district thermal plants, villa owners can benefit from a 23.13% reduction in their annual thermal bill without affecting the profitability of the operator or adding any expenses on the initial cost of the villa. The operator can achieve a net present value of 12.145 Million USD with an internal rate of return of 12.39% and a payback period of 9 years and 4 months if the new electricity production price was implemented in 2025 as per ECRA. The government can save annually 950 tons of oil equivalent of primary energy, and 510 102 USD worth of electrical subsidies due to the reduction in electrical consumption by 3 779 MWh, and 2 660 tons of CO2 emissions which could pollute our world. Besides, distributing the evacuated tubes solar collectors over the roofs of the villas can save more than 12 226 m2 of land and thus enhances the profitability of the operator by 34.89% if compared to central solar plants and by 15.86% if compared to using higher

CRediT authorship contribution statement Mohamed Hmadi: Conceptualization, Methodology, Software, Writing - original draft. Adel Mourtada: Project administration, Supervision, Visualization. Remi Daou: Supervision, Visualization, Formal analysis. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. References [1] United Nations Environment Program UNEP. District Energy in Cities: Unlocking the Potential of Energy Efficiency and Renewable Energy. https://wedocs.unep.org/ bitstream/handle/20.500.11822/9317/-District_energy_in_cities_unlocking_the_ potential_of_energy_efficiency_and_renewable_ene.pdf?sequence=2&isAllowed=y; 2015.

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