Keyword

1 Introduction

The world’s energy demand is increasing, and fossil fuel sources are declining.

Therefore, finding solutions to manage their consumption of particular importance, especially to reduce emissions. One of the best solutions is to use renewable sources (RESs), especially solar (Makkiabadi et al. 2021a, b) and wind energies (Kokkos et al. 2021). RES can provide an affordable and safe supply (Mago and Hueffed 2010). If the rate of extraction of an energy source does not exceed the natural rate of replenishment, it can be called as a sustainable energy source (Makkiabadi et. al 2021a, b; Razmjoo et al. 2021). Building sector consumes the highest amount of energy and electricity (Lamagna et al. 2020), especially to maintain their standards (Astiaso Garcia 2016). Building information modeling (BIM) is a digital tool used in different aspects, engineering design, construction, and management, understanding the sharing and transmission of building data in the whole life cycle of project planning, operation, and maintenance based on the integration of building data and information model (Agostinelli et al. 2022). Then, engineering and technical personnel can understand and take efficient response to various building information, providing the collaborative assistance model for all construction entities including design team, and construction and operating units (Peng et al. 2020). In addition, given the statistics, 85% of the Internet of Things (IoT) devices use digital twins’ technologies for security monitoring, so applying the digital twins to the construction of smart cities has become the research hotspot in the field (Qin et al. 2021). Different parameters of buildings energy can be linked to the digital twin building section of the neighborhood for energy consumption monitoring, costs, and optimization (Manfren et al. 2021).

With the advent of technology, RES can be employed for electricity and heat generation in this sector (Nastasi 2019). Ahn (2019) examined the environmental and economic performances of an absorption chillers versus hybrid chillers in a CCHP system in a hospital. Those kinds of systems can offer stability (Konečná et al. 2020), controllability (Gu et al. 2012), electricity (Ehyaei and Bahadori 2007), and heat generation (Ebrahimi and Keshavarz 2013). Researchers have studied simultaneous generation to reduce peak load using multi-objective planning and concluded that electricity prices, natural gas prices, and PV efficiencies have different effects on performance (Yang et al. 2021). Qian et al. (2021) proposed a novel combined model based on multi-objective decision-making to analyze the performance evaluation of the wind–solar–CCHP systems. The use of thermal photovoltaics by Lianga et al. (2015) in a residential building in China showed that 31.7% of the thermal energy of the building could be supplied with 132 m2 of collectors. Moreover, the use of solar energy in the facade of a building in one of the cities in Iran was investigated to provide at least 20% of the monthly electricity required for the critical month (Hoseinzadeh et al. 2021). The use of solar energy on the roofs of buildings in Valencia has also been analyzed to meet electricity demand (Gomez et al. 2021). Several researchers have also studied the combined PVT/water (Chow et al. 2007) and PVT/air systems (Kalogirou and Tripanagnostopoulos 2006). They have found that the natural flow of water is more efficient for receiving heat from the module and lowering the cell temperature. Jalalizadeh et al. (2021) simulated and studied a new combination of building solar heat collectors and absorption cooling system, as a three-dimensional production system, to meet the thermal and electrical energy needs of a residential building. The use of this proposed system has contributed to energy and economic savings and reduced the building energy consumption (De Santoli et al. 2018). CCHP is a powerful tool for increasing energy efficiency, and RES is ideal energy alternatives. Thus, the integration of them is a promising solution to remedy energy-related issues.

Compared with a conventional CCHP system, the hybrid CCHP system has better energy-saving and CO2 reduction performance. However, the hybrid CCHP system consumes higher annual total cost on account of its high initial investment (Yang and Zhai 2018).

In this paper, the design, management, and evaluation of the CCHP system coupled with RES for a 23-storey office building in Mashhad (Iran) were carried out.

The CCHP system includes a gas microturbine, as primary actuator for power supply, in addition to an absorption and compression chillers for cooling and a boiler for heating. PV and solar thermal panels were used to supply electricity and hot water.

2 Weather

The collection of climatic information, such as the amount of sunlight and air temperature, is of particular importance in the design of RES (Manfren et al. 2020).

Figure 9.1 depicts the minimum, maximum, and average temperatures of Mashhad separately for each month.

Fig. 9.1
A box plot traces the Mashhad location from January to December. The highest quartile is recorded for March, while the lowest one is for June and July.

Source PVSOL software

Temperature graph of Mashhad in each month.

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In Fig. 9.2, the average dry temperature and the percentage of air humidity in Mashhad are shown separately for 24 h each month.

Fig. 9.2
12 graphs plot the dry bulb versus relative humidity in the Mashhad location for each month from January to December with a fluctuating trend. The comfort zone in all months is from 20 to 25 on the y-axis. All values are estimated.

Source PVSOL software

Chart of dry temperature and humid temperature of Mashhad in one year.

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Figure 9.3 represents the average dry air temperature in Mashhad over one year at different times of the day for each month in the color spectrum.

Fig. 9.3
A timetable plot of the dry bulb temperatures in the Mashhad region from January to December. It plots a color gradient waveform with a fluctuating trend between March and November and the highest intensity between 10 a m and 10 p m. All values are estimated.

Source PVSOL software

Mashhad dry temperature diagram for one year.

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In the diagram in Fig. 9.4, the amount of solar radiation is illustrated as a bar graph for each month.

Fig. 9.4
A grouped bar graph of the radiation range in the Mashhad location from January to December. June has the highest direct normal, global horizontal, and total surface, while December has the lowest data for 3.

Source PVSOL software

Chart of solar radiation by month.

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Figure 9.5 shows the wind speed, temperature, and sundials of Mashhad in a period of one year as a flow chart.

Fig. 9.5
A wind wheel chart of the Mashhad location from January to December. The relative humidity is low in the northwest and southeast at less than 30. Temperature is high in the northeast with a wind speed of 10. All values are estimated.

Source PVSOL software

Flower diagram of a year in Mashhad.

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The diagram in Fig. 9.6 describes the position of the sun in different months along with the temperature of Mashhad.

Fig. 9.6
A sun shading chart traces the Mashhad location. The highest record of warm hot is for June at noon with more than 27 degrees Celsius. The lowest record of cool cold is for December at noon with less than 20 degrees Celsius. All values are estimated.

Source PVSOL software

Analysis of the position of the sun over a period of one year at the project site.

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3 Photovoltaic System

Since the project is inside the city and uses solar electricity to achieve maximum power and optimal use of radiation, the considered PV system is a grid-connected system. According to the architectural plans and consumption table, about 150 kW of solar panels with an efficiency of 14.7% was considered on the roof. PV panels were placed as follows.

The presence of a shelter on the roof of the building (Fig. 9.7) necessitated examination and analysis of the shadows of this shelter on the solar panels. This analysis was performed with the software for one year. The results are shown as a color spectrum in Fig. 9.8. In this form, green spaces have very little shade and spaces that go red have the most shade in a year. In addition, spaces that do not cast shadows during the year are colorless. Figure 9.9 demonstrates how the PV panels were connected, which were then connected to the inverter.

Fig. 9.7
A schematic presents the top view of a building. Four rows of solar panels are labeled ridge at the top, eaves at the bottom, and roof view Southeast at the third. There are 2 structures at the bottom of the panels. The left and right are labeled cable end Southwest and Northeast.

Source PVSOL software

How to place a photovoltaic panel on the roof of an office building.

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Fig. 9.8
A schematic presents the top view of a building. Four rows of solar panels with two buildings are at the bottom. A few areas at the top right and the bottom left, along with the buildings are blurred due to shadowing.

Source PVSOL software

Results of roof shadow analysis of office building.

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Fig. 9.9
A diagram presents a pair of solar panel networks connected to the inverter via power sources. They are 80.0 and 64.0 kilowatts. The panels are inclined at 0 to 45 degrees.

Source PVSOL software

How to connect solar panels.

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4 Energy Consumption

To calculate the heat and cooling load of the office building, HAP2 software was used. Thus, cooling, heating, and hot water loads were calculated according to Table 9.1.

Table 9.1 Results of energy demand analysis in a high-rise office project
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The daily profile of the use of electrical equipment for this office building is based on the architectural plan and according to the reference Qian et al. (2021).

5 Problem Definition

To obtain the energy demand estimation system in the mentioned office and to increase the reliability and stability of the system, a combination of PV system with a unique CCHP system was used in comparison with the separate production system, whose schematic is shown in Fig. 9.10. To determine the quality and superiority of the combination of CCHP and PV production systems, this case was compared to other scenarios in Table 9.2. The total project cost in dollars per year was obtained via Eq. (9.1).

Fig. 9.10
A circuit diagram of the C C H P system. It has inputs from the thermal photovoltaic, microturbine, boiler, and building. Each flows through a converter, H R S G, absorption chiller, and cool air compression chiller. The output is combined and given to the electricity network.

Schematic of CCHP system with a PV system

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Table 9.2 Scenarios studied
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$${\text{Net cost}} = C + C^{F} + C^{M} + C^{G} - B^{G} - B_{Q}$$
(9.1)

where C is the total initial cost of the purchase in dollars per year. CF is the total gas consumption, boilers, and gas microturbines in dollars per year. CG is the total cost of purchasing electricity from the grid in dollars per year. BG is the revenue from electricity sales of gas microturbines and PV systems in dollars per year. BQ is the revenue generated by the heat generation of gas microturbines and PV systems in dollars per year. In this case, it was assumed how much it will cost if the amount of heat produced by the gas microturbine or the amount of hot water produced by the PV collector for one year is provided by the boiler. This cost is the revenue generated for heating from gas microturbines and hot water from PV collectors.

6 Results

Table 9.3 shows the design results of combining a PV system with a CCHP system in comparison with other systems in four scenarios.

Table 9.3 Design results of combining PV system with CCHP and separate production system using different scenarios
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Considering Table 9.3, in Scenario 1, it was assumed that the building's electricity demand is met by the electricity grid distribution, heated with a boiler, and the requested cooling is provided with a compression chiller. In this case, the project net cost is 21 k$/y. This system did not have income and capital return because it was just a consumer. In Scenario 2, the capacity of the compression chiller was slightly reduced, and an absorption chiller was added to the system. The project net cost was reduced by 65%. Still, like in Scenario 1, the system did not have revenue and return on investment just because it was a consumer. In Scenario 3, the same combination of Scenario 2 plus gas microturbine was used. This resulted in a net project cost of 2.32 times higher than Scenario 2. The revenue from the sale of gas microturbines’ heat to the distribution network was estimated to be 108.43 k$/y, and the revenue from the heat generation of gas microturbines (to reduce boiler consumption) was estimated to be 15.39 k$/y. In total, the return on investment was calculated about 5.46 years. In Scenario 4, the use of the same devices as in Scenario 3 in combination with the PV system was considered. Therefore, with this combination of CCHP and PV, the project cost increased by 6.18%. However, the revenue from the sale of electricity to the distribution network was 166 k$/y, which was about 54% more than that in Scenario 3. The revenue from heat generation from gas microturbines and PV systems also increased by 25% per year compared to Scenario 3. Furthermore, the income after 20 years was at least the lifespan of the equipment. Considering the inflation rate of 20.6%, it was estimated to be 43 k$/y, which is 1.5 times more than in Scenario 3. Scenario 4, a PV thermal system was combined with a CCHP system, including gas microturbines, boilers, absorption chillers, and compression chillers.

The superiority of Scenario 4 was owing to the minimum return on investment and the highest income in the minimum life of equipment.

7 Conclusions

Integration of CCHP and RES makes a very strong strategy since it is conducive to the supply of clean energy for commercial and residential buildings. The CCHP technologies could provide methods for improving the utilization efficiency of RES energy. RES will provide a clean and cheap energy source.

The integration of CCHP system with RES energy can realize mutual compensation of two kinds of technologies. Governments have made very good policies to make further use of RES energy and CCHP production systems and to reduce fossil fuel consumption. Iran is no exception to this rule. The encouragement of the Ministry of Energy and the New Energy Organization of Iran (SABA) has been highly effective. Among them, the following could be mentioned:

  • Guaranteed purchase, electricity generated by solar systems, and CCHP generation systems at a very reasonable price compared to the selling price.

  • Fuel supply of production systems at the same time as the fuel supply rate of power plants for 20 years.

Hence, utilization of the proposed design in this article could be a promising, suitable, and economical option for investment, reducing energy consumption, and reducing environmental pollutants for the design of commercial, residential, and especially commercial buildings for regions with similar climatic conditions to Mashhad.

At first, wind speeds are predicted for future using a new combined intelligent model. For this purpose, three feedforward networks have been used. This type of wind speed prediction can be very efficient in the Iranian wind energy industry, and this research in this field is not similar in the world. The proposed model was evaluated with various network models, functions, and different numbers of neurons to extract optimal network structure. Furthermore, training and validation data were used to evaluate and compare diverse network structures’ performance. The proposed model also was trained with training algorithms BFGS, LM, and BR. As the results show, with the right Perceptron neural network training methods, the HNN neural network can be trained better than a single neural network. Training a Perceptron neural network with an LM algorithm leads training error to reduce quickly since the LM algorithm is reasonably fast. Therefore, it is logical to select as the training algorithm of the first-level neural network in the hybrid model.