3.1. Effect of White Tariff on Energy Cost
In Example 1, the effect of adopting a new tariff on the costs and other benefits to a company was verified.
Table 2 shows the composition of the costs with energy consumed by the Sorocaba Technology Park, which chose the White Tariff and provided this research with data from a period of one year. In order to implement the white rate system in its smart grid project, the management made a decision that the technology park companies should shift their working hours until 6 pm, avoiding the use of internal spaces during peak hours.
The calculation used the
LCD1 tariffs as its basis, (shown in
Table 1), as all invoices were issued by this energy supplier. An average monthly consumption of 32 MW is observed and of these less than 10% (3 MW) refers to the peak tariff period. The average monthly energy cost is US
$4924; which equals an average price of 0.1515 US
$/kWh.
Figure 5 shows the composition of energy costs consumed by the Sorocaba Technology Park, based on the White Tariff. Although the price of energy consumed at peak hours is high, with the reduction of consumption at peak times, its impact has been reduced to 17% of the total cost. As previously mentioned, for a project using the White Tariff to be viable, the contribution of the amount of energy during peak hours must be less than 30% [
48].
Table 3 shows the composition of the costs with energy consumed from the same company if it chose to use the conventional
LCD1 tariff, using the data presented in
Table 1 and the same average energy consumption for calculations. As noted, the average monthly cost of energy rose to US
$6148; which is equivalent to an average price of 0.1891 US
$/kWh. After comparing the results obtained for each tariff, it was observed that the use of the White Tariff gave the Sorocaba Technological Park a 19% economy with its energy costs, which is equivalent to saving of US
$1223/month or US
$14,684 of annual savings, which can be invested in infrastructure improvement, or hiring new employees, or research and development.
By opting for the White Tariff, the Sorocaba Technologic Park achieved some advantages:
- (i)
Reduction of expenses with energy consumption;
- (ii)
Contributes to the reduction of power outages and blackouts;
- (iii)
Because of its conscious consumption, it contributes to the reduction of environmental impacts, due to the decrease of peak energy consumption reduces the need for thermoelectric plants;
- (iv)
Consequently, reduces gaseous emissions for power generation;
- (v)
And improves its image before society [
13,
24,
25,
51,
53].
According to Connor et al. [
39], all sources of risks and uncertainties must be addressed prior to the implementation of a smart grid project so that its success will be achieved, but as noted, even in a proposal without spare power sources, the success of a smart grid project. White fare has been proven, demonstrating that this proposed Brazilian fare is economically viable.
3.2. Effect of Combining of White Tariff with Generator Set
In example 2, the effect of adopting a new tariff combined with energy cogeneration in a generator set on the costs and other benefits to a company A was verified. From the data collected in the condominium invoices (company A), which buys energy from distributor
LCD2.
Table 4 could be assembled, which represents the monthly energy costs if the condominium had not opted for the White Tariff combined with the generator set. A total cost of US
$4787 per month has been found and a unit energy cost of 0.1738 US
$/kWh, which is lower than shown by example 1 indicating that the distribution company
LCD2 has a lower price of energy than
LCD1.
From the choice of Company A, presented in the methodology, a generator set was used 5 h per day use, exclusively at peak hours, which is equivalent to 5737.50 kWh/month. Under these conditions, the software simulated the possible generator sets that could be used, and of the 20 found in its database, five were indicated (as shown in
Table 5) to show the types, characteristics, and costs associated with generators that best fit the smart grid project for the condominium. As noted, the most suitable was the S450 generator set which although having a high fuel consumption have the lowest energy cost, which was 0.126619 US
$/kWh. As this value is lower than the peak hour energy tariff (seen
Table 1: US
$0.088936 + 0.078289 = 0.16723 US
$/kWh), its effect is likely to be beneficial in the final conclusion.
The project involving choosing the generator set, financing, and cost analysis was handled with the Horosazonal software. The total financing was US$71,052.63, with a down payment of 20% and the remainder in 36 monthly installments and an interest rate of 2%. Once fed with the financing data on the generator set and data on energy purchased from LCD2, along with the associated tariffs and rates, Horosazonal software was able to simulate cost analysis as follows:
Based on the applied simulation, the White Tariff is the best tariff modality, presenting the lowest amount to pay. Considering the equipment depreciation, the demand increasing by adding more electronic equipment, tariff values increase, and others, the correction factor is 25% beyond total. In this simulation, it can already find the implementation costs of the energy generator system and other maintenance expenses.
The Horosazonal software has estimated that energy generator power rating will be 200 kW, considering 0.8 as a power rating factor for on-peak and intermediate consumption profile, which, combined, equal to 19%, considering general supply conditions [
52]. The nominal commercial power rating of the energy generator, applied to Equation (8), will be 250 kVA. It appears in the same display as the payable value for White Tariff consumption, without its rates.
where
P(kVA) is the apparent power,
P(kW) is the useful power, and cos
φ is the power factor.
The investment indicated above for acquiring and installing equipment may be quickly amortized if performed with own resources. Acquiring the equipment can be also done by bank financing, ensuring, from the beginning, a monthly gain even with the payment of benefits. At this point, it is observed that economic viability for deployment will be possible by apportioning costs for all tenants, considering that most of them will pay for this financing. The software returned the input data with an initial value of US
$14,921.05 down payment and 36 installments of US
$2157.37/month.
Figure 6 summarizes the financial feedback from smart grid project presented by company A. The financial feedback occurs from the 16th month, with a profit of more than US
$17,000 at the end of the financing and a profit of over US
$100,000 at the end of the useful life of the generator set.
Table 6 shows the composition of the costs with energy consumed by the company A (a condominium), which chose the White Tariff combined with a generator set and provided this research with data from a period of one year. The calculation basis used was
LCD2 tariffs, shown in
Table 1, as all invoices were issued by this energy supplier. An average monthly consumption of 27.5 MW is observed, and 0% refers to the peak tariff period. The smart grid divided the energy quota in 21.5 MWh from the power utility from distributor
LCD2 and at peak time was supplied by the 5737 kWh cogeneration of the generator set. Cogenerated energy cost is exclusively associated with the financing and maintenance of the generator set. The average monthly energy cost is US
$3958; which equals an average price of US
$0.1437/kWh, which is smaller than the White Tariff project alone (example 1) and after the funding period (36 months) this value drops to US
$0.06538/kWh, proving to be more efficient than that.
Monthly profit of $828 (9940 per year) and an economy of 17.31% had been found, which is lower than the savings obtained by example1 (white rate only), but after 36 months of financing the savings are up to US$2986/month (US$35,832/year) and 62.38% savings, which gives an average of 35.34% economy over 5 years of generator set life.
Figure 7 shows the composition of energy costs consumed by company A, based on the White Tariff combined with a generator set. There is a dilution of the costs with the acquisition of energy from distributor
LCD2, and the cost is borne primarily through financing, such that when the financing ends, the costs are reduced by more than 45%. This explains the sharp rise in the economy and profit after 36 months [
13].
Several authors have pointed out that software and computer systems are essential in the control of measuring instruments, data collection and processing, and in communication and management of systems, and Horosazonal software is essential because it is specific for decision making, mainly in smart grid project in the area of electrical engineering [
2,
3,
5,
6,
7,
8,
9,
10,
11,
12,
13,
15,
16,
18,
19].
In addition,
Table 7 presents the accounting of carbon credits of the smart grid project. As it turns out, a profit of
$103 per month is earned, which can be used to offset maintenance costs and improve project effectiveness. In addition to the economic contribution, the most important of carbon credits is the association with the reduction of greenhouse gas emissions, which in this case were 3.21 tons CO
2, which makes the condominium environmentally friendly. Thus, it can be evidenced that this smart grid project is cleaner than the example1 (with only the White Tariff).
Good projects have also been reported in the literature, such as Carr et al. [
32], who made the comparison the performance of baseline and price responsive controls in a smart grid project in a building, with a power reduction of 60% achieved during a period of peak consumption and grid congestion corresponding to a large price surge. Aleksic and Mujan [
54] also showed a similar cost reduction, using software that evaluated it throughout the life cycle of energy production, and underscored its importance.
3.3. Effect of Combining of White Tariff with Photovoltaic Cells
Example 3 presents a smart grid project composed of the photovoltaic system consists of a set of photovoltaic plates with 13% conversion yield, 97–99% efficiency, nominal power of 300 kWh/m
2.month and installed on the roof of the building, occupying a total area of 300 m
2, therefore, the sunroof can produce an energy total equivalent of 90,000 kWh. Where the wiring leads the energy to a string box that is used for direct current (dc) protection, which powers an inverter that turns dc into alternating current, which powers the condominium. Intelligent electrical switchboards are installed in all condominium apartments and a two-dimensional energy meter measures the energy consumed [
3,
5,
6,
7] and surplus (generated by photovoltaic cells), so that compensation is made at the end of the month, as monetary credits to the condominium [
44].
However, photovoltaic generators have their generating capacity according to incidence and time of solar irradiation. Thus, based on the average annual global horizontal radiation map of Brazil, in the amount of daily solar irradiation hours of the southeastern region, where the state of São Paulo is located (9 to 12 h of daily irradiation), its photovoltaic cell efficiency drops to 61%, which is equivalent to 183 kWh/m
2.month, reducing the energy produced from 90,000 to 54,900 kWh/month [
51].
Table 8 shows the costs associated with this photovoltaic cell system. There was no need to calculate the return on investment because the photovoltaic cells were installed when the building was completed, being part of the internal costs of building the condominium. As it turns out, the annual cost with the photovoltaic system is less than US
$600, or simply US
$50 per month; which is irrelevant to the cost shown below.
Table 9 shows the composition of the costs with energy consumed by Company B, which chose the White Tariff combined with a photovoltaic power generation system and it also made available a year’s data for this research. In an interview with the manager, it was shown that the condominium uses one hour a day during peak hours (17–18 h) or 1934 kWh and the other hours (18–22 h) uses the energy stored in the photovoltaic system batteries (7738 kWh), the average energy derived LDC2 peak hour was 1572 kWh/month, as shown in
Table 9.
The calculation basis used was
LCD2 tariffs, shown in
Table 1, as all invoices were issued by this energy supplier. As noted, an average monthly consumption of 29.2 MW is observed, and of this only 5.22% (1.9 MW) refers to the peak tariff period. The average monthly energy cost is US
$ 2037; which equals an average price of US
$0.0696/kWh. Comparing with the use of the tariff without the photovoltaic energy, in example1, it is noted that for similar energy consumption, the energy cost is less than half that of example1 (White Tariff alone) and example 2 (White Tariff and generator set), demonstrating the economic gain of the photovoltaic system.
Figure 8 shows the composition of energy costs consumed by the condominium (company B), based on the White Tariff combined with a photovoltaic cell system. Although the price of energy consumed at peak hours is high, with the reduction of consumption at peak times, its impact has been reduced to 22.86% of the total cost; this is because its price is 7 times higher than the off-peak energy price. However, in the composition of the total energy consumed this value is reduced to 5.23%, which made this project more efficient because the amount of energy used during peak hours was well below the 30% indicated.
Table 10 presents the composition of the costs, with energy consumed from the same condominium in a prior situation (with no photovoltaic system) using the conventional
LCD2 tariff, based on the data presented in
Table 1 and using the same average energy consumption for calculations. Note that the average energy consumption and cost were 37 MWh/month and 6430.23 US
$/month; which is equivalent to an average price of 0.1738 US
$/kWh. Seen that, the values are similar to those in example1, which validates the reasoning made about the data. It can see the values are much higher than the current condominium stage (White Tariff and photovoltaic system).
After comparing the results obtained for each tariff, it was observed that the use of the White Tariff combined with photovoltaic cell systems gave company B a 68.31% savings with its energy costs, which is equivalent to savings of US
$4393/month or US
$52,712 in annual savings, that can be invested in other important condominium activities, such as reducing the internal fees charged to condominium residents. As the conditions are similar, it can be said that the project of combining White Tariff with photovoltaic was 3.6 times more profitable than the project with White Tariff alone (example1) and 1.5 to 5.3 times more profitable than using a combined generator set (example 2). This cost reduction is only similar to that presented by Carr et al. [
32], who also used a photovoltaic cell system on the smart grid of a commercial building in the USA.
Table 11 shows other sources of profit from smart grid project of condominium of the condominium that chose to mix the White Tariff with the photovoltaic system. In this table, it is clear that the project reached an amount equivalent to US
$5388 profit per month and is 2.4 more than the invoice to be paid to
LCD2 (seen
Table 6). That is, there will be no costs associated with the project, but a profit of over US
$2833 per month.
Other sources of profits are the compensation made by LCD2 due to excess energy generated by the photovoltaic system that will go to the distribution grid of LCD2 and carbon credits due to reduced energy consumption of the distribution system and clean energy generation (photovoltaic). About 99% of the profit is associated with the sale of excess energy.
In addition, the project adopted allows the reduction of emissions by the electricity consumption of the condominium by up to 1.5 tons CO
2 per month, or almost 18.4 tons CO
2 per year. However, the carbon credit profit is not high and is sufficient to pay for the monthly maintenance of the photovoltaic cell system (see
Table 5).
Because the reduction of greenhouse gas emissions is associated with public image, a greater contribution of carbon credits will be associated with an improvement in public image as energy consumption is now seen as non-polluting. In this same sense is the use of photovoltaic cells, as it is a source of energy considered renewable and clean energy. Consequently, in terms of energy use, this condominium can be considered as environmentally friendly and improving their image before society [
7,
8,
24,
51].
In China, Liwen et al. [
36] show that the low-carbon benefit of a smart grid is 224.57 billion yuan (33.1 billion US
$), which provides a reference for the construction of smart grid in the coming years. Therefore, the use of tariffs that encourage conscious consumption of energy, besides being environmentally correct, proves to be economically viable, generating profits that, with proper use, can be invested in improvements for society and/or the environment.
According to Carr et al. [
32], the advent of the smart grid and smart building concepts have enabled these innovations to be brought to the level of the retail electricity market, where even individual buildings will be able to adjust their consumption based on price signals from the market. This has been proven in this study by demonstrating that a tariff that encourages the conscious use of energy can reduce business costs.