The results section consists of three case studies. The first focuses on investigating the impacts of the electricity rate subsides in Qatar under various conditions, including the premise of having an FIT, and electricity unit prices comparable with those of the global average. The second case study focuses on the impacts of permitting FITs in Qatar. Finally, the third case study investigates the design process and the economic impacts of energy storage on household owners with rooftop PV systems.
3.2.1. Economic Viability of Rooftop PV Systems without Energy Storage and Feed-In Tariff in Qatar
The data of the houses and the model variables are summarized in
Table 4 and
Table 5. The selection of panels in this case study is subject to many factors, mainly the available rooftop space and financial constraints of the household owners, as presented in
Table 1 and
Table 2. The energy data in
Table 4 show the breakdown of the total yearly PV generation into the total self-consumed energy and total surplus generated energy, calculated with the help of collected data from the energy monitors installed in each house.
According to the IEA, the global average electricity price is USD 0.13/kWh for the residential sector [
15]. In contrast, it is USD 0.049/kWh for the residential sector in Qatar, owing to the substantial subsidies provided by the local government. This circumstance presents a significant obstacle for the rooftop PV systems to be financially viable for household owners. Luckily, there are also incentive programs provided by the government, energy suppliers, and various organizations that support rooftop PV systems. In many cases, incentive programs and tax credits can cover well above 50% of the total installation cost in the USA [
22]. To that end, we can investigate the impact of solar incentive programs in Qatar for 25%, 50%, and 75% of the installation cost.
Figure 5 and
Figure 6 demonstrate that for the Solar Incentive Program (SIP) under 25% and 50%, the rooftop PV systems in Qatar would not be economically viable, as the payback period exceeds the expected lifespan of the system.
Figure 7 demonstrates the impact of a 75% SIP on the payback period of rooftop PV systems.
Table 6 presents an economic analysis of this scenario. The results show that the payback year’s range is from 7 to 12 years. Houses 2 and 4 have a longer payback period due to high power consumption. All their generated PV energy is self-consumed at an energy price equivalent to the highly subsidized low grid electricity unit prices. House 3 has the highest total savings because they have higher investment, as reflected by the higher system capacity. Furthermore, houses that can afford to sell more power at higher selling energy prices tend to have higher return rates and investment rates.
The following scenario investigates the impact of changing the number of panels on the economic viability of the PV system in house number 10, as demonstrated in
Figure 8. The results become more apparent after observing the results in
Table 7. The system becomes more profitable as the number of panels increases and the self-consumption ratio decreases, indicating that the ratio favors sold surplus energy, more valuable under the circumstances of the study. Globally, the energy prices sold to the grid are competitive with the energy prices from the power suppliers. Therefore, if the price of the sold energy is lower, the results of the impacts of the system size would be different.
Electricity prices have been consciously rising in Qatar, and the following scenario demonstrates the impact of applying average global electricity rates on the model while decreasing the SIP to approximately 30%.
Figure 9 and
Table 8 demonstrate the impact of decreasing the subsidies and SIP on the economic viability in Qatar.
3.2.3. Economic Viability of Rooftop PV Systems with Energy Storage
This section discusses the economic viability of using energy storage for low self-consumption and surplus energy production, especially during winter, when the load demands are at their lowest values. The energy storage requirements for houses H1, H3, H5, H6, H7, and H9 were calculated. Houses H2, H4, H8, and H10 are omitted, as they have high loads and high self-consumption values throughout most of the year. Therefore, energy storage would not apply to these houses.
Moreover, in contrast to the previous case studies, the number of panels was adjusted to provide a more comprehensive result. It was determined that installing rooftop PV systems with energy storage is not economically viable for these houses under current circumstances. These houses face the same issue as other houses with high self-consumption owing to electricity subsidies, and they also replace less of the electricity supplied by the utility. While it is true that some of the houses examined will require smaller and cheaper PV system sizes, the addition of the storage system will dramatically increase the price of the system. Solar energy storage systems exist mainly in batteries, costing on average USD 400 to 700/kWh [
23], depending on the type of batteries.
Moreover, the lifespan of the batteries ranges from 5 to 15 years, which means the energy system will require replacement once or more over the lifespan of the PV module, estimated to be 20 to 30 years. These results pose a dilemma, as it may not be economically viable for a low-income family to acquire energy storage systems. Moreover, the peak electricity consumption in Qatar takes place in summer afternoons. Hence, the energy storage units do not appear to play a critical role in peak reduction applications. Finally, solar energy storage works best when Qatar has not yet introduced a time-of-use scheme. As a result, the load can be shifted and consumed easily during low electricity costs. All these factors add financial burdens that lead to the conclusion that solar energy storage in Qatar is not economically viable, as the payback period will exceed the system’s lifespan by a substantial duration. Therefore, different business models are required, including utility companies’ operation of shared storage units to manage excess demands and overvoltage issues in specific parts of the network.
The PV production load profiles provided in the previous section are essential in distribution system planning and operation as they reveal the amount of power that will be sent back to the grid. Moreover, the results show consumption patterns in Qatar are highly dependent on weather conditions and that changes in PV production do not change proportionally with changes in power demand; this is further elaborated in our previous studies [
7,
24]. Moreover, electricity is a must in Qatar for comfortable living, especially in summers. Hence, potential blackouts from bidirectional power flows must be minimized. One practical approach is to use energy storage units to store excess energy from PV production. Owing to the high capital costs, energy storage systems need to be optimally sized to meet the predefined objectives. The size of the storage units can be determined based on a confluence of drivers, including the size of the PV system, electricity prices, and consumption factors. In the case of Qatar, certain barriers are facing PV adoption: (1) electricity prices are mostly subsidized and are too low as compared to international benchmark prices; (2) there are no financial rebate programs for the promotion of PV systems; and (3) most residents are expats, who stay in the country for a short amount of time. Therefore, new business models are needed, and PV and storage systems are likely to be owned and operated by the utility company. This study assumes that storage units are sized to minimize the average reverse power flow.
After calculating the self-consumption values, important information regarding the potential and viability of energy storage can be deduced. The self-consumption rates reflect the percentage of PV production consumed locally.
Table 9 summarizes all the self-consumption values and ratios from Equation (1) for all houses from the available monthly data. After analyzing the results, we can deduce H2, H4, H8, and H10 have high load demand during peak hours and consume all the PV production during most months, making energy storage redundant. The immediate solution is to increase the number of panels; however, there are limiting factors to consider, including the cost and the available rooftop space.
As for the remaining houses, we can deduce the maximum storage size requirement by choosing the month with the lowest value of self-consumption, often found during a cold month with low load demand. By plotting the load demand against the PV power generation, the surplus area of PV generation on the top of the load demand represents the power that can be stored or sold back to the grid. As selling PV-generated power back to the grid is not yet a viable option in Qatar, all the surplus power should be stored for later use. It is noteworthy to mention that we chose 20 panels of PV generation for all the houses, except for H3, owing to its small rooftop area and small overall load demand; therefore, for H3, it would have been illogical to choose 20 PV panels. Typically, 12-volt batteries are used to store PV energy;
Table 10 summarizes the maximum energy size requirement for the selected houses in Ampere hours (Ah), with a 20% safety factor increase to the actual size requirement. The storage requirements, PV generation, and load demands for houses H1, H3, H5, H6, H7, and H9 are shown in
Figure 12.