Photovoltaic (PV) and energy storage: a viable symbiosis or an overrated investment?
The quick answer is – it depends…
Technical cost-benefit analysis of a PV system complemented with energy storage for increased electricity self-sufficiency.
Questions
In order to properly analyze the costs and benefits of complementing a PV system with a storage system to increase self-sufficiency, several questions need to be answered. In the following, these questions are outlined.
- What’s the required capacity of the energy storage system?
- What’s the savings and how long is the amortization period of the investment?
Background
There are many factors that influence the answers to these questions. In this post, I analyze the costs and benefits of complementing a PV system with an energy storage system to increase the electricity self-sufficiency of a residential unit (could be a family house or similar). Additionally, parameters with a high impact on the analysis are discussed.
Let’s start with a bit of background why it could be beneficial to combine a PV system with an energy storage. Basically, it boils down to one simple reason: The electricity consumption does (usually) not coincide with the PV generation. Electricity is consumed around the clock while the sun only shines during the day and, therefore, the PV only produces electricity during the day. With an energy storage, this problem can be tackled by storing energy when there is a surplus of PV production and releasing energy when the consumption is higher.
That means, the mismatch between the consumption and PV generation is either consumed from or fed back to the electric grid. For the consumed electricity from the grid, you need to pay to your energy provider, grid operator, and the state in the form of taxes. Depending on the tariff policy, you might get paid for the PV generation that you feed back to the grid. Nowadays, usually, you pay more for the electricity you consume than you get paid for the electricity from your PV system. This is also the incentive to self-consume as much as possible of your PV production because it will reduce your electricity bill. Ideally, all of your consumption can be supplied by the combination of your PV and energy storage.
Study case description
The cost-benefit analysis is done in the form of a study case that represents a residential unit with an already existing PV system. Therefore, the costs of the PV system are not considered. The yearly consumption of the unit is assumed to be 5000 kWh which represents approximately a four-person household. The PV system capacity is varied from 0 to 18 kWp, which is realistic for a family house. The parameters of the energy storage system are chosen according to the current state-of-the-art (in doubt rather conservative). The energy storage capacity is varied between 0 and 14 kWh. The electricity price is assumed at 0.20 €/kWh, which is about the average Austrian electricity price. The guaranteed remuneration for feeding back electricity from the PV system is 0.028 €/kWh which is the minimum guaranteed tariff in Austria. The parameters for the study are summarized in Table 1.
Parameters
Before diving into the analysis, we need to discuss the parameters which set the boundaries for the analysis. Basically, the parameters can be divided into three groups: energy storage specifications, PV system specifications, and consumption. Table 1 shows a summary of the parameters including a description of their impact on the analysis.
Table 1: Parameters for the analysis
| Type | Value/Range | Unit | Description |
| Energy storage specifications | |||
| Efficiency | 0.9 | - | Efficiency for charging and discharging: Higher efficiency leads to a smaller energy storage capacity due to reduced losses for charging and discharging and vice versa. |
| Energy storage capacity | 0 - 16 | kWh | Maximum capacity: The higher the capacity the more energy can be stored. However, the price of the energy storage is directly linked to the capacity. The higher the more expensive. |
| Max. discharging power | - 40 % of energy storage capacity | kW | Maximum discharging power: The power rating is defined to be -40 % of the storage capacity, e.g. for a capacity of 10 kWh the max. discharging power is -4 kW. |
| Max. charging power | + 40 % of energy storage capacity | kW | Maximum charging power: The power rating is defined to be 40 % of the storage capacity, e.g. for a capacity of 10 kWh the max. charging power is 4 kW. |
| Lifetime | 12 | years | Expected lifetime: Longer lifetime increases the return of the investment. In other words, longer lifetime reduces the yearly cost of the energy storage. |
| Specific cost | 500 | €/kWh | Specific cost: Lower specific costs make the energy storage cheaper and, therefore, the investment more viable and vice versa. |
| PV system specifications | |||
| Specific yearly yield | 1000 | kWh/kWp | Specific yearly yield of the PV system: Higher specific yield leads to more energy output for the equal-sized PV system and vice versa. Depends on the location and orientation of the PV system. The Global Solar Atlas is a nice reference: https://globalsolaratlas.info/map |
| Peak power | 0-18 | kWp | Capacity of the PV system: Larger PV system produces more electricity and vice versa. The yearly profile, which is scaled with the maximum PV output, can be downloaded on the website of the Austrian Balance Group Coordinator (Austrian Power Clearing and Settlement): https://www.apcs.at/de/clearing/technisches-clearing/lastprofile |
| Consumption | |||
| Yearly consumption | 5000 | kWh | Yearly consumption: The higher the consumption the higher the electricity costs. This also means a higher potential for savings. The yearly profile (H0 for residential units), which is scaled with the yearly consumption, can be downloaded on the website of the Austrian Balance Group Coordinator (Austrian Power Clearing and Settlement): https://www.apcs.at/de/clearing/technisches-clearing/lastprofile |
| Additional parameters | |||
| Electricity tariff | 0.20 | €/kWh | Electricity price: The cheaper the electricity the lower the room for savings and vice versa. |
| PV tariff | 0.028 | €/kWh | PV tariff: Remuneration for feeding electricity back to the grid. Tariff according to the remuneration from OeMAG (Abwicklungsstelle für Ökostrom AG): https://www.oem-ag.at/de/home/ (Website is available in German only) |
Analysis
In the following, the approach for the analysis is described step-by-step. The analysis is based on yearly consumption and PV data from the APCS (please refer to Table 1) with a granularity of one hour, i.e. a total of 8760 hours.
Step 1
Calculate the optimized energy storage schedule such that the electricity exchange with the grid is minimal. That means, the energy storage charges when there is a surplus of PV generation and discharges when the consumption is higher. The optimization takes care of that the storage system operates within its limits at all times.
Step 2
Repeat Step 1 with different energy storage and PV system capacities. Fig. 1 shows an example of the optimal storage schedule for two consecutive days with a 6 kWp PV system and a storage capacity of 4 kWh.
Step 3
Calculate the energy consumed from the grid and the energy fed back to the grid for the whole year for all storage and PV scenarios.
Step 4
Monetary calculations.
Based on the energy exchanged with the grid the costs for consumption and remuneration from the surplus of PV generation can be calculated. In order to get the overall costs, the storage costs and its lifetime need to be included. The costs of the storage system depend on the specific costs and energy capacity. To take this into account on a yearly basis, the total storage costs are divided by its lifetime and summed up with the consumption costs and PV remuneration. In this way, you get conclusive yearly costs that allow a quantitative assessment as shown in Fig. 2.
The yearly savings including the storage costs (Fig. 3) are calculated based on the costs without energy storage for each PV scenario, i.e. the reference costs are the costs where the storage capacity is equal to zero.
Additionally, the amortization period (Fig. 4) is calculated by dividing the total storage cost by the yearly savings (without storage costs).
Results
Fig. 2 shows the yearly costs or savings (negative costs represent savings) for different storage and PV capacities. The presented costs include consumption costs, remuneration for PV generation, and storage costs. The red line shows the reference case, where no PV system is present. When the energy storage capacity is zero, the total yearly costs are 1000 € (5000 kWh * 0.2 €/kWh) because you don’t generate anything yourself and consume everything from the grid. That is why it is also clear that the costs increase linearly with increasing storage capacity as the yearly storage costs are simply added to the electricity costs.
However, it starts to become interesting when there is a PV system present. The first observation is that the PV system alone reduces the yearly costs significantly. Greater PV capacity leads to greater cost reduction because a part of the PV generation is self-consumed and the remuneration for the injected surplus offsets the consumption costs. With increasing storage capacity, the costs decrease and then increase again. Why? The total costs increase when the yearly costs of the energy storage system are higher than the achieved cost reduction. The optimal storage capacity for each PV capacity is given by the minimum of the respective curve which corresponds to the minimum costs, e.g. for the PV system with a capacity of 12 kWp, the optimal storage capacity is 4 kWh.
Fig. 3 shows the yearly savings based on the yearly costs without storage for each PV scenario, respectively. Comparing the maximum savings in Fig. 3 with the minimum costs in Fig. 2, it can be seen that they correspond to each other. A negative benefit means that the storage system costs are higher than its benefit, thus the investment only makes sense when the savings are positive. The yearly benefit for each scenario in the form of savings can be directly seen in the graphic, e.g. for the PV system with a capacity of 12 kWp and a 4 kWh storage, the maximum savings are about 50 € per year.
Fig. 4 shows the amortization period for the different scenarios which is a traditional way of analyzing the viability of an investment. Comparing Fig. 4 and Fig. 3 shows that the intersection of the storage lifetime with the amortization period corresponds to zero yearly savings, i.e. when the yearly savings are zero, the storage amortizes exactly within its lifetime and does not create benefit. When the amortization period is below the lifetime, the investment creates a positive return and vice versa. For the PV system with a capacity of 12 kWp and a 4 kWh storage, the amortization period is about 9 years.
Summary
By analyzing the yearly costs, savings, and amortization periods for different energy storage and PV capacities it is possible to extract all necessary information to decide whether an investment in a storage system makes sense under the specified circumstances. The most important information extracted from the analyzed study case is summarized in Table 2. It is interesting that the yearly savings are quite low when considering the storage costs. This is mainly due to the fact that the storage costs are fairly high and, thus, the storage costs are one of the main factors which affect the outcome of the analysis. However, also other parameters, such as the electricity and PV tariff, have a significant impact on the results, because the higher the spread (electricity tariff – PV tariff) between the two tariffs, the higher the savings potential. The same applies to the yearly consumption, the higher the yearly consumption, the higher the savings potential.
Table 2: Summary of the optimal storage capacity for different PV capacities and cost/benefit analysis and answer to the questions outlined at the beginning of the article.
| @ optimal storage capacity and all costs/savings including the storage costs | ||||
| PV | optimal storage capacity | yearly costs | yearly savings compared to no storage | amortization period |
| kWp | kWh | € | € | years |
| 6 | 2 | 401 | 15 | 10.1 |
| 12 | 4 | 154 | 50 | 9.2 |
| 18 | 4 | -30 | 50 | 9.2 |
All in all, you can say that an analysis of whether it makes sense to complement a PV system with an energy storage must be made on a case-to-case basis because it depends on the specific circumstances – though – mostly on the market conditions.
If you want to perform this analysis for your specific scenario, download the Python code. Just click on the banner below to go to the resources section and find out more. Step-wise instructions on how to use the code can be found here.
I hope you find this article insightful. Consider leaving a comment to let me know your thoughts on the topic.
More insights within energy are to follow in the next article.
Michael
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