Maintaining the Value of Solar Generation

Traditionally, solar electricity generation has been driven by feed-in tariffs. Each kilowatt-hour of electricity generated by a solar system has been given a fixed high value independent from the time of the day and location. But, as Navigant Research has discussed in the past, that is not the real value of the produced electricity as electricity prices fluctuate depending on supply and demand. This approach is changing as countries around the world reduce feed-in tariffs or eliminate net metering to better reflect the value of solar generation once it hits the grid. To exemplify this shift, we look at a residential installation but the concepts apply to larger behind-the-meter installations.

Design of the solar installation according to the customer needs will be key to maximize its value. Case study data reveals that increasing self-consumption is key to increasing value the electricity generated by the solar installation. Work by ABB in Italy (irradiance 1,300 kWh/kWp) shows that a household with a yearly consumption of 4,100 kWh with a 2.0 kWp PV system would achieve a self-sufficiency of 20-25 percent. Self-sufficiency is defined as the amount of the yearly consumption that was supplied by the PV system. The same work shows that the self-consumption — the amount of the electricity produced by the PV system consumed at home and not sent to the grid, was around 40 percent. This means that if Italy didn’t have net metering, the kWh value of 40 percent of the generation would be the retail electricity price paid by the household. The remaining 60 percent would have a lower value as, most likely, it would go to the local wholesale electricity market.

A study from Utrecht University found more or less the same values are found for PV systems in the Netherlands. However, if net metering was not present, the value of electricity produced would be reduced about 80 percent.

Self-Consumption as a Way to Increase Value

The easiest way to increase self-consumption and hence the value of electricity production is to optimize the installation so it covers most of the baseload household consumption. To achieve almost 100 percent self-consumption, a system would have to be sized to match baseload on the day with the highest irradiation. Following this strategy would result in small systems in most areas in the world.

While such a strategy gives the highest value possible per kilowatt-hour generated, there are negative repercussions. First, small systems would have a negative impact on the overall self-sufficiency of the household and the environmental benefits that they could bring. Second, the overall economics of the systems could worsen, as the installation cost per watt of installed capacity would rise. As a result, the fixed costs of the installation would remain the same—and with that, the levelized cost of energy (LCOE). Third, due to the small system size, only small portions of the roofs in the built environment would be used for solar installations, leaving an untapped potential of otherwise unused area and making it much harder for more aesthetic alternatives such as solar roofs.

A better strategy for increasing both self-consumption and self-sufficiency — and therefore the value of the solar installation, is to actively try to match as much of the energy demand of a household (or other type of energy consumer) with the generation profile of the PV installation.

Shifts in Household Consumption

While the future of solar generation probably ties to energy storage systems, low hanging fruits are currently accessible doing demand-side management actively to shift energy demand in time to match the solar generation profile of the system. The research report Sustainable Energy, Grids and Networks — co-authored by Maarten Staats — worked with data from a smart grid project that tracked the multiple appliances of 100 households in the Netherlands to estimate how much of a household electricity demand could be easily shifted in time. Based on this data, analysis was completed to evaluate the effect of shifting loads in a household’s self-consumption levels.

However, not all energy demand can be shifted. The research report ranked appliances based on ease of adaption. Consumer electronics such as TVs, DVDs, computers, game consoles, and audio represent 21 percent of the total consumption of an average Dutch household. Together with consumer electronics, lighting (13 percent), cooking appliances (12 percent), and other small appliances (9 percent) are more difficult to shift due to a more fixed time-of-use. Wet appliances like washing machines, dishwashers, and tumble dryers consume 17 percent of total consumption and are the easiest to shift. The other groups with medium difficulty to shift are heating and ventilation devices like electric boilers and mechanical ventilation (14 percent), and cold appliances like refrigerators and freezers (14 percent).

Due to the ease of adapting wet appliances, the research focused on the effects of managing self-consumption manually—the owner would switch on the appliances or the appliance would automatically start at an ideal time of day. However, the results were less promising than expected. In this specific case study, optimizing the use of these appliances only increased self-consumption between 1 percent and 6 percent when all three wet appliances are utilized.

More important than the actual results are the issues with demand-side management highlighted in the report as some of the current limitations could be overcome in the near future; these show that only about 45 percent of energy demand can be shifted to a different time of day. Batteries will soon solve this issue, but currently, they are still expensive without any incentives.

The report focuses on the shared importance of seasonal and daily mismatches — for example, you cannot wait until July to put your Christmas cutlery in the dishwasher to increase self-consumption. This is less of an issue for solar installations closer to the equator, but it should be taken into account as well. The report also emphasizes the opportunities that automation could bring to improve self-consumption—like optimizing each appliance’s peak demand and other cycles. For example, users could wait until the washing machine finishes heating water to turn the dishwasher on and then wait until a passing cloud stops shadowing the system to do the rinsing. Automation will be even more important for managing the next set of appliances in the easiness of adaptation ranking, heating and ventilation, and especially cold appliances, which have little tolerance to error due to spoilage.

Finally, the report shows the limitations of trying to add value to a solar system only from the household perspective. It is likely easier to optimize the system, and hence add value, for a district or province using the existing electricity grid, rather than a single building.

Understanding how to maintain value to solar installations is key for solar players if they want to grow and thrive in the new policy environment without feed-in tariffs or net-metering. Solar players will need to stop focusing solely on lowering the cost of solar and instead examine how to add as much value as possible to every installation they perform. To do this, they need to pivot from solar players to distributed energy players, offering integrated solutions such as energy management, energy storage, and aggregation.

Roberto Labastida (left) is a senior research analyst with Navigant Research, contributing to the Energy Technologies program. Roberto has more than 10 years of experience as a strategy and economics consultant in the energy sector. Prior to joining Navigant Research, Roberto spent eight years with Bloomberg New Energy Finance (BNEF), focusing on clean energy, including biofuels, wind, and solar technologies.

Maarten Staats (MSc) is a Consultant and started working for Ecofys in September 2016. Maarten works on projects on the intersection of sustainable buildings, energy infrastructure and sustainable transport. Prior to joining Ecofys, Maarten finalised his University of Utrecht BSc degree in Innovation Management and MSc degree in Energy science. 

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