energycioinsights

Cost Is No Longer King: Picking the Right Metrics to Evaluate Solar Power

By Jason Prince, Senior Associate, Rocky Mountain Institute And Todd Zeranski, Marketing Manager, Rocky Mountain Institute

Jason Prince, Senior Associate, Rocky Mountain Institute

Oscar Wilde once wrote that a cynic “knows the price of everything, and the value of nothing.” This insight has found unlikely resonance in the current solar market, as wary buyers often adopt the cynical approach and focus on the price of solar without appreciating the value it provides.

Start with Value

As Rocky Mountain Institute’s Shine™ team has previously highlighted, value should be the most important consideration for solar buyers. This is the case because distribution-scale solar (DSS)—arrays of between 0.5 megawatts (MW) and 10 MW sited near the demand they serve—offer numerous benefits to buyers by avoiding a range of all-in electricity cost components that could not be accessed by utility-scale solar, and which ultimately drive DSS value. But in practice, how should buyers quantify value?

Demonstrated by Shine’s work supporting electric cooperatives procure DSS, it has become clear that value is driven by buyer-specific circumstances. For example, a levelized price target of $40 per megawatt-hour (MWh) can create substantially different values for two buyers depending on their avoided all-in electricity costs: Over 20 years, a solar system of 1MW-AC priced at $40/MWh will cost a total of roughly $1.3M ($40/MWh*1,600MWh/yr*20yrs). Over the same period, Buyer A with an all-in avoided electricity cost of $110/MWh will avoid over $3.5M of energy expenditures, while Buyer B with an all-in avoided electricity cost of $90/ MWh will avoid only nearly $2.9M; hence the savings for Buyer A in this simplified example is 40 percent greater, roughly $2.2M of savings for Buyer A vs. $1.6M for Buyer B.

This first example is rather straightforward – but even when a buyer knows it sall-in avoided costs, choosing solar by the lowest sticker price may still result in a suboptimal value proposition because doing so does not account for other important project elements. Assume now that a buyer solicits two bids that have similar prices. As the example below illustrates, if the buyer chooses the lower-priced project,it would actually captureless value than with the more-expensive project, given the different rates of annual solar production. It is important to note that these differences in annual production can be driven by system design (e.g., tracking vs fixed), and both reflect solar installations with the same 1MW-AC capacity.

Todd Zeranski, Marketing Manager, Rocky Mountain Institute

In this next example comparing the impact of solar production on value, consider that our same Buyer B with the $90/MWh all-in avoided electricity cost is now deciding between two bids. Bid 1, with an output of 1,600 MWh/yr at a price of $40/MWh will create $1.6M savings as noted in the first example. But Bid 2, which has a higher price of $45/ MWh also has a higher solar production rate of 2,400MWh/yr, and so will save $2.16M, or 35% more compared to Bid 1($45/ MWh*2,400MWh/yr*20yrs=$2.16 Mvs.avoided all-in electricity cost of $90/MWh*2,400 MWh/yr*20yrs=$4.32M).

Make Value Work for You

For buyers to select the solar projects that provide the most benefits, they must focus on value as the main goal in procurement. But it is not as straight forward as simply asking for the greatest net present value (NPV). Buyers must also think critically about what constraints exist for their individual projects and guide developers to design systems that maximize value given their circumstances. We have listed below some of the constraints that have the strongest implications for system design, and suggested the most relevant metrics for comparing different bids:

 

Constraint

Metric

1

Land Area

NPV/m2

2

Capacity

NPV/MW

3

Output / No Constraint

NPV/MWh

1. Land Area Constraint

If a buyer has a limited amount of land area available for construction, then system design needs to maximize the value that can be derived per available area. In this scenario, the most appropriate metric to consider is NPV/ m2. Power density will need to be maximized, and in such cases, tracking systems will likely not be as desirable as for example, dual-tilt systems, which offer a higher ground-coverage ratio. Although there would be less production per panel, the increased panel density would deliver more production perland area. Also, more expensive high performing panels and emerging technologies such as bifacial will add disproportional value under these constraints.

2. Capacity Constraint

The net generation capacity of a system can be constrained either by physical interconnection opportunity or by regulations. In some jurisdictions, for example in Texas, to avoid transmission demand charges systems must be sized less than 1MW-AC. Buyers with this type of constraint should encourage project bidders to optimize for NPV/MW-AC, using system designs that maximizes the output from each panel (MWh/MW) and have a higher DC-to-AC ratio. This implies a preference for tracking systems with high Inverter Loading Ratios (ILR) and likely high value for integrated batteries.

3. Output / No Constraint

For buyers where the output is constrained, likely by the contracted off-take, the most relevant metric is the same as when you have no constraints, which is NPV/MWh – arguably relatively well represented in the prevailing LCOE concept. The project with the highest NPV/MWh would provide the most value and maximize the benefit of each increment of production. Knowing this metric, buyers can choose a system size that meets their needs while ensuring the most value. The specific system design that brings most value will be primarily contingent on factors such as solar resource, rate structures and land cost.

Picking the Best Bottom Line

Value plays a key role in each of the metrics highlighted above. In each example though the assessment of value is tailored to a buyer’s individual constraints. This tailoring of value determination is an important tool to help ensure buyers structure their project procurements to maximize the value solar energy can offer them. As a buyer, it is important to understand what your most critical constraint is so that you ask for the right system design when you engage with the developer market through RFPs or otherwise.

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