Methodology to Assess the System Value of Different Corporate Procurement Strategies in Developing Economies

The number of corporates announcing clean and renewable electricity goals has increased greatly, with for example the RE100 initiative now covering over 380 TWh of corporate electricity demand, which if it were a country would place it just outside the top 10. Under this initiative, companies commit to acquire renewable electricity equal to 100% of their annual electricity demand.

There are also initiatives such as the 24-7 Carbon Free Energy Compact, targeting a more precise match between clean generation and electricity consumption. This approach aims to source clean generation on the grids where companies consume, and to match real time demand on an hourly basis with clean generation.

For developing economies, increased corporate demand for clean energy is an opportunity to foster local development, open up new models for developing renewables, support country-level renewables deployment targets and attract foreign investment. It is thus in the interest of all that the grid accommodates developments linked to corporate procurement. At the same time, it is critical that the costs and benefits of projects connected to the grid are handled fairly so that all consumers pay their correct share of the costs.

In some cases, exempting renewable developers or customers with either power purchase agreements or behind-the-meter renewables generation from some system charges is an appropriate way to promote deployment. However, it is important to quantify these subsidies in order to predict and control their future progression as regions move to higher VRE (Variable Renewable Energy) shares. Funding should be explicitly allocated to these subsidies to ensure they do not result in utilities not covering their financial costs or costs being unfairly shared by other grid users. 

Companies have a range of options for procuring clean energy, although these vary in how accessible they are. The main choices for corporate clean electricity procurement are behind-the-meter installations (BTM), power purchase agreements (PPAs), energy attribute certificates (EACs), or choosing a green tariff. These are briefly described below.

Behind-the-meter: installation of on-site generation on the client side which is then consumed directly or may be injected into the grid during hours of overproduction.

Power purchase agreements: the company enters into an agreement to pay a generator for its electricity production at a certain price for a fixed period of time. These come in many forms including physical and ‘virtual’ arrangements depending on whether the supplier is feeding the electricity into the same grid that the consumer is located on or of it is a purely financial arrangement.

Purchase of EACs: created for each MWh of renewable electricity generated, these are a way for buyers to claim the environmental benefit of that electricity. They may be combined with the purchase of the power (bundled) or not (unbundled). These include Renewable Energy Certificates (RECs) in the US and Guarantees of Origin (GOs) in Europe.

Green tariffs: the company buys electricity from their utility under either a standard tariff offering or a tailored contract where the electricity is identified as being renewable. The basis of the green tariff could range from the retailer purchasing EACs to some type of PPAs.

These approaches all have different advantages and disadvantages, and all types of procurement have seen increased activity in recent years. Behind-the-meter generation and PPAs are often preferred since they allow companies to clearly point to increased renewables deployment as a result of their efforts. 

PPAs in particular play an important role in global renewables development, and accounted for 31 GW of new installations globally in 2021, more than 10% of the total renewables capacity additions (around 290 GW). At the same time, obtaining PPAs can be challenging due to the need for relatively long-term commitments as well as barriers to development such as long or complex permitting processes in many regions. This article focuses in particular on approaches that increase new renewable generation capacity on the grid, and is therefore most relevant for PPA-style procurement, as well as behind-the- meter assets.

In general, green tariffs may be a simpler and more accessible solution where available, and unbundled EACs are the most feasible option in many cases as they can be bought on a short-term basis and do not require complex agreements or long-term commitments that may not be feasible for smaller companies. 

The type of clean energy strategy a company adopts directly influences its impact on emissions.

Strategies which seek to match the global electricity consumption of the company with renewable generation from anywhere in the world may result in renewables deployment on completely different grids from where the electricity is consumed. This raises some points to consider.

The first is that the rate of emissions on the grid where procurement and consumption takes place may differ, which leads to discrepancies between the corporate electricity-based emissions vs the emissions reduction resulting from renewables production. If the load is situated on a high-emitting grid but the generation is from a cleaner system where perhaps renewables resources are more abundant and lower cost, then the actual reduced emissions may be much less than the emissions caused by the company’s demand.

Second, since it is much easier to obtain low-cost PPAs in some regions than others, matching electricity consumption on a global basis could produce a concentration of corporate PPAs in regions where development is most accessible. As a result, regions with more challenging development conditions, where the benefit of these investments would be greater, will tend to benefit less.

The period of time over which the company matches its load with clean electricity production significantly impacts the size of the resulting emissions reduction. In annual matching strategies, the company will produce excess renewables in some hours and depend on grid electricity during other hours. In systems with significant amounts of variable renewables, the hours in which new projects generate electricity will tend to correspond with the hours when the average emissions of the system are lowest, since this tends to be when other renewables generators are producing, particularly for solar. In contrast, the hours in which the new project has low generation and the company needs to ‘import’ from the grid will also tend to coincide with higher average grid emissions, since other renewables production will also tend to be lower.

This principle is driving an increasing interest in locational and time-based matching for corporate procurement. It should be recognised that annual-based matching such as the RE100 initiative loses its value as the variable renewables share increases.

Strategies to match 100% of electricity demand annually, such as those within the RE100 initiative, have favoured resources with the lowest energy-only cost. In most markets this will tend to lead to procurement of mainly solar PV and wind generation. On the other hand, hourly matching strategies will need to include dispatchable resources such as demand response, energy storage, and clean dispatchable generation such as hydropower or biomass to respond to changes in supply and demand.

We have modelled a case study of corporate procurement in India, based on annual, monthly and hourly energy balancing strategies. This analysis highlights a sharp difference in the resulting technology mix depending on the strategy employed, with hourly matching resulting in both a higher total capacity and a more diverse set of technologies. 

These different portfolios present different costs for the corporate buyer and result in different impacts on the system. In each case, 10% of commercial and industrial load is assumed to join a consortium to procure a clean electricity supply equal to their electricity demand, either on an annual, monthly or hourly basis.

It should be noted that an hourly matching strategy on a consumer-by-consumer basis is highly inefficient as it misses out on the benefits of large, interconnected power systems where the aggregated demand from many consumers is smoothed and is more cost-effective to serve than many individual loads. This is a potential drawback of hourly matching strategies if 100% matching is pursued from a ‘siloed’ approach, as this would lead to inefficiencies in both developing and dispatching the power system.

Corporate clean generation portfolios will have very different system impacts depending on whether they are based on annual or hourly matching strategies. Annual strategies focus on energy supply over the period of a year. In order to maintain secure electricity supply, however, multiple different services are needed in addition to just the supply of energy, including stability that allows the power system to ride through sudden changes in supply or demand, flexibility to ramp generation to follow demand, and meeting capacity needs in peak hours.

Variable renewables are in many cases already the cheapest source of energy, but they make limited contributions to other services, unlike the dispatchable resources required to satisfy hourly matching. The greater effective system value of clean dispatchable sources should be recognised in charges for the use of the grid.

In addition to balancing, flexibility and peak capacity requirements, where variable renewables tend to make a limited contribution, the value of the energy that a company draws from the grid may be higher than the value of the renewables generation injected. This occurs in annual matching strategies because the value of energy, reflected in the wholesale price, tends to be lower during hours of high renewables production because of their low variable cost. In addition, the new variable renewables generation may increase other operating costs such as generator start-up and shutdown costs, which can offset some of the savings in fuel costs.

We can illustrate this effect by looking at the operational cost for the central system in different scenarios. The baseline cost of generation for serving the corporate portfolio is first calculated by comparing the operating cost in the reference scenario with the operating cost with the corporate load excluded, and then calculating how much this cost is reduced by a corporate portfolio meeting an annual matching strategy. This is undertaken for reference scenarios in India in 2019, 2030 STEPS and 2030 SDS. 

This analysis illustrates that the value brought by an annual matching strategy is highly dependent on the variable renewables share, and system flexibility of the underlying scenario. In India in 2019, an annual matching portfolio is able to offset 98% of the costs to serve the corporate load, but this reduces to 90% in 2030 in STEPS and to only 62% in 2030 SDS. This is both because some fossil fuels are still required to serve the corporate load due to the mismatch in timing between load and variable renewables generation, and also because at increasing renewables share the system does not have sufficient flexibility to easily integrate the additional renewables, resulting in additional start-up and shutdown and ramping costs relative to a scenario without corporate procurement.

This effect also results in emissions differing between procurement strategies. We see that the hourly matching strategy reduces almost all of the emissions that the company would have caused while the annual or monthly matching may have less impact. This is highly scenario dependent – in India in 2019 annual balancing avoids 100% of the emissions that would otherwise be imposed, while in STEPS there is a 95% reduction and in the SDS 90%. 

To understand how the different strategies impact the system, we must first quantify the effective cost to the system of the different services being provided to the corporate consumer. We can then evaluate what part of those costs is avoided as a result of the corporate portfolio, or in other words the value brought to the system by that portfolio.

Each of these components can be quantified to estimate the total cost that the corporate demand would impose on the system without any procurement strategy, and illustrate how that is offset by the value brought to the system under different procurement strategies. 

This comparison shows that in the SDS in India in 2030, the value brought to the system by the annual matching corporate portfolio is less than one third of the cost of meeting the corporate load, while the value brought by the hourly matching portfolio is around 91%. While it is clear these strategies have very different cost impacts on the system, in jurisdictions where companies can use monthly or annual energy banking, the difference in the tariffs for the two cases may be negligible since the overall energy balance is similar.

This leads to potential concerns. The first is that in the case of an annual matching strategy, if the system services being provided are not all accounted for in the tariff arrangement, then this can result in unintended subsidies for some consumers. For systems where renewable development requires policy support, then of course such subsidies can be appropriate, but it is important that they are explicitly recognised and the funding to cover them is allocated intentionally, rather than coming from cross-subsidies between consumers that may not be intended.

The second aspect to consider is that if the extra value of the hourly matching portfolio is not recognised within the tariff structure, there may be no cost benefit for the company, even though it brings more value to the system. In addition to not being fair between consumers, this is against the interests of the system as a whole, since consumers adopting hourly matching strategies help bring additional value to the system and have the potential to lead the deployment of technologies that will be needed to support the clean energy transition, such as dispatchable low carbon sources, energy storage and demand response.

European Union

This publication has been produced with the financial assistance of the European Union as part of the Clean Energy Transitions in Emerging Economies programme. This publication reflects the views of the International Energy Agency (IEA) Secretariat but does not necessarily reflect those of individual IEA member countries or the European Union (EU). Neither the IEA nor the EU make any representation of warranty, express or implied, in respect to the article's content (including its completeness or accuracy) and shall not be responsible for any use of, or reliance on, the publication. The Clean Energy Transitions in Emerging Economies programme has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 952363.