Virtual Power Plants: How Disparate DERs Can Be Integrated into a Single, Dispatchable Resource: Part I

By John Bonnin

John Bonnin

For decades, utilities have used Demand Response (DR) and Distributed Energy Resources (DER) as the basis for reducing peak demand, reducing coincident peaks, managing circuit-specific issues, and assisting the grid in emergencies. With the introduction of Virtual Power Plants (VPP), however, energy companies are in a fortunate position to also deploy DERs into the wholesale market.

DERs with VPPs is a shift in strategy from essentially “defense” to “offense” seen by many as unlocking the hidden potential of these resources, creating more flexibility, better reserve margins, lower emissions, and additional value streams in tomorrow’s energy environment.

DER and DR programs are varied, both in size and capability, and each has a different value proposition to the market. So how can the diverse capabilities of DER and DR be organized into coherent, seamless dispatch? How does each puzzle piece fit into the VPP’s capability and how does the VPP then present this capability to the wholesale market?

This two-part blog covers how to harness the individual capabilities of all these diverse resources and capabilities to operate as a single, virtual power supply asset that can be successful in the wholesale electricity market.

Organizing diverse capabilities into a single dispatch: An Approach

The approach offered here involves a systematic analysis of the performance attributes, costs, and value of each kind of DDR and DER. For simplicity’s sake, in this article, I refer to all these types of assets or capabilities as simply “resources,” even though they are a highly diverse, heterogeneous set of technologies and capabilities.

Each VPP resource type will be analyzed through a series of steps, described by these questions:

 

  1. How will each resource type deploy in the market, and what are the products it can offer?
  2. What is the pricing strategy for each resource type?
  3. How can a resource stack be created, sorted by cost?
  4. How can constraints be integrated into the resource stack?
  5. How can we automate the re-creation of the resource stack to enable daily or hourly adjustment?

 

This blog post will cover the first two steps, then in Part II we will address the remaining steps.

1. How will each resource type be deployed in the market?

As mentioned, the resources are varied, both in size and capability, and each has a different value proposition to the market. Here are several types to consider:

Residential HVAC thermostat programs: A utility can signal thousands of thermostats to increase by three to five degrees during hot summer periods. This reduces demand by switching off scores of energy-hungry A/C compressors, reducing load almost immediately. However, on really hot days, these homes will simply heat up, and the A/C units will switch back on in a half-hour or so to maintain the higher setpoint. Operators have developed approaches to use this capability: if a large reduction is needed at one time, the entire fleet is deployed. If longer duration load reduction is needed, portions of this fleet are cycled sequentially, and deployed every 15 minutes. The residential thermostat program is both a short-term capacity product and a short-term energy product.

Commercial demand response programs: Many large commercial customers can reduce lighting, HVAC, and other loads for specific durations at the utility’s command. These actions are either manually initiated or through an automated signal. This capability is also a capacity product and an energy product , though limited by contract terms.

Industrial customers are able to shift production: Industrial customers have the capability to shut down specific equipment quickly when called upon. If capable of doing so within a 10-minute time frame from receipt of notification, this capability can be a responsive reserve product, in addition to capacity and energy.

Distribution-level storage: Energy storage facilities on the distribution system originally constructed as non-wires alternatives to circuit upgrades can be marketed as responsive reserves, for frequency regulation, for energy, and for capacity.

Backup generation: Customers have backup generators that can be started at a moment’s notice. These customers can be contracted to remotely deploy these units for coincident peak reduction and emergencies. This backup generation can be marketed as responsive reserves, energy, and capacity.

This segmentation of the types and capabilities of the resources helps to classify what aspect of the market each will participate in and documents any operational constraints present.

2. What is the pricing strategy for each VPP resource type?

The options available for resources in the market include energy, responsive reserves, frequency regulation, black start, and the like.

Capacity: Capacity is generally procured in advance of the real-time market for purposes of bolstering reserve margin, protecting a sales position, and for other reasons. In some regions, a capacity market exists, but this is not in all markets. In any case, the VPP will deploy capacity that is available to it on an hour-by-hour and day-by-day basis. Capacity’s value, therefore, is that it’s a “gateway” to deployable energy, constrained by the specific attributes of the resource. If the energy is flexible and low-cost, then the capacity value is higher, and vice versa. Good benchmarks for valuing capacity are the aforementioned capacity market, market quotes for call options, as well as other statistical methods that have been developed for that purpose. What’s important about capacity is once it’s procured, it enables the resource to deploy energy or reserves on its own merits and cost structure.

Energy: The chief consideration when arriving at a price for the energy available by the VPP (defined as the demand reduction from the DRs and DERs, as well as battery discharge) is the following question:

What price must the market reach before I’m willing to deploy that resource, knowing its limited duration, and the fact that it may not be available later? In other words, what is the opportunity cost of deploying now versus later?

Obviously, the threshold price should at least compensate the company for the lost energy sales during the deployment. Above that, the pricing should reflect either the marginal cost for deployment (for energy storage and backup generation resources), or a market analysis of scarcity (for demand response resources).

Marginal cost for deployment: DER such as energy storage or backup generation are similar to traditional power generators in the approach to pricing. Their primary functions are to provide power in the event of an outage, but beyond that, they have the potential to earn revenue (or reduce costs) when not used as a backup resource. It follows that this type of resource should be offered into the market at its marginal cost (which is derived from, but is not identical to, its variable cost). This approach enables the unit to earn revenue when it’s “in the money” but avoid operating when it’s “out of the money.”

Output limitations: Certain backup generators are hours-limited and can only be used for a limited amount of time each year when not actively backing up a facility during an outage. These limits can be based on air emissions permits, warranty provisions, or other reasons. Energy storage resources (batteries) may be limited by the number of design cycles per year. As a result, if not carefully monitored, a unit could be dispatched profitably (based on market conditions) for long stretches at the beginning of any given year, only to reach its limit and miss out on lucrative market conditions later in the year.

The offer price can be developed, reflecting market scarcity. For this, a price forecast must be developed to estimate when scarcity creates the highest prices and when the unit can capture the most value in any calendar year. For example, if a unit can only run 500 hours per year (which is 500/8760, or 5.7% of the year) then an analysis of a price forecast can pinpoint the threshold price to offer the unit such that it will most likely capture the top 500 highest priced hours of the year. To do this, a price duration curve is developed by taking the chronological (daily and hourly) price forecast and sorting low to high. The high-priced end of the resulting curve is analyzed to draw the pricing threshold.

chronological-price-forecast

(The chronological price shows expected prices hour by hour, as expected each day of the year.)

price-duration-curve

(The price duration curve shows prices sorted low to high to better analyze the extent of scarcity expected in the market.)

On the above chart we see the top 500 hours of this price duration curve are above approximately $100/MWH. Offering a unit to deploy at this price gives us a chance of fully utilizing the available hours.

Granted, this is only a forecast of the price. Actual prices will certainly be different, but this can be a starting point. The actual deployment of the resource throughout the year, plus actual pricing experienced in the real time market must be monitored and plans should adjust to fit real-world trends.

Market analysis for thermostat programs and other demand response: Thermostat programs may have even more limited availability than backup generators. Most residential customers will tolerate the utility company’s temperature setback during times of genuine power emergencies or when voluntary conservation appeals have been made. Frequent use of this program has shown to lead to “customer fatigue” and customers opting out of the programs. For these reasons, even more care should be made in pricing this capability for the wholesale market.

Perhaps customer focus groups have reported willingness to endure five events per month, for example. If each deployment is for two hours, then the VPP should offer this capability into the market at such a price that it’s only likely to be deployed the highest-priced 10 hours each month. Again, the price duration curve can point the way.

Commercial customers with contractual demand response obligations can be analyzed in a similar way. The number of deployments could be explicitly agreed-upon in the contract. It’s therefore useful to consult the price duration curve to arrive at an offer price that is likely to fully use this resource while reducing the chances it will miss profit opportunities.

Responsive Reserve and Frequency Regulation: We have discussed energy and capacity pricing analysis for DR and DERs. Responsive Reserve Service (RRS) and Frequency Regulation (FR) are types of specific services (called Ancillary Services, or A/S) procured each day by the grid operator to maintain reliability of the system. Prices are set in a daily auction conducted by the grid, but can also be bought and sold using bilateral contracts. Most energy storage resources can provide both services, and some backup generators can provide at least one of them. Even some curtailable load can sell RRS if it meets specific criteria.

An essential feature of RRS is that when a particular customer has sold its resource’s capability to the grid, this capability cannot participate in the energy market. Selling RRS is an opportunity because the resource can earn revenue during times when it wouldn’t have been otherwise deployed for energy. It’s a risk because once obligated it could miss out on high-priced energy sales.

The offer price for RRS must be carefully developed to earn revenue when the resource’s energy is out of the money, but enable energy sales during times when it’s in the money. This “co-optimization” of energy and AS is a crucial skill that successful energy companies have integrated into their daily operations.

Frequency regulation (FR) is unlike RRS in that the backup generator or energy storage resource will receive constant signals to increase or decrease production in order to help manage system frequency. It will therefore produce energy, for which it is compensated at the prevailing energy price, when deployed upwards. Downward deployments settle as if the resource purchased the energy at the prevailing price. Upward deployment at high prices is good, although upward deployment at low prices may not cover the energy cost of the resource. Similarly, downward deployments when prices are high cause the resource to lose opportunity and indeed can cost money, while downward deployment at low prices are not as much of a risk. Once again, careful analysis of a resource’s suitability to deploy frequency regulation is needed.

Conclusion:

DR and DER are capabilities and technologies that fit into several areas of the energy market. They are not like traditional resources, however, when it comes to strategies for presenting them to the market. Much analysis of the market and price forecasts is needed.

In the next blog post, we look at how these resources can be “stacked” into a single dispatchable entity in the wholesale market, how each resources’ unique constraints can be factored into the stack, and how it must be constantly updated and adjusted automatically for successful market participation.

John Bonnin has nearly 30 years of industry experience, including 18 years at CPS Energy as Vice President of Energy Supply and Market Operations. His focus was managing market risks to native load customers and optimal dispatch of CPS Energy’s power generation fleet, which included over 1.5 GW renewable energy and 200 MW Demand Response capability. Mr. Bonnin has a Master of Science in Management/Computer Resource Management from Webster University and a B.S. in Chemistry from LSU.

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