In our previous articles, we provided an introduction to our approach to developing an energy procurement strategy for the California High-Speed Rail System (HSR), as well as a detailed exploration of our methodology in building an energy use model. In this final installment, we will explore considerations for several procurement options including:

  • Solar PV & Battery Energy Storage Systems
  • Resiliency (Backup Power)
  • Retail vs. Wholesale Procurement


Modeling solar PV energy production is relatively straightforward. A solar PV system’s design revolves primarily around two variables:

System Size (measured in MW)

    • System production is proportional to system size. Solar facility sizing is typically based on a specific production target.

Given that, in many cases, (a) larger projects receive better pricing and (b) there is diminishing financial performance gains with increased production at a certain point, the optimal balance between system production and cost needs to be assessed.

System Configuration (Orientation and Mounting)

    • The orientation of a solar facility is made of up the tilt (angle relative to the ground) and azimuth (the compass direction that the panels face), both of which have a significant impact on the amount of energy that a system will produce.
    • Solar facilities can be installed on fixed structures or mechanical systems (tracking systems) that will rotate panels toward the sun throughout the day in order to increase production. Based on the land availability and increased project costs for tracking systems, optimal designs may vary between fixed tilted structures or tracking systems.

Batteries can be charged and discharged on command, which makes them suitable for a variety of applications. This utilization variability increases the complexity of modeling and identifying optimal battery design and operation strategies. To assess the potential value of batteries, we first identify the applications which should be considered. We optimize our dispatch strategy by modeling iterative scenarios. Each simulation amplifies some price signals while dampening others. The optimal scenarios are those which produce significant financial benefit without wearing out the batteries. Given the resiliency objectives of this evaluation, we also aim to maintain sufficient battery capacity to provide backup power in the event of unexpected grid outages.

A sophisticated battery operation plan considers multiple price signals when deciding when to charge, discharge, or to idle the battery. Here are a few examples of competing opportunities:

  • The Frequency Regulation Market (Wholesale) encourages market participants to correct to second-to-second supply/demand imbalances
  • The Real Time Market (Wholesale) encourages the same, but at five-minute intervals
  • Time of Use (TOU) Pricing Structures create an opportunity for a battery to charge when electricity is less expensive and then be discharged to meet energy needs when energy is more expensive
  • Peak Demand Charges (Retail) are charged to some retail customers based on the peak 15-minute period of electricity use, and batteries are able to reduce these peaks to generate energy cost savings

In addition to the challenges presented by the variability of these price signals, there are system performance and longevity considerations that come into play for establishing the optimal operating strategy.  For example, a well-managed battery should rarely be fully charged, and even more rarely fully discharged. Staying within an intermediate state of charge preserves the battery system while allowing the battery to create supply or demand at any time.


To put a price on combined solar and storage systems, we first look at the existing pricing for similar systems. For example, a recent project developed by 8minutenergy Renewables on behalf of LADWP has strong similarities to those projects anticipated in this HSR evaluation. This 8minuteenergy system will be built approximately 20 miles southeast of the proposed Bakersfield train station and will include 400MWac of solar along with a 300MWac / 4-hour duration battery. The PPA rate for this project (including the cost of the storage system) is $0.03962/kWh.

For this analysis, TerraVerde used similar rates as a baseline assumption to estimate pricing for the envisioned HSR solar plus storage projects. Adjustments are then made to the baseline cost, based on the following key differences between the LADWP system and the HSR system:

  • Differences in the scale of the projects (HSR first-stage projects will likely be smaller)
  • HSR will have a larger battery relative to the solar size
  • Cost impacts of the declining level of Federal Investment Tax Credits (ITC)
  • Anticipated costs declines between now and the project procurement
  • Cost benefits of including these projects in HSR’s larger energy procurement processes, including additional phases of HSR system expansion

Based on these variables, the assumed price per kWh of projects procured by HSR will initially be higher than that of the LADWP system.


Since energy supply reliability is a key consideration and objective for this evaluation, we analyzed both N-1 and N-2 failure scenarios:

  • N-1 Scenario: assumes failure of one grid feed
  • N-2 Scenario: assumes failure of two adjacent grid feeds

The modeled solar and storage systems are interconnected at each grid feed and sized based on the usage at that feed.

The results of the study were extremely positive.

Distributed solar PV and battery energy storage systems, sized for optimal economic performance, are able to provide 100% of the power needed to support the High Speed Rail System in the event of a grid outage.

  1. Our analysis showed that if two adjacent feeds were to lose power, the HSR system could remain operational indefinitely, using the modeled solar and storage systems and power from the remaining functioning grid feeds.
  2. Furthermore, if all grid feeds were to go down during sunny months, the modeled solar and storage systems could still provide the power necessary for the continued operation of the entire HSR system.
  3. The storage is adequate to provide power to the system overnight, as well as through days of poor weather when solar production is reduced.
  4. During winter months, there is not enough sun to power the trains as scheduled (at operating speeds of 220 mph), using only the modeled solar plus storage systems. However, by reducing top speed by 50% (to 110 mph) the energy consumption is decreased by over 60%, allowing the trains to be powered by the modeled solar and battery storage systems indefinitely. Assuming that moderate increases in trip time are an acceptable worse-case scenario, HSR could provide indefinite backup power with solar and storage systems optimized for energy savings.


By default, HSR would pay retail rates for electricity according to PG&E’s B-20-T tariff. Modeling these retail rates is relatively straight forward.

Alternatively, if HSR were to become a Load Serving Entity (LSE), they would buy and sell electricity in the wholesale markets. Becoming an LSE is a complex process that requires approval from the State Legislature. Becoming an LSE also requires contracting with or hiring a team to manage forecasting, scheduling, and procurement. In the wholesale market, an LSE places bids for each hour of electricity consumption in the Day-Ahead-Market (DAM) and respond to the price signals from the Real-Time Market (RTM), which settles every five minutes. The increased complexity and costs of managing this level of procurement engagement should be weighed against the potential wholesale market savings to determine whether becoming an LSE is the right strategy for your organization.

Batteries, when designed and operated strategically, can generate significant value in the RTM. The RTM is naturally much more volatile than the DAM, because it is designed to quickly rectify unexpected supply/demand imbalances that arise. For example, if a large generator fails to provide the electricity bid the previous day due to a system failure, there could be sudden and dramatic under-supply and a spike in RTM prices. These spikes can be expensive for LSEs that cannot quickly reduce energy usage. However, this spike presents an opportunity for generators and users who are quickly able to respond to market signals. A generator that can quickly ramp up production (increase supply), can sell power at an increased price. A large power consumer that can quickly reduce a significant load, such as an industrial process (decrease demand), has an equivalent opportunity. Unlike traditional grid resources, batteries can instantly create supply or demand. Significant variability in the market allows batteries to store cheap power when supply is abundant and discharge to meet demand when the market price is high.

To provide an understanding of pricing volatility, here are some figures from the CAISO RTM market*:

  • Average price: $35.30/MWh
  • Maximum price: $1,100.32/MWh
  • Minimum price: $-55.30/MWh (significant over-supply results in negative pricing)

*for NP-15 Hub, year of 2019

We hope you found this three-part series useful. TerraVerde Energy provides a wide range of independent advisory services to support CCAs, public agencies, and commercial enterprises with evaluating, deploying, and managing smart energy programs. To learn more, write to us at

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