In light of electrification plans, renewable energy targets, and ever increasing costs, developing a smart energy strategy continues to be among the top priorities for many teams. In addition, emerging concerns around energy resiliency & reliability are pulling groups into the complex world of designing & deploying backup power systems. Given the rapidly evolving landscape in programs, markets, and technologies, it can be incredibly challenging for organizations to get their bearing and identify the right path forward.
TerraVerde Energy has been engaged by the California High Speed Rail Authority to assist in the development of their energy procurement strategy. When it achieves full operation, the High-Speed Rail System (HSR) will be the largest single user of electricity in the state of California. In this three-part blog article series, we will be sharing some of the details regarding our approach and findings. We hope that our learnings shared here will be a helpful resource to other teams that are in the midst of developing their own strategic approach to energy procurement.
At the onset of the analysis, HSR & TerraVerde established the following three objectives:
- COST OPTIMIZATION: minimize electricity costs
- 100% RENEWABLE: power the trains and stations with 100% renewable energy
- RESILIENCY: leverage solar PV and battery storage systems to provide back-up power that would enable continued train operation in the event of a grid outage
The analysis began with the creation of a physics-based simulation model that quantified train performance and corresponding electricity demand. As there were no existing models available to reference for the HSR operation, TerraVerde had to model each mile of the track and calculate the power draw (energy) required to propel the train. We then built into the model an extensive list of energy procurement strategies and conducted a financial assessment of these strategies. Finally, we further examined the most attractive financial options to assess their potential to provide reliable back-up power under various grid outage scenarios, including N-1 and N-2 failure scenarios (N-1 assumes failure of one grid feed, N-2 assumes failure of two adjacent grid feeds).
In part-one of this series, we will discuss the following principles:
- Establishing an energy cost baseline
- Key factors in optimizing costs
ESTABLISHING AN ENERGY COST BASELINE
The first stage of the California High-Speed Rail System will stretch 171 miles through PG&E’s service territory in the Central Valley, connecting Bakersfield to Merced. The trains will travel at top speeds of 220 mph (350 kph) and will stop at 2 stations along the way (Fresno & Madera). Passengers will make the full 171-mile trip in one hour.
Table: Comparison of HSR and Automobile Performance
|Top Speed||220 mph||75 mph|
|Average Speed||170 mph||68 mph|
|Total Time||1 hour (includes 2 stops)||Over 2 ½ hours (with no traffic)|
The trains will draw power from different grid feeds as they move along the track. Each of these feeds will be metered and are represented in TerraVerde’s model as a monthly electricity bill. To establish an energy cost baseline, we modeled these electricity bills using the new “evening peak” time-of-use (TOU) rate structure, which is scheduled to take effect in November of this year. By default, HSR would pay for the electricity flowing through these feeds according to PG&E’s TOU-B-20 (transmission voltage) rate schedule for high voltage interconnections. This projected cost (based on the energy use model, procured from PG&E under the TOU-B-20 rates structure) was established as the baseline for this evaluation.
KEY FACTORS IN OPTIMIZING COST
Given the high volume of electricity that will be consumed by HSR, it is important to investigate the available procurement options (including wholesale procurement as well as distributed solar PV & battery energy storage systems) and quantify how each strategy impacts costs. We consider the following variables:
- Wholesale markets and retail rates
- Default and special option rates
Solar and Battery Storage Options
- Project Ownership Structures (lease, PPA, or purchase)
- Mounting Configuration (fixed tilted or tracking system)
- Siting (on-site or remotely located)
- Power Capacity (maximum power output in MW)
- Energy Capacity (duration in hours)
- Utilization Strategies
- Demand reduction
- Energy arbitrage
- Regenerative braking power capture
- Backup power
- Grid import & export
Each of these variables have impacts on several others and cannot be optimized in isolation. For example, the tariff selected affects the value of the solar generated energy. Similarly, a south-facing solar facility design may generate the more energy than a west-facing facility, however a west-facing facility will generate more electricity in the evening when electricity rates are the highest. Depending on the timing of solar production and the energy storage capacity that is available, it may make sense to store afternoon production in a battery for evening use.
Based on the complex relationship of these variables, determining optimal strategies required analysis of thousands of iterative scenarios, including the calculation and ranking of the financial performance of those scenarios. This required a very flexible model, designed to ingest an extensive list of inputs, in order to simulate the electricity bills and system costs under each scenario.
In our next articles, we will dive into the more technical details of this study, including:
- Modeling train electricity usage (i.e., the math and physics)
- Comparing wholesale vs. retail market options
- Evaluating solar PV, battery storage, and resiliency strategies
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 email@example.com.