The decarbonization of the economy, coupled with increasing extreme weather events, presents a significant challenge to electric grids. They must simultaneously integrate zero-carbon generation, maintain reliability, and enhance resilience against major disruptions. Traditional reliability approaches, relying on peaker plants (inefficient fossil fuel-fired turbines), are becoming unsustainable. The growing uncertainty in supply and demand fluctuations, exacerbated by unpredictable weather and intermittent renewable generation, necessitates exploring alternative solutions. Climate-driven extreme weather events challenge the grid's resilience—its ability to adapt to and recover from low-probability, high-impact disruptions. Resource adequacy, ensuring sufficient power supply to meet demand plus a reserve margin, is crucial for electric reliability. Historically, this has been achieved through peaker plants; however, this approach is inadequate in the face of evolving grid risks. The increasing heterogeneity and intensity of risks (extreme heat, cold, renewable generation droughts, storms) make it expensive and difficult to mitigate every risk in every region. The deep uncertainty surrounding these events' probability, duration, and location makes investment prioritization challenging. This necessitates investigating alternative grid approaches for climate risk reduction under uncertainty. Transmission lines offer one solution by diversifying supply and demand exposure. However, political and logistical challenges often hinder transmission expansion, particularly at interregional levels. The limited operational hours contributing to a transmission line's value also warrant exploring alternatives. Recent advancements in battery technology and cost reductions open new opportunities for mobile storage applications. While electric vehicles (V2G) and road-based transport have been explored, their weight-carrying capacity limits their application. Rail transport, with its immense weight capacity, offers a compelling alternative. A single train can carry a significant amount of battery storage, exceeding the capacity of numerous semi-trucks. The extensive US rail network, covering a vast distance and reaching densely populated and transmission-congested areas, provides an ideal infrastructure for transporting large battery assemblies. Previous studies have shown benefits such as lower renewable curtailment, increased operational flexibility, and transmission congestion relief, but they lack real-world freight scheduling considerations and a national-scale assessment of low-frequency, high-impact events.

Several studies have incorporated mobile battery storage on rail into daily power systems operational models. These studies have demonstrated various benefits, including lower renewable curtailment, increased operational flexibility, transmission congestion relief, and peak load shaving. However, these studies often rely on theoretical representations of freight networks and unrealistically assume perfect scheduling coordination between the rail and power sectors. While providing a theoretical basis for the benefits of mobile energy storage (MES), these studies leave significant gaps in assessing feasibility considering real-world freight constraints and evaluating the potential for rail-based MES to address low-frequency, high-impact reliability challenges on a national scale. This paper aims to address these gaps by evaluating the feasibility and cost-effectiveness of RMES in mitigating such events.

The study assesses the feasibility and cost-effectiveness of Rail-Based Mobile Energy Storage (RMES) for enhancing grid reliability during high-impact, low-frequency events. **Feasibility of RMES:** The researchers first examined the feasibility of RMES within the context of existing freight rail operations. They analyzed Waybill rail shipment data to determine the average daily number of trains traveling between different grid operating regions (ISOs). Travel times between ISOs were estimated, considering scheduling time and industry-reported travel speeds. Three conditions were identified for RMES feasibility: 1) High-impact, low-frequency grid stressors must occur at non-coincident times between operating regions. 2) Grid stressors must be sufficiently separated in time to allow for RMES relocation between regions. 3) Events must be predictable enough to schedule RMES shipments. To assess the coincidence of high-impact grid events, the study examined the correlation of locational marginal prices (LMPs) between ISOs from 2010 to 2021. Transmission valuation methods were used to determine the spatial coincidence of major grid stressors, focusing on the top 1% highest-valued hours for each simulated transmission connection. The study also examined the predictability of high-impact events, considering emergency events, price spikes, and annual peak-demand events. Day-ahead market prices were used as a proxy for short-term predictability, and gross load forecasts were used to assess predictability 2-7 days in advance. **Cost-Effectiveness Analysis:** The cost-effectiveness of RMES was compared to two alternative strategies: 1) investing in stationary generating capacity (battery storage) in each region and 2) investing in transmission lines between regions. The analysis considered the fixed and variable costs of each strategy, including battery costs, interconnection costs, transmission line costs, freight delivery costs, and energy losses. The cost comparison was performed for varying event frequencies and distances between regions. **Case Study: New York:** A case study of New York State was conducted to demonstrate the potential benefits of RMES. The analysis examined LMP data and transmission connection values to assess the potential for RMES to replace underutilized resources and alleviate transmission constraints. **Data Sources:** The study utilized electricity system data from various ISOs, Waybill rail shipment data, LMP data from 2010 to 2021, and gross load forecast data from 2010 to 2020.

The study's key findings include: 1. **Feasibility of RMES:** The analysis of freight rail data suggests that RMES deployment is feasible, as most ISOs have sufficient train traffic to accommodate RMES shipments without significant disruption to freight operations. The travel times between ISOs (1-6 days) are compatible with the predictability of many high-impact events. 2. **Non-Coincidence of High-Impact Events:** Analysis of LMP data showed that high-impact events in different regions often occur at non-coincident times, enabling the sharing of RMES resources between regions. The value of transmission lines is concentrated in a small percentage of hours, indicating the potential for RMES to be highly effective during infrequent, high-value events. 3. **Predictability of High-Impact Events:** Many high-impact events, including emergency events, price spikes, and annual peak events, exhibit sufficient predictability (days to weeks in advance) to allow for effective RMES deployment. Day-ahead market prices provide a reliable signal for short-term scheduling, while gross load forecasts offer reasonable accuracy for longer-term planning. 4. **Cost-Effectiveness of RMES:** RMES offers substantial cost savings compared to stationary battery storage and new transmission lines for low-frequency, high-impact events. For events occurring less than 2% annually per region, RMES is more economical than stationary batteries for short distances (<400km). RMES becomes increasingly cost-effective than transmission lines as the distance between regions increases. For extremely rare events (0.1% annually), RMES is beneficial compared to stationary capacity at all distances. 5. **New York Case Study:** The New York case study showed that RMES could replace underutilized resources and alleviate transmission constraints, offering a cost-effective alternative to significant transmission investments. A high percentage of potential transmission arbitrage value is concentrated in a small number of high-impact hours, making RMES particularly valuable in New York's context of upstate-downstate price separation. 6. **Regulatory and Interconnection Considerations:** Successful RMES deployment requires addressing interconnection challenges and revising regulatory frameworks. Strategic siting to leverage existing interconnections and revising market rules to allow flexible participation of RMES in reliability markets are essential for successful implementation.

The findings demonstrate that RMES is a viable and cost-effective strategy for improving grid reliability and resilience in the face of climate uncertainty. The ability to share flexible, multi-purpose RMES assets across regions significantly reduces the economic burden of addressing diverse and uncertain supply shortfall risks compared to relying solely on stationary assets or dedicated transmission investments. While RMES doesn't provide the same dynamic reserve capability as fast-response stationary assets, it effectively addresses predictable high-impact events. The non-coincidence of high-impact events in different regions maximizes the value of RMES by allowing a single resource to serve multiple locations. Replacing multiple stationary storage or transmission investments with RMES offers substantial cost savings. While there are no technical barriers to RMES implementation, addressing interconnection logistics and electricity regulation is crucial. Strategic siting and revised market rules can facilitate the widespread adoption of RMES, unlocking its substantial potential for enhancing grid reliability and resilience.

This study demonstrates the significant potential of RMES as a cost-effective solution for improving grid reliability and resilience, especially for low-frequency, high-impact events. The findings highlight the importance of addressing interconnection challenges and regulatory barriers to enable large-scale deployment. Future research should focus on integrating RMES into more sophisticated grid models to fully quantify its operational benefits and assess its performance under various scenarios, including those with increasing renewable penetration and more frequent extreme weather events. Exploring cross-sectoral applications of RMES, such as providing energy-as-a-service to the freight industry, could offer further economic and environmental gains.

The study relies on historical data, which may not fully capture the evolving nature of high-impact events driven by renewable energy and climate change. The analysis focuses on cost savings and does not fully model the operational benefits of RMES. The study's scope is primarily focused on the US context, and the generalizability of the findings to other countries with different rail networks and grid structures requires further investigation. Further, the model simplifies several aspects such as detailed load forecasting which could be improved by utilizing more advanced methodologies.