Retail electricity revenue: transportation: Maryland (Thousand USD) - United States - EIA - Monthly
This series is part of the dataset: US retail electricity prices (EIA)
Download Full Dataset (.xlsx)Latest updates. In Maryland, the retail electricity revenue in the transportation sector stood at 6,465 Thousand USD in July 2026, compared to 6,065 in the previous month. This marks an increase of 6.6 percent.
Sample. The monthly time series shown in the plot has 199 observations. The time period covered by the series is from January 2010 to July 2026.
History. Here's a snapshot of some summary statistics we computed on the entire sample: the retail electricity revenue hit a maximum of 7,015 Thousand USD in December 2025; it reached its minimum of 1,380 in October 2019; it had an average value of 3,748.
Latest values
| Date | Value - Thousand USD |
|---|---|
| 2026-05-31 | 5,757.91 |
| 2026-06-30 | 6,065.16 |
| 2026-07-31 | 6,465.41 |
Tip. For easier exploration, we organize time series into worksheets and datasets. If you look below, you will find how we arranged further material linked to the statistics provided here.
Not for investment purposes. Data and any other information shared on FetchSeries are not suitable for investment purposes or as a basis for financial-decision making. Users should seek expert advice and perform independent analysis before taking any financial risk.
Series Metadata
| Field | Value |
|---|---|
| Description | Retail electricity revenue for the transportation sector in Maryland |
| Country | United States |
| Economic concept | Flow |
| Data type | Value |
| Seasonally adjusted | No |
| Deflation method | Not applicable |
| Rescaling | None |
| Measure type | Level |
| Frequency | Monthly |
| Unit | Thousand USD |
| Source | U.S. Energy Information Administration (EIA) |
| Source type | Government agency |
| Data licence | Public domain |
| Other information | Transportation sector state-level data begin in January 2010. |
| FSR temporal aggregation code | LM1 |
Series in the same data set
Discover the other time series included in this data set.