Demand for grid-supplied electricity in the presence of distributed solar energy resources
Evidence from New York City
Bibliographic Data
| ID | 12245349 |
|---|---|
| Authors | Kevin F Forbes (0000-0002-9521-6845, corresponding author) |
| Year | 2022 |
| Volume | 80 |
| Pages | 101447-101447 |
| Publication date | 2022-12-10 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Utilities Policy (JOURNAL) |
| Journal identifiers | ISSN: 0957-1787 • E-ISSN: 1878-4356 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.jup.2022.101447 |
| OpenAlex | W4311760069 |
| Language | EN |
| References cited | 9 |
The increasing utilization of distributed energy resources such as behind-the-meter solar has given rise to a grid-supplied load profile conditional on solar conditions that are difficult to forecast using conventional methods. As a result, the accuracy of the load forecasts is reduced, representing a possible operational challenge to system operators. This paper presents a method to resolve this challenge using New York City electricity zone data. The analysis presented in this paper demonstrates that the load forecasting challenges associated with behind-the-meter solar can be successfully addressed using econometric time-series methods and better forecast information
Distributed generation · Econometrics · Economics · Electrical engineering · Electricity · Electricity demand · Electricity generation · Environmental economics · Geography · Grid · Meteorology · Metre · Power (physics · Renewable energy · Solar energy · Computer Science · Energy Load and Power Forecasting · Engineering · Environmental Science · Integrated Energy Systems Optimization · Mathematics · Smart Grid Energy Management
| Highly cited | No |
|---|