Abstract
This paper examines the challenge of bidding a battery system on an electrical power market with varying prices. Optimizing bids for each market interval is a complex challenge since the bid size for one market interval affects the battery availability during several subsequent market intervals. In this paper, a renewable generation unit such as Photovoltaic (PV) and a battery storage are considered, with the battery used to shift electricity sales from low-price market intervals to high-price market intervals. The battery can also be used to smooth momentary fluctuations in generated power, cope with differences between actual and forecasted generation, and help to meet the maximum power limit constraint. This paper evaluates how to best manage the battery for optimal bidding in an electrical power market.
| Original language | English |
|---|---|
| Title of host publication | 2023 IEEE 32nd International Symposium on Industrial Electronics, ISIE 2023 - Proceedings |
| Publisher | IEEE |
| ISBN (Electronic) | 979-8-3503-9971-4 |
| DOIs | |
| Publication status | Published - 2023 |
| MoE publication type | A4 Conference publication |
| Event | International Symposium on Industrial Electronics - Espoo, Finland Duration: 19 Jun 2023 → 21 Jun 2023 Conference number: 32 |
Publication series
| Name | Proceedings of the IEEE International Symposium on Industrial Electronics |
|---|---|
| Volume | 2023-June |
| ISSN (Electronic) | 2163-5145 |
Conference
| Conference | International Symposium on Industrial Electronics |
|---|---|
| Abbreviated title | ISIE |
| Country/Territory | Finland |
| City | Espoo |
| Period | 19/06/2023 → 21/06/2023 |
Keywords
- artificial intelligence
- battery
- electricity market
- frequency reserve.
- reinforcement learning
