Abstract
When new energy is added to the grid, issues can be resolved via energy storage, energy storage through the provision of ancillary services to gain revenue. This paper proposes a combined energy storage and renewable energy optimization model that takes ancillary services into account, and establishes an operation-planning two-layer model to optimize the site selection and capacity allocation for energy storage and renewable energy. Finally, the IEEE33 bus system is utilized as an example for simulation analysis after the model is solved using the improved particle swarm optimization algorithm. The results demonstrate that, in addition to having a lower overall system cost and more ancillary service benefits from energy storage, the configuration result obtained by the joint optimization of energy storage and renewable energy taking into consideration the ancillary service benefits is more reasonable.
| Original language | English |
|---|---|
| Pages (from-to) | 1743-1747 |
| Number of pages | 5 |
| Journal | IEEE Information Technology, Networking, Electronic and Automation Control Conference, ITNEC |
| Issue number | 2024 |
| DOIs | |
| State | Published - 2024 |
| Externally published | Yes |
| Event | 7th IEEE Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2024 - Chongqing, China Duration: 20 Sep 2024 → 22 Sep 2024 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- ancillary services
- energy storage
- frequency regulation
- peak shaving
- the particle swarm optimization algorith
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