Abstract
Integration of renewables into the power grid imposes several challenges owing to their intermittence. In this regard, the optimal operational planning becomes a tedious as well as highly uncertain. This projects a negative impact on the market potential and integrative feasibility of renewables energy sources. In this paper, a stochastic robust optimization (SRO) is formulated to develop an intermediate optimization framework between the stochastic and robust optimization. The problem description includes unit commitment, economic dispatch, conventional generation-replacement with solar PV-Battery, and optimal management of battery. The proposed framework is tested and validated on an IEEE 14 bus system. The results obtained proves the suitability and efficacy of the SRO by obtaining a moderate optimal operation of the system between a stochastic and robust optimization framework.
| Original language | English |
|---|---|
| Title of host publication | 2023 International Conference on Control, Automation and Diagnosis, ICCAD 2023 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9798350347074 |
| DOIs | |
| State | Published - 2023 |
| Event | 2023 International Conference on Control, Automation and Diagnosis, ICCAD 2023 - Rome, Italy Duration: 10 May 2023 → 12 May 2023 |
Publication series
| Name | 2023 International Conference on Control, Automation and Diagnosis, ICCAD 2023 |
|---|
Conference
| Conference | 2023 International Conference on Control, Automation and Diagnosis, ICCAD 2023 |
|---|---|
| Country/Territory | Italy |
| City | Rome |
| Period | 10/05/23 → 12/05/23 |
Bibliographical note
Publisher Copyright:© 2023 IEEE.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- Battery
- Solar PV
- Unit commitment
- energy storage management
- scheduling
- stochastic robust optimization
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Science Applications
- Computer Vision and Pattern Recognition
- Control and Systems Engineering
- Safety, Risk, Reliability and Quality
- Control and Optimization
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