Abstract
To maximize the microgrids profit in presence of renewable energy resources (RERs), this paper employs the transactive energy (TE) technique for optimal scheduling of the distributed energy resources (DERs) throughout the system. Microgrids can exchange energy with the main grid not only to meet their demand but also to make a profit by active participation in energy and reserve provision process. In this regard, TE can be applied as an effective solution for energy supply management and dynamic balancing between the microgrids and the power grid. In this paper, the participation of five grid-connected commercial microgrids in day-ahead (DA) market is considered. The applicability and the satisfactory performance of the proposed approach are tested and validated on a 10-bus IEEE test system. Simulation results indicate that maximum profit can be achieved for the microgrids with optimal scheduling of the DERs based on the TE approach.
| Original language | English (US) |
|---|---|
| Title of host publication | SEST 2019 - 2nd International Conference on Smart Energy Systems and Technologies |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9781728111568 |
| DOIs | |
| State | Published - Sep 2019 |
| Event | 2nd International Conference on Smart Energy Systems and Technologies, SEST 2019 - Porto, Portugal Duration: Sep 9 2019 → Sep 11 2019 |
Publication series
| Name | SEST 2019 - 2nd International Conference on Smart Energy Systems and Technologies |
|---|
Conference
| Conference | 2nd International Conference on Smart Energy Systems and Technologies, SEST 2019 |
|---|---|
| Country/Territory | Portugal |
| City | Porto |
| Period | 9/9/19 → 9/11/19 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
All Science Journal Classification (ASJC) codes
- Artificial Intelligence
- Computer Networks and Communications
- Energy Engineering and Power Technology
- Renewable Energy, Sustainability and the Environment
- Electrical and Electronic Engineering
- Control and Optimization
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