Abstract
In the future, flexible demand with the combination of renewable energy may hold the key for a sustainable power grid. However, if not managed properly, this combination may pose a threat to the reliability of the grid. In this paper, we analyze the effect on the cost-optimal operation of the flexible building in the presence of locally connected solar photovoltaic (PV) system. Based on a detailed thermal model of a building, an optimization based operational strategy has been presented. The objective of this strategy is to optimally schedule energy and reserve in the presence of flexible loads and the PV system. Two forecasting methods, in a rolling horizon fashion, are deployed to evaluate the interaction between the uncertain PV output and the operation of the whole system. Case studies are performed using the pricing framework of the National Energy Market Singapore (NEMS). Results show that a trade-off exist between the cost optimality of the overall system and the excess PV output fed to the grid (reverse power flow).
| Original language | English |
|---|---|
| Title of host publication | 2016 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2016 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9781509051670 |
| DOIs | |
| State | Published - 9 Dec 2016 |
| Event | 2016 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2016 - Minneapolis, United States Duration: 6 Sep 2016 → 9 Sep 2016 |
Publication series
| Name | 2016 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2016 |
|---|
Conference
| Conference | 2016 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2016 |
|---|---|
| Country/Territory | United States |
| City | Minneapolis |
| Period | 6/09/16 → 9/09/16 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- Buildings
- Cost Optimal
- Demand Response
- Forecasting Methods
- Photovoltaic
- Reverse Power Flow
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