Abstract
The current upward trend of the residential energy demand and the high penetration of new renewable resources have changed the conception of the electrical grid. The centralized distribution scheme is currently moving forward to a distributed layout where the paradigm of Smart Energy Communities has emerged, meaning a set of households that share a Microgrid, have tied renewable production and can be either connected or disconnected from the main grid. In this context, due to the reduced dispatchability of the renewable generation, the planning of the installed PV power as well as the storage capacity is the cornerstone in order to achieve a high degree of both self-generation and self-consumption. However, the lack of detailed hourly or sub-hourly data makes it difficult. Therefore, this paper aims to present a high-resolution simulation method for evaluating the PV power and storage capacity requirements for a Smart Community based on a stochastic demand model and real PV production data, so the interplay between consumption and generation can be better understood.
| Original language | English |
|---|---|
| Title of host publication | EEEIC 2016 - International Conference on Environment and Electrical Engineering |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9781509023196 |
| DOIs | |
| Publication status | Published - 29 Aug 2016 |
| Externally published | Yes |
| Event | 16th International Conference on Environment and Electrical Engineering, EEEIC 2016 - Florence, Italy Duration: 7 Jun 2016 → 10 Jun 2016 |
Publication series
| Name | EEEIC 2016 - International Conference on Environment and Electrical Engineering |
|---|
Conference
| Conference | 16th International Conference on Environment and Electrical Engineering, EEEIC 2016 |
|---|---|
| Country/Territory | Italy |
| City | Florence |
| Period | 7/06/16 → 10/06/16 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- Energy Consumption
- energy storage
- load modeling
- solar power generation
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