Abstract
This paper presents a Model Predictive Controller (MPC) for electrical heaters’ predictive power consumption including maximizing the use of local generation (e.g. solar power) in an intelligent building. The MPC is based on dynamic power price and weather forecast, considering users’ comfort settings to meet an optimization objective such as minimum cost and minimum reference temperature error. It demonstrates that this MPC strategy can realize load shifting, and maximize the PV self-consumption in the residential sector. With this demand side control study, it is expected that MPC strategy for Active Demand Side Management (ADSM) can dramatically save energy and improve grid reliability, when there is a high penetration of Renewable Energy Sources (RESs) in the power system. © 2012 IEEE
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 3rd IEEE PES Innovative Smart Grid Technologies (ISGT) Europe Conference |
| Number of pages | 8 |
| Publisher | IEEE |
| Publication date | 2012 |
| Pages | 6465618 |
| ISBN (Print) | 9781467325974 |
| DOIs | |
| Publication status | Published - 2012 |
| Event | 3rd IEEE PES Innovative Smart Grid Technologies (ISGT) Europe Conference (IEEE PES ISGT Europe 2012) - Berlin, Germany Duration: 14 Oct 2012 → 17 Oct 2012 Conference number: 3 |
Conference
| Conference | 3rd IEEE PES Innovative Smart Grid Technologies (ISGT) Europe Conference (IEEE PES ISGT Europe 2012) |
|---|---|
| Number | 3 |
| Country/Territory | Germany |
| City | Berlin |
| Period | 14/10/2012 → 17/10/2012 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
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