Abstract
Recent advancements in the power electronics and communication technologies provide the technical infrastructures for the net-zero energy buildings (nZEB) with its home energy management system (HEMS). HEMS is vital for the effective performance of an nZEB to maximize the grid power independency. An nZEB with its HEMS works in an effective and economical way as long as these steps including modeling, operation, and protection are defined well and work in a proper way. Thereby, the modeling, real-time operation, and protection approaches need to be studied in-depth in order to have an effective nZEB. This chapter studies different modeling techniques such as mathematic models and data-driven approaches for nZEB components that include solar photovoltaic (PV) array, home load demand, energy storage systems (ESS), electric vehicle (EV), and heat pump (HP). The impact of uncertainties is analyzed for the performance of the different home component models. The benefits, challenges, impacts, and problems of employing these techniques are presented and some of them are proposed in detail. Online control techniques, such as online scheduling, model predictive control (MPC), and stochastic dynamic programming (SDP), are presented and an MPC is implemented to minimize home grid power dependency. Last but not least, the protection methods are executed to protect the correct performance of the house and increase the security of the system.
Original language | English |
---|---|
Title of host publication | Food-Energy-Water Nexus Resilience and Sustainable Development : Decision-Making Methods, Planning, and Trade-Off Analysis |
Editors | Somayeh Asadi, Behnam Mohammadi-Ivatloo |
Publisher | Springer |
Publication date | 1. Jan 2020 |
Pages | 141-179 |
ISBN (Print) | 9783030400514 |
ISBN (Electronic) | 9783030400521 |
DOIs | |
Publication status | Published - 1. Jan 2020 |
Externally published | Yes |
Keywords
- Home energy management system
- Model predictive control
- Modeling
- Net-zero energy building
- Protection
- Stochastic optimization
- Uncertainties