Abstract
Considering recent developments in photovoltaic (PV) systems, storage, and electrical vehicles, not unexpected that one day smart homes will also take part in energy markets directly. In this regard, the presented paper proposes a stochastic programming approach to manage the consumption of a smart home according to intermittent PV system production and uncertain energy prices to make the smart home available for taking part in the local day-ahead (DA) energy market. A battery storage system is integrated to make flexibility against price fluctuations. Furthermore, modeling of plug-in electric vehicles (PEV) is also provided, where the traveling pattern is modeled through scenarios. The goal is to maximize the daily profit of the smart home while the welfare of the inhabitants is satisfied by considering comfort constraints. In addition, the conditional value at risk (CVaR) risk index is considered to manage associated risk with gained profit. The obtained results show the effectiveness of the optimization framework, in which the expected daily profit of the homeowner can reach $1.72 per day in the risk-neutral condition.
| Original language | English |
|---|---|
| Title of host publication | 2022 IEEE International Conference in Power Engineering Application : ICPEA |
| Publisher | IEEE |
| Publication date | 2022 |
| ISBN (Electronic) | 9781665416290 |
| DOIs | |
| Publication status | Published - 2022 |
| Event | ICPEA 2022 - Duration: 7 Mar 2022 → 8 Mar 2022 |
Conference
| Conference | ICPEA 2022 |
|---|---|
| Period | 07/03/2022 → 08/03/2022 |
Keywords
- Uncertainty
- Fluctuations
- Stochastic Processes
- Smart homes
- Programming
- Batteries
- Indexes
- conditional value at risk (CVaR)
- energy market
- stochastic programming
- energy management
- smart home
