Smart Household Operation Considering Bi-Directional EV and ESS Utilization by Real-Time Pricing-Based DR
By Ozan Erdinc, Nikolaos G. Paterakis, T. D. P. Mendes, Anastasios G. Bakirtzis, João P. S. Catalão. IEEE Transactions on Smart Grid, 2015
443 citations recorded by the source corpus.
Subfields: Control and Systems Engineering, Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/999d680319e716be1fab6ddc6f5cfde67c9c30cb
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Control and Systems Engineering
- Mengmeng Yu
- Seung Ho Hong
- João P. S. Catalão
- Nikolaos G. Paterakis
- Eslam Al Hassan
- Azah Mohamed
- Maytham S. Ahmed
- Hussain Shareef
In Electrical and Electronic Engineering
- Mengmeng Yu
- Ozan Erdinc
- Seung Ho Hong
- João P. S. Catalão
- Nikolaos G. Paterakis
- Eslam Al Hassan
- Azah Mohamed
- Maytham S. Ahmed
Citations in the corpus
- An overview of Demand Response: Key-elements and international experience (2017, background): “Apart from shifting load manually in response to price signals, residential customers may invest on an automated system, namely a HEMS, which monitors and controls the consumption of several appliances [68].”
- A Real-Time Demand-Response Algorithm for Smart Grids: A Stackelberg Game Approach (2016, background): “In [12]–[14], utilized mixed integer linear programming (MILP) to solve the problem of DR.”
- Review on Home Energy Management System Considering Demand Responses, Smart Technologies, and Intelligent Controllers (2018, background): “Many utility companies are convinced that RTP programs, as the most efficient DR program, are flexible and highly acceptable in electricity markets [49].”
- Model-Free Real-Time EV Charging Scheduling Based on Deep Reinforcement Learning (2019, background): “In recent years, numerous day-ahead scheduling approaches have been proposed for this problem [7]–[18].”