Anuradha kannan

@rnsit.ac.in

Assistant Professor
RNS institute of Technology

Anuradha kannan

EDUCATION

Ph D (From PES university, Bangalore)

RESEARCH, TEACHING, or OTHER INTERESTS

Multidisciplinary, Transportation, Ecology, Evolution, Behavior and Systematics, Statistics, Probability and Uncertainty
3

Scopus Publications

14

Scholar Citations

3

Scholar h-index

Scopus Publications

  • Energy trading for electric vehicle aggregator under random participation of EV owners
    Anuradha Kannan, Vamsi Krishna Tumuluru
    Energy Systems, 2024
  • Shared investment in PV panels and battery storage for residential building
    Anuradha Kannan, Vamsi Krishna Tumuluru
    Energy Ecology and Environment, 2022
  • Behavioral Modeling of Electric Vehicles Using Price Elasticities
    Anuradha Kannan, Vamsi Krishna Tumuluru
    International Conference on Innovative Smart Grid Technologies Isgt Asia 2018, 2018
    In the future, electric vehicles (EVs) are assumed to assist the day-ahead electricity market (DEM) operators in the form of large-scale controllable and flexible loads. For example, EVs can charge or discharge in response to the DEM prices. Therefore, an important problem to address is to mathematically represent the flexibility (i.e., extent of the hourly demand shifting and/or curtailment) offered by the EVs to the DEM operator over the next day. In this paper, an electric vehicle aggregator (EVA) uses a three step approach to model the flexibility offered by the EV consumers at different load buses in a transmission network using convex programming. First, the 24-hour reference response values (demand/supply) are determined using the data of the EV consumers and some chosen reference price. Second, the optimal 24-hour aggregate response of the EVA (i.e., new hourly demand/supply values) corresponding to each randomly perturbed scenario of the day-ahead prices is determined. Third, using the reference values and the different scenario specific response values, the price elasticities are determined. These price elasticities act as indicators of the flexibility offered by the EV consumers. The results demonstrate the effectiveness of the proposed approach besides providing insights into the degree of demand shifting that can occur across various DEM price scenarios.

RECENT SCHOLAR PUBLICATIONS

  • Optimal Revenue Maximization of Electric Vehicle Fleet under Charging and Computing Network
    VK Tumuluru
    2025 International Conference on Engineering and Emerging Technologies … , 2025
    2025
  • Energy trading for electric vehicle aggregator under random participation of EV owners
    A Kannan, VK Tumuluru
    Energy Systems 15 (3), 1127-1149 , 2024
    2024
    Citations: 3
  • Shared investment in PV panels and battery storage for residential building
    A Kannan, VK Tumuluru
    Energy, Ecology and Environment 7 (3), 236-249 , 2022
    2022
    Citations: 7
  • Behavioral modeling of electric vehicles using price elasticities
    A Kannan, VK Tumuluru
    2018 IEEE Innovative Smart Grid Technologies-Asia (ISGT Asia), 593-598 , 2018
    2018
    Citations: 4

MOST CITED SCHOLAR PUBLICATIONS

  • Shared investment in PV panels and battery storage for residential building
    A Kannan, VK Tumuluru
    Energy, Ecology and Environment 7 (3), 236-249 , 2022
    2022
    Citations: 7
  • Behavioral modeling of electric vehicles using price elasticities
    A Kannan, VK Tumuluru
    2018 IEEE Innovative Smart Grid Technologies-Asia (ISGT Asia), 593-598 , 2018
    2018
    Citations: 4
  • Energy trading for electric vehicle aggregator under random participation of EV owners
    A Kannan, VK Tumuluru
    Energy Systems 15 (3), 1127-1149 , 2024
    2024
    Citations: 3
  • Optimal Revenue Maximization of Electric Vehicle Fleet under Charging and Computing Network
    VK Tumuluru
    2025 International Conference on Engineering and Emerging Technologies … , 2025
    2025