A novel pricing scheme for managing virtual energy communities and promoting behavioral change towards energy efficiency

• Published in: Electric power systems research 2019-02, Vol.167, p.130-137
• Main Authors: Mamounakis, Ioannis, Efthymiopoulos, Nikolaos, Makris, Prodromos, Vergados, Dimitrios J., Tsaousoglou, Georgios, Varvarigos, Emmanouel (Manos)
• Format: Article
• Language: English
• Subjects: Algorithms; Alternative energy; Behavioral change; Communities; Consumer behavior; Demand response; Electric rates; Energy consumption; Energy costs; Energy efficiency; Energy management; Real time; Real time pricing; Social networks; Time of use electricity pricing; Virtual energy communities; Virtual reality
• ISSN: 0378-7796; 1873-2046
• DOI: 10.1016/j.epsr.2018.10.028

•Ιncreasing need for modern pricing schemes to effectively incentivize willing users to modify their energy consumption pattern.•Current energy pricing schemes do not adequately compensate for behavioral changes.•We propose a Community aware — Real Time Pricing (CRTP) scheme to reduce system’s energy cost.•We propose an Energy Community Formation Algorithm (ECFA).•The proposed scheme achieves considerable reduction in the system’s energy cost and greater aggregated users’ welfare. The harmonization between the variable rate of energy production in the era of massive renewable energy penetration is a major challenge in an open, competitive and resilient electricity market. As a result, there is an increasing need for modern pricing schemes, which will effectively incentivize willing users to modify their energy consumption pattern to meet this objective. Current energy pricing schemes (e.g. real time pricing) treat all users the same, and do not adequately compensate for behavioral changes, thus mitigating the behavioral change dynamics. In this paper, we propose a Community Real Time Pricing (CRTP) scheme together with an Energy Community Formation Algorithm (ECFA), where users are clustered in Virtual Energy Communities (VECs) according to: (i) their level of flexibility in modifying their Energy Consumption Curve (ECC), and (ii) their relationships in Online Social Networks (OSNs), modelling peer-pressure capabilities. We show that CRTP with ECFA can simultaneously achieve considerable reduction in the system’s energy cost and greater aggregated users’ welfare than with the state-of-the-art real time pricing. CRTP–ECFA adopts a truly fair pricing policy, as each user is rewarded exactly according to his/her individual contribution in reducing system costs, thus promoting the desired behavioral change.