The Evaluation of Security and Privacy Components in the Context of Peer-To-Peer Power Trading Methodologies using Network Intelligence


  • Cuddapah Anitha Associate Professor, Department of Computer Science and Engineering, School of Computing, Mohan Babu University, (Erstwhile Sree Vidyanikethan Engineering College, Tirupati, Andhra Pradesh.
  • Niti Saxena Associate Professor, Department of Commerce, Jagannath International Management School, New Delhi
  • Prakash Chandra Swain Assistant Professor, Department of Commerce, School of Social, Financial & Human Sciences, Kalinga Institute of Industrial Technology (KIIT), Bhubaneswar, Odisha, India
  • S. Pramila Associate Professor, School of Commerce Finance & Accountancy, Christ University, Delhi, NCR
  • Deepali Rani Sahoo Assistant Professor, Symbiosis Law School, Noida, Symbiosis International (Deemed University), Pune, India
  • K. K. Bajaj RNB Global University, Bikaner, Rajasthan
  • Umesh Kumar Professor, Glocal University Pharmacy College, Glocal University, Saharanpur, U.P.


Peer-to-peer (P2P), Security, Privacy, Network Intelligence, Power Trading Methodologies


The widespread implementation of renewable energy sources, along with a more proactive approach to managing electricity use, is causing a shift in the way power systems operate and electricity is traded in the market. The P2P economy in particular is benefiting from this change. To efficiently handle the fast changes in renewable power generation at the distribution network level, a local market mechanism that can adapt is required. The efficient and safe operation of the distribution network is also bound to be affected by the extensive adoption of P2P energy trading. This study presents a new paradigm for P2P power trading that accounts for constraints imposed by distribution network security. Specifically, the design makes use of the generalised quick dual ascent method. The article lays out the groundwork for an event-based local peer-to-peer market, which would facilitate rapid and efficient energy swaps inside a certain region. The next step in making sure the distribution system is secure is to evaluate the impact of peer-to-peer transactions on the network using the nodal voltage and network loss in relation to nodal power injections. This allows for an internal determination of how to distribute the costs of P2P energy trading and the incorporation of the external operating constraints. Distributed market-clearing is also applied efficiently by means of a universal quick dual ascent technique. The numerical results show that the proposed model can implement P2P energy trading securely into the distribution system. Furthermore, the method for solving the problem shows remarkable efficiency in achieving convergence.


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How to Cite

Anitha, C. ., Saxena, N. ., Swain, P. C. ., Pramila, S. ., Sahoo, D. R. ., Bajaj, K. K. ., & Kumar, U. . (2024). The Evaluation of Security and Privacy Components in the Context of Peer-To-Peer Power Trading Methodologies using Network Intelligence. International Journal of Intelligent Systems and Applications in Engineering, 12(15s), 464–470. Retrieved from



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