Status : Verified
| Personal Name | Santos, Ren Zedec S. |
|---|---|
| Resource Title | A Two-Layer Peer-to-Peer (P2P) Energy Trading System Towards a Secure Cyberphysical Power System (CPPS) |
| Date Issued | 14 January 2025 |
| Abstract | This dissertation presents a two-layer peer-to-peer (P2P) energy trading system towards a secure cyberphysical power system (CPPS). The lower layer utilizes a probabilistic framework to ensure network security by calculating the probability of network violations for each user, referred to as the network security risk index (NSRI). The upper layer of the two-layer network has the CPPS security framework that utilizes a forecasting-aided state estimator (FASE) to predict network states and detect anomalies. This two-layer approach contributes towards CPPS security amidst the volatility of energy trading. A probabilistic framework is implemented in the lower layer that uses numerical probabilistic load flow (NPLF) to calculate the likelihood of each user causing a voltage violation, creating the NSRI. This allows the community manager to derive a generation limit table based on the NSRI, filtering potential users to prevent network violations. Also, a matchmaking energy trade is implemented, allowing users to autonomously select their trading partners. The primary objective of this matchmaking implementation is to evaluate the effectiveness of the probabilistic framework under conditions of user-driven trading volatility. The matchmaking with probabilistic framework incorporates various acceptance levels, allowing user autonomy while providing network security. Simulations of the probabilistic framework have been conducted observing true positive rates (TPR), representing users filtered in energy trading that actually contribute to a network violation and false positive rates (FPR), representing users that are filtered but did not actually contribute to a network violation. Results have generally shown a high TPR, with values ranging from 90.65% to 98.22%, and a low FPR, with values between 9.86% and 11.94%. Simulation results validate the effectiveness of the probabilistic framework, demonstrating high TPR and low FPR. In the upper layer of the two-layer networ |
| Degree Course | Doctor of Philosophy in Electrical and Electronics Engineering |
| Keyword | Power systems, transactive energy, energy trading, cyberphysical power system |
| Material Type | Thesis/Dissertation |
Preliminary Pages
18.54 Mb
Category : F - Regular work, i.e., it has no patentable invention or creation, the author does not wish for personal publication, there is no confidential information.
Access Permission : Open Access