A Secure & reserved pricing mechanism for peer-to-peer energy trading using additive secret sharing and blockchain

This paper presents a secure and efficient peer-to-peer (P2P) energy trading framework that integrates data privacy, optimized energy allocation, and tamper-proof financial settlement. The proposed model ensures privacy of participants’ energy and price information using additive secret sharing with message authentication codes, enabling verification against data tampering during transmission. Based on the reconstructed information, the market operator (MO) determines the final trading price (FTP) through a negotiation process, accommodating both buyers’ and sellers’ market modes. Energy allocation is optimized using a modified Vogel’s Approximation Method (VAM), ensuring fairness, minimizing buyers’ energy bills, and maximizing sellers’ satisfaction while respecting supply-demand constraints. The financial transactions are executed via a blockchain-enabled model, providing secure, transparent, and immutable settlement without requiring multiple contracts between participants. The framework is evaluated on a 4-year real-time dataset of 22 participants, demonstrating effective data privacy enforcement, accurate price determination, optimized energy allocation, and significant reduction in buyers’ bills with increased sellers’ revenues compared to existing models. The results validate the proposed model’s efficiency, scalability, and practical applicability in real-time smart grid operations.

Authors

Institutions

Publication Details

Journal
Journal of King Saud University - Computer and Information Sciences
Published
2025-12-30
DOI
https://doi.org/10.1007/s44443-025-00417-4
Citations
1
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
3.25
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Secure & reserved pricing mechanism for peer-to-peer energy trading using additive secret sharing and blockchain

Mahira Afzal, Iqra Nazir, Hassam Ishfaq, Sania Kanwal et al.
1 citations
Journal of King Saud University - Computer and Information Sciences
Blockchain Technology Applications and Security
3.25
article

A Secure & reserved pricing mechanism for peer-to-peer energy trading using additive secret sharing and blockchain

Mahira Afzal, Iqra Nazir, Hassam Ishfaq, Sania Kanwal, Nermish Mushtaq, Waqas Amin
article en
1 citations

Abstract

This paper presents a secure and efficient peer-to-peer (P2P) energy trading framework that integrates data privacy, optimized energy allocation, and tamper-proof financial settlement. The proposed model ensures privacy of participants’ energy and price information using additive secret sharing with message authentication codes, enabling verification against data tampering during transmission. Based on the reconstructed information, the market operator (MO) determines the final trading price (FTP) through a negotiation process, accommodating both buyers’ and sellers’ market modes. Energy allocation is optimized using a modified Vogel’s Approximation Method (VAM), ensuring fairness, minimizing buyers’ energy bills, and maximizing sellers’ satisfaction while respecting supply-demand constraints. The financial transactions are executed via a blockchain-enabled model, providing secure, transparent, and immutable settlement without requiring multiple contracts between participants. The framework is evaluated on a 4-year real-time dataset of 22 participants, demonstrating effective data privacy enforcement, accurate price determination, optimized energy allocation, and significant reduction in buyers’ bills with increased sellers’ revenues compared to existing models. The results validate the proposed model’s efficiency, scalability, and practical applicability in real-time smart grid operations.

Journal of King Saud University - Computer and Information SciencesVol. 38(2)
Southwest University of Science and Technology (CN), University of Lahore (PK)
Affordable and clean energy
Openalex Percentile: Top 5%
Blockchain Technology Applications and Security
3.25
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.