| Author: | Feng, Yi |
| Title: | Development of a scalable energy trading system using blockchain-based methods |
| Advisors: | Bu, Siqi (EEE) |
| Degree: | M.Sc. |
| Year: | 2024 |
| Department: | Department of Electrical and Electronic Engineering |
| Pages: | 70 pages : color illustrations |
| Language: | English |
| Abstract: | Blockchain technology has attracted widespread attention in academic research and industrial applications due to its decentralised architecture and data immutability. In particular, the introduction of blockchain technology into an integrated energy system can solve the trust problem caused by a multitude of distributed users joining the system. Blockchain is a shared, decentralized database which can increase trust between energy companies and reduce human intervention and information asymmetry. However, blockchain is poorly scalable due to its low transaction performance and high storage overhead. To tackle this shortcoming, we design a new transaction method to improve its scalability by categorising users. Specifically, chains with low-level users use fast, power-saving, less secure consensus mechanisms; high-level users use more secure consensus mechanisms. Through cross-chain technology, users of different levels can conduct cross-chain transactions or transactions within their respective classifications. To assess the efficacy of the suggested approach, experiments are conducted on Hyperledger Fabric. Transaction throughput per second (TPS) and average transaction delay are the two primary performance indicators that we specifically looked at in this study. The studies' outcomes demonstrate that the approach we propose could significantly boost throughput while lowering delay. In order to guarantee the precision and dependability of the test results, the average of 10 independent tests was used for each experiment. In terms of the experimental setup, we specify that one block is generated for every 10 transactions. The block generation interval is 2s. At a cross-chain ratio of 20% to 50%, the energy trading system's throughput is found to be lower compared to a traditional system utilizing the solo consensus method. Nevertheless, it demonstrates a higher throughput when contrasted with a conventional system that incorporates the raft consensus algorithm. This is not attributed to any deficiency in the performance of the system under design; rather, it is a consequence of the inherent characteristics of the solo consensus algorithm. As a single-node consensus mechanism, it demonstrates high throughput in testing environments, yet it is not adept for application in production environments. After the cross-chain ratio exceeds 50%, the performance of our system decreases, and the throughput is lower than that of the single-consensus algorithm system. In terms of latency, the latency of our designed transaction system is much lower than the traditional system when processing 1000 transactions. It shows that it can complete transaction confirmation faster when processing the same number of transactions. When the ratio of cross-chain transactions exceeds 50%, the latency of the designed system remains lower than that of the conventional system employing the Raft consensus algorithm, even if the number of transactions reaches 2000. However, after exceeding 50%, the latency advantage is no longer obvious. This may be explained by the fact that the increase in cross-chain transactions results in more data and complex transaction logic to be processed by the system, thus increasing the latency. Overall, this transaction method has the benefit of being able to offer customized services to various user groups. By optimising the use of the consensus mechanism, it effectively reduces the overall computational power consumption and enhances the scalability of the system. It achieves high efficiency and cost-effectiveness in energy trading. |
| Rights: | All rights reserved |
| Access: | restricted access |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 8488.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 2.07 MB | Adobe PDF | View/Open |
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