Performance of Smart Grid Based on Data Aggregation Using Wireless Communication Network Technology
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Summary
This paper addresses the inefficiencies of traditional power grids, which struggle with rising consumer demand, poor transmission management, and a lack of centralized communication. The authors propose a smart grid (SG) framework that integrates wireless sensor networks (WSN) and data aggregation to improve reliability, reduce energy wastage, and ensure nominal supply voltage. The research aims to investigate quality of service (QoS) in low-power environments, propose a low-cost network topology, and develop data prediction algorithms to minimize transmission latency and redundancy. The study utilizes MATLAB/SIMULINK to model and simulate a smart grid incorporating both wind and solar energy sources. The proposed architecture includes Smart Meters (SM), Town Servers (TS), and a Main Server (MS). The TS acts as a central decision-maker for local users, communicating with the MS via PSTN to manage data and power distribution. The model defines mathematical equations for wind turbine power output based on wind speed and efficiency coefficients, as well as photovoltaic current based on cell temperature and irradiance. The system is designed to handle bidirectional electricity and information transfer, allowing for dynamic load management between renewable sources and the general electricity grid (GEN). Simulation results demonstrate the system's performance across residential and industrial loads. For residential users, the smart grid successfully manages power fluctuations by switching between wind energy and the GEN based on demand peaks; for instance, a home powered by a 4KW wind turbine relies on the GEN only during high-demand periods exceeding local generation. Industrial simulations show similar adaptability: a factory with a 5MW wind turbine uses GEN support during startup peaks (7MW) but operates independently when demand drops to 5MW. Similarly, a solar-powered industrial facility switches between GEN and solar energy depending on time-of-day availability and load requirements, ensuring continuous supply without overloading the main grid. The significance of this work lies in its demonstration of a robust, low-complexity communication and power management system that enhances smart grid efficiency. By integrating WSN for data collection and utilizing TS/MS hierarchies for centralized control, the proposed model reduces bandwidth usage and mitigates network misuse risks. The authors conclude that this approach offers a more organized supply delivery method compared to existing solutions, though they note that future work must incorporate cost-benefit analyses and advanced transmission systems like satellite communications to further optimize energy delivery costs.
Provenance
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | Crossref | — | — | 1 | 2026-06-19 |
| archive | success | canonical_url | — | — | 1 | 2026-06-26 |
| extract | success | cached | — | — | 2 | 2026-06-26 |
| clean | success | clean | — | — | 1 | 2026-06-19 |
| chunk | success | chunk | — | — | 1 | 2026-06-19 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-06-19 |
| promote | success | — | — | — | 1 | 2026-06-19 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 1 | 2026-06-26 |
| tag | success | vector_similarity | — | — | 6 | 2026-06-19 |
| verify | success | — | — | — | 1 | 2026-06-26 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-26; verification: verified.
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