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Enhancing Campus Energy Efficiency Through Rank-based Evolutionary Particle Swarm Optimization (REPSO) for Energy Management Under the Enhanced Time of Use (EToU) Tariff Structure
One-line summary
A solar energy research paper on Enhancing Campus Energy Efficiency Through Rank-based Evolutionary Particle Swarm Optimization (REPSO) for Energy Management Under the Enhanced Time of Use (EToU) Tariff Structure.
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Chinese explanation / 中文解读
中文解读待补充：本站会优先为光伏效率、钙钛矿太阳能电池、储能技术、太阳能热利用、BIPV、并网技术等高价值论文补充中文说明。
Original abstract
Malaysia's economic growth has led to a substantial increase in electricity demand, especially during peak periods. This rising demand puts significant pressure on the national grid, making effective load management during these peak hours critical. Poor handling of peak loads not only threatens grid reliability but also drives up energy costs and contributes to greater environmental impact. In response, Demand Side Management (DSM) strategies are being adopted to reshape energy usage patterns and enhance energy efficiency. This study explores advanced optimization techniques for energy management in the commercial sector, focusing on two solar photovoltaic (PV) campuses of Universiti Teknologi MARA (UiTM) located at Alor Gajah, Melaka, and Permatang Pauh, Pulau Pinang. The objective is to minimise electricity costs and improve demand distribution using intelligent optimization under two commercial tariff schemes, which are the Medium Voltage General Commercial Tariff (C1) and the Enhanced Time of Use (EToU) tariff. Three algorithms are evaluated, namely the traditional Particle Swarm Optimization (PSO), the Evolutionary PSO (EPSO), and the Rank-based EPSO (REPSO). Results show that REPSO, with 40% load shifting under the EToU tariff, achieved the highest cost savings of 12.04% and 4.89% at Alor Gajah, and 14.42% and 6.77% at Permatang Pauh during weekdays and weekends, respectively. Meanwhile, under the C1 tariff, savings were lower. A 5% energy saving was achieved across all scenarios. These findings demonstrate that REPSO-EToU is the most effective strategy for improving cost efficiency and load distribution in solar-powered commercial buildings under dynamic pricing schemes.
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