Optimasi Alokasi Distribusi Daya PLTS pada Tiga Ruang Kelas Departemen Teknik Elektro Otomasi ITS Menggunakan Metode Linear Programming

Rohmawati, Firdiana (2026) Optimasi Alokasi Distribusi Daya PLTS pada Tiga Ruang Kelas Departemen Teknik Elektro Otomasi ITS Menggunakan Metode Linear Programming. Other thesis, Institut Teknologi Sepuluh Nopember.

Text 2040221070-Undergraduate_Thesis.pdf - Accepted Version Restricted to Repository staff only Download (5MB) | Request a copy

Abstract

Sistem Pembangkit Listrik Tenaga Surya (PLTS) on-grid di Departemen Teknik Elektro Otomasi (DTEO) Institut Teknologi Sepuluh Nopember (ITS) dimanfaatkan sebagai sumber energi pendukung untuk mengurangi penggunaan listrik dari jaringan PLN. Namun, keluaran daya PLTS dipengaruhi oleh kondisi cuaca dan intensitas radiasi matahari sehingga besarnya daya yang dihasilkan berfluktuasi sepanjang waktu. Fluktuasi tersebut mengakibatkan daya PLTS yang tersedia tidak selalu mampu memenuhi kebutuhan seluruh beban secara bersamaan, sehingga diperlukan strategi optimasi untuk menentukan alokasi distribusi daya yang paling optimal sesuai dengan kapasitas daya yang tersedia. Proyek ini bertujuan memperoleh kombinasi distribusi daya PLTS yang optimal pada sembilan jalur beban yang terdiri atas pendingin ruangan (AC), lampu, dan stopkontak di ruang kelas BB102, BB202, dan BB303 menggunakan metode Linear Programming (LP) serta membandingkan hasilnya dengan Particle Swarm Optimization (PSO). Proyek menggunakan data produksi daya PLTS dan konsumsi daya beban berbasis Internet of Things (IoT) selama periode 1–20 Mei 2026 dengan resolusi satu menit. Optimasi dilakukan pada kondisi kapasitas PLTS aktual dan skenario peningkatan kapasitas PLTS sebesar tiga kali lipat. Hasil proyek menunjukkan bahwa pada kondisi kapasitas aktual, distribusi daya PLTS didominasi oleh beban lampu dan stopkontak, sedangkan beban AC hanya memperoleh alokasi terbatas karena kebutuhan dayanya melebihi daya PLTS yang tersedia. Pada kondisi cuaca cerah tanggal 7 Mei 2026 pukul 12.00, saat daya PLTS tersedia sebesar 1.393,9 W, metode Linear Programming mampu mengalokasikan 1.366,9 W atau 98,06% dari daya yang tersedia, sedangkan Particle Swarm Optimization mengalokasikan daya yang sama. Pada skenario peningkatan kapasitas PLTS sebesar tiga kali lipat, daya PLTS yang tersedia meningkat menjadi 4.181,7 W. Metode Linear Programming berhasil mengalokasikan 4.168,8 W atau 99,69% dari daya yang tersedia, sedangkan Particle Swarm Optimization mengalokasikan 4.163,6 W atau 99,57%. Secara keseluruhan, metode Linear Programming menghasilkan tingkat pemanfaatan daya PLTS sebesar 61,76% pada kondisi aktual dan 71,12% pada skenario peningkatan kapasitas PLTS, sedikit lebih tinggi dibandingkan metode Particle Swarm Optimization.
=====================================================================================================================================
The on-grid solar power generation system (PLTS) at the Department of Electrical and Automation Engineering (DTEO) of the Sepuluh Nopember Institute of Technology (ITS) is used as a supplementary energy source to reduce electricity consumption from the PLN grid. However, the system’s power output is influenced by weather conditions and solar radiation intensity, causing the amount of power generated to fluctuate over time. These fluctuations mean that the available power from the PLTS is not always sufficient to meet the needs of all loads simultaneously, necessitating an optimization strategy to determine the most optimal power distribution allocation based on available capacity. This project aims to determine the optimal power distribution combination for the solar power plant across nine load circuits comprising air conditioners (ACs), lights, and electrical outlets in classrooms BB102, BB202, and BB303 using the Linear Programming (LP) method, and to compare the results with those from Particle Swarm Optimization (PSO). The project uses Internet of Things (IoT) based data on solar power plant generation and load consumption during the period of May 1–20, 2026, with a one-minute resolution. Optimization was performed under conditions of actual solar power plant capacity and a scenario where the solar power plant capacity was tripled. The project results show that under actual capacity conditions, the power distribution from the solar power plant is dominated by lighting and outlet loads, while air conditioning loads receive only a limited allocation because their power requirements exceed the available power from the solar power plant. Under sunny conditions on May 7, 2026, at 12:00 PM, when the available PV system power was 1,393.9 W, the Linear Programming method was able to allocate 1,366.9 W, or 98.06% of the available power, while Particle Swarm Optimization allocated the same amount of power. In a scenario where the solar power plant capacity is tripled, the available solar power plant capacity increases to 4,181.7 W. The Linear Programming method successfully allocated 4,168.8 W, or 99.69% of the available capacity, while Particle Swarm Optimization allocated 4,163.6 W, or 99.57%. Overall, the Linear Programming method achieved a solar power plant power utilization rate of 61.76% under actual conditions and 71.12% in the scenario where the solar power plant’s capacity was increased, which is slightly higher than that of the Particle Swarm Optimization method.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Pembangkit Listrik Tenaga Surya, Linear Programming, Particle Swarm Optimization, optimasi, distribusi daya PLTS, Solar Power Plant, Linear Programming, Particle Swarm Optimization, optimization, PLTS power distribution
Subjects:	T Technology > T Technology (General) > T57.74 Linear programming T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK1007 Electric power systems control T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK3030 Electric power distribution systems
Divisions:	Faculty of Vocational > 36304-Automation Electronic Engineering
Depositing User:	Firdiana Rohmawati
Date Deposited:	04 Aug 2026 04:52
Last Modified:	04 Aug 2026 04:52
URI:	http://repository.its.ac.id/id/eprint/142317

Actions (login required)

View Item