Techno-Economic Optimisation of a Hybrid PV-Wind-Battery Energy System for Adaptive Melon Greenhouse Using Priority-Based Load Management and HOMER Pro

Irfan Amri Balia Malqan; Kresna Bayu Setiyoadi; Haura Zeeba Karima; Muhammad Alwan Thirafi Daniswara; Singgih Dwi Prasetyo

doi:10.37934/progee.32.4.112

Authors

Irfan Amri Balia Malqan Power Plant Engineering Technology, Faculty of Vocational Studies, State University of Malang, 65145 Malang, Indonesia
Kresna Bayu Setiyoadi Power Plant Engineering Technology, Faculty of Vocational Studies, State University of Malang, 65145 Malang, Indonesia
Haura Zeeba Karima Power Plant Engineering Technology, Faculty of Vocational Studies, State University of Malang, 65145 Malang, Indonesia
Muhammad Alwan Thirafi Daniswara Power Plant Engineering Technology, Faculty of Vocational Studies, State University of Malang, 65145 Malang, Indonesia
Singgih Dwi Prasetyo Power Plant Engineering Technology, Faculty of Vocational Studies, State University of Malang, 65145 Malang, Indonesia https://orcid.org/0000-0001-5391-5819

DOI:

https://doi.org/10.37934/progee.32.4.112

Keywords:

Hybrid Renewable Energy System, Greenhouse Automation, Priority-based Load Management, Load Shedding, Component Sizing

Abstract

Greenhouse automation requires reliable power; a load profile mismatched to available renewables inflates generation, storage and capital costs. This study assessed how priority-based load management affects demand, component sizing and initial cost of a hybrid renewable energy system for a 200 m² melon greenhouse in Trenggalek, East Java. HOMER Pro simulations, using Indonesian prices, compared three scenarios: PV-battery and PV-wind-battery at full load, and PV-wind-battery with priority-based load shedding. Loads were classed critical (pumps, sensors), semi-critical (fans) or flexible (night lighting). Load shedding cut daily consumption from 5.00 to 3.24 kWh (35.2%) and peak load from 1.06 to 0.76 kW (28.3%). Scenario three required 2.00 kW PV, three LiFePO₄ batteries (3 kWh total), a 1.00 kW wind turbine and 1.00 kW converter, costing about $1,079.85. Relative to scenario one, PV and converter capacities halved and battery units fell 57.1%. Load prioritisation can therefore reduce demand, component size and capital cost.