Work

Multi-Objective Optimization of Rooftop Photovoltaic Installation for School Buildings

Year: 2026

Type: conference-paper

Abstract: Rooftop photovoltaic systems are an effective solution for improving energy sustainability in school buildings with high daytime electricity demand. However, optimal system sizing is constrained by trade-offs between self-sufficiency, self-consumption, and life cycle cost, especially under limited grid-export conditions. This paper proposes a multi-objective optimization framework for rooftop PV design that simultaneously considers SS, SC, and LCC. The framework integrates parametric modeling in Rhino-Grasshopper, hourly building energy simulation using Energy Plus, and the NSGA-II evolutionary algorithm to identify Pareto-optimal solutions. A secondary school building in Ho Chi Minh City, Vietnam, is used as a case study. Hourly PV generation and electricity demand profiles are obtained from dynamic simulations and used as inputs to the optimization process. The results demonstrate that moderate PV capacities provide the most robust performance, while extreme system downsizing or oversizing leads to inferior economic and operational outcomes.

Source: International Conference on Green Energy and Applications (ICGEA)

DOI: 10.1109/icgea69553.2026.11642811

Authors: Hoang-Anh Dang, Van Manh Nguyen, Dung Dao-Van, Hoang Minh Nguyen, Trung Kien Nguyen

Institutions: Trường Đại học Khoa học và Công nghệ Hà Nội, Hanoi University of Science and Technology, Concordia University, Concordia University

Language: English

Topic: Photovoltaic System Optimization Techniques

Subfield: Renewable Energy, Sustainability and the Environment

Field: Energy

Domain: Physical Sciences

SDGs: Affordable and clean energy, Climate action, Sustainable cities and communities, Industry, innovation and infrastructure

Open Access status: hybrid

OpenAlex ID: W7203672789

FWCI:

Cites: 9

Cited by:

Related to: 10