Manage Risks in Industrial Rooftop Solar Power Projects: Monte Carlo Simulation Based Approach

DOI

10.2991/978-94-6239-622-7_16How to use a DOI?

Keywords

Rooftop solar power; Financial risk; Monte Carlo simulation; Net Present Value (NPV); Internal Rate of Return (IRR)

Abstract

This research applies a Monte Carlo simulation approach to analyze financial risks in an industrial rooftop solar power project, aligning with global energy transition goals and the net-zero commitment by 2050. Evaluating risk exposure is crucial for industrial enterprises adopting onsite renewable energy. Focusing on the rooftop solar project at FIT Voltaira, the study uses Crystal Ball software to simulate scenarios by assigning probability distributions to key input variables: solar energy yield, electricity price, and initial investment cost. The results show an 87.56% probability of achieving a positive Net Present Value (NPV) and an Internal Rate of Return (IRR) above the minimum acceptable rate, illustrating both potential opportunities and downside risks. Sensitivity analysis indicates that investment cost, solar yield, and electricity price are the most influential drivers of financial uncertainty. The study offers practical insights for investors—such as securing fixed-price EPC contracts and optimizing system design—while also providing a probabilistic evidence base for emerging rooftop solar policies, including the integration of carbon credits.

Research purpose: This research evaluates the financial efficiency and risk management of industrial rooftop solar power projects in Vietnam, aligning with net-zero goals. Monte Carlo simulation is used to assess financial viability, providing appropriate investment policy recommendations in a high-risk environment.

Research motivation: Global energy transition and Vietnam’s net-zero pledge drive urgent demand for industrial rooftop solar, reducing costs and fostering sustainable development. Fluctuations in key financial factors create significant risks. This study addresses a gap in analyzing these projects amidst new Net Zero 2050 challenges.

Research design, approach, and method: This study employs a Monte Carlo simulation approach using Crystal Ball software to analyze a rooftop solar project at FIT Voltaira Vietnam factory. Key uncertain input variables—solar energy yield, EVN’s electricity price, and initial investment costs—were assigned probability distributions. The model was run 10,000 times to evaluate financial indicators.

Main findings: Baseline analysis showed high feasibility (NPV>0, IRR 16% > 13% MARR, 8-year payback). Monte Carlo simulation confirmed high profitability potential, with an 87.56% probability of positive NPV and IRR exceeding MARR. Sensitivity analysis highlighted investment cost, solar yield, and electricity price as the most significant risk factors.

Practical/managerial implications: Investors should prioritize controlling initial investment costs (e.g., fixed-price EPC contracts), maximizing solar yield (optimal design, monitoring), and aligning to electricity prices. This research also provides a scientific basis for Vietnam’s evolving rooftop solar legal framework, emphasizing detailed financial analyses and new carbon credit incentives.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Nguyen Linh Dan
AU  - Do Mai Linh
AU  - Vu Tien Dung
PY  - 2026
DA  - 2026/04/21
TI  - Manage Risks in Industrial Rooftop Solar Power Projects: Monte Carlo Simulation Based Approach
BT  - Proceedings of the International Conference on Emerging Challenges: Business Dynamics in Disruptive Economy (ICECH 2025)
PB  - Atlantis Press
SP  - 248
EP  - 257
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6239-622-7_16
DO  - 10.2991/978-94-6239-622-7_16
ID  - Dan2026
ER  -