This Nonthaburi residential-building case study compared two 60-kW DC chargers, one 60-kW DC plus two 22-kW AC chargers, and four 22-kW AC chargers. Assumptions included a seven-year project, 5.5% discount rate, mean selling price of THB7.25/kWh, service time of 4, 6, or 8 hours per day, and electricity costs of THB4.50, 4.73, or 4.95/kWh, giving 27 scenarios. All three portfolios were financially feasible under the specified conditions. Two DC chargers gave the strongest return at eight hours per day and THB4.50/kWh, while four AC chargers better fit long parking durations and lower capital and maintenance costs.
Key findings
- All three configurations were financially feasible across the 27 specified conditions, but results were strongly driven by daily utilization and the selling-price–electricity-cost margin.
- Two 60-kW DC chargers at eight service hours per day and THB4.50/kWh electricity cost yielded NPV THB3,258,975.10, IRR 45.52%, and a 2.04-year payback, the strongest modeled case.
- Four 22-kW AC chargers offered an option for buildings with long parking durations because of lower initial capital and maintenance costs, although they did not maximize return in the high-use case.
Why this matters globally
The comparison helps building managers, investors, and policymakers distinguish high-throughput DC charging from lower-cost AC charging suited to long dwell times, while showing that utilization and electricity margins dominate returns. The framework can inform pre-investment models elsewhere only after localizing tariffs, pricing, condominium rules, demand, and grid constraints. It does not demonstrate carbon reductions or grid effects, and its return estimates are not universal benchmarks.
Thai researcher contribution
Chatchaphon Ketviriyakit of Uttaradit Rajabhat University, Pasura Aungkulanon of King Mongkut's University of Technology North Bangkok, and Lakkana Ruekkasaem of Thammasat University developed a model around Thai tariffs and residential parking patterns. The work combines industrial technology, logistics, and applied quantitative expertise for a Nonthaburi EV-infrastructure decision and reports parameters in Thai baht that local managers can adapt.
Limitations to consider
All results come from one case building and deterministic assumptions rather than long-run operations. Service hours proxy actual demand and do not capture arrivals, queues, seasonality, outages, or price volatility. The abstract does not report detailed power-flow validation, demand charges, transformer upgrades, financing risk, tax, inflation, or ancillary revenue. A seven-year horizon and fixed selling price materially condition the result, and financial feasibility does not establish condominium-governance, safety, or electrical-capacity readiness.