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<p>Roadway infrastructure is a persistent energy consumer for lighting, signage, and intelligent transport systems, creating an opportunity to recover a fraction of vehicle-induced mechanical energy through piezoelectric energy harvesting (PEH). Most prior studies emphasize device-level performance, while project sponsors require a transparent, end-to-end assessment of practical viability. This paper develops a reproducible, data-driven decision framework that integrates (i) Weigh-In-Motion (WIM)–based yield modelling, (ii) life-cycle techno-economic evaluation using a fully parameterized levelized cost of energy (LCOE), (iii) quantified risk assessment, and (iv) a consistency-checked Analytic Hierarchy Process (AHP) synthesis. The framework is demonstrated on an illustrative high-traffic freeway-lane scenario parameterized using published California WIM spectra. Results indicate that, under the baseline scenario, PEH could supply approximately 78.6% of the example lighting demand for the segment. Using the accompanying year-by-year cashflow/energy trace, the deterministic LCOE is 4.10 USD/kWh. When uncertainty in CAPEX, routine O&amp;M, replacement costs, energy yield, and discount rate is propagated via Monte Carlo simulation (<i>N</i> = 5000), the mean LCOE is 4.28 USD/kWh with a 90% interval of 3.08–5.71 USD/kWh. Sensitivity analyses show that CAPEX and traffic volume are the dominant levers; a ± 20% CAPEX change shifts LCOE by approximately ± 16%, while a ± 20% traffic change shifts LCOE by about − 16.7%/25.0%. Risk screening identifies high capital cost and uncertain long-term pavement integrity as critical threats. Overall, PEH is presently best suited to niche, high-density corridors, and broader deployment will depend on cost reductions and durability improvements.</p>

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A data-driven framework for the feasibility of piezoelectric energy harvesting: powering sustainable smart city infrastructure

  • 期刊论文

  • 发表日期：

    2026年3月17日

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  • Saleem Ahmed Al-Azazi

摘要

Roadway infrastructure is a persistent energy consumer for lighting, signage, and intelligent transport systems, creating an opportunity to recover a fraction of vehicle-induced mechanical energy through piezoelectric energy harvesting (PEH). Most prior studies emphasize device-level performance, while project sponsors require a transparent, end-to-end assessment of practical viability. This paper develops a reproducible, data-driven decision framework that integrates (i) Weigh-In-Motion (WIM)–based yield modelling, (ii) life-cycle techno-economic evaluation using a fully parameterized levelized cost of energy (LCOE), (iii) quantified risk assessment, and (iv) a consistency-checked Analytic Hierarchy Process (AHP) synthesis. The framework is demonstrated on an illustrative high-traffic freeway-lane scenario parameterized using published California WIM spectra. Results indicate that, under the baseline scenario, PEH could supply approximately 78.6% of the example lighting demand for the segment. Using the accompanying year-by-year cashflow/energy trace, the deterministic LCOE is 4.10 USD/kWh. When uncertainty in CAPEX, routine O&M, replacement costs, energy yield, and discount rate is propagated via Monte Carlo simulation (N = 5000), the mean LCOE is 4.28 USD/kWh with a 90% interval of 3.08–5.71 USD/kWh. Sensitivity analyses show that CAPEX and traffic volume are the dominant levers; a ± 20% CAPEX change shifts LCOE by approximately ± 16%, while a ± 20% traffic change shifts LCOE by about − 16.7%/25.0%. Risk screening identifies high capital cost and uncertain long-term pavement integrity as critical threats. Overall, PEH is presently best suited to niche, high-density corridors, and broader deployment will depend on cost reductions and durability improvements.