Ocean wave energy remains pre-commercial after four decades, with under 3 MW deployed against some 80 GW of offshore wind. Cost and efficiency explanations are incomplete: structural and station-keeping failure recur in documented WEC terminations. This review examines WEC structural integrity over 2016–2026 and asks what the sector can learn from offshore wind. The methodology is two-part. Part A is a PRISMA 2020 systematic review of the WEC literature (Scopus, Web of Science, IEEE Xplore) plus grey literature; Part B is a purposive review of five pre-defined offshore wind practice areas. Together these draw on 150 references (117 in-window 2016–2026; 33 foundational). Addressing RQ1, WEC failures parallel early offshore wind in three respects: subsystem failure dominates primary-structure failure; the gap between codified and observed design loads persists; and condition monitoring is now the operational response to residual risk. They diverge in two critical ways: offshore wind can feather its rotor into a low-load survival state, whereas WECs must use active, high-energy survival configurations with their own failure modes; and offshore wind has the fleet scale that underpins reliability benchmarking. Addressing RQ2, transferability against four criteria (physical analogy, data availability, regulatory maturity, economic feasibility) shows that reliability benchmarking, standards content, and SCADA-based monitoring transfer only partially, while vibration monitoring and coupled analysis transfer fully. Digital-twin methodology transfers asymmetrically: physics-based models suit single-prototype validation, whereas data-driven monitoring is constrained by the absence of a WEC fleet. We argue for a compressed rather than replicated trajectory and identify four priority research directions.

Battery-electric passenger boat studies usually treat range, charging and capital cost as binding constraints, assume near-zero-carbon grids, and ignore the speed passengers already receive. We developed a bi-objective mixed-integer linear program that jointly sizes the vessel fleet, charging infrastructure, pier photovoltaics, battery storage and discrete service speed for seven scheduled routes across four Thai island clusters, minimising discounted cost and maximising emission reduction against a scope-matched diesel baseline. Electrified journey time may not exceed the fastest incumbent's beyond a scanned tolerance. Inputs combine published pier coordinates, operator timetables, the national vessel registry, Marine Department passenger statistics and Coriolis fuel-meter measurements on twelve vessels; carbon credit potential is computed ex ante but not optimised. Journey time, not battery range, determines feasibility: it excludes every displacement hull, and two of seven services cannot be served by any commercially available vessel. Eligible electric vessels carry 10–30 passengers against incumbents of 8–350, so optimal fleets reach 24–968 vessels and USD 35.2–693.9 million of investment. Sixteen of twenty configurations cut emissions by up to 41.0% of the baseline; the other four increase them by up to 5.5% under a grid emission factor of 0.4857 kg CO2 kWh−1. No configuration is economically viable: break-even carbon prices of USD 8,296–16,070 per tCO2e lie close to three orders of magnitude above traded prices. Only pier photovoltaics with storage is marginally viable (net present value USD 0.22 million), supplying 45%–50% of charging energy. Electrifying non-speed-competitive services is justified now; speed-competitive services await larger high-speed electric vessels.

This paper presents a model-free Best Efficiency Point (BEP) tracking method for centrifugal pumps without head measurement or manufacturer-provided characteristic curves. The proposed approach combines a discrete finite-difference extremum-seeking control (ESC) scheme with an efficiency approximation proxy derived from measurable variables—namely, flow rate and electrical power. Under constant head conditions, the proxy function is analytically shown to be proportional to the true pump efficiency, enabling real-time BEP localization using only motor feedback signals. The ESC algorithm employs a sign-based gradient rule with adaptive step-size reduction to achieve rapid and stable convergence without mathematical models. A Python-based simulation using a Schneider SUB 15-0.5cv pump demonstrates that the method can track the BEP with negligible steady-state error (less than 0.1% efficiency deviation). The proposed framework offers a cost-effective solution for efficient optimization for mobile pumping applications in large water resources where installing head sensors is impractical.