Optimal Maintenance Policy for Offshore Wind Systems
| Autor: | Tai-Sheng Su, Shih-Wei Lin, Vincent F. Yu, Thi Huynh Anh Le |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Technology
Control and Optimization Renewable Energy Sustainability and the Environment Computer science Optimal maintenance Energy Engineering and Power Technology Failure rate Fuzzy logic Reliability engineering Offshore wind power Electricity generation Order (exchange) offshore wind system Electricity market Electrical and Electronic Engineering Engineering (miscellaneous) fuzzy multi-objective programming Reliability (statistics) failure rate Energy (miscellaneous) maintenance threshold optimal maintenance policy |
| Zdroj: | Energies, Vol 14, Iss 6082, p 6082 (2021) Energies Volume 14 Issue 19 |
| ISSN: | 1996-1073 |
| Popis: | Employing maintenance threshold plays a critical step in determining an optimal maintenance policy for an offshore wind system to reduce maintenance costs while increasing system reliability. Considering the limited works on this topic, we propose a two-stage procedure to determine the optimal maintenance thresholds for multiple components of an offshore wind power system in order to minimize maintenance costs while achieving the highest possible system reliability. First, using genetic algorithms, a dynamic strategy is developed to determine the maintenance thresholds of individual components where the cost of maintenance and the rate of failure are critical. Then, fuzzy multi-objective programming is applied to find the system’s optimal maintenance threshold considering all components. A variety of factors including weather conditions, system reliability, power generation losses, and electricity market price are carefully considered to enhance the system’s reliability and reduce the costs of maintenance. When maintenance threshold results are compared, component-wise versus system-wise, an average system savings of 1.19% for maintenance cost is obtained while the system reliability is increased by 1.62% on average. |
| Databáze: | OpenAIRE |
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