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市場調查報告書

獲得與最大化風力發電廠數據

Capturing and Maximizing Wind Power Plant Data

出版商 Navigant Research 商品編碼 619844
出版日期 內容資訊 英文 15 Pages; 6 Tables, Charts & Figures
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獲得與最大化風力發電廠數據 Capturing and Maximizing Wind Power Plant Data
出版日期: 2018年03月28日 內容資訊: 英文 15 Pages; 6 Tables, Charts & Figures
簡介

本報告針對風力發電性能改善與O&M (維持管理) 成本管理、最小化目的、風力發電產業數據收集分析。

使用O&M最佳化風力發電廠性能數據

  • 供應商概要展示O&M種類、方法的多樣性
  • Navigant GKS Wind Benchmarking Data為出發點
  • 同儕團體特徵是反應小型方案、但為主要製造商
  • 風力發電廠O&M最佳化最重要的9項重點
  • SCADA系統是風力渦輪發動機的神經
  • 收集GADS數據的義務
  • 工程報告數據收集:主要研究
  • 收集石油、潤滑脂分析數據自動化
  • 振動監視數據收集:動力傳動分析、其他

風力發電廠擁有者的貴重數據

  • 風力發電廠數據收集、分析4項調查領域摘要
  • APR與其他統計方法不可缺少
  • 供應商從ERP系統獲得極大的利益
  • 平台為了渦輪發動機、網站表現最適化而被使用
  • 數據平台在渦輪發動機生命循環可信度、可用性派上用場

存在數據技術生態系統相關人士大型市場

  • 風力發電廠相關人士數據分析投資
目錄
Product Code: SI-DCS-18

Wind plant owners are facing increasing pressure to manage and reduce operations and maintenance (O&M) costs, optimize the performance of their wind projects, and foresee impending component failures. At the same time, an increasingly sophisticated data technology ecosystem of sensors, condition monitoring systems (CMSs), turbine optimization platforms, and predictive analytics (PA) software is being adopted industrywide. Collecting the data required and making useful sense of it, however, is a formidable challenge given the sheer volume of data that can be captured from today's highly instrumented multi-megawatt wind turbines.

What Navigant Research's findings suggest is that not all wind plant owners have maximized the use of data analytics systems. This conclusion skews toward smaller and midsize wind plant owners or owners of any size operating older wind turbines. The O&M budgets of operational wind plants are thin; many have limited funds to purchase aftermarket retrofit CMS and turbine optimization platforms. Yet, many also see cost savings and risk management upside with the variety of offerings on the market today. Thus, there is considerable room for further deployment of data collection and analysis systems across the market.

This Navigant Research report focuses on data collection within the wind power industry as asset owners seek to improve wind plant performance and manage and minimize O&M costs. The study analyzes the data collection strategies of anonymized wind plant owners surveyed as part of Navigant's Generation Knowledge Service (GKS) Wind Benchmarking service. It also examines how and when CMS and PA platforms are being deployed in the marketplace for new and operational turbines. Recommendations are provided on how wind turbine OEMs other stakeholders should explore the growing addressable market for data collection and analysis platforms.

Key Questions Addressed:

  • What are the primary data points captured and analyzed on wind turbines and wind plants?
  • What areas of data collection and analysis are more important than others?
  • What proportion of surveyed wind plant owners are using advanced pattern recognition (APR) systems?
  • How many surveyed wind plant owners are using platforms to address turbine and site performance optimization?
  • How many surveyed wind plant owners are using a platform to address turbine lifecycle reliability and availability?
  • What proportion of surveyed wind plant owners are using enterprise resource planning (ERP) systems?
  • What are some of the value proposition differences between solutions offered by wind turbine manufacturers and independent vendors?

Who needs this report?

  • Wind turbine manufacturers
  • Wind power plant owners
  • Data analytics vendors
  • Condition monitoring equipment manufacturers
  • Wind turbine component suppliers
  • Government agencies, policymakers, and researchers
  • Investor community

Table of Contents

Spark

Context

Recommendations

Mining Wind Plant Performance Data to Optimize O&M

  • Vendor Overview Shows Diversity in Type and Approach to O&M
  • Navigant GKS Wind Benchmarking Data Is a Starting Point
  • Peer Group Characteristics Reflect Smaller Projects, but Major Manufacturers
  • The Nine Most Important Data Points for Wind Plant O&M Optimization
  • SCADA Systems Are the Nervous System of the Wind Turbine
  • GADS Data Collection Became Mandatory in 2018
  • Engineering Reports Data Collection: Key Studies
  • Room for Automation in Oil and Grease Analysis Data Collection
  • Vibration Monitoring Data Collection: Critical Drivetrain Analysis
  • Met Tower Data Collection: Searching for Instrument Misalignment
  • Substation Data Collection: Central Vulnerability Point
  • Work Orders Collection: Cataloguing for Cost Savings
  • Blade Inspection Data Collection: Proven Techniques versus Drones

Some Wind Plant Owners Are Leaving Valuable Data on the Table

  • Summary of Four Surveyed Areas of Wind Plant Data Collection and Analysis
  • Using APR or Other Statistical Modeling Methods Is Vital
  • A Notable Percentage of Vendors Benefit from ERP Systems
  • Platforms Can be Used to Address Turbine and Site Performance Optimization
  • Data Platforms Can Help to Address Turbine Lifecycle Reliability and Availability

Large Addressable Market Exists for All Parties in This Data Technology Ecosystem

  • Wind Plant Stakeholders Should Invest in Data Analytics

List of Tables and Figures

  • Common Wind Turbine Components and Subcomponents Monitored
  • Select Data Collection Segments and Collection Procedures
  • Use of APR or Other Statistical Modeling Methods
  • Use of an ERP System
  • Use of Platforms to Address Turbine and Site Performance Optimization
  • Use of a Platform to Address Turbine Lifecycle Reliability and Availability
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