配電自動化市場(2012-2016年):技術及數位電網的策略 是由出版商Greentech Media Inc.在2012年01月所出版的。
這份英文市場調查報告書價格從美金2995起跳。
本報告提供配電自動化(DA)市場上機會，經濟及競爭情形調查，DA的技術分析及公共事業方面的商務解決方案，技術及DA投資的障礙，公共事業專用的DA策略及企劃案例，到2016年為止的DA產品的美國市場預測，競爭情形，策略性市場機會等的相關分析，為您概述為以下內容。
第1章 摘要整理
第2章 智慧配電的轉變
第3章 配電市場
- DA市場佔有率
- 加州市場
- ARRA(美國經濟措施法)為基礎財源
- DA市場分類法
- 實行的課題
第4章 技術·應用程式
- 電力品質的重要性的增加
- 可靠性
- 斷斷續續的分散發電和電動車的整合
- 智慧型資產管理
第5章 競爭分析
- 配電產業的問題
- 引進促進因素
- 公共事業供應商市場環境
- 配電自動化的前五名企業間的收購，投資及主見
- 新一代的電網穩定裝置
- 分析師的見解:配電自動化(DA)通訊
第6章 實行策略及目前企劃
第7章 供應商分析
- 供應商比較表
- 市場領導
- 有潛力的供應商
- 市場參與企業
圖表
Abstract
With utilities investing a significant amount of capital into infrastructure,
communications, and software for the distribution grid, GTM Research publishes
an in-depth analysis on the requirements, technologies and strategies that are
ushering in the new age of distribution automation (DA).
Current utility DA upgrades are just beginning to scratch the surface of what
will be required to support the proliferation of distributed renewables and
electric vehicles. New capacitor banks, voltage regulators, and load tap
changers, along with the retrofit of older units with monitoring and control
modules to allow for feeder, substation, or system-wide coordination will be
crucial for the next-gen grid. The three large California IOUs already plan to
spend more than $700 million on enabling feeder automation and VVO over the
next decade, and seventeen utilities receiving stimulus funds have spent $46
million on automated capacitor banks and automated voltage regulators. The
American Recovery and Reinvestment Act also helped 32 utilities fund $43
million in automated switch purchases from the first quarter of 2009 through
the second quarter of 2011. These investments are just the beginning, as GTM
Research forecasts the annual DA market in the U.S. to reach roughly $3
billion per year by 2015.
Figure: Selected DA Projects in the U.S. by Utility and DA Technology
Source: GTM Research
At nearly 150 pages, this report is the leading resource for understanding the
DA market's opportunity, economics and competitive landscape. The report
includes market forecasts through 2016 for automated switches, capacitor
banks, reclosers, substation transformer monitors, voltage regulators,
distribution management system (DMS) platforms, fault location, isolation, and
service restoration (FLISR) applications, and volt/VAR optimization
applications. It also examines utility-specific DA project economics. In
addition, GTM Research compares and profiles over 20 of the leading DA vendors.
VALUE-ADDED ELEMENTS
- DA technology analysis and utility-side DA business solutions.
- The technical and investment obstacles of DA implementation.
- Utility-specific DA strategies and project examples.
- U.S. market forecast for DA products to 2016 (includes automated switches,
capacitor banks, reclosers, substation transformer monitors, voltage
regulators, DMS platforms, FLISR applications, and volt/VAR optimization
applications).
- DA market taxonomy examining competitive landscape and strategic market
opportunity.
- Vendor-specific M&A, investment and partnership analysis in DA market.
About Greentech Media
Greentech Media is an integrated online media company designed to deliver the
highest-quality content in the industry, whether it is research, news or
critical networking events.
Table of Contents
1. EXECUTIVE SUMMARY
- 1.1. Executive Summary
- 1.2. Key Findings
- 1.2.1. Transitioning to a 21st Century Grid
- 1.2.2. Distribution Automation Communications
- 1.2.3. Voltage and Reactive Power Control
- 1.2.4. Improving Reliability
- 1.2.5. Distributed Generation and Electric Vehicle Integration
- 1.2.6. Intelligent Asset Management
- 1.2.7. Market Insights
2. THE TRANSITION TO SMART DISTRIBUTION
- 2.1. 20th Century Distribution
- 2.2. Factors Driving Distribution Automation and Grid Optimization
- 2.2.1. The Importance of MAIFI
3. THE DISTRIBUTION MARKET
- 3.1. DA Market Share
- 3.2. The California Market
- 3.2.1. The California Forecast
- 3.2.2. U.S. Forecast Based on California IOU Spending
- 3.3. ARRA-Based Funding
- 3.4. Product-Based Forecast
- 3.4.1. Product-Based Forecast Methodology
- 3.4.2. The Typical American Feeder
- 3.4.3. So - ware Forecast
- 3.4.4. Field Equipment Forecast
- 3.4.5. DA Product Market Forecast
- 3.5. DA Market Taxonomy
- 3.6. Barriers to Implementation
- 3.6.1. Lack of a Proven Business Case
- 3.6.2. Long-Term DA Plans
- 3.6.3. Non-Traditional Benefi ts
- 3.6.4. Lack of Interoperability
- 3.6.5. Resistance to Change
4. TECHNOLOGY AND APPLICATIONS
- 4.1. The Increasing Importance of Power Quality
- 4.1.1. Power Factor
- 4.1.2. Traditional Volt/VAR Control Systems
- 4.1.3. Volt/VAR Optimization Systems
- 4.1.4. Integrating DG and EV With VVO
- 4.2. Reliability
- 4.2.1. The Cause of Faults
- 4.2.2. Legacy Investment
- 4.2.3. The Smart Circuit
- 4.2.4. Automated Line Switching
- 4.3. Integrating Intermittent Distributed Generation and Electric Vehicles
- 4.3.1. DG Interconnection Standards
- 4.3.2. The EV Market: Waiting to Explode
- 4.4. Intelligent Asset Management
- 4.4.1. Types of Asset Management
5. COMPETITIVE ANALYSES
- 5.1. Distribution Business Problems
- 5.1.1. Improving grid effi ciency
- 5.1.2. Improving outage response time
- 5.1.3. Reducing the frequency and length of outages
- 5.1.4. Identifi able failure or malfunction of grid assets
- 5.1.5. Generation constraints
- 5.1.6. Reducing power quality events
- 5.2. Driving Adoption
- 5.3. Utility Vendor Market Environment
- 5.4. Acquisitions, Investments, and Partnerships in DA Among the Big 5
- 5.4.1. ABB
- 5.4.2. Alstom Grid
- 5.4.3. GE Energy
- 5.4.4. Schneider Electric
- 5.4.5. Siemens
- 5.5. The Next Generation of Grid Stability Devices
- 5.6. Analyst Opinion: DA Communications
6. IMPLEMENTATION STRATEGIES AND CURRENT PROJECTS
- 6.1. Smart Grid Driving California Legislation and Regulation
- 6.1.1. Southern California Edison
- 6.1.2. Pacifi c Gas and Electric
- 6.1.3. San Diego Gas and Electric
- 6.1.4. Burbank Water and Power
- 6.1.5. Duke Energy
- 6.1.6. Electric Power Board of Chattanooga
7. VENDOR ANALYSES
- 7.1. Vendor Comparison Charts
- 7.2. Market Leaders
- 7.2.1. ABB Ltd.
- 7.2.2. Cooper Power Systems
- 7.2.3. General Electric Energy
- 7.2.4. S&C Electric Company
- 7.2.5. Schneider Electric
- 7.2.6. Schweitzer Engineering Laboratories, Inc.
- 7.2.7. Siemens Energy
- 7.3. Up-and-Coming Vendors
- 7.3.1. Alstom Grid
- 7.3.2. PCS Utilidata
- 7.3.3. Power Tagging
- 7.3.4. Survalent Technology
- 7.3.5. Tollgrade Communications, Inc.
- 7.4. Other Market Players
- 7.4.1. DC Systems
- 7.4.2. Dranetz
- 7.4.3. Efacec ACS
- 7.4.4. ETAP
- 7.4.5. GridSense
- 7.4.6. G&W Electric
- 7.4.7. Hubbell Incorporated
- 7.4.8. PowerSense
- 7.4.9. Sentient Energy, Inc.
LIST OF FIGURES
- Figure 1-1: Cooperative Utilities' on using AMI Communications for DA
- Figure 1-2: Municipal Utilities' on using AMI Communications for DA
- Figure 1-3: Cooperative Utilities' EV Integration Concerns
- Figure 1-4: Smart Grid Benefi ts Survey
- Figure 1-5: DA Spending by Functional Area and Quarter
- Figure 1-6: Forecasted California Investor-Owned Utility CAPEX Spending
- Figure 2-1: Moore's Law
- Figure 2-2: The Evolution of IED Communications
- Figure 2-3: Distribution Automation Drivers
- Figure 2-4: Reliability Reporting Requirements
- Figure 2-5: RPS Standards by State
- Figure 2-6: RPS Standards With Solar Provisions
- Figure 2-7: DA Graph
- Figure 3.1: Distribution Automation Projects Map (Infographic)
- Figure 3.2: Master United States DA Forecast
- Figure 3.3: Reported California IOUs' Planned DA Spending ($ M)
- Figure 3.4: Estimated DA Spending by California IOUs, 2012-2016
- Figure 3.5: Estimated Total U.S. Distribution Automation Market Size
- Figure 3.6: California Spending-Based U.S. Market Forecast
- Figure 3.7: U.S. DA Market Forecast Based on California IOU Spending
- Figure 3.8: ARRA DA Spending by Quarter (Q1 2009-Q2 2011)
- Figure 3.9: ARRA DA Spending by Quarter
- Figure 3.10: DA Equipment and So - ware by System
- Figure 3.11: Prototypical Feeder Types
- Figure 3.12: Benefi ts of CVR at Various U.S. Feeder Penetration Levels
- Figure 3.13: So - ware Forecast
- Figure 3.14: DA So - ware Market Forecast
- Figure 3.15: Field Equipment Forecast
- Figure 3.16: United States DA Product-Based Forecast
- Figure 3.17: United States DA Product-Based Forecast by Year
- Figure 3.18: United States Product-Based DA Forecast
- Figure 3.19: DA Market Taxonomy
- Figure 3.20: DA Implementation Barriers
- Figure 4-1: ANSI C84.1 Voltage Utilization Ranges
- Figure 4-2: Voltage Disruptions and Causes
- Figure 4-3: Unity, Leading, and Lagging Voltage
- Figure 4-4: Traditional Volt/VAR Control (Info graphic Traditional
Volt/VAR Scheme)
- Figure 4-5: Various Electrical Load Types
- Figure 4-6: Substation-Based Volt/VAR Optimization
- Figure 4-7: Control Center-Based Volt/VAR Optimization (from Info graphic)
- Figure 4-8: GTM Research's U.S. PV Installation Forecast
- Figure 4-9: Cost of a Single Hour of Power Interruption
- Figure 4-10: FLISR Operation Sequence
- Figure 4-11: Incremental Upgrade Costs of Reduced Customer Minutes
Interrupted (CMI)
- Figure 4-12: Mitigation of the Eff ects of Intermittent DG at Varying
Penetration Levels
- Figure 4-13: DG Grid Stability Challenges and Solutions
- Figure 4-14: Missing Title
- Figure 4-15: Cost per kVAR Compensation by Device
- Figure 4-16: Five Steps of Smart Grid Upgrades to Support EVs)
- Figure 4-17: Challenges and Solutions for EV Integration
- Figure 4-18: Worst Case Scenarios Due to Higher EV Penetrations
- Figure 4-19: Best Case Scenarios Due to Higher EV Penetrations)
- Figure 4-20: Transformer Overloading due to Electric Vehicles
- Figure 4-21: Equipment With Highest Value for Intelligent Asset Management
- Figure 4-22: States of Asset Management
- Figure 4-23: Vendor Example of Stages of Asset Health Analysis
- Figure 4-24: The 4 Steps of Condition-Based Maintenance
- Figure 4-25: Condition-Based Maintenance Infographic
- Figure 4-26: Advanced Asset Management
- Figure 5-1: Utility Distribution Business Problems
- Figure 5-2: Major Causes of Outages in the United States
- Figure 5-3: Top Three Smart Grid Benefi ts Identifi ed By Utility Co-Op
Executives
- Figure 5-4: Partial Volt/VAR Optimization Vendor Environment
- Figure 5-5: Partial Automated Line Switching Vendor Environment
- Figure 5-6: Strategic Activities of the Big 5 Smart Grid Vendors
- Figure 5-7: The Next Generation of Grid Stability Devices
- Figure 5-8: DA Communications Requirements and Near-Term Predictions
- Figure 6-1: California Legislation and Regulation Aff ecting Utility
Decisions
- Figure 6-2: SCE Smart Distribution Deployment Schedule
- Figure 6-3: PG&E Territory T&D Summary Statistics as of December 31, 2010
- Figure 6-4: PG&E Roadmap for Distribution Automation
- Figure 6-5: Capital and Expense Estimates for PG&E Distribution Automation
- Figure 6-6: SDG&E Reliability and Safety Roadmap
- Figure 6-7: SDG&E Distribution Automation Project Timelines
- Figure 6-8: Duke-Progress Proposed Utility Territory
- Figure 7-1: DA Network and Control Center Infrastructure Product Ecosystem
- Figure 7-2: Volt/VAR Control Product Ecosystem
- Figure 7-3: Reliability Product Ecosystem
- Figure 7-4: Asset Management Product Ecosystem
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