MDM strategies are evolving and are influenced by smart grid vision, goals
and objectives. These factors drive business requirements that, in turn, define the types of data that need to be collected, where it needs to go, and the
format it needs to be in to make it usable. An organization with a coherent
MDM platform strategy will be better equipped to take advantage of their smart
grid capabilities and make informed technology choices down the road. The
Emergence of Meter Data Management (MDM): A Smart Grid Information Strategy
Report analyzes the best plans for MDM deployment and presents technology
drivers and inhibitors as MDM strives toward significant growth along side
the rollout of smart meters and AMI infrastructure in North America.
Figure 2-1: Smart Grid Architecture from an AMI Data Management Perspective
source: GTM Research
One of the initial hurdles to MDM' s breakthrough has been identifying the
technology' s role and value to utilities. GTM Research' s report begins by
presenting a definitive taxonomy of MDM' s core components - data
repositories, enterprise integration platforms and enhanced smart meter
functionality. The report then pinpoints MDM market opportunity and forecasts
the current market to grow by over 300% from $54 million in 2009 to $221
million by 2014. In addition, GTM Research profiles and ranks the top MDM
vendors vying for this market, including Aclara, Ecologic Analytics,
EnergyICT, eMeter, Hansen Technologies, Itron, NorthStar Utilities Solutions,
Oracle, OSIsoft, SAP MDUS and Telvent.
The Emergence of Meter Data Management (MDM): A Smart Grid Information
Strategy Report is an incisive analysis of first-wave MDM deployment in North
America, and will be integral to define MDM' s functionality, value and
Figure 8-2: Selection from Vendor Feature comparison chart
source: GTM Research
Note: Complete version of chart available in section 8 of the report.
SELECT KEY FINDINGS
- Meter data management (MDM) is necessary to turn the data from smart grid
infrastructures into intelligence
- The GTM Research MDM Taxonomy establishes a rigorous and complete
technology framework composed of:
- a. Meter data repository (MDR) - the database for storing meter data,
- b. Meter data management (MDM) - a platform of data communication and
management services that supports enterprise meter data needs, and
- c. Smart grid applications - existing utility applications enhanced by
smart meter data and entirely new applications enabled by smart meter data.
- A well-articulated smart grid strategy is the best starting point for MDM.
A strategy should include smart grid goals and business requirements and
identify constituents, the decisions they need to make, and the meter data
they need to make them.
- Organizations that implement AMI without MDM are having problems
delivering basic functionality and implementing smart grid applications.
Designing and rolling out MDM systems in parallel with, or prior to, AMI
systems is a best practice that improves overall chances for success
- Flexible service-oriented architectures (SOA) provide a platform for
building flexible and robust smart grid applications using meter data. An MDM
SOA turns data access and delivery into a common service, enabling any
application to subscribe for relevant data.
- The most important meter data repository (MDR) business process is the
meter-to-cash cycle. An MDR creates billing determinants by validating and, if
necessary, automatically estimating each meter read.
- The collection of meter data enables new and better business processes
that cut across departments and organizational boundaries. Examples include
improved outage management, load forecasting, market settlements, and
distribution sizing. Implementing MDM is as much about business process
reengineering as it is about technology.
- Pricing analysts need access to historical meter data to build rate plans
that win regulatory approval, to help customers save money, and to understand
the revenue implications of new rate plans and timeof-use programs like
residential demand response (DR), critical peak pricing (CPP) rebates and
time of-use-pricing (ToU). Customers also need data access to gain comfort
with new programs and make better power consumption decisions.
- MDM can serve as an integration hub that replaces expensive static
point-to-point application connections.
- Select MDM vendors that will forge long-term relationships and provide
expertise. However, do not cede control to your vendor. Create your own smart
grid roadmap that establishes control over direction and strategy.
- Vendors need to expand their offerings to create new growth opportunities,
and MDM provides a springboard for new applications like consumer web portals,
demand response, and outage management. Vendor MDM vision and road maps are
important both for vendor success and for satisfying emerging customer needs.
Table of Contents
1. Key Findings
2. MdM Planning considerations
- 2.1. What is MDM?
- 2.2. What problem are we trying to solve?
- 2.3. What is our strategy for managing meter data?
- 2.4. How mature is the market?
- 2.5. What are the keys to successful MDM Deployment?
3. the MdM Market
- 3.1. Market Drivers
- 3.2. Emergence of Residential AMI Causes MDM Market Disruption
- 3.3. Typical MDM Pricing Models
- 3.4. Market Size
- 3.5. Vendor Strategies
4. defining Meter data Management: taxonomy and capabilities
- 4.1. Tracing Data Flows Through the GTM MDM Taxonomy
- 4.2. Meter Data Repository Functions
- 4.3. Meter Data Repository Technical Requirements
- 4.4. Advanced Meter Infrastructure Functions and Data
- 4.5. Consumer Participation Smart Grid Applications
- 4.6. The Meter Data Management Platform
- 4.7. Load and Energy Management Smart Grid Applications
- 4.8. Utility Operations Smart Grid Applications
- 4.9. Decision Support Smart Grid Applications
5. MDR challenges and limitations
- 5.1. Database Design and Performance
- 5.2. Data Congestion and Unreliable Reads
- 5.3. Lack of Standards
- 5.4. Lack of Skilled Technical Talent
6. Best Practices in deployment
- 6.1. Begin with a Smart Grid Strategy and Plan
- 6.2. Use Data Architectures to Design Solutions
- 6.3. Identify Supporting Components with Persistence, Latency and Business
- 6.4. Build a Phased Roadmap
- 6.5. Streamline AMI Rollout to Quickly Reach Critical Mass
- 6.6. Develop Cross-Functional Business Processes
- 6.7. Educate and Engage Consumers
- 6.8. Drive Requirements With Use Cases
- 6.9. Create a Service-Oriented Architecture Blueprint
- 6.10. Future-Proof and Anticipate Vaporware and Broken Promises
7. Utility Profiles
- 7.1. Pacifi c Gas & Electric
- 7.2. Westar Energy
8. Vendor Rankings and Ratings
- 8.1. Overall Ratings
- 8.2. Vendor Feature Comparison Chart
9. Vendor Profiles
- 9.1. eMeter
- 9.2. NorthStar Utilities Solutions
- 9.3. Ecologic Analytics
- 9.4. SAP MDUS
- 9.5. Energy ICT
- 9.6. Telvent
- 9.7. Hansen Technologies
- 9.8. Oracle
- 9.9. Aclara
- 9.10. OSISoft
- 9.11. Itron