There are a host of components needed for a smart grid to function at its utmost capacity. In 2008 the Department of Energy (DOE) in America put together a task force of some of the foremost thinkers and shapers of the smart grid sector, and they agreed on a few defining characteristics of a smart grid that would be able to meet the needs it was created for; this is what they came up with:
- Enable active participation by consumers
- Accommodate all generation and storage options
- Enable new products, new services and new markets
- Provide power quality for the wide range of needs in a digital economy
- Optimise asset use and operating efficiency
- Expect and respond to system disturbance in a self-healing manner
- Operate resiliently against physical and cyber-attacks as well as natural disasters
From the list above, we see that a lot of communication and data management is necessary for the workability of smart grids, and one of the solutions to this crucial communication need is the (AMI)-advanced metering infrastructure. AMI is a foundational component that enables smart grid technology to work cohesively.
The advanced metering infrastructure (AMI) is an integrated system made up of smart meters, communication networks and data management systems that allows two-way communication between the utilities provider and customer. This infrastructure is an essential step in the modernisation of grid technologies because it directly includes the customer into the working framework of the smart grid, which increases the added value to the services rendered.
Since AMI is a critical infrastructure of the smart grid, it is also deployed with its unique components:
- Smart meters and data concentrators
- Wide-area communication network (WAN)
- Meter data central (MDC) system
- Meter data management (MDM) system
- Home area network (HAN)
This is where meter management systems, or more concise, meter data management systems, come into play.
What is Meter Data Management System And How it Work?
According to OpenEI, “a meter data management system (MDMS) collects and stores meter data from a head-end system and processes that meter data into information that can be used by other utility applications including billing, customer information systems and outage management systems”.
This system is built on the MDC system, whose primary function includes the validation, estimation, and editing (VEE) of meter data that are later passed on to utility systems, even though disruption of meter data flows may occur.
An MDMS is essential to handling the large amounts of data generated through automated metering or the advanced metering infrastructure. It allows loose coupling between systems.
Several automated meter reading (AMR) systems send their data through their respective head-end servers for the VEE routine to fill gaps in their data, creating clean, integrated and bill-ready data sets. Other utility systems like a data warehouse, outage management, or billing also get their data for their specific purposes from MDMS.
Some AMR/AMI systems that provide meter data to MDMS are gas meters, electric meters and water meters. Compared to conventional grid systems, MDMS enables the consumer/customer to view all their consumption data under one structure, with the ability to manage both analogue and interval data to optimise usage and costs.
The Role Of MDMs
Despite its defining role as a data source, the MDMS plays some other functional roles within the larger IT ecosystem. It can be a traffic director, a data repository, a data framing engine, an infrastructure map and an asset management system.
- Traffic director: in this role, the MDMS can connect back-end applications to specific AMR/AMI systems on a dynamic basis; this makes access to data easy and transparent for users.
- Data repository: in this role, MDMS can serve as an intermediary between the back-end applications that request meter information and specific AMR/AMI systems that collect the data. While MDMS is primarily an online transaction processing system, it can act as an interim data repository.
- Data framing engine: in this role, MDMS can assign interval usage data into specific billing determinants to allow billing of complex rates. This comes in handy when customers are on particular incentives such as time-of-day or peak day pricing rate where the pricing varies exponentially.
- Infrastructure map: in this role, MDMS can save a very detailed virtual map of the electric infrastructure components and their interconnections. These components include meters, transformers, distribution circuits, substations and the like. This map is used as a connectivity model to pass that information like outage alarms to outage management systems and other notifications to their respective systems.
- Asset management system: in this role, the infrastructure map that MDMS already has can be augmented with asset data to be used as an asset management system that can come in handy for small-scale utility companies that may be unable to afford a stand-alone asset management system.
There are numerous roles the MDMS can fit into in the ever-evolving smart grid sector. It is, however, worthy to note that there are a few challenges with its deployment, such as data synchronisation, system integration, scalability, system configuration and time synchronisation, which all have to do with the massive amount of data that runs through the MDM system.
Once the amount of data finds a perfect working synergy within the MDMS, these challenges should be a thing of the past.
The Future of MDMS?
The MDMS is meant to provide effective integration with reduced infrastructure complexity that can easily accommodate any change to its numerous parts without affecting the whole system.
In the global energy market, there is growing consumer demand and the rise of the prosumer, driving an increase in the deployment of smart grids, which need working and sustainable components to meet these demands and boost market growth. Like the Hive Platform, which easily plugs to DSO’s MDMs as a data source for our algorithms and smart grid analytics modules.
Other factors like integration of AMI systems with cloud computing and Internet-of-Things (IoT), extensive research and development will drive the global MDMS market further than anticipated.