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.
Smart grids are the future innovations when it comes to sustainable energy distribution. This also involves a huge amount of data that needs processing at a constant rate. Data management here is essential to the proper running and stability of smart grids and their functionality.
What Is Data Management?
The term ‘Data Management’ refers to the process or practice of collecting, compiling and using information securely and efficiently while saving costs. This activity aims to enable the analysis of information when needed to make sense of the very vast quantities of data at our disposal today. However, data management is streamlined to just the information required to run the grids effectively when it has to do with intelligent grid systems.
Another reason for proper data management in grid systems is for corrective actions to be taken when the need presents itself so that grid participators can maximize benefits within the energy sector. The scope of data management is vast but can be understood within the following factors:
- To create, access, and update data across a differing data tier
- Store data across numerous platforms
- Provide high availability and disaster recovery
- Use data in a growing variety of apps, analytics, and algorithms
- Ensure the privacy and security of data
- Archive and destroy data following retention schedules and compliance requirements
To get the most out of data management, organizations and administrators need data management systems that are peculiar to their requirements. The point is to find the necessary information for analysis.
Data Management In Smart Grid Systems
Smart grids come with their peculiar advantages and changes that involve the information and communication technologies systems sector. These new changes include:
- New forms of information flow coming from the electricity grid
- New players like decentralized producers of renewable energies, prosumers and involved consumers
- New uses linked with DERs such as electric vehicles and connected houses
- New communicating equipment such as smart meters, sensors and remote-control points
These changes will bring a huge amount of information to grid operators and administrators due to the many variables involved in energy production, distribution and consumption. Smart grids are seen as a concrete solution to the concurrent changes hitting the electrical energy sector, and they help with the efficient integration of the entire network. So, because smart grids ensure high integration of the electric grid from production to consumption, large amounts of data are expected to pass through.
This data is not sorted as in conventional grids that would, for example, have one meter reading total consumption in a month. With a feature such as a smart meter that could be set to send consumer readings every 15 minutes, smart grids get larger amounts of data per time set, which means more information to sort through, with higher analysis thresholds. This is why data management is required; intelligent grids need to deal with high-velocity data, storage capacity and advanced data analytics.
There are two main data systems linked with smart grids that we will discuss here; Communication systems and Information systems.
Communication systems in smart grid data management
Communication is a crucial factor in any relationship, even between computer components. In smart grids, maintaining that connection so that data can be relayed between components is essential. This system needs to be secure and capable of high bandwidth and speed. Three types of networks fall under this system, Home Area Networks (HANs), Business Area Networks (BANs) and Neighbourhood Area Networks (NANs). These network types can further be classified into two broad categories, which are wired and wireless technologies.
Information systems in smart grid data management
These are components of the smart grids that communicate together for scalability and flexibility of the grid. They control and load data from the field then use it to extract values and understand the condition of the lines, equipment, energy use etc. There are several components within the information system such as:
- Supervisory control and data acquisition (SCADA) is a safe and reliable system of software and hardware elements used for monitoring control within the grid. The system controls energy distribution processes, monitors and collects real-time data, keeps records of events and interacts with devices through a human-machine interface. SCADA can also be applied in industrial sectors like energy, oil and gas, transportation and recycling. These systems are essential because they help to maintain efficiency, process data more intelligent and mitigate downtime with system issues.
- Advanced metering infrastructure (AMI) helps with cost and time efficiency by compiling data about energy consumption and production. AMI creates two-way communication meters between consumers and utility operators that enable high-frequency data collection of energy consumption within intelligent grids. This gives utility operators the ability to modify the different service level parameters for customers and gather data on usage frequencies and fluctuations.
- Outage management system (OMS) is vital in minimizing the effects and diagnosing the causes of power outages, and improving the system’s availability and reliability. This system is capable of restoring network models after an outage has occurred. They are also capable of tracking, displaying and grouping outages.
- Customer information system (CIS) is needed to develop and understand the relationship between the utilities and consumers. It is a complete customer relationship management system that assists in obtaining customer information efficiently. It helps to provide quality services to consumers by utilizing their collected data.
- Geographic information system (GIS) is considered a visualization tool to gather information about the grid, consumers and technologies. It captures, stores, checks and displays seemingly unrelated data concerning positions on Earth’s surface, which helps to solve real-world problems through understanding spatial patterns.
- Demand response management system (DRMS) gives the utilities the ability to create automated, flexible and integrated platforms to manage demand response solutions efficiently and speedily. It is the critical link between the demand response side of the grid and the utility operators. It helps with the integration of the much-needed two-way communication between consumers and grid operators.
Daki, H., El Hannani, A., Aqqal, A. et al. Big Data management in smart grid: concepts, requirements and implementation. J Big Data 4, 13 (2017).
Data management systems maintain the effectiveness of smart grids, lower costs where necessary, increase response time, and reduce the cumbersome nature of data collection by managing them efficiently. Just as the future is catching up with far-reaching innovations, the Hive Power platform makes various technical options available, especially with robust data analytics and management tools.