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.
We have talked about the smart grid in our previous blog posts and its relation to energy storage, grid stability, and future power needs. It is undeniable that smart grid technology is changing the power sector; how these technologies are correctly applied matters, especially in achieving sustainability goals for a better future.
Six Smart Grid Technology Applications Leading the Change.
Conventional grid technologies perform a simple function, the transmission of electrical power generated at a central power plant. This happens with voltage transformers that increase and decrease voltage levels gradually while delivering energy to the end-users. Smart grids, however, perform all the conventional functions with the added ability or advantage of monitoring all the activities remotely for better and quicker responses and performance.
We will discuss six key applications for Smart Grid technology in this blog post. They are advanced metering infrastructure, demand response, electric vehicles, wide-area situational awareness; distributed energy resources and storage; and distribution grid management.
1. Advanced Metering Infrastructure
This is also known as AMI. It’s simply applying technologies like smart meters to help with the two-way flow of information between customers and utility agencies. This information revolves around consumption time, amount and appropriate pricing. It enables smart grids to have a wide range of functions compared to conventional grid technologies.
These functions include but are not limited to:
- Remote consumption control
- Time-based pricing
- Consumption forecast
- Fault and outage detection
- Remote connection and disconnection of users
- Theft detection and loss measurements
- Effective cash collection and debt management
Having these functions means gaining better control over power efficiency and quality in smart grids across the globe. Still, there are a few drawbacks that worry consumers and utility agencies alike, such as privacy and confidentiality issues and cybersecurity issues relating to unauthorised access to the AMI devices.
2. Demand Response
Demand response (DR) programs are recent and emerging applications for demand‐side management (DSM). Examples are applications that improve grids’ reliability by providing services such as frequency control, spinning reserves and operating reserves, and applications that help reduce wholesale energy prices and their volatility.
The development of energy regulatory commissions with open wholesale markets and policy support has enabled demand response applications in grid technology. There are two categories of demand response programs from the customer perspective:
- Price‐based DR where customers adjust their electricity consumption in response to the time-variant prices created by their utility agencies to maximise their electricity usage and save on bills
- Incentive‐based DR where benefits are increased by promoting an incentive to influence customer behaviours to change their demand consumptions
DR provides the opportunity for consumers to reduce or shift their electricity usage during peak periods through the programs mentioned above, giving them a huge role in the operation of electric grids with the hopes of balancing supply and demand needs.
3. Electric Vehicles (EVs)
This may seem like a misplaced application for smart grids, but with the obvious electrification of the transport industry, EVs are a preferred solution to global warming issues. In terms of smart grid technologies, plug-in electric vehicles’ introduction comes with myriad challenges and opportunities to sustain power systems. If EVs are added to the grids as regular loads, then there will be no allowance for flexibility of load variables, which will endanger the grid as a whole.
However, these challenges can be managed successfully with controlled approaches, especially when charging is shifted to low‐load hours. EVs can also promote Smart grid sustainability by operating as distributed storage resources (V2G) that contribute to ancillary services such as frequency regulation, peak‐shaving power for the system or the integration of fluctuating renewable resources.
4. Wide-Area Situational Awareness
This refers to the implementation of a set of technologies designed to improve the monitoring of the power system across large geographic areas — effectively providing grid operators with a broad and dynamic picture of the functioning of the grid.
WASA systems provide operators and engineers with the right information at the right time for efficient operation and analysis of the power system, according to SELinc. The ultimate goal here remains the same: to understand and optimise the smart grid’s reliability through its performance and anticipate where necessary changes need to occur before problems abound.
Smart grids use phasor measurement units as sensors for collecting data over large geographical areas making phasor measurement sensors the bane of wide-area measurement systems. They can be relied upon to relay situational awareness over large interconnected areas through:
- Real-time monitoring
- Prediction of future disturbances
5. Distributed Energy Resources and Storage
Distributed energy resources are also known as DER and are part of Distributed generation; they refer to energy sources or generation units that are smaller and located on the consumer side of the electricity generation meter.
Energy is generated from sources (mostly renewable) near the point of use rather than from a centralised system. Some examples are rooftop solar photovoltaic units and wind generating units.
While DER storage involves systems that store distributed energy for later use. This is done with two components; DC-charged batteries and bi-directional inverters. It helps in balancing energy generation, demand and supply. Some other key features are:
- Peak shaving
- Load shifting
- Voltage regulation
- Renewable integration
- Back-up power
6. Distribution Grid Management
A distribution grid includes all the equipment needed for energy distribution, such as wires, poles, transformers etc. The management of the distribution grid in smart grids has to do with having a system “capable of collecting, organising, displaying and analysing real-time or near real-time electric distribution system information” as needed.
This system can also allow grid operators to plan and place complex tasks to increase efficiency, meet targets, prevent failures and optimise energy flow. It can also work hand in hand with other systems to create a combined outlook of distributed operations.
Smart grid technologies are created to be smart, with the capabilities of predetermining faults that can then be prevented, cut costs where possible, and deliver the best value to consumers when needed.