Electrical Standards, Smart Grids and Your Air Conditioner

When we plug into the giant grid of information we call the Web, we are used to the fact that whatever we do – visiting websites, downloading stuff or just chatting, voluminous amounts of data get exchanged. We also take the Web itself for granted, often forgetting that without access to another giant grid – the electrical one – any data exchange and all the rest we do on the Web would be impossible.

Interestingly, this works the other way round as well. Many of the data exchange processes on the electrical grid are (or would benefit from being) carried out with Web standards.

But what has the electrical grid to do with data exchange on the Web, integration and interoperability? And can these processes be optimized and made more efficient if they are mapped to Linked Data principles and semantic technologies?

Let’s find out by first looking at the major challenges of electrical grids, then diving into the standards guiding electricity data exchange and last by seeing how these challenges can be met with using semantic technology on top of the existing standards.

Electrical Grids: Powers and Limitations

Have you ever considered the complexity and, as we currently saw with California rolling blackouts, the vulnerability of electrical grids?

In the case of California, where in 2020 extreme heat led to excessive demand and supply shortage, and ultimately to rolling blackouts, some very important things became evident. Namely, that to deliver electricity reliably, first of all we need sufficient generation and storage capacity together with adequate transmission infrastructure. But, also, that everything would work much more efficiently if there was real-time information exchange.

If we think about it, when we turn on the air conditioner (which is what everybody in California did at the same time), it connects to a vast and complex power system to keep it working. And we are not the only ones connecting to this system every time we use an electrical appliance. The number of market participants communicating across the grid is astounding – producers, consumers, traders, transmitters, distributors, etc.

Simply put, there is a constant transfer and exchange of data all across the electrical grid. And for all this communication to go smoothly (and for us to survive the heat with a working air conditioner at a reasonable price), the more formalized, standardized and automated the exchange, the better and more effective it is.

Thankfully, there are electrical standards governing all this exchange.

The Common Information Model – the Mother of All Electrical Standards

One of the most important standards developed by the electrical power industry is CIM (the Common Information Model).

It enables the exchange of information about electrical networks, thus governing electrical power transmission, distribution and many other processes relevant to the electricity enterprise. Functions covered by various CIM standards include: electricity transmission, electricity distribution, energy management, SCADA, planning, optimization, network model exchanges, outage management, metering, balancing, congestion management, demand response, flexibility management, work management, geographic information, asset management, customer information, enterprise resource planning, market operations, distributed energy resources, etc.

CIM is officially adopted by the International Electrotechnical Commission (IEC) and by ENTSO-E (the European Network of Transmission System Operators for Electricity). To support the implementation of EU energy policy, ENTSOE and the national electricity transmission system operators (TSOs) it represents have the legal authority to collect electricity information and market participants have to submit it in a timely manner.

The Energy Identification Codes and the Power of Unique Identifiers

Another important standard for the energy industries is EIC (Energy Identification Code). 

This is a coding scheme originally designed by ENTSO-E (for electricity) that however is now also used by ENTSO-G (for gas) and other energy industries. It provides unique codes to various energy related entities – from power plants, individual reactors or power units they have, tielines, transformers and substations; to the companies responsible for power plants, balancing authorities controlling the generation and transmission of electricity throughout a region, control and bidding zones, energy exchanges, regulators, etc. EIC is administered in a distributed manner by ENTSO-E, ENTSO-G, TSOs, major energy producers, etcл and is openly available. It has been added to Wikidata and the large number of source websites for this Wikidata property shows various EIC issuers and where EIC lists can be downloaded from.

By identifying resources in a unique and universal manner, EIC helps resolve identities and makes data easy to exchange.

A Little Semantics Can Go a Long Way: Taking CIM to Its Full Potential

From a data exchange perspective, CIM is a robust foundation for the electrical power industry as it is composed of a series of standards comprising unified UML semantic models, profiles, XMI files, RDF/RDFS schemas (now working on RDF shapes) and serialization rules.

From a data interoperability perspective, though, what the standard lacks is “a little semantics.” As you might have guessed, where there is so much standardization already happening and a market dependent on efficient data exchange, Linked Data and semantic technologies can go a long way.

And while CIM provides formalization and standardization to a large degree, it is far from being utilized to its full semantic potential. Instead of using it only for the exchange of RDF XML messages that become obsolete the moment they are received, it can be used as RDF for Linked Data. Wouldn’t it be so much better to have distributed electricity master data that’s available on demand and is as up-to-date as it is kept by the organization responsible for it?

Going even further, once individual resources have been unambiguously identified with EIC codes, it would pay off big if CIM used these codes as permanent URLs for all energy resources and market participants (rather than blank nodes or temporary Globally Unique IDs).

The electricity data market is ripe for semantically integrating and interconnecting all its data into a living model that fully represents the dynamics of the electrical power industry. ENTSO-E is already doing a great job of collecting electricity data of all kinds at its Transparency Platform.

The next logical step would be to create a rich, live, distributed Energy Knowledge Graph (EKG) that serves the needs of the market for timely, updated and accurate data.

The Knowledge Graph Angle

Knowledge graphs have become increasingly popular in the last few years thanks to their ability to provide access to dynamic, richly interconnected, machine-processable data.

If the huge volumes of data collected at the ENTSO-E Transparency Platform are integrated and interlinked in a semantic model, then spotting and correcting errors, inconsistencies and other problems would be a breeze. This will not only improve the quality of the collected data significantly but will also provide the foundation for a better EKG in the future.

Another thing that an EKG of ENTSO-E Transparency data can vastly improve is to make what’s behind the collected data even more transparent. For example, right now we can see the forecasts for the scheduled electricity generation in a given country a day ahead, but we don’t know what’s exactly behind each of these figures. By making the provenance of the data more transparent, an EKG will enable market participants to have more comprehensive information about what’s happening and this will help the market function much better.

Last but not least, when we have a rich EKG where each energy resource has a permanent URL, every time we click on a resource, we will get the most up-to-date data about it. And each and every point of this data will be clickable, too, so we’ll be able to follow any further connections or check any additional information we are interested in. For example, which organization submitted this information, where is it located, what is its VAT number, what projects it participated in, who it collaborated with on these projects, etc.

The Potential of Semantic Data For Smart Grids

We can even take it a step further. As knowledge graphs make it easy to integrate data, we can ingest data from other domains (such as gas and other energy sources, smart buildings, energy efficiency measures, etc.). Interlinking these external data sources with energy data will open a huge potential for more efficient cross-industry data exchange.

For example, CIM covers many things in the electrical power industry and BIM (Building Information Management) is a standard for architecture design of buildings. But at present, these two standards don’t talk to each other. If we bridge this gap, we can have access to relevant and current data every time we are interested in the energy efficiency of a building or its demand response. Or we need to analyze a complex model that includes data provided by many participants.

To get back to our AC and the case in California, there is a Facility Smart Grid Information Model (FSGIM) standard, through which the grid can communicate with a building (and the devices in it). It can say: “There’s a deficit, please lower your consumption, else you’ll be hit by a high price.” Or even: “Give us your energy from your power storage cells and we’ll remunerate it nicely”. This standard allows smart devices such as smart electric car chargers, ACs and boilers to receive real-time information and to try to use electricity when it’s abundant and cheap.

Making a grid smarter does not only take standardization and formalization. It also requires uniquely identified resources that can access the latest update of each resource on the market at any time. Only then it will be possible for appliances (and whole buildings) to be powered up and shut down not even according to the schedule we’ve set for cheaper energy consumption, but based on the dynamic prices and other market conditions at each moment.

Epilogue: Better Information Exchange Across Electricity Market Participants

It is clear that furthering the use of CIM in the EU towards a knowledge graph will not only have positive long-term effects on the energy market but will also bring major benefits for cross-industry data exchange. This is because it will cover important Big Data aspects such as variety (data complexity), veracity (data quality) and value (through better timeliness, interoperability and ability to integrate data across engineering disciplines).

Accessing timely, relevant and reliable information is mission-critical to the electricity market exchange and Linked Data principles are key for enabling it. Likewise, a little semantics can go a long way for efficient, reliable and sustainable energy services and, ultimately, for a more competitive, customer-centred EU electricity market.

It’s electrifying!