The life geospatial - Feeling Energetic?
Of course you are, as I write this the 17th May looms large in the consciousness. This type of energy may be more prosaic.
Wind energy efficiencies 30-50% and solar over 20% bodes well for people and planet
So, boil the kettle and fire up the laptop. Easy to say and do unless you can’t or have the brownouts that plague parts of Africa, Asia and even California. That energy supply can be a fickle thing but we’ve learnt to be unable to live without it (for very long). Lights out, laptops off, routers down, mobile telephony gone, freezers thawing, where are the candles?! And that’s just domestic.
As we head towards the end of coal, past peak oil, the rise and rise of renewables present new challenges and opportunities to sustain our lives and the wider economy. Massively distributed energy production from offshore and onshore sources coupled to the shifting energy demand patterns of a 21st century digital economy is a fundamentally different model from the last 100 years. Location of sources and distribution and patten of consumption provide necessitate a near real time 3D framework with which to plan, build, manage and mitigate variation in these new networks and patterns.
Add to that the post-Covid shift in work-life balance, the rapid expansion of electric vehicles, likely vehicle-to-grid (V2G) and expansion of existing household to grid energy flows from solar, wind and ground/air source and storage walls. Rising customer expectations challenge network design and control, siting of inter-connectors, maintenance scheduling, smart pricing and much more, all under the watchful eye of the regulator.
All of which puts a very location centric lens energy generation at the top end. Forecasting energy yield from existing assets and siting future assets onshore and off to reflect both short term weather patterns and longer term climate trends. For hydro, what water levels are we expecting in the dams is a function of the weather and stable and dynamic catchment characteristics including slope, land use, land cover, soil and geology.
The industry has long used geospatial data management tools that have become increasingly sophisticated as geo has become ever more important. Bentley, Autodesk, IQGeo, ESRI and GE (Smallworld) will be familiar names to some. Typical early adoption was in records management and for asset registers and management. More recently, integration between these toolsets and with ERP, SCADA and a wide array of control and IoT-enabled systems make the power industry a very data rich business with almost every data point have a location, from customer to meter to sub-station and so on up the system. Network design is at the cutting edge of smart grid evolution where demands for integration and access to coherent, accurate data across different tool sets is a prerequisite. By contrast the in-situ demands of network management, power distribution, load scheduling and resource deployment for maintenance scheduling are increasingly products of machine-to-machine (M2M) communication, the deployment of AI techniques and automation based on those same integrated data sets.
With a requirement to reduce CapEx while maintaining customer service, infrastructure maintenance and update without flexibility to increase charges the power industry are actively seeking ways to improve operational efficiency and improve customer performance. Being location sensitive and location smart is fundamental to realising these ambitions. So, there are 3 lenses across the industry, from the field to the C-suite via operations and customer service:
- Connect everyone by ensuring all users have access to the same network location data
- Ensure stakeholders are aware of relevant organisation data and its limitation and possibilities, and
- Enable the organisation to benefit from the rich well of data through providing the tools and talent that can synthesise and analyse that data to reveal relationships between disparate data sets and detect or predict issues and problems to drive informed decision making
As consumers our experience of the industry tends to be framed by the cost and by disruption. The latter we see and feel in streetworks and congestion, often conditioned by the perception that they are never-ending and repetitive.
There are on-going efforts to mitigate both aspects of this through ever-improving data capture on the one hand and adoption of GIS and Common Information Model (CIM) integration tools and investment in data sharing across underground assets stakeholders (electric, gas, water, waste, telco, transport, oil, fuel) on the other.
On top of this the industry is talking more and in more accessible language that resonates with consumer and C-suite alike. While GIS is likely to become an ever more embedded feature of back end systems across the energy sector owing to the ubiquity of location within the data model so will customer and stakeholder expectations rise. We will demand:
- Why have I got no power
- When will it be back
- Where is the engineer
- How long will the engineer be
- And much more
And expect to be told! After all they know everything about us thanks to the use of AI on the data from our smart meters (a topic for another time).