Canada is the largest supplier of energy to the United States, and this trade partnership increases the need for energy reliability.

Energy mapping is increasingly being used to improve the efficiency of public buildings and infrastructure, help with renewable energy development, and develop emissions reduction plans. Energy mapping relies on geospatial data—some of which is available through national Spatial Data Infrastructure (SDI) or via interoperable web services. These web services use Open Geospatial Consortium (OGC) standards (opengeospatial.org) for geospatial data integration, exchange, and visualization.

For example, the International Renewable Energy Agency’s Global Renewable Energy Atlas (globalatlas.irena.org) is a repository for high-quality renewable energy resource data for planning, developing policy, and attracting investors to emerging energy markets. The system is entirely decentralised; data layers and web services are hosted remotely on servers belonging to project partners in distributed locations. The atlas is a direct implementation of OGC standards, and its success is due to the widespread use of software standards.

When energy mapping is conducted by a city or utility, geographic information systems (GISs) are typically used (these are often OGC-compliant or developed through OGC-standard web services). More building information modelling (BIM) data is needed on public buildings and infrastructure. The current challenge is improving interoperability between SDI, GIS, BIM, and intelligent building systems to create more realistic, data-rich energy maps.

Top-down approach
British Columbia is taking a leading role in energy mapping. The Ministry of Jobs, Tourism and Skills Training’s BC Energy Map tool supports the development of the province’s energy sector. Key partnerships include BC Hydro—which has identified around 7,000 renewable energy options and the major transmission lines throughout the province—and the Ministry of Environment’s Community Energy and Emissions Inventory (CEEI).

With initiatives like the CEEI and community-scale energy and emissions modelling available (toolkit.bc.ca/CEEI and toolkit.bc.ca/CEEM), the BC Community Energy Association developed a practical approach to go into communities and, in a day and a half, develop a year-by-year Community Energy Plan (CEP), along with projections, impacts, economic development potential, and estimated costs. The association has done about 36 CEPs throughout British Columbia over the course of three years. British Columbia is currently developing a new web-based spatial data-mapping tool that is slated to launch this year. Called the BC Economic Atlas, the tool will combine publicly available economic data from across government into a single powerful, user-friendly, and nearly real-time interface.

Bottom-up approach

Local examples include various provincial renewable resource maps as well as city-level integrated energy mapping, done by organizations such as the Canadian Urban Institute in Ontario. In Alberta, climate change and sustainability agency C3 is involved in waste heat mapping in the Industrial Heartland (heartlandenergymapping.c-3.ca). Across Canada, integrated community energy systems are compiled into a national map by QUEST (questcanada.org/themap). These examples of energy mapping provide important insights into potential market needs for energy spatial-data infrastructure.

Municipalities in Canada and the United States are still largely reliant on bottom-up approaches to renewable resource mapping and community energy modelling using GIS and web services. Some energy-related data and statistics are available in Canada via the GeoConnections Discovery Portal (geodiscover.cgdi.ca) as “self-serve” rather than being organized in a slick web client like the U.S. Energy Mapping System (eia.gov/state/maps.cfm). Another example is the U.S. National Renewable Energy Laboratory’s Geothermal Prospector (maps.nrel.gov/gt_prospector), a web-based GIS application that supports geothermal resource assessment and data exploration by compiling data from a wide variety of sources and using standard data provision formats.

Looking forward
Future building locations, solar-path orientations, and functions may be strategically determined in collaboration with local governments and utilities with evidence collected and analyzed through the use of energy SDI and energy maps. To optimize energy needs and requirements by location, it is important to compare standardized local weather and climate conditions with equally consistent and ongoing building-envelope performance data. Ideal energy SDI should be able to process normalized climate data in GIS with standardized public-buildings datasets in BIM. Doing this would help  measure and improve energy efficiency of various building types, using SDI to establish repeatable models and simulations.

Energy SDI might also be driven by advancements in hardware and sensors for data capture and display. Technical standards are needed to ensure reliable, realistic, network-wide drill downs, data compression, and “unfolding” display techniques—all while protecting privacy of data. Energy SDI based on OGC standards can provide a real-time interoperable platform for decision support, machine-to-machine interfaces, aggregated dispatches, and repeatable routines. Energy SDI should also provide the interfaces necessary for integration of typical, but diverse, data sources—from weather, forecasts, population, land use, system performance, building typologies, energy-resource-availability, and other defined characteristics.

Energy SDI should provide geospatial information to utilities, including detailed demand profiles, load forecasting, roll out of smart-grid components, upgraded substations and meters, and aggregation of data above and below meter levels. Many utility systems are 3D-modelled or mapped in GIS, and the purpose of SDIs is to stitch everything together in a way BIM data can also be integrated. The cross-section of measured, modelled, and simulated data could significantly improve energy performance of municipal- and utility-owned public buildings and infrastructure in Canada and the United States.

The sweet spot
Energy SDI could serve as a hub between diverse technologies and organizations to create robust measureable processes for any type of building in any location with any available utilities. It could address untapped potential of BIM interoperating with OGC Sensor Web Enablement (SWE) standards that make all types of sensors data repositories accessible and useable via the web,  by tying real-time facility performance to local weather conditions and utility capacities. Energy SDI could be implemented with critical infrastructure that are constructed, operated, and maintained by local governments and need to stay up and running (such as schools, hospitals, transit, and public safety services). Standardization efforts within OGC (opengeospatial.org/domain/EnergyUtilities) and SGIP 2.0 (sgip.org) will ensure improved geospatial data interoperability and integration for numerous emerging applications.

Ultimately, energy SDI should support multiple types of end-use mapping, from a local to international basis. This could be considered in national policy or as part of the Canadian Geomatics Community Round Table’s pan-Canadian geomatics strategy (cgcrt.ca/draft-strategy-3).

The age old adage “keep it simple” still applies: people need to clearly see themselves in the process and the resulting success.

 

Eddie Oldfield is the owner of Spatial Quest Solutions, and Deborah MacPherson is a senior associate with Cannon Design.

 

LEAVE A REPLY

Please enter your comment!
Please enter your name here