In today’s dynamically changing world, operators rely on data systems to
make data drive decisions that impact their operating systems. As these data
systems mature, operators can begin asking and answering tough questions.
One such maturing field is asset proximity analysis. In particular,
structures and occupancies are major considerations for operators. The
demand for this analysis is driven by stakeholders and regulators alike as
they generate information useful for asset classification, load forecasting,
and more.
A major hurdle of asset proximity analyses is the scale of the problem.
Assets span vast distances and frequently reside in densely populated areas.
Furthermore, population behaviors are dynamic and difficult to model.
EN Data Solutions is uniquely positioned to offer a team with extensive GIS,
analytics, and integrity management expertise. EN’s team understands
operators’ systems and can answer their difficult questions.
EN Data Solutions specializes in custom solutions to help its clients
locate, analyze, and interactively connect data to their assets and
customers. This can be done through several services EN offers using various
tools, processes, and modeling systems. This provides EN’s clients with a
deeper understanding of their data and enables them to make and support
critical decisions within their organization.
One of these solutions, a custom population analysis tool, provides
operators with an aggregated structure data source with an assigned
estimated population. The tool outputs can be used as a supplemental data
source to drive operating and planning decisions and to satisfy regulatory
requirements. Activities that can benefit from this analysis include:
The custom population analysis tool aggregates multiple structure data
sources and operators’ customer information into one data collection. As the
structure data sets are aggregated, the structures are classified as
residential and nonresidential.
The residential structures are assigned an estimated population based on
census data and/ or other data sources to meet operator needs. The
non-residential structures are further classified into a structure type,
that uses either data sources or Natural Language Processing (NLP) to
classify the structure type based on the business name that is currently
occupying the structure. The non-residential structures are then assigned an
estimated population based on the structure type and size.
The analysis tool results are aggregated into a single structure feature
class representing the spatial location of the structure, assigned
population, and other relevant information. The results can be used in
various analyses to meet the operator’s needs.
EN’s data solutions team has developed a custom population tool that can be
applied to any service area. The tool parameters are fully customizable to
meet the needs of EN’s clients.
For example, EN Data Solutions assisted a client by estimating population
for 1.7 million structures within their service area. The results from this
population analysis were used within the client’s natural gas distribution
risk model to calculate the consequence factors within their system.