FOUNDATION WORKING GROUP (FWG) MEETING #2 Recap of FWG Meeting #1 – April 22, 2015

May 20, 2015

• The following slides summarize those topics covering during the first Foundation Working Group (FWG) meeting held on April 22, 2015

• Please note that the views represented in these slides reflect the diverse views of members of the FWG and not necessarily those of the IESO.

Recap of Foundation Working Group Meeting #1

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• In May 2015, the Government of Ontario released a draft Open Data Directive for public consultations.

• The draft Open Data Directive aims to maximize access to Ontario government data based on the principles of “open by default”.

• This draft directive is not yet finalized. Feedback and input received through this public consultation process will be used to help shape the final directive.

• Feedback can be provided online or during one of the in-person consultation sessions. Please visit Ontario.ca/open to learn more about the consultations.

Recent News: Draft Government Open Data Directive

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MDM/R DATA ACCESS FOUNDATION (FOUNDATION)

Project Plan Overview

• Ontario has made a significant investment in smart meters and in the central repository (the MDM/R) for high quality, consistent residential and small commercial electricity consumption data. This repository is currently being used by LDCs in the processing and management of smart meter data to support billing of electricity customers on time-of-use rates and in fulfilling other LDC regulated obligations.

• The IESO as the Smart Metering Entity has the obligation “To provide and promote non-discriminatory access, on appropriate terms and subject to any conditions in its licence relating to the protection of privacy, by distributors, retailers, the IESO and other persons”

• The IESO has the authority to collect information on the metering of consumers’ consumption and related data.

• The IESO is able to use smart metering data and related information to fulfill its regulated obligations.

Background

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The data set in MDM/R offers significant potential value for designing conservation and demand response programs, system planning, policy development, academic research and to support innovation in Ontario. Capturing that potential value will involve two requirements:

− Defining the information required to be associated with electricity consumption information (such as geo-location) to enable analysis of this information;

− The development of rules and protocols for data access to meter data from the MDM/R and the MDM/R Data Mart by third parties, and builds in the necessary measures to ensure the security and privacy of the data.

Foundation Project: Objectives

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Included in the scope of the Foundation project are the following efforts: • Communicating the objectives of the project to government, OEB, IPC,

LDCs, potential data users, and interested stakeholders. • Developing and stakeholdering of the required information to be associated

with MDM/R electricity consumption data for relating it to other data sources to support analysis by LDCs, the IESO and other stakeholders.

• Considering the implementation of the additional information into the MDM/R and, if so:

– Planning for the implementation of the interface specifications and data requirements.

– Supporting LDC implementation and compliance with the interface specifications and data requirements.

• Developing, stakeholdering, and implementing the rules for data access by third parties that preserves the security and privacy of personal data that would be accessible

Foundation Project: Scope

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Excluded from the scope of the Foundation project are: • All of the activities required by LDCs to send required data according to

the MDM/R Technical Interface Specifications and at the required level of quality.

• Development and implementation of new automated or online systems and interfaces to support access to data by third parties, which is in scope of the MDM/R Data Access Platform business case (i.e. only the current existing MDM/R and MDM/R Data Mart data access interfaces and capabilities will be used for the Foundation implementation).

• Additional data sets to the MDM/R or MDM/R Data Mart (e.g. commercial and industrial consumption data, property information), which are in the scope of the MDM/R Data Access Platform (MDAP)business case.

• Access by third parties to individual customer’s energy consumption data (with their consent) thru the their LDC is handled under the Green Button Initiative (GBI)

Foundation Project: Areas Not in Scope

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• Stakeholdering and Communications • Geo-location and Customer Identification Information • Security, Privacy and Rules for Data Access by Third

Parties • One or more third party experts may be involved to work with the

IESO in the area of privacy and security.

• Cost Recovery

Foundation Project: Major Work Streams

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Foundation Project: High Level Schedule

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Questions?

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METER DATA MANAGEMENT AND REPOSITORY (MDM/R)

System Overview

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Smart Metering System

Meters

Advanced Metering Control Computer

(AMCC) Local Area

Network

Regional Collector

Wide Area

Network

Advanced Metering Infrastructure (AMI)

Monitors and Displays

Third Parties

Retailers, Energy Service Companies

Customer Information and Billing Systems

Meter Data Management

Meter Data Repository

Meter Data Management

and Meter Data Repository

(MDM/R)

Source: Ontario Ministry of Energy

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Customers

Information Flows

File Transfer Services

• Universal SDP ID Assignment • Synchronization • Meter read data • Billing quantity - pull • Reports

Graphical User Interface

• View master / meter read data • Edit Interval data • View most reports

Web Services

MDM/R LDC or Agent

LDC ORG ID

AMI ORG ID

Billing Agent ORG ID

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Processing Overview

SDP ID and USDP ID Assignment

Synchronization

Meter Read Data Collection & Validation

Validation, Estimation and Editing

Storage in DB

IESO Use

Setting up service delivery points

Meter Read Data Collection to Storage and Use/Access Processes

3rd Party Access

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MDM/R Reports

• All reports are delivered via File Transfer Service (FTS)

• Most reports are also available via the GUI

• Who gets what reports? – Some reports are only sent to submitting organization. – LDCs must authorize Agents to receive specific reports by

including them in the LDC Organizational Relationships and Authority Delegation Form.

– Some reports may be received by multiple organizations.

There are guides and technical specifications available to help users understand the contents of all the reports and how to interpret the information presented in each.

Security and Privacy

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MDM/R Information – Relevant Fields

Field Name Field Type Required (Y/N)

Description

LDC ORG_ID Alphanumeric (length=8)

Y The unique Organization identifier assigned to the LDC

Universal SDP ID

Numeric (length=8)

Y The Ontario-wide unique identifier assigned by the MDM/R

SDP ID

Alphanumeric (max length=50)

Y This identifier is maintained in the LDC systems and uniquely identifies the SDP.

Interval Length

Numeric (length=3)

Y This field is populated with the length of the interval in minutes

Premise Address

Alphanumeric (max length=100)

Y The physical address of the SDP. Alternatively, the LDC may provide the Premise ID or other value as may be determined by the LDC.

City

Alphanumeric (max length=20)

Y This is the city in which the SDP exists or other value as may be determined by the LDC.

Province

Alphanumeric (max length=20)

Y This is the province in which the SDP exists or other value as may be determined by the LDC.

Postal Code

Alphanumeric (max length=10)

Y This is the postal code associated with the SDP or other value as may be determined by the LDC.

Existing Fields

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MDM/R Information – Relevant Fields

Existing Fields (cont’d)

Field Name Field Type Required (Y/N) Description

Account ID Alphanumeric (max length=50)

N This is the account identifier that is associated with the Universal SDP ID.

Energy Consumption Time Series

Multiple Fields Y This is the time series of interval energy consumption data for a Service Delivery Point

GPS (Latitude & Longitude)

Subject to definition

Exists in underlying data

base but not in the interface

Could be added to the system if required. Extent of changes would depend on nature of additions.

Extra Premise Fields (1 – 4)

Alphanumeric (max length=50)

Must be empty Reserved for future use.

Demographic-Firmographic Fields (1-4)

Alphanumeric (max length=50)

N Placeholder for future firmographic-demographic data.

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The mnemonic “SDP” is the abbreviation for “Service Delivery Point” which is the point where energy consumption is measured. The “SDP ID” forms a unique identifier within each LDC, but it is not unique across the province. A “Universal Service Delivery Point ID”, or “USDP ID”, is generated by the MDM/R for each LDC’s SDPs and this identifier is unique across the entire province.

Address fields in the MDM/R are mandatory fields but the content of those fields varies from LDC to LDC. Part of the Foundation project scope is to determine what address information is needed and establish its required format.

The Account ID field in the MDM/R is an optional field. There exist four demographic/firmographic fields in the MDM/R that are

reserved for future use. Demographic information is about individuals and firmographic information is about organizations; however, there is flexibility within the MDM/R as to the future use of these fields.

MDM/R Information – Relevant Fields

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Questions?

GEO-LOCATION AND CUSTOMER IDENTIFICATION INFORMATION Summary of Use Cases

• Define the information required to be associated with electricity consumption information to enable analysis of this information: • Geo-location Identification/Attribute Information • Customer Identification/Attribute Information

• Requesting Working Group input on • What geo-location information is necessary for analysis and

mapping consumption data to other data sources? • What customer information is necessary for analysis and

mapping consumption data to other data sources?

Objective

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• Objective: – Better target CDM marketing efforts utilizing integrated

consumption, demographics and structure data

• Data Sets: – Annual kWh – CIS system – Demographic data – Environics Analytics

• Age, housing tenure, education, job type, ethnic presence, official language, social values, preferences (e.g. lifestyles, hobbies), household income

– Structure data – MPAC • Address, property code description, AC flag, heat type, year built, total floor

area

• Outcome: – Twice the SBL installations – Peaksaver Conversion Rate from 0.86% - 2.86%

Use Case: Horizon Utilities Energy Mapping for Delivery of CDM Programs

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Use Case: Horizon Utilities Energy Mapping for Delivery of CDM Programs (cont’d)

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• Data Integration • kWh and structure

data matched using street address

• Demographic data matched using postal code

• Database/visual analysis using GIS

• Not for profit that establishes partnerships and technological means to share geospatial data amongst community organizations to create safer, healthier and more prosperous communities.

• 15 years experience, 50-60 partners.

Use Case: Sault St. Marie Community Geomatics Center

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• Objective: – Alert 911 services of vulnerable persons affected by power

outage.

• Data sets: – Utility CIS – Transmission system map – Street address – Vulnerable persons list

Use Case: Sault St. Marie Community Geomatics Center – Vulnerable Persons

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• Data Integration – Meter structure entire transmission station – Vulnerable persons matched using street address

• Lessons Learned

– Vast majority of data is matched using street address and postal code – Do not need names of individual vulnerable persons – Privacy protocol: cannot disclose data at the level that can be utilized to

identify an individual – Permission to see data comes from data-set – Most addresses do not adhere to a standard per se, but most generally

follow Canada Post Standards – No widely adopted standards for geolocation or customer identification

information

Use Case: Sault St. Marie Community Geomatics Center – Vulnerable Persons

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• Objective: – Determine the impact of time of use savings so that LDCs can count

them towards their CDM targets

• Process: – OPA conducting study (technically 3rd party) – Access 12 months data pre and post TOU (i.e. pre and post MDM/R) – 8 LDCS (7 in MDM/R) – Sample from each LDC: customer base eligible customers sample

size request data from MDM/R from each LDC

Outcome – Project ongoing, OPA (now IESO) and consultant evaluate using a data-

set that is stripped of all LDC and MDM/R identifiers.

Time Of Use Study

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Summary of Findings

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Geo-location and Customer Identification Information Experience • Address and customer move in/move out information are key elements to

add to the data set to make it useful for analysis • Automated matching techniques achieved an approximately 85% match

rate that was insufficient for analysis. A much higher match rate (e.g. 99%) between data sets is necessary. Manually matching the last 14% is very costly and time consuming. The Tract and Neighbourhood Data Modelling (TaNDM) project in British Columbia geocoded the data, which significantly reduced the required level of effort. Once matched, in many cases data can be aggregated for reporting.

• There was agreement among members of the FWG that attributes about the customer and the location are also important information that enables further analyses. Square footage, building type, and demographic/firmographic attributes were all mentioned as needed data.

• Need almost all consumption points mapped to identify energy efficiency and make it useful to planners, especially for conservation and demand management.

Questions?

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PRIVACY, SECURITY, AND THIRD PARTY ACCESS

Summary of Discussions

• In Scope: – Recommendations of the rules for access to data by

third parties that preserves the security and privacy of personal information.

• Out of Scope: – Any development of new processes, procedures,

systems and/or systems enhancements to support the implementation of the recommended rules

Objective

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• There are different use cases for different third parties; for example, a green house gas (GHG) inventory for a municipality versus targeted sales by a private company. The spectrum of use cases needs a spectrum of data granularity access.

• If there is concern about third parties using data for predatory sales, the discussion should be about how to protect customers rather than withholding data.

• Consumers’ personal data needs to be protected through privacy and security protection measures, not through the withholding of their data from stakeholders.

• Controls at the SME and the MDM/R include those to prevent unauthorized organizations and users from accessing data. The annual MDM/R audit includes an assessment of controls over access to systems and data.

Summary of Discussions Around 3rd Party Access

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• The IESO is bound by the Freedom of Information and Projection of Privacy Act (FIPPA)

• Information that is adequately de-identified (not personally identifiable) is not “personal information” as defined in FIPPA

• There are many techniques to de-identify personal identifiable information.

• One way to protect privacy may be for the IESO to do the analysis and publish the results in de-identified form.

• Use of firewalls and data clean rooms may help in ensuring privacy while enabling analysis of granular information subject to appropriate terms and conditions.

Summary of Discussions Around Privacy & Security

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Questions?

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