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An Introduction to the Cal-Adapt An Introduction to the Cal-Adapt

An Introduction to the Cal-Adapt - PowerPoint Presentation

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An Introduction to the Cal-Adapt - PPT Presentation

Analytics Engine California Energy Commission EPIC Program EPC20007 Primary Funding Provided by Owen Doherty PhD Principal Investigator Eagle Rock Analytics Mark Koenig Project Manager ID: 913293

adapt analytics climate cal analytics adapt cal climate data engine org projections energy future historical pir epc 007 006

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Slide1

An Introduction to the Cal-Adapt

Analytics Engine.

California Energy Commission – EPIC Program (EPC-20-007)

Primary Funding Provided by:

Owen Doherty, Ph.D.

Principal Investigator

Eagle Rock Analytics

Mark Koenig

Project Manager

Eagle Rock Analytics

analytics.cal-adapt.org/

Managed by:

Susan Wilhelm, Ph.D., M.S.E. (CEC)

Chief Advisor: Mike

Mastrandrea

, Ph.D. (CEC/Stanford)

Slide2

CAL-ADAPT ANALYTICS ENGINE

Statement of Problem

analytics.cal-adapt.org/

To support climate resilient investment and vulnerability studies California has invested a lot in producing climate projections

But this data can be difficult to access and utilize for many users

Therefore, we are building a cloud-based analytics platform to help transform the petabytes of data into useful and accessible data products.

Slide3

What Is the Analytics Engine?

Climate Data

A massive, open data repository full of CEC funded climate data localized to California (WECC wide) with high spatial and temporal coverage.

3

Cloud Compute

AWS cloud compute resources tailored and ready to run to execute on climate data

2

Code

Jupyter Notebooks pre-loaded with energy sector applications; an open source code repository full of common climate and energy functions.

1

analytics.cal-adapt.org/

CAL-ADAPT ANALYTICS ENGINE

Slide4

CAL-ADAPT ANALYTICS ENGINE

What’s a

Jupyter Notebook?

analytics.cal-adapt.org/

Slide5

CAL-ADAPT ANALYTICS ENGINE

How Does It Work?

JUPYTER

HUB

OUR CODE

analytics.cal-adapt.org/

Slide6

CAL-ADAPT ANALYTICS ENGINE

Standing on the Shoulder of Giants

analytics.cal-adapt.org/

Historical climate products. SIO/UCSD (PIR-19-007) and Eagle Rock Analytics (PIR-19-006)

Historical Products

Fifth Climate Assessment and other future research work.

Future Climate Research

SIO/UCSD and UCLA are generating the next generation climate projections. (EPC-20-006)

Projections

DATA

Slide7

Historical climate products. SIO/UCSD and UCLA (PIR-19-007)

Historical Products

5

th

Assessment and other future research work.

Future Climate Research

SIO/UCSD and UCLA are generating the next generation climate projections. (EPC-20-006)

Projections

Recent weather and past weather observations and information. ERA and LBNL (PIR-19-006)

Historical Data PlatformCal-Adapt.org has visualizations and download capacities. UCB/GIF (EPC-17-033, PIR-17-012)Cal-AdaptComputing resources on top of climate data information for technical users. ERA, UCB, SIG, E3 (EPC-20-007)Cal-Adapt: Analytics EngineCAL-ADAPT ANALYTICS ENGINE

Expanded Cal-Adapt Enterpriseanalytics.cal-adapt.org/

DATA

ACCESS

Slide8

CAL-ADAPT

DATABASE (2.5 PB+)

CAL-ADAPT ENTERPRISEanalytics.cal-adapt.org/

CLIMATE

HISTORICAL

HEAVY USER

FUTURE

GENERAL USER

DATA CATALOGUE

JUPYTER

HUB

YOUR CODE

OUR CODE

Visualize & Download

Direct Grab

ProjectionsEPC-20-006HistoricalPIR-19-007

Weather

PIR-19-006

Slide9

CAL-ADAPT ANALYTICS ENGINE

How Is This Different Than Cal-Adapt?

analytics.cal-adapt.org/

Slide10

The Analytics Engine represents a major step forward for the Extended Cal-Adapt Enterprise

Reproducible workflowsUnmatched computational resources

Lots of data coming… too much data comingTransparent….or secure and secretiveState of the art and a unique opportunityWe’ll be ready to help

CAL-ADAPT ANALYTICS ENGINE

How Will the Cal-Adapt Analytics Engine Help You?

analytics.cal-adapt.org/

Slide11

CAL-ADAPT ANALYTICS ENGINE

How Can You Get Involved?

Join our co-production process

Become a test user of the Analytics Engine

Join us this Fall!

analytics.cal-adapt.org/

Slide12

Renewable Energy Generation

05

Use climate projections in renewable energy resource modeling - including distributed energy resources (e.g., microgrids), solar or wind generation models, etc. Use climate projections to examine the value of long-duration storage.

Climate & Wildfire

04

Use climate data to inform wildfire mitigation plans and actions - including anticipation, prevention or hardening actions, as well as how to maintain critical operations during a fire.

‘Hourly climate profiles’ for Energy Modeling

03

Use climate data to develop a time series of hourly climate profiles. The time series can then be input into various models, such as Production Cost Models, Load Forecasting Models, or Capacity Expansion Models to support Integrated Resource Plans, Reliability Analysis, etc.

Extreme Heat & Energy

02

Use climate data to forecast energy loads. Use climate data to determine how extreme events impact peak loads or demands (e.g. extreme heat + increased A/C usage, droughts + increased groundwater pumping; etc.).

Threshold & Asset Vulnerability

01

Use climate data to inform asset-by-asset vulnerability assessments by 1) geographical location, 2) metrics of interest, and 3) thresholds that are likely to be exceeded in the future (e.g. exceeding 3 consecutive days of 95th percentile temperature at a specific location).

Ready Now:In Development:

CAL-ADAPT ANALYTICS ENGINE

Priority Use Cases

Slide13

Currently

Soft launch of the Analytics Engine Platform with

some

analytic notebooks and

some

projections.

Fall 2022

Full launch of the Analytics Engine Platform, analytic notebooks and most of projections. Training Workshop.

Spring 2023

Statewide launch event.

CAL-ADAPT ANALYTICS ENGINE

Key Upcoming Activities

analytics.cal-adapt.org/

Slide14

Is the Analytics Engine for me?

YES!

Contact Us

:

analytics@cal-adapt.org

jbui@sig-gis.com

acsaydah@sig-gis.com

owen@eaglerockanalytics.com

Thanks To Our Funders:

analytics.cal-adapt.org/Thanks To Our Supporters: