LOAD FORECASTING AND DEMAND SIDE MANAGEMENT Dr. G Garland La - PowerPoint PPT Presentation

LOAD FORECASTING AND DEMAND SIDE MANAGEMENT Dr. G Garland La Laliberte Bipol ole III Co Coalition

Weather-Adjusted Historic and Forecast Gross Firm Energy before DSM, projected from 20-year historic data, GWh 35000 33000 31000 29000 27000 25000 23000 21000 Historic MH15 Forecast MH16 Forecast MH17 Forecast Linear (Historic) 19000 17000

Weather-Adjusted Historic and Forecast Gross Total Peak before DSM, projected from 20-year historic data, MW 6400 6000 5600 5200 4800 4400 4000 3600 3200 Historic MH15 Forecast MH16 Forecast MH17 Forecast Linear (Historic)

Weather-Adjusted Historic and Forecast Gross Firm Energy before DSM, projected from 10-year historic data, GWh 35000 33000 31000 29000 27000 25000 23000 21000 Historic MH15 Forecast MH16 Forecast MH17 Forecast Linear (Historic)

Weather-Adjusted Historic and Forecast Gross Total Peak before DSM, projected from 10-year historic data, MW 6400 6000 5600 5200 4800 4400 4000 3600 3200 Historic MH15 Forecast MH16 Forecast MH17 Forecast Linear (Historic)

Weather-Adjusted Historic and Forecast Gross Firm Energy before and after DSM, GWh 35000 33000 31000 29000 27000 25000 23000 21000 Historic MH17 Forecast MH17 Forecast after MH17 DSM

Weather-Adjusted Historic and Forecast Gross Firm Energy before and after DSM, GWh 35000 33000 31000 29000 27000 25000 23000 21000 Historic MH17 Forecast MH17 Forecast after MH17 DSM MH17 Forecast after EM DSM

Tw Twenty-year ar F Financi cial al I Impac acts on on Dom omesti tic R c Revenue Ove ver-for orecas asting $2. $2.3B Effici ciency M y Man anitob oba D DSM SM $5. $5.1B Tot otal al $7. $7.4B

Weather-Adjusted Historic and Forecast Gross Total Peak before and after DSM, MW 6400 6000 5600 5200 4800 4400 4000 3600 3200 Historic MH17 Forecast MH17 Forecast after MH17 DSM

Weather-Adjusted Historic and Forecast Gross Firm Energy before DSM, GWh 35000 33000 31000 29000 27000 25000 23000 21000 Historic MH17 Forecast Linear (Historic)

Weather-Adjusted Historic and Forecast Gross Total Peak before DSM, MW 6400 6000 5600 5200 4800 4400 4000 3600 3200 Historic MH17 Forecast Linear (Historic)

Weather-Adjusted Historic and Forecast Gross Total Peak before and after DSM, MW 6400 6000 5600 5200 4800 4400 4000 3600 3200 Historic MH17 Forecast MH17 Forecast after MH17 DSM Linear (Historic) after MH17 DSM Linear (Historic)

Weather-Adjusted Historic and Forecast Gross Firm Energy before and after DSM, GWh 35000 33000 31000 29000 27000 25000 23000 Historic MH17 Forecast MH17 Forecast after MH17 DSM MH17 Forecast after EM DSM Linear (Historic) 21000

Weather-Adjusted Historic and Forecast Gross Firm Energy before and after DSM, GWh 35000 33000 31000 29000 27000 25000 23000 Historic Linear (Historic) after MH17 DSM Linear (Historic) after EM DSM Linear (Historic) 21000

Weather-Adjusted Historic and Forecast Gross Firm Energy before and after DSM, GWh 35000 33000 31000 29000 27000 25000 Historic MH15 Forecast MH16 Forecast 23000 MH17 Forecast MH17 Forecast after MH17 DSM MH17 Forecast after EM DSM Linear (Historic) after MH17 DSM Linear (Historic) after EM DSM Linear (Historic) 21000

Weather-Adjusted Historical and Forecast Gross Total Peak before and after DSM, MW 6400 6000 5600 5200 4800 4400 4000 3600 3200 Historic MH15 Forecast MH16 Forecast MH17 Forecast MH17 Forecast after MH17 DSM Linear (Historic) after MH17 DSM Linear (Historic)

Weather-Adjusted Historic and Forecast Gross Firm Energy before and after DSM, GWh 35000 33000 31000 29000 27000 25000 MH13 Forecast (NFAT) Historic MH15 Forecast MH16 Forecast 23000 MH17 Forecast Linear (Historic) MH17 Forecast after MH17 DSM MH17 Forecast after EM DSM 21000

Recommendation No. 1 The Public Utilities Board should direct Manitoba Hydro to revise its electric load forecast downward to more adequately reflect recent historic experience, price elasticity impacts and insights into factors driving load forecasts in other North American jurisdictions for consideration in its current General Rate Application.

Recommendation No. 2 The Public Utilities Board should direct Manitoba Hydro to conduct its own analysis of the impact on Manitoba Hydro’s balance sheet of the Government’s legislated plan for Demand Side Management of electric energy and to report its findings to the Public Utilities Board as part of its next General Rate Application.

LOAD FORECASTING AND DEMAND SIDE MANAGEMENT Dr. G Garland La - PowerPoint PPT Presentation

LOAD FORECASTING AND DEMAND SIDE MANAGEMENT Dr. G Garland La Laliberte Bipol ole III Co Coalition Weather-Adjusted Historic and Forecast Gross Firm Energy before DSM, projected from 20-year historic data, GWh 35000 33000 31000 29000

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Chapter 8 Forecasting Demand Qualitative Forecasting Methods Moving Averages and Smoothing

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LOAD FORECASTING AND DEMAND SIDE MANAGEMENT Dr. G Garland La - PowerPoint PPT Presentation

LOAD FORECASTING AND DEMAND SIDE MANAGEMENT Dr. G Garland La Laliberte Bipol ole III Co Coalition Weather-Adjusted Historic and Forecast Gross Firm Energy before DSM, projected from 20-year historic data, GWh 35000 33000 31000 29000

Workshop DD Demand Side Management Best Practices &amp; Case Studies on Innovations in Load

Smart Energy Electricity usage and demand side management in households Ganesh Ramanathan

demand, grid stability, energy storage and demand side management A Platform for Integrating

A Review of Manitoba Hydr os Electric Load Forecasting a 5 January 2018 presentation to the

Tool Demonstration: Demand Forecasting PACE D 2.0 RE Team Agenda Demand Forecasting

What are the contributions of Demand Side Management for balancing power systems? 9 th Conference

Long-term electric load Why Forecast Electric Load forecasting is necessary so that Decisions on

SWEEP Workshop November 13, 2015 Integrated Demand Side Management DEMAND RESPONSE: a ENERGY

Challenges in Demand Forecasting Raj Protim Kundu ERLDC, POSOCO Need for forecasting IEGC

TCP on Demand Side Management Chair: David Shipworth &lt;d.shipworth@ucl.ac.uk&gt; Where next

Briefing on day-ahead load forecasting Amber Motley, Manager Short Term Forecasting Board of

Side Load Measurements Presented by: (First and Last name of presenter(s) H O S T E D B Y : C O

CDM Forecasting Initiative Stan But March 22, 2011 Manager, Economics &amp; Load Forecasting 1

Dynamic demand side management of heat pump integrated with thermal energy storage Christopher

Integration of renewable energy sources and demand-side management into distribution networks by

Forecasting demand in the National Electricity Market October 2017 Agenda Trends in the

Lecture 9: Demand Uncertainty: Demand Uncertainty: Lecture 9: Forecasting Forecasting

Chapter 8 Forecasting Demand Qualitative Forecasting Methods Moving Averages and Smoothing

Chapter 8 Forecasting Demand Qualitative Forecasting Methods Moving Averages and Smoothing

The Demand Side of the The Demand Side of the Market Market Starring Starring Utility

NATIONAL ENERGY PLANNING &amp; PERSPECTIVE: SPECIAL FOCUS ON DEMAND SIDE MANAGEMENT : 25 th

Electric lectrical al load forecasting load forecasting E using artificial neural using

The Demand Side of the The Demand Side of the Market Market Starring Starring N Utility Theory

The Demand Side of the The Demand Side of the Market Market Starring Starring N Utility Theory

Workshop DD Demand Side Management Best Practices & Case Studies on Innovations in Load

TCP on Demand Side Management Chair: David Shipworth <d.shipworth@ucl.ac.uk> Where next

CDM Forecasting Initiative Stan But March 22, 2011 Manager, Economics & Load Forecasting 1

NATIONAL ENERGY PLANNING & PERSPECTIVE: SPECIAL FOCUS ON DEMAND SIDE MANAGEMENT : 25 th