Combining Sister Load Forecasts

Tao Hong, PhD Graduate Program Director and Assistant Professor

University of North Carolina at Charlotte

June 24, 2015

• Energy Production & Infrastructure Center (EPIC)

• Systems Engineering & Engineering Management

• Big Data Energy Analytics Laboratory (BigDEAL)

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Agenda

• Electric load forecasting

• Forecast combination

• Sister load forecasts

• Global Energy Forecasting Competition

• Case study

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In case Rob didn’t cover these…

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Electric Load Forecasting

• Conventional – Aggregated level, point output

• (Hong, 2010)

• What’s new – Hierarchical load forecasting

• (Hong, Pinson and Fan, 2014); (Hong, Wang and White, 2015)

– Probabilistic load forecasting • (Hong and Fan, 2016); (Hong, Pinson, Fan, Zareipour, Troccoli and

Hyndman, 2016)

– Load forecast combination • (Liu, Nowotarski, Hong and Weron, 2015)

• (J. Liu, 2015) (Nowotarski, Liu, Weron and Hong, 2015)

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Forecast Combination – Why?

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A man with a watch knows what time it is. A man with two watches is never sure. BUT …

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Forecast Combination – How?

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Combination methods

Simple average & median

Simple average

Modified simple average

Median

Trimmed mean & Winsorized mean

Trimmed mean

Winsorized mean

Group Analysis

Using absolute residual

Using MAPE

Rolling combination

Using absolute residual

Using daily MAPE

Using mean of N-day absolute residual

Using mean of N-day absolute residual by hour

Using mean of N-day square of residual by hour

Regression combination

Forecast Combination – What?

• Common practice: “independent experts”

– Hard to find

– Expensive

– Black box

– Structural changes

– …

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Sister Load Forecasts

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P. Wang, B. Liu and T. Hong, "Electric load forecasting with recency effect: a big data approach', submitted to IJF, 2015 M. Pesaran and A. Pick, “Forecast combination across estimation windows,” Journal of Business and Economic Statistics, vol. 29, no. 2, pp. 307–318, 2011.

Sister Load Forecasts

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GEFCom2012

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GEFCom2014

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GEFCom2014-L

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GEFCom2014-L

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4.2

4.25

4.3

4.35

4.4

4.45

4.5

4.55

4.6

MA

PE

(%)

Forecast combination MAPEs for validation period

Benchmark 1

Benchmark 2

4.575

4.385

4.299

GEFCom2014-L

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Techniques Validation MAPE (%)

Test MAPE (%)

Benchmark 1 4.575 5.013

Benchmark 2 4.385 5.081

Regression combination

4.299 4.545

A More Extensive Study

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Further Readings

Key references

• P. Wang, B. Liu and T. Hong, "Electric load forecasting with recency effect: a big data approach', submitted to IJF, 2015

• B. Liu, J. Nowotarski, T. Hong and R. Weron, "Probabilistic load forecasting via quantile regression averaging on sister forecasts", TSG, 2015

• J. Liu, “Combining Sister Load Forecasts”, MS Thesis, UNC Charlotte, 2015

• J. Nowotarski, B. Liu, R. Weron and T. Hong, "Improving short term load forecast accuracy via combining sister forecasts", submitted to EGY, 2015

• T. Hong, P. Pinson, S. Fan, H. Zareipour, A. Troccoli and R. J. Hyndman, "Probabilistic energy forecasting: state-of-the-art 2015", IJF, 2016

Questions?

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For more information, please contact Dr. Tao Hong

hong@uncc.edu www.drhongtao.com blog.drhongtao.com