Forecasting the responses of market based control of residential electrical heating loads

Pekka Koponen; Pekka Takki

Forecasting the responses of market based control of residential electrical heating loads

Pekka Koponen, Pekka Takki

Helen Oy

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

Abstract

The value of demand responses depends much on their predictability. In Helsinki dynamic smart metering based dynamic demand response can control about 35 MW of residential full storage heating. A partly physically based model for forecasting this aggregated load and its responses to control signals and ambient air temperature is being developed. Also interval measured consumption is used as model input. The initial results show that the control response model developed improves the forecasting accuracy very much. This research and its initial results are reported in this paper.

Original language	English
Title of host publication	Challenges of Implementing Active Distribution System Management
Subtitle of host publication	CIRED Workshop 2014
Publisher	International Conference and Exhibition on Electricity Distribution CIRED
Number of pages	5
Publication status	Published - 2014
MoE publication type	Not Eligible
Event	CIRED Workshop 2014 - Rome, Italy Duration: 11 Jun 2014 → 12 Jun 2014

Conference

Conference	CIRED Workshop 2014
Country/Territory	Italy
City	Rome
Period	11/06/14 → 12/06/14

Keywords

electricity consumption
forecasting
demand response
heating

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http://www.cired.net/publications/workshop2014/papers/CIRED2014WS_0178_final.pdf

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Koponen, P., & Takki, P. (2014). Forecasting the responses of market based control of residential electrical heating loads. In Challenges of Implementing Active Distribution System Management: CIRED Workshop 2014 Article 0178 International Conference and Exhibition on Electricity Distribution CIRED. http://www.cired.net/publications/workshop2014/papers/CIRED2014WS_0178_final.pdf

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title = "Forecasting the responses of market based control of residential electrical heating loads",

abstract = "The value of demand responses depends much on their predictability. In Helsinki dynamic smart metering based dynamic demand response can control about 35 MW of residential full storage heating. A partly physically based model for forecasting this aggregated load and its responses to control signals and ambient air temperature is being developed. Also interval measured consumption is used as model input. The initial results show that the control response model developed improves the forecasting accuracy very much. This research and its initial results are reported in this paper.",

keywords = "electricity consumption, forecasting, demand response, heating",

author = "Pekka Koponen and Pekka Takki",

note = "CA2: BA2135; CIRED Workshop 2014 ; Conference date: 11-06-2014 Through 12-06-2014",

year = "2014",

language = "English",

booktitle = "Challenges of Implementing Active Distribution System Management",

publisher = "International Conference and Exhibition on Electricity Distribution CIRED",

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Koponen, P & Takki, P 2014, Forecasting the responses of market based control of residential electrical heating loads. in Challenges of Implementing Active Distribution System Management: CIRED Workshop 2014., 0178, International Conference and Exhibition on Electricity Distribution CIRED, CIRED Workshop 2014, Rome, Italy, 11/06/14. <http://www.cired.net/publications/workshop2014/papers/CIRED2014WS_0178_final.pdf>

Forecasting the responses of market based control of residential electrical heating loads. / Koponen, Pekka; Takki, Pekka.
Challenges of Implementing Active Distribution System Management: CIRED Workshop 2014. International Conference and Exhibition on Electricity Distribution CIRED, 2014. 0178.

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

TY - GEN

T1 - Forecasting the responses of market based control of residential electrical heating loads

AU - Koponen, Pekka

AU - Takki, Pekka

N1 - CA2: BA2135

PY - 2014

Y1 - 2014

N2 - The value of demand responses depends much on their predictability. In Helsinki dynamic smart metering based dynamic demand response can control about 35 MW of residential full storage heating. A partly physically based model for forecasting this aggregated load and its responses to control signals and ambient air temperature is being developed. Also interval measured consumption is used as model input. The initial results show that the control response model developed improves the forecasting accuracy very much. This research and its initial results are reported in this paper.

AB - The value of demand responses depends much on their predictability. In Helsinki dynamic smart metering based dynamic demand response can control about 35 MW of residential full storage heating. A partly physically based model for forecasting this aggregated load and its responses to control signals and ambient air temperature is being developed. Also interval measured consumption is used as model input. The initial results show that the control response model developed improves the forecasting accuracy very much. This research and its initial results are reported in this paper.

KW - electricity consumption

KW - forecasting

KW - demand response

KW - heating

M3 - Conference article in proceedings

BT - Challenges of Implementing Active Distribution System Management

PB - International Conference and Exhibition on Electricity Distribution CIRED

T2 - CIRED Workshop 2014

Y2 - 11 June 2014 through 12 June 2014

ER -

Forecasting the responses of market based control of residential electrical heating loads

Abstract

Conference

Keywords

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