Production simulation of power systems considering the forecast error of renewable energy

Ding Kun; Wang Ningbo; Haipeng Xie; Zhaohong Bie

doi:10.1109/APPEEC.2016.7779855

Production simulation of power systems considering the forecast error of renewable energy

Ding Kun
, Wang Ningbo
, Haipeng Xie
, Zhaohong Bie

School of Electrical Engineering

Gansu Electric Power Corporation Wind Power Technology Center

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Scopus citations

Abstract

A short-term stochastic production simulation method considering the forecast error of renewable sources power is proposed to focus on the issue that conventional production simulation method is incapable of depicting the forecast error of renewable sources power. The proposed method contains two hierarchies, i.e. the day-ahead simulation and the real-time simulation. As for day-ahead simulation, a day-ahead scheduling of conventional units and renewable energy plants is determined by solving a unit commitment model on the basis of forecasted renewable sources power and load profiles. Real-time simulation is the supplement to day-ahead simulation and it corrects the results in day-ahead simulation. The validity of the proposed method is proved with a real power grid in Northwest China. Case studies show that conventional units may be still the major resource of power grids although these installed capacity is no larger than renewable energy resources. Meanwhile, forecast errors actually impact reliability of power systems.

Original language	English
Title of host publication	IEEE PES APPEEC 2016 - 2016 IEEE PES Asia Pacific Power and Energy Engineering Conference
Publisher	IEEE Computer Society
Pages	2091-2095
Number of pages	5
ISBN (Electronic)	9781509054183
DOIs	https://doi.org/10.1109/APPEEC.2016.7779855
State	Published - 9 Dec 2016
Event	2016 IEEE PES Asia Pacific Power and Energy Engineering Conference, APPEEC 2016 - Xi'an, China Duration: 25 Oct 2016 → 28 Oct 2016

Publication series

Name	Asia-Pacific Power and Energy Engineering Conference, APPEEC
Volume	2016-December
ISSN (Print)	2157-4839
ISSN (Electronic)	2157-4847

Conference

Conference	2016 IEEE PES Asia Pacific Power and Energy Engineering Conference, APPEEC 2016
Country/Territory	China
City	Xi'an
Period	25/10/16 → 28/10/16

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

forecast error
renewable energy
stochastic production simulation
unit commitment

Access to Document

10.1109/APPEEC.2016.7779855

Cite this

Kun, D., Ningbo, W., Xie, H., & Bie, Z. (2016). Production simulation of power systems considering the forecast error of renewable energy. In IEEE PES APPEEC 2016 - 2016 IEEE PES Asia Pacific Power and Energy Engineering Conference (pp. 2091-2095). Article 7779855 (Asia-Pacific Power and Energy Engineering Conference, APPEEC; Vol. 2016-December). IEEE Computer Society. https://doi.org/10.1109/APPEEC.2016.7779855

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title = "Production simulation of power systems considering the forecast error of renewable energy",

abstract = "A short-term stochastic production simulation method considering the forecast error of renewable sources power is proposed to focus on the issue that conventional production simulation method is incapable of depicting the forecast error of renewable sources power. The proposed method contains two hierarchies, i.e. the day-ahead simulation and the real-time simulation. As for day-ahead simulation, a day-ahead scheduling of conventional units and renewable energy plants is determined by solving a unit commitment model on the basis of forecasted renewable sources power and load profiles. Real-time simulation is the supplement to day-ahead simulation and it corrects the results in day-ahead simulation. The validity of the proposed method is proved with a real power grid in Northwest China. Case studies show that conventional units may be still the major resource of power grids although these installed capacity is no larger than renewable energy resources. Meanwhile, forecast errors actually impact reliability of power systems.",

keywords = "forecast error, renewable energy, stochastic production simulation, unit commitment",

author = "Ding Kun and Wang Ningbo and Haipeng Xie and Zhaohong Bie",

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Kun, D, Ningbo, W, Xie, H & Bie, Z 2016, Production simulation of power systems considering the forecast error of renewable energy. in IEEE PES APPEEC 2016 - 2016 IEEE PES Asia Pacific Power and Energy Engineering Conference., 7779855, Asia-Pacific Power and Energy Engineering Conference, APPEEC, vol. 2016-December, IEEE Computer Society, pp. 2091-2095, 2016 IEEE PES Asia Pacific Power and Energy Engineering Conference, APPEEC 2016, Xi'an, China, 25/10/16. https://doi.org/10.1109/APPEEC.2016.7779855

Production simulation of power systems considering the forecast error of renewable energy. / Kun, Ding; Ningbo, Wang; Xie, Haipeng et al.
IEEE PES APPEEC 2016 - 2016 IEEE PES Asia Pacific Power and Energy Engineering Conference. IEEE Computer Society, 2016. p. 2091-2095 7779855 (Asia-Pacific Power and Energy Engineering Conference, APPEEC; Vol. 2016-December).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Ningbo, Wang

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AU - Bie, Zhaohong

PY - 2016/12/9

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N2 - A short-term stochastic production simulation method considering the forecast error of renewable sources power is proposed to focus on the issue that conventional production simulation method is incapable of depicting the forecast error of renewable sources power. The proposed method contains two hierarchies, i.e. the day-ahead simulation and the real-time simulation. As for day-ahead simulation, a day-ahead scheduling of conventional units and renewable energy plants is determined by solving a unit commitment model on the basis of forecasted renewable sources power and load profiles. Real-time simulation is the supplement to day-ahead simulation and it corrects the results in day-ahead simulation. The validity of the proposed method is proved with a real power grid in Northwest China. Case studies show that conventional units may be still the major resource of power grids although these installed capacity is no larger than renewable energy resources. Meanwhile, forecast errors actually impact reliability of power systems.

AB - A short-term stochastic production simulation method considering the forecast error of renewable sources power is proposed to focus on the issue that conventional production simulation method is incapable of depicting the forecast error of renewable sources power. The proposed method contains two hierarchies, i.e. the day-ahead simulation and the real-time simulation. As for day-ahead simulation, a day-ahead scheduling of conventional units and renewable energy plants is determined by solving a unit commitment model on the basis of forecasted renewable sources power and load profiles. Real-time simulation is the supplement to day-ahead simulation and it corrects the results in day-ahead simulation. The validity of the proposed method is proved with a real power grid in Northwest China. Case studies show that conventional units may be still the major resource of power grids although these installed capacity is no larger than renewable energy resources. Meanwhile, forecast errors actually impact reliability of power systems.

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KW - renewable energy

KW - stochastic production simulation

KW - unit commitment

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Production simulation of power systems considering the forecast error of renewable energy

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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