A Simulation Approach to Multi-station Solar Irradiance Data Considering Temporal Correlations

Xingbo Fu; Feng Gao; Jiang Wu; Ruanming Huang; Yichao Huang; Fei Fei

doi:10.1109/ISGT-Asia.2019.8881133

A Simulation Approach to Multi-station Solar Irradiance Data Considering Temporal Correlations

Xingbo Fu
, Feng Gao
, Jiang Wu
, Ruanming Huang
, Yichao Huang
, Fei Fei

Faculty of Electronic and Information Engineering

Xi'an Jiaotong University
State Grid Shanghai Electric Economic and Technology Research Institute

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

Abstract

Solar energy is one of important renewable energy sources and simulation of solar irradiance can be used as input for simulation of photovoltaic (PV) generation. This paper proposes a simulation algorithm of multi-station solar irradiance data considering temporal correlations. First of all, we group all the days of the observed data to k clusters for each station based on their daily features of solar irradiance and the daily states constitute Markov chain of days. Then, we reduce state permutations of different stations before getting Markov Transition Probability Matrix (MTPM). In terms of the observed data and MTPM, the simulation approach is proposed. Finally, we test our approach by applying to solar irradiance data of three stations and show that the properties of simulated data match those of the observed data.

Original language	English
Title of host publication	2019 IEEE PES Innovative Smart Grid Technologies Asia, ISGT 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	4215-4220
Number of pages	6
ISBN (Electronic)	9781728135205
DOIs	https://doi.org/10.1109/ISGT-Asia.2019.8881133
State	Published - May 2019
Event	2019 IEEE PES Innovative Smart Grid Technologies Asia, ISGT 2019 - Chengdu, China Duration: 21 May 2019 → 24 May 2019

Publication series

Name	2019 IEEE PES Innovative Smart Grid Technologies Asia, ISGT 2019

Conference

Conference	2019 IEEE PES Innovative Smart Grid Technologies Asia, ISGT 2019
Country/Territory	China
City	Chengdu
Period	21/05/19 → 24/05/19

UN SDGs

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

SDG 7 Affordable and Clean Energy

Keywords

Feature clustering
MTPM
PV generation
solar irradiance simulation
state space reduction

Access to Document

10.1109/ISGT-Asia.2019.8881133

Cite this

Fu, X., Gao, F., Wu, J., Huang, R., Huang, Y., & Fei, F. (2019). A Simulation Approach to Multi-station Solar Irradiance Data Considering Temporal Correlations. In 2019 IEEE PES Innovative Smart Grid Technologies Asia, ISGT 2019 (pp. 4215-4220). Article 8881133 (2019 IEEE PES Innovative Smart Grid Technologies Asia, ISGT 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISGT-Asia.2019.8881133

@inproceedings{8cc13f70474f48d3b6509084059ff8b3,

title = "A Simulation Approach to Multi-station Solar Irradiance Data Considering Temporal Correlations",

abstract = "Solar energy is one of important renewable energy sources and simulation of solar irradiance can be used as input for simulation of photovoltaic (PV) generation. This paper proposes a simulation algorithm of multi-station solar irradiance data considering temporal correlations. First of all, we group all the days of the observed data to k clusters for each station based on their daily features of solar irradiance and the daily states constitute Markov chain of days. Then, we reduce state permutations of different stations before getting Markov Transition Probability Matrix (MTPM). In terms of the observed data and MTPM, the simulation approach is proposed. Finally, we test our approach by applying to solar irradiance data of three stations and show that the properties of simulated data match those of the observed data.",

keywords = "Feature clustering, MTPM, PV generation, solar irradiance simulation, state space reduction",

author = "Xingbo Fu and Feng Gao and Jiang Wu and Ruanming Huang and Yichao Huang and Fei Fei",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 IEEE PES Innovative Smart Grid Technologies Asia, ISGT 2019 ; Conference date: 21-05-2019 Through 24-05-2019",

year = "2019",

month = may,

doi = "10.1109/ISGT-Asia.2019.8881133",

language = "英语",

series = "2019 IEEE PES Innovative Smart Grid Technologies Asia, ISGT 2019",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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}

Fu, X, Gao, F, Wu, J, Huang, R, Huang, Y & Fei, F 2019, A Simulation Approach to Multi-station Solar Irradiance Data Considering Temporal Correlations. in 2019 IEEE PES Innovative Smart Grid Technologies Asia, ISGT 2019., 8881133, 2019 IEEE PES Innovative Smart Grid Technologies Asia, ISGT 2019, Institute of Electrical and Electronics Engineers Inc., pp. 4215-4220, 2019 IEEE PES Innovative Smart Grid Technologies Asia, ISGT 2019, Chengdu, China, 21/05/19. https://doi.org/10.1109/ISGT-Asia.2019.8881133

A Simulation Approach to Multi-station Solar Irradiance Data Considering Temporal Correlations. / Fu, Xingbo; Gao, Feng; Wu, Jiang et al.
2019 IEEE PES Innovative Smart Grid Technologies Asia, ISGT 2019. Institute of Electrical and Electronics Engineers Inc., 2019. p. 4215-4220 8881133 (2019 IEEE PES Innovative Smart Grid Technologies Asia, ISGT 2019).

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

TY - GEN

T1 - A Simulation Approach to Multi-station Solar Irradiance Data Considering Temporal Correlations

AU - Fu, Xingbo

AU - Gao, Feng

AU - Wu, Jiang

AU - Huang, Ruanming

AU - Huang, Yichao

AU - Fei, Fei

PY - 2019/5

Y1 - 2019/5

N2 - Solar energy is one of important renewable energy sources and simulation of solar irradiance can be used as input for simulation of photovoltaic (PV) generation. This paper proposes a simulation algorithm of multi-station solar irradiance data considering temporal correlations. First of all, we group all the days of the observed data to k clusters for each station based on their daily features of solar irradiance and the daily states constitute Markov chain of days. Then, we reduce state permutations of different stations before getting Markov Transition Probability Matrix (MTPM). In terms of the observed data and MTPM, the simulation approach is proposed. Finally, we test our approach by applying to solar irradiance data of three stations and show that the properties of simulated data match those of the observed data.

AB - Solar energy is one of important renewable energy sources and simulation of solar irradiance can be used as input for simulation of photovoltaic (PV) generation. This paper proposes a simulation algorithm of multi-station solar irradiance data considering temporal correlations. First of all, we group all the days of the observed data to k clusters for each station based on their daily features of solar irradiance and the daily states constitute Markov chain of days. Then, we reduce state permutations of different stations before getting Markov Transition Probability Matrix (MTPM). In terms of the observed data and MTPM, the simulation approach is proposed. Finally, we test our approach by applying to solar irradiance data of three stations and show that the properties of simulated data match those of the observed data.

KW - Feature clustering

KW - MTPM

KW - PV generation

KW - solar irradiance simulation

KW - state space reduction

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M3 - 会议稿件

AN - SCOPUS:85074917088

T3 - 2019 IEEE PES Innovative Smart Grid Technologies Asia, ISGT 2019

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EP - 4220

BT - 2019 IEEE PES Innovative Smart Grid Technologies Asia, ISGT 2019

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2019 IEEE PES Innovative Smart Grid Technologies Asia, ISGT 2019

Y2 - 21 May 2019 through 24 May 2019

ER -

Fu X, Gao F, Wu J, Huang R, Huang Y, Fei F. A Simulation Approach to Multi-station Solar Irradiance Data Considering Temporal Correlations. In 2019 IEEE PES Innovative Smart Grid Technologies Asia, ISGT 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 4215-4220. 8881133. (2019 IEEE PES Innovative Smart Grid Technologies Asia, ISGT 2019). doi: 10.1109/ISGT-Asia.2019.8881133

A Simulation Approach to Multi-station Solar Irradiance Data Considering Temporal Correlations

Abstract

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UN SDGs

Keywords

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