Optimal microgrid operation based on wind/PV power prediction

Xiaobo Zhang; Baohui Zhang; Xiong Wu

doi:10.16081/j.issn.1006-6047.2016.03.004

Optimal microgrid operation based on wind/PV power prediction

Xiaobo Zhang
, Baohui Zhang
, Xiong Wu

School of Electrical Engineering

Xi'an Jiaotong University

Research output: Contribution to journal › Article › peer-review

15 Scopus citations

Abstract

The ARMA (AutoRegressive Moving Average) model is used to predict the wind power, the multiple linear regression method is used to predict the photovoltaic power, the piece-wise linearization method is used to present the relationship between the fuel cost and output power of MT (MicroTurbine), and a battery model considering the charging/discharging efficiency and states is established. With the minimum internal fuel cost and the minimum electricity purchase cost as the objectives, the control strategy of microgrid operation is optimized by charging and discharging the battery. CPLEX software is applied to solve the optimization function and the results of optimal operation are presented, which show that, with the proposed optimization strategy, the battery is charged when the electricity price is lower while discharged when the electricity price is higher and the operating cost is less than that of the traditional control strategy.

Original language	English
Pages (from-to)	21-25 and 40
Journal	Dianli Zidonghua Shebei/Electric Power Automation Equipment
Volume	36
Issue number	3
DOIs	https://doi.org/10.16081/j.issn.1006-6047.2016.03.004
State	Published - 10 Mar 2016

Keywords

Economy
Electric batteries
Microgrid
Optimization
Photovoltaic
Prediction
Wind power

UN SDGs

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

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10.16081/j.issn.1006-6047.2016.03.004

Cite this

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title = "Optimal microgrid operation based on wind/PV power prediction",

abstract = "The ARMA (AutoRegressive Moving Average) model is used to predict the wind power, the multiple linear regression method is used to predict the photovoltaic power, the piece-wise linearization method is used to present the relationship between the fuel cost and output power of MT (MicroTurbine), and a battery model considering the charging/discharging efficiency and states is established. With the minimum internal fuel cost and the minimum electricity purchase cost as the objectives, the control strategy of microgrid operation is optimized by charging and discharging the battery. CPLEX software is applied to solve the optimization function and the results of optimal operation are presented, which show that, with the proposed optimization strategy, the battery is charged when the electricity price is lower while discharged when the electricity price is higher and the operating cost is less than that of the traditional control strategy.",

keywords = "Economy, Electric batteries, Microgrid, Optimization, Photovoltaic, Prediction, Wind power",

author = "Xiaobo Zhang and Baohui Zhang and Xiong Wu",

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doi = "10.16081/j.issn.1006-6047.2016.03.004",

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}

TY - JOUR

T1 - Optimal microgrid operation based on wind/PV power prediction

AU - Zhang, Xiaobo

AU - Zhang, Baohui

AU - Wu, Xiong

PY - 2016/3/10

Y1 - 2016/3/10

N2 - The ARMA (AutoRegressive Moving Average) model is used to predict the wind power, the multiple linear regression method is used to predict the photovoltaic power, the piece-wise linearization method is used to present the relationship between the fuel cost and output power of MT (MicroTurbine), and a battery model considering the charging/discharging efficiency and states is established. With the minimum internal fuel cost and the minimum electricity purchase cost as the objectives, the control strategy of microgrid operation is optimized by charging and discharging the battery. CPLEX software is applied to solve the optimization function and the results of optimal operation are presented, which show that, with the proposed optimization strategy, the battery is charged when the electricity price is lower while discharged when the electricity price is higher and the operating cost is less than that of the traditional control strategy.

AB - The ARMA (AutoRegressive Moving Average) model is used to predict the wind power, the multiple linear regression method is used to predict the photovoltaic power, the piece-wise linearization method is used to present the relationship between the fuel cost and output power of MT (MicroTurbine), and a battery model considering the charging/discharging efficiency and states is established. With the minimum internal fuel cost and the minimum electricity purchase cost as the objectives, the control strategy of microgrid operation is optimized by charging and discharging the battery. CPLEX software is applied to solve the optimization function and the results of optimal operation are presented, which show that, with the proposed optimization strategy, the battery is charged when the electricity price is lower while discharged when the electricity price is higher and the operating cost is less than that of the traditional control strategy.

KW - Economy

KW - Electric batteries

KW - Microgrid

KW - Optimization

KW - Photovoltaic

KW - Prediction

KW - Wind power

UR - https://www.scopus.com/pages/publications/84963781769

U2 - 10.16081/j.issn.1006-6047.2016.03.004

DO - 10.16081/j.issn.1006-6047.2016.03.004

M3 - 文章

AN - SCOPUS:84963781769

SN - 1006-6047

VL - 36

SP - 21-25 and 40

JO - Dianli Zidonghua Shebei/Electric Power Automation Equipment

JF - Dianli Zidonghua Shebei/Electric Power Automation Equipment

IS - 3

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Optimal microgrid operation based on wind/PV power prediction

Abstract

Keywords

UN SDGs

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