Energy storage modeling of inverter air conditioning for output optimizing of wind generation in the electricity market

Meng Song; Ciwei Gao; Jianlin Yang; Huaguang Yan

doi:10.17775/CSEEJPES.2016.01480

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Energy storage modeling of inverter air conditioning for output optimizing of wind generation in the electricity market

更新时间：2025-12-18

- Energy storage modeling of inverter air conditioning for output optimizing of wind generation in the electricity market
- CSEE Journal of Power and Energy Systems Vol. 4, Issue 3, Pages: 305-315(2018)
- 作者机构：
  
  1. Southeast University,,, CN,Jiangsu,Nanjing
  2. Shanghai Power Company Economic Research Institute,Shanghai,China,200120
  3. China Electric Power Research Institute,Beijing,China,100192
- 作者简介：
- 基金信息：
- DOI：10.17775/CSEEJPES.2016.01480
  CLC：
- Published：2018
- 稿件说明：
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Meng Song, Ciwei Gao, Jianlin Yang, et al. Energy storage modeling of inverter air conditioning for output optimizing of wind generation in the electricity market[J]. CSEE Journal of Power and Energy Systems, 2018, 4(3): 305-315.
DOI：

Meng Song, Ciwei Gao, Jianlin Yang, et al. Energy storage modeling of inverter air conditioning for output optimizing of wind generation in the electricity market[J]. CSEE Journal of Power and Energy Systems, 2018, 4(3): 305-315. DOI： 10.17775/CSEEJPES.2016.01480.

摘要

Abstract

In order to achieve the compatibility of the air conditioning (AC) loads with the current dispatch models

this paper utilizes demand response (DR) technology as energy storage resources to optimize the aggregator's behaviors in the real-time market for less economic loss caused by the fluctuations of wind power. The inverter AC

as a typical demand response resource

is constructed as a power type battery model (PTBM) and a capacity type battery model (CTBM) according to the different control methods

which are expressed through a circuit model and mathematical model to describe the energy storage characteristics of ACs. Moreover

the comparisons between the PTBM and CTBM are given analytically by their response speed

power &energy capacity and the cost of control

which will be helpful to guide the associated operators to choose the appropriate models to take part in demand response. Considering that the wind generation fluctuates frequently and greatly

the PTBM is chosen to take part of the demand response for output optimizing of the wind generation. The simulation results demonstrate that PTBMs can work in the way of conventional batteries (CBs) to optimize wind generation in the real-time market.

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