Study on selftuning-weight EMAP model applied in collaborative operation of renewable power generation system

Author

Kong, Lingzhi ; Tang, Xisheng ; Qi, Zhiping

Author_Institution

Grad. Univ., Chinese Acad. of Sci., Beijing

fYear

2008

fDate

17-20 Oct. 2008

Firstpage

2723

Lastpage

2728

Abstract

In this paper, a renewable power generation system is firstly introduced. This system consists of four important subsystems: a diesel generation subsystem, a photovoltaic (PV) subsystem, a DC/AC conversion subsystem and an electric double-layer capacitor (EDLC) energy-storage subsystem. The corresponding control methods of these subsystems are given in this paper. Next, a new prediction model-selftuning-weight Euler-type moving average prediction (EMAP) model is proposed to operate the distributed generation system in autonomous mode. The simulation results by MatlabSimulink and PSIM indicate that the response characteristics of this renewable generation system are good, and the required capacity of EDLC to compensate the fluctuation of both photovoltaic output and load demand are also greatly reduced.

Keywords

DC-AC power convertors; diesel-electric power stations; distributed power generation; electrolytic capacitors; moving average processes; photovoltaic power systems; power generation control; DC/AC conversion subsystem; Euler-type moving average prediction model; MatlabSimulink simulation; PSIM simulation; diesel generation subsystem; distributed generation system; electric double-layer capacitor energy-storage subsystem; photovoltaic subsystem; power system operation; renewable power generation system collaborative operation; selftuning-weight EMAP model; subsystem control methods; AC generators; Collaboration; DC generators; Mathematical model; Photovoltaic systems; Power generation; Power system modeling; Predictive models; Solar power generation; Supercapacitors;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical Machines and Systems, 2008. ICEMS 2008. International Conference on

Conference_Location

Wuhan

Print_ISBN

978-1-4244-3826-6

Electronic_ISBN

978-7-5062-9221-4

Type

conf

Filename

4771216