Title :
Photovoltaic power penetration capacity assessment considering static voltage stability
Author :
Wangyang Du ; Ming Zhou ; Bing Lin ; Guang Yang
Author_Institution :
State Key Lab. of Alternate Electr. Power Syst. with Renewable Energy Sources, North China Electr. Power Univ., Beijing, China
Abstract :
Considering the randomness of photovoltaic (PV) output and load, the paper proposes a new method to analyze PV power penetration limit based on probabilistically optimal power flow. The proposed model based on chance constrained programming, is a nonlinear programming model with multi-constraints which has random variables. It takes the maximal PV power capacity that can be accepted by power grid as objective function, takes power flow equations, secure operation of power grid and particularly static voltage stability margin as constraints. According to the characteristics of the problem, stochastic simulation technique and particle swarm optimization algorithm are applied. The method is analyzed on the IEEE-30 system, the results show that the proposed model is suitable for calculating PV capacity limit considering the randomness of PV output and load, also the results demonstrate the accuracy and conciseness of the model, which can be available for the planning of PV power station.
Keywords :
IEEE standards; load flow; nonlinear programming; particle swarm optimisation; photovoltaic power systems; power grids; power system stability; stochastic processes; voltage control; IEEE-30 system; PV power capacity; PV power station planning; chance constrained programming; nonlinear programming model; optimal power flow; particle swarm optimization algorithm; photovoltaic load; photovoltaic output; photovoltaic power penetration capacity assessment; power flow equations; power grid operation; static voltage stability; stochastic simulation technique; Load flow; Load modeling; Mathematical model; Power generation; Power grids; Power system stability; Stability analysis; Photovoltaic power penetration limit; chance constrained programming; particle swarm optimization; probabilistically optimal power flow; stochastic simulation;
Conference_Titel :
Power and Energy Engineering Conference (APPEEC), 2013 IEEE PES Asia-Pacific
Conference_Location :
Kowloon
DOI :
10.1109/APPEEC.2013.6837180