A new method for smoothing output power fluctuations of PV system connected to small power utility

A photovoltaic (PV) systempsilas power output is not constant and fluctuates depending on weather conditions. Fluctuating power causes frequency deviations in the power utilities when PV power penetration is large. Using a battery is one feasible measure to stabilize a PV systempsilas power output, but it requires additional costs and results in additional waste of used batteries. In this paper, to overcome these problems, we propose a new method for leveling the fluctuations in a PV systempsilas power output. By means of the proposed method, output power control of PV system considering the conditions of power utilities becomes possible and the conflicting objective of output power leveling and maximizing energy capture are achieved. Here, fuzzy reasoning is used to generate the output leveling power command. This fuzzy reasoning has three inputs of average insolation, variance of insolation, and absolute average of frequency deviation. Power converter is used to achieve output power same as command power employing PI control law. The proposed method is compared with the method where extracted maximum power is given to the utility without leveling. The simulation results show that proposed method is effective for leveling output fluctuations and feasible to reduce the frequency deviation of the small power utility.

[1]  R. Belmans,et al.  Voltage fluctuations on distribution level introduced by photovoltaic systems , 2006, IEEE Transactions on Energy Conversion.

[2]  Rainer Dr Wagner,et al.  Large lead/acid batteries for frequency regulation, load levelling and solar power applications , 1997 .

[3]  T. Senjyu,et al.  Output levelling of renewable energy by electric double-layer capacitor applied for energy storage system , 2006, IEEE Transactions on Energy Conversion.

[4]  Takeyoshi Kato,et al.  Evaluation of LFC capacity for output fluctuation of photovoltaic power generation systems based on multi-point observation of insolation , 2001, 2001 Power Engineering Society Summer Meeting. Conference Proceedings (Cat. No.01CH37262).

[5]  K. Otani,et al.  Statistical smoothing of power delivered to utilities by distributed PV systems , 1998 .

[6]  Kenji Kobayashi,et al.  A study on a two stage maximum power point tracking control of a photovoltaic system under partially shaded insolation conditions , 2003, 2003 IEEE Power Engineering Society General Meeting (IEEE Cat. No.03CH37491).

[7]  T. Funabashi,et al.  Output Power Control for Large Wind Power Penetration in Small Power System , 2007, 2007 IEEE Power Engineering Society General Meeting.

[8]  Lefteri H. Tsoukalas,et al.  Fuzzy and neural approaches in engineering , 1997 .

[9]  Kenji Kobayashi,et al.  A study on a two stage maximum power point tracking control of a photovoltaic system under partially shaded insolation conditions , 2003, IEEE Power Engineering Society General Meeting.

[10]  Jinjun Liu,et al.  Modeling diode reverse recovery and corresponding implementation in fast time-domain simulation , 2007, 2007 7th Internatonal Conference on Power Electronics.

[11]  M. Vitelli,et al.  Optimization of perturb and observe maximum power point tracking method , 2005, IEEE Transactions on Power Electronics.

[12]  Susumu Yamashiro,et al.  Development of an Advanced Grid-Connected PV-ECS System Considering Solar Energy Estimation , 2005 .

[13]  Jongrong Lin,et al.  Implementation of a DSP-controlled photovoltaic system with peak power tracking , 1998, IEEE Trans. Ind. Electron..

[14]  John P. Barton,et al.  A probabilistic method for calculating the usefulness of a store with finite energy capacity for smoothing electricity generation from wind and solar power , 2006 .

[15]  Li-Ming Wu,et al.  A half bridge flyback converter with ZVS and ZCS operations , 2007, 2007 7th Internatonal Conference on Power Electronics.