Conference Paper

# Power loss analysis of grid connection photovoltaic systems

Dept. of Electr. Eng., Nat. Chung Cheng Univ., Ming-Hsiung, Taiwan

DOI: 10.1109/PEDS.2009.5385738 In proceeding of: Power Electronics and Drive Systems, 2009. PEDS 2009. International Conference on Source: IEEE Xplore

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**ABSTRACT:**This paper presents power loss comparison of single- and two-stage grid-connected photovoltaic (PV) systems based on the loss factors of double line-frequency voltage ripple (DLFVR), fast irradiance variation + DLFVR, fast dc load variation + DLFVR, limited operating voltage range + DLFVR, and over- all loss factor combination. These loss factors will result in power deviation from the maximum power points. In this paper, both single-stage and two-stage grid-connected PV systems are consid- ered. All of the effects on a two-stage system are insignificant due to an additional maximum power point tracker, but the tracker will reduce the system efficiency typically about 2.5%. The power loss caused by these loss factors in a single-stage grid-connected PV system is also around 2.5%; that is, a single-stage system has the merits of saving components and reducing cost, and does not penalize overall system efficiency under certain operating voltage ranges. Simulation results with the MATLAB software package and experimental results have confirmed the analysis.IEEE Transactions on Energy Conversion 01/2011; 26(2):707-715. · 2.43 Impact Factor - [Show abstract] [Hide abstract]

**ABSTRACT:**This paper presents power loss analysis for PV dc-distributed systems based on the loss factors of double line-frequency voltage ripple (DLFVR), fast irradiance variation + DLFVR, fast dc load variation + DLFVR, limited operating voltage range + DLFVR, and overall loss factor combination. These loss factors will result in power deviation from the maximum power points. In the paper, both single-stage and two-stage grid-connected PV systems are considered. All of the effects on a two-stage system are insignificant due to an additional maximum power point tracker, but the tracker will reduce the system efficiency typically about 2.5%. The power loss caused by these loss factors in a single-stage grid-connected PV system is also around 2.5%; that is, a single-stage system has the merits of saving components and reducing cost, while does not penalize overall system efficiency in dc-distribution applications. Simulation results with the MATLAB software package and experimental results have confirmed the analysis.01/2011; - [Show abstract] [Hide abstract]

**ABSTRACT:**This paper proposes a methodology of designing a Maximum Power Point Tracking (MPPT) controller for photovoltaic systems (PV) using a Fuzzy Gain Scheduling of Proportional-Integral-Derivative (PID) type controller (FGS-PID) with adaptation of scaling factors (SF) for the input signals of FGS. The proposed adaptive FGS-PID method is based on a two-level control system architecture, which combines the advantages of fuzzy logic and conventional PID control. The initial values of the PID's gains are determined by the Ziegler–Nichols tuning method. During transient and steady states, the PID's gains are adapted by the FGS-PID to damp out the transient oscillations, to reduce settling time and to guarantee system stability and accuracy. Also, the conditioned input signals of the FGS-PID are tuned dynamically by gain factors which are based on fuzzy logic system (FLS). The FLS is characterized by a set of fuzzy rules which are fuzzy conditional statements expressing the relationship between inputs (error and change of error) and outputs. This approach creates an adaptive MPPT controller and achieves better overall system performance. The simulation results demonstrate the effectiveness of the proposed adaptive FGS-PID and show that this approach can achieve a good maximum power operation under any conditions such as different levels of solar radiation and PV cell temperature for varying PV sources. Compared to conventional methods (PID, perturb and observe method P&O), this method shows a considerable high tracking performance.Renewable Energy 02/2014; 60:202–214. · 2.99 Impact Factor

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