Modeling and Control of a Photovoltaic Energy System Using the State-Space Averaging Technique

Abstract

Problem statement:This study presented the modeling and control of a stand-alone Photovoltaic (PV) system using the state-space averaging technique. Approach: The PV module was modeled based on the parameters obtained from a commercial PV data sheet while state-space method is used to model the power converter. A DC-DC boost converter was chosen to step up the input DC voltage of the PV module while the DC-AC single-phase full-bridge square-wave inverter was chosen to convert the input DC comes from boost converter into AC element. The integrated state-space model was simulated under a constant and a variable change of solar irradiance and temperature. In addition to that, maximum power point tracking method was also included in the model to ensure that optimum use of PV module is made. A circuitry simulation was performed under the similar test conditions in order to validate the state-space model. Results: Results showed that the state-space averaging model yields the similar performance as produced by the circuitry simulation in terms of the voltage, current and power generated. Conclusion/Recommendations: The state-space averaging technique is simple to be implemented in modeling and control of either simple or complex system, which yields the similar performance as the results from circuitry method.

A Systematic Controller Design for a Photovoltaic Generator with Boost Converter Using Integral State Feedback Control

“…It demonstrates the response of the system according to different values of irradiation (500, 1000, and 800), and it shows that the desired maximum power is reached for Ir = [1000 800]. Furthermore, the rules of the boost are verified, where ܸ ௩ ൏ ܸ , ݅ ௩ ݅ , and the duty cycle is equal to the theoretical value given by (8). In addition, the PV voltage follows the reference value, whereby the state feedback controller is verified under variable irradiation.…”

“…C. Validation of the State-Space Model of the PV Generator Authors in [8,12,13,17] did not take into account the PV panel as a non-linear independent system that could negatively influence the results of the approach used to control the boost converter for maximum power, especially in state-space modeling. Hence, a separate modeling and study of the PV system is very important.…”

“…In our case, we considered this effect because the non-linearity of the PV cell can affect the stability and robustness of the system. Authors in [8][9][10] used classic maximum power point tracking (MPPT) algorithms, such as perturb and observe (P&O) and incremental conductance (IC), as a way to control the converter [11]. Instead of P&O MPPT heuristics, a state feedback controller approach to achieve optimal operation was proposed, where the reference voltage of the PV systems is calculated by the P/U curve of the PV cells.…”

Implementation of Fuzzy Logic Maximum Power Point Tracking Controller for Photovoltaic System

“…However, it does not provide a direct control method for online controlling. In contrast, fuzzy logic technique is rapid and provides direct control system (Jamri and Wei, 2010 …”

“…The MPPT methods are various in the complexity, convergence speed, popularity, cost, operating range, sensor dependence, capability of escaping from local optima and their applications (Jamri and Wei, 2010;Lopez-Lapena et al, 2012). Ease of implementation and simplicity are the parameters that can make some methods, such as hill climbing and P and O, popular (Ishaque et al, 2011;Safari and Mekhilef, 2011b;2011c).…”