Real-time Modelling, Diagnostics and Optimised MPPT for Residential PV Systems

Publikation: ForskningPh.d.-afhandling

Abstrakt

The work documented in the thesis has been focused into two main sections. The first part is centred around Maximum Power Point Tracking (MPPT) techniques for photovoltaic arrays, optimised for fast-changing environmental conditions, and is described in Chapter 2. The second part is dedicated to diagnostic functions as an additional tool to maximise the energy yield of photovoltaic arrays (Chapter 4). Furthermore, mathematical models of PV panels and arrays have been developed and built (detailed in Chapter 3) for testing MPPT algorithms, and for diagnostic purposes.
In Chapter 2 an overview of the today’s most popular MPPT algorithms is given, and, considering their difficulty in tracking under variable conditions, a simple technique is proposed to overcome this drawback. The method separates the MPPT perturbation effects from environmental changes and provides correct information to the tracker, which is therefore not affected by the environmental fluctuations. The method has been implemented based on the Perturb and Observe (P&O), and the experimental results demonstrate that it preserves the advantages of the existing tracker in being highly efficient during stable conditions, having a simple and generic nature, and has the benefit of also being efficient in fast-changing conditions. Furthermore, the algorithm has been successfully implemented on a commercial PV inverter, currently on the market. In Chapter 3, an overview of the existing mathematical models used to describe the electrical behaviour of PV panels is given, followed by the parameter determination for the five-parameter single-exponential model based on datasheet values, which has been used for the implementation of a PV simulator taking in account the shape, size ant intensity of partial shadow in respect to bypass diodes.
In order to eliminate the iterative calculations for parameter determinations, a simplified three-parameter model is used throughout Chapter 4, dedicated to diagnostic functions of PV panels. Simple analytic expressions for the model important parameters, which could reflect deviations from the normal (e.g. from datasheet or reference measurement) I −V characteristic, is proposed.
A considerable part of the thesis is dedicated to the diagnostic functions of crystalline photovoltaic panels, aimed to detect failures related to increased series resistance and partial shadowing, the two major factors responsible for yield-reduction of residential photovoltaic systems.
Combining the model calculations with measurements, a method to detect changes in the panels’ series resistance based on the slope of the I − V curve in the vicinity of open-circuit conditions and scaled to Standard Test Conditions (STC) , is proposed. The results confirm the benefits of the proposed method in terms of robustness to irradiance changes and to partial shadows.
In order to detect partial shadows on PV panels, a method based on equivalent thermal voltage (Vt) monitoring is proposed. Vt is calculated using the simplified three-parameter model, based on experimental curve. The main advantages of the method are the simple expression for Vt, high sensitivity to even a relatively small area of partial shadow and very good robustness against changes in series resistance.
Finally, in order to quantify power losses due to different failures, e.g. partial shadows or increased series resistance, a model based approach has been proposed to estimate the panel rated power (in STC). Although it is known that the single-exponential model has low approximation precision at low irradiation conditions, using the previously determined parameters it was possible to achieve relatively good accuracy. The main advantage of the method is that it relies on already determined parameters (Rsm, Vt) based on measurements, therefore reducing the errors introduced by the limitation of the single-exponential model especially at low irradiation conditions.
Luk

Detaljer

The work documented in the thesis has been focused into two main sections. The first part is centred around Maximum Power Point Tracking (MPPT) techniques for photovoltaic arrays, optimised for fast-changing environmental conditions, and is described in Chapter 2. The second part is dedicated to diagnostic functions as an additional tool to maximise the energy yield of photovoltaic arrays (Chapter 4). Furthermore, mathematical models of PV panels and arrays have been developed and built (detailed in Chapter 3) for testing MPPT algorithms, and for diagnostic purposes.
In Chapter 2 an overview of the today’s most popular MPPT algorithms is given, and, considering their difficulty in tracking under variable conditions, a simple technique is proposed to overcome this drawback. The method separates the MPPT perturbation effects from environmental changes and provides correct information to the tracker, which is therefore not affected by the environmental fluctuations. The method has been implemented based on the Perturb and Observe (P&O), and the experimental results demonstrate that it preserves the advantages of the existing tracker in being highly efficient during stable conditions, having a simple and generic nature, and has the benefit of also being efficient in fast-changing conditions. Furthermore, the algorithm has been successfully implemented on a commercial PV inverter, currently on the market. In Chapter 3, an overview of the existing mathematical models used to describe the electrical behaviour of PV panels is given, followed by the parameter determination for the five-parameter single-exponential model based on datasheet values, which has been used for the implementation of a PV simulator taking in account the shape, size ant intensity of partial shadow in respect to bypass diodes.
In order to eliminate the iterative calculations for parameter determinations, a simplified three-parameter model is used throughout Chapter 4, dedicated to diagnostic functions of PV panels. Simple analytic expressions for the model important parameters, which could reflect deviations from the normal (e.g. from datasheet or reference measurement) I −V characteristic, is proposed.
A considerable part of the thesis is dedicated to the diagnostic functions of crystalline photovoltaic panels, aimed to detect failures related to increased series resistance and partial shadowing, the two major factors responsible for yield-reduction of residential photovoltaic systems.
Combining the model calculations with measurements, a method to detect changes in the panels’ series resistance based on the slope of the I − V curve in the vicinity of open-circuit conditions and scaled to Standard Test Conditions (STC) , is proposed. The results confirm the benefits of the proposed method in terms of robustness to irradiance changes and to partial shadows.
In order to detect partial shadows on PV panels, a method based on equivalent thermal voltage (Vt) monitoring is proposed. Vt is calculated using the simplified three-parameter model, based on experimental curve. The main advantages of the method are the simple expression for Vt, high sensitivity to even a relatively small area of partial shadow and very good robustness against changes in series resistance.
Finally, in order to quantify power losses due to different failures, e.g. partial shadows or increased series resistance, a model based approach has been proposed to estimate the panel rated power (in STC). Although it is known that the single-exponential model has low approximation precision at low irradiation conditions, using the previously determined parameters it was possible to achieve relatively good accuracy. The main advantage of the method is that it relies on already determined parameters (Rsm, Vt) based on measurements, therefore reducing the errors introduced by the limitation of the single-exponential model especially at low irradiation conditions.
OriginalsprogEngelsk
Udgivelses stedAalborg
UdgiverInstitut for Energiteknik, Aalborg Universitet
Antal sider189
ISBN (trykt)978-87-89179-76-6
StatusUdgivet - 2009

Download-statistik

Ingen data tilgængelig
ID: 19704664