Data processing and analytics for a power system with renewable generation
Due to the intermittent nature of solar photovoltaic power generation and its impact on the power system, there is a need to estimate solar photovoltaic (PV) output power to study and prepare the power system to handle this renewable form of energy. This project provides an efficient method to es...
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| Format: | Final Year Project (FYP) |
| Language: | English |
| Published: |
2019
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| Online Access: | http://hdl.handle.net/10356/78125 |
| Summary: | Due to the intermittent nature of solar photovoltaic power generation and its impact on
the power system, there is a need to estimate solar photovoltaic (PV) output power to
study and prepare the power system to handle this renewable form of energy. This
project provides an efficient method to estimate solar PV output power via the forming
of a mathematical model by curve fitting. This model can calculate and obtain power
output fluctuations from the frequency data of the power system. A simulation model
that represents a typical power system is formed for simple reference and
understanding of the various components in the power system. The frequency of the
power system is measured using a frequency disturbance recorder (FDR), which can
accurately measure frequency data from up to 4 significant figures and obtain several
data for easy reference. This frequency data is cured from any anomalies and missing
data that may affect the accuracy of results obtained through the use of the linear
interpolation method. By generating a code in MATLAB based on this model, the solar
PV output fluctuations at any given time and day can be obtained and calculated
efficiently. The variables controlled in this project is that the day and the time
measured must be similar when selecting the frequency and load data for calculation. |
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