Probabilistic evaluation of wind and solar photovoltaic energy production

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Dr. Hartmann Bálint
Department of Electric Power Engineering

The difficulty of integrating solar panels and wind power plants into the power system is partly the stochastic aviability of the renewable energy sources. Because of the unpredictable energy production we cannot forecast the effects affecting the network – like the conventional power plants – either. Beside this the renewable energy using power plants also have to meet the requirements of connecting to the network.

The energy producion of the nuclear and fossils using power plants can be simulated with appropriate accuracy. We can give proper estimation with changing the step-by-step production for example: with stopping one block we can observe the change of produced energy and fluctuations in Power Delivery Systems.

The wind speed can fluctuate even within hours and this also affects the energy production. The treatment of this variability is different from the most traditional sources of energy, the latter is typically constant use, while wind power is not the result of a stable, constant flow. Examinating the wind of given sites uses a statistical method to approximate variability: every location has different capabilities. Since the energy produced is proportional to the cube of the wind speed, the annual energy output vary significantly between individual sites. Areas with high-speed-, constant-force wind allow higher annual energy production.

The study of solar energy is based on the so-called solar constant, which indicates the amount of radiation reaching the boundary of Earth's atmosphere. The amount of extractable energy from the solar cell’s surface in given timelapse depends on many things: season; time of day; latitude, altitude above sea level; the specific weather conditions: humidity, ambient temperature, wind speed, cloud coverage.

If we could predict the daily energy production of solar cells and wind turbines, the conventional power plants could have been replaced. This requires more accurate weather forecast, and in-depth examination about their effects on energy production and consequences of their integration. We can distinguish deterministic and stochastic effects during the analysis. These impacts are studied in my master's thesis.


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