MODELING OF DISTRIBUTION LAWS FOR WIND TURBINE AND SOLAR BATTERY OUTPUT POWER

• Main Authors: Vadim Z. Manusov, Boris Yu. Lemeshko, Sherzod K. Khaldarov
• Format: Article
• Language: Russian
• Published: Tomsk Polytechnic University 2020-09-01
• Series: Известия Томского политехнического университета: Инжиниринг георесурсов
• Subjects: probability distribution laws; renewable energy sources; probabilistic output power; third kind of beta-distribution
• Online Access: http://izvestiya.tpu.ru/archive/article/view/2806/2305

Relevance. The power provided by generating stations based on wind and solar energy depends on the state of the environment at a particular geographical point, the prevailing wind speeds and the level of solar insolation. The wind speeds and solar insolation characterizing patterns are probabilistic in nature and depend on the terrain and season. This means that the power provided by generating stations based on renewable energy sources is also probabilistic. Risks associated with an inaccurate knowledge of the probabilistic patterns describing renewable energy sources, as well as the unpredictability (uncertainty) of the natural environment affecting renewable energy sources, are the reasons why system operators do not take into account such stations in calculating the power balance. This situation does not allow considering the generating stations as full-fledged market participants, covering the flow of investments in such projects. Accurate determination of the output power distribution laws for solar and wind power stations, based on the wind speed and solar insolation data analysis can significantly help system operators in power predicting of the power stations. Aim of study is building models of distribution laws that best describe the results of wind speed and solar insolation observations, as well as models of distribution laws for the generated power of wind and solar stations. Methods: methods for estimating the parameters of distribution laws, methods for testing statistical hypotheses. Results. It is shown, that the 3rd kind of beta distribution laws and their mixtures describe the series of measured wind speed and solar insolation better in the territory. The same concerning the probability distribution of the wind and solar stations power. Distribution law models for wind speed, solar insolation and power of the corresponding stations are constructed. It is shown that on the basis of the law of the distribution of wind speed and the mathematical relationships that connect power with wind speed, good models can be constructed for the probability distributions of power of wind power stations. The models can be used as an auxiliary tool for power system operators to predict output power.