Short-Term Photovoltaic Power Generation Forecasting Based on Multivariable Grey Theory Model with Parameter Optimization

Owing to the environment, temperature, and so forth, photovoltaic power generation volume is always fluctuating and subsequently impacts power grid planning and operation seriously. Therefore, it is of great importance to make accurate prediction of the power generation of photovoltaic (PV) system in advance. In order to improve the prediction accuracy, in this paper, a novel particle swarm optimization algorithm based multivariable grey theory model is proposed for short-term photovoltaic power generation volume forecasting. It is highlighted that, by integrating particle swarm optimization algorithm, the prediction accuracy of grey theory model is expected to be highly improved. In addition, large amounts of real data from two separate power stations in China are being employed for model verification. The experimental results indicate that, compared with the conventional grey model, the mean relative error in the proposed model has been reduced from 7.14% to 3.53%. The real practice demonstrates that the proposed optimization model outperforms the conventional grey model from both theoretical and practical perspectives

Stochastic symplectic ice

In this paper, we construct solvable ice models (six-vertex models) with stochastic weights and U-turn right boundary, which we term "stochastic symplectic ice". The models consist of alternating rows of two types of vertices. The probabilistic interpretation of the models offers novel interacting particle systems where particles alternately jump to the right and then to the left. Two colored versions of the model and related stochastic dynamics are also introduced. Using the Yang-Baxter equations, we establish functional equations and recursive relations for the partition functions of these models. In particular, the recursive relations satisfied by the partition function of one of the colored models are closely related to Demazure-Lusztig operators of type C.Comment: 35 page

Short-Term Photovoltaic Power Generation Forecasting Based on Multivariable Grey Theory Model with Parameter Optimization

Owing to the environment, temperature, and so forth, photovoltaic power generation volume is always fluctuating and subsequently impacts power grid planning and operation seriously. Therefore, it is of great importance to make accurate prediction of the power generation of photovoltaic (PV) system in advance. In order to improve the prediction accuracy, in this paper, a novel particle swarm optimization algorithm based multivariable grey theory model is proposed for short-term photovoltaic power generation volume forecasting. It is highlighted that, by integrating particle swarm optimization algorithm, the prediction accuracy of grey theory model is expected to be highly improved. In addition, large amounts of real data from two separate power stations in China are being employed for model verification. The experimental results indicate that, compared with the conventional grey model, the mean relative error in the proposed model has been reduced from 7.14% to 3.53%. The real practice demonstrates that the proposed optimization model outperforms the conventional grey model from both theoretical and practical perspectives

Combustion Instability of Swirl Premixed Flame with Dielectric Barrier Discharge Plasma

The effects of plasma on the combustion instability of a methane swirling premixed flame under acoustic excitation were investigated. The flame image of OH planar laser-induced fluorescence and the fluctuation of flame transfer function showed the mechanism of plasma in combustion instability. The results show that when the acoustic frequency is less than 100 Hz, the gain in flame transfer function gradually increases with the frequency; when the acoustic frequency is 100~220 Hz, the flame transfer function shows a trend of first decreasing and then increasing with acoustic frequency. When the acoustic frequency is greater than 220 Hz, the flame transfer function gradually decreases with acoustic frequency. When the voltage exceeds the critical discharge value of 5.3 kV, the premixed gas is ionized and the heat release rate increases significantly, thereby reducing the gain in flame transfer function and enhancing flame stability. Plasma causes changes in the internal recirculation zone, compression, and curling degree of the flame, and thereby accelerates the rate of chemical reaction and leads to an increase in flame heat release rate. Eventually, the concentration of OH radicals changes, and the heat release rate changes accordingly, which ultimately changes the combustion instability of the swirling flame