KEYWORDS: Risk assessment, Data modeling, Wind speed, Statistical modeling, Power consumption, Design and modelling, Solar energy, Education and training, Wind turbine technology, Wind energy
With the trend of clean energy gradually replacing traditional energy as the main energy, the risk assessment of the electric energy spot market is facing new characteristics. Firstly, the paper analyzes the risk characteristics brought about by the two new features of the high-proportion clean energy spot market, the time-of-use price signal of electric energy is not clear, and the cross-regional electricity market and the multi-electricity commodity market are coupled together. And then a risk transmission chain for clean energy units is built to participate in the power spot market. Secondly, a risk assessment model based on CEEMDAN-LSTM for the high proportion of clean energy electricity spot market is constructed. Among them, the CEEMDAN method solves the problem that the risk factor sequence in the high proportion of clean energy electricity spot market is non-stationary and it is difficult to extract new features of the cycle. The LSTM model fully identifies the time-dependent characteristics of risk factors. Finally, the paper verifies the model based on the actual market data.
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