Search

In recent years, China has promoted many new energy projects in order to meet the growing demand for electricity. Therefore, China's offshore wind power installed capacity has grown rapidly. China has a long coastline and abundant offshore wind energy resources. Offshore wind power is an important area for the development of renewable energy, which can promote wind power technology advancement and energy structure adjustment. Therefore, conducting effective research and forecast on the cumulative installed capacity of China's offshore wind power will help the government to rationally deploy and reduce the risk of investment in offshore wind power. In order to accurately predict the future prospects of offshore wind power in China, this paper firstly constructed a set of influencing factors and used gray correlation analysis to screen the main influencing factors. Then, this paper proposed a novel forecasting model named e‐VMD‐PCA‐RELM. The algorithm is based on the traditional RELM (robust extreme learning machine) algorithm, which effectively processes the noise information through the PCA (principal component analysis) algorithm, and extracted the feature elements of the RELM hidden layer to reduce the information redundancy. At the same time, the e‐VMD (variational mode decomposition optimized by entropy) algorithm is used to decompose the original time series to obtain multiple components. By comparing with the other forecasting algorithms, it is proved that the proposed forecasting model has strong generalization ability and has achieved good prediction result. Finally, the e‐VMD‐PCA‐RELM model is used to predict the scale of offshore wind farms in China from 2019 to 2035. We find that the cumulative installed capacity of China's offshore wind power will exceed 60 GW in 2035, and the installed capacity will increase year by year. In 2030, there will be a large increase, with a relative growth rate of 20%. [ABSTRACT FROM AUTHOR]

With the promulgation and implementation of a large number of renewable energy policies in China, the rapid development of renewable energy is accompanied by the prominent phenomenon of renewable energy abandoning wind and light. Energy storage technology is the key technology to promote the consumption of renewable energy. The government can promote the energy storage technology through the incentive policy of energy storage industry. Firstly, content analysis method is used to analyze China's energy storage policy, and five incentive policies for promoting energy storage technology are obtained. Secondly, built a game model of energy storage technology promotion based on the evolutionary game theory. Finally, use MATLAB software for numerical simulation. Numerical simulation results show that: (a) When the local government chooses to promote less, energy enterprises will eventually adopt the nonconfigure strategy; (b) when the local government chooses to promote more vigorously, energy enterprises will finally adopt the configure strategy; (c) increase in the total electricity sold by energy enterprises with energy storage devices, the sales price of energy stored per unit, the compensation price of energy stored per unit, tax relief standards, and incentive costs of local governments can promote energy enterprises to choose configure strategies; and (d) the reduction of unit energy storage cost, configure cost, and comprehensive tax rate can promote energy enterprises to choose configure strategy. [ABSTRACT FROM AUTHOR]