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Rapidly increasing the proportion of installed wind power capacity with zero carbon emission characteristics will help adjust the energy structure and support the realization of carbon neutrality targets. The intermittency of wind resources and fluctuations in electricity demand has exacerbated the contradiction between power supply and demand. The time-of-use pricing and supply-side allocation of energy storage power stations will help “peak shaving and valley filling” and reduce the gap between power supply and demand. To this end, this paper constructs a decision-making model for the capacity investment of energy storage power stations under time-of-use pricing, which is intended to provide a reference for scientific decision-making on electricity prices and energy storage power station capacity.

Based on the research framework of time-of-use pricing, this paper constructs a profit-maximizing electricity price and capacity investment decision model of energy storage power station for flat pricing and time-of-use pricing respectively. In the process, this study considers the dual uncertain scenarios of intermittency of wind resources and random fluctuations in power demand.

(1) Investment in energy storage power stations is the optimal decision. Time-of-use pricing will reduce the optimal capacity of the energy storage power station. (2) The optimal capacity of the energy storage power station and optimal electricity price are related to factors such as the intermittency of wind resources, the unit investment cost, the price sensitivities of the demand, the proportion of time-of-use pricing and the thermal power price. (3) The carbon emission level is affected by the intermittency of wind resources, price sensitivities of the demand and the proportion of time-of-use pricing. Incentive policies can always reduce carbon emission levels.

This paper creatively introduced the research framework of time-of-use pricing into the capacity decision-making of energy storage power stations, and considering the influence of wind power intermittentness and power demand fluctuations, constructed the capacity investment decision model of energy storage power stations under different pricing methods, and compared the impact of pricing methods on optimal energy storage power station capacity and carbon emissions.

1. Electricity pricing and capacity of energy storage power stations in an uncertain electricity market.

2. Investment strategy of energy storage power stations on the supply side of wind power generators.

3. Impact of pricing method on the investment decisions of energy storage power stations.

4. Impact of pricing method, energy storage investment and incentive policies on carbon emissions.

5. A two-stage wind power supply chain including energy storage power stations.

Electricity pricing and capacity of energy storage power stations in an uncertain electricity market.

Investment strategy of energy storage power stations on the supply side of wind power generators.

Impact of pricing method on the investment decisions of energy storage power stations.

Impact of pricing method, energy storage investment and incentive policies on carbon emissions.

A two-stage wind power supply chain including energy storage power stations.

Based on the background of enterprise digital transformation, this paper aims to examine the impact of digitization on the cooperative behavior and environmental performance of green technology innovation.

By constructing a model of quantity competition between the two enterprises, this paper examines the impact of digitization on the cooperative behavior and environmental performance of green technology innovation from the micro level. It uses Shanghai and Shenzhen A-share-listed companies as research samples. An unbalanced panel data set from 2011 to 2018 was constructed to empirically test the effect of digital transformation on the environmental performance of enterprises.

The findings reveal the following. First, digital transformation can significantly improve the environmental performance of enterprises. Second, green technological innovation sharing plays an intermediary role between digital transformation and enterprise environmental performance. Third, when the level of digitization is high, the sharing effect of green technology innovation brought about by digital technology is stronger and enterprises tend to carry out cooperative green technology innovation. Lastly, the level of development of regional science and technology finance plays a positive regulatory role in digital transformation and enterprise environmental performance.

This paper first proposes that green technology innovation-sharing is an important mechanism that can significantly improve enterprises' environmental performance. The authors empirically examine the mechanism and analyze the heterogeneity of the impact of digitalization level on enterprises' environmental performance. The authors also discuss the moderating effect of regional technology and finance development levels on the relationship between digitalization and enterprises' environmental performance.

Because of the rapid progress of global value chains (GVCs), it is worthwhile to study their impact on innovation. This study aims to explore the impact of GVC position of high-tech industries in the developing-country context of China on innovation performance; it also aims to explore the moderating effects of industrial agglomeration (specialization agglomeration and diversification agglomeration) on the relationship between GVC position and innovation performance.

The study is based on data gathered on Chinese high-tech industries in 30 provinces from the 2005–2015 period. The econometric analysis relies on merged data from the China Premium Database and the Trade in Value Added 2018 Database.

The regression results show that GVC position of China’s high-tech industries significantly affects their innovation performance, and both specialization agglomeration and diversification agglomeration significantly enhance the positive relationship between GVC position and innovation performance of China’s high-tech industries. After dividing the country into coastal and inland regions, new findings appear.

This study highlights the importance of GVC position and its effect on innovation performance of China’s high-tech industries. It contributes to the literature on the relationship between GVCs and innovation by elaborating on the moderating effects of industrial agglomeration on this relationship.