In the process of building a new power system with new energy sources as the mainstay, wind power and photovoltaic energy enter the multiplication stage with randomness and uncertainty, and the foundation and support role of large-scale long-time energy storage is highlighted. Considering the advantages of hydrogen energy storage in large-scale, cross-seasonal and cross-regional aspects, the necessity, feasibility and economy of hydrogen energy participation in long-time energy storage under the new power system are discussed. Firstly, power supply and demand production simulations were carried out based on the characteristics of new energy generation in China. When the penetration of new energy sources in the new power system reaches 45%, long-term energy storage becomes an essential regulation tool. Secondly, by comparing the storage duration, storage scale and application scenarios of various energy storage technologies, it was determined that hydrogen storage is the most preferable choice to participate in large-scale and long-term energy storage. Three long-time hydrogen storage methods are screened out from numerous hydrogen storage technologies, including salt-cavern hydrogen storage, natural gas blending and solid-state hydrogen storage. Finally, by analyzing the development status and economy of the above three types of hydrogen storage technologies, and based on the geographical characteristics and resource endowment of China, it is pointed out that China will form a hydrogen storage system of “solid state hydrogen storage above ground and salt cavern storage underground” in the future.

This paper presents a doubly fed induction generator (DFIG) wind power system with hydrogen energy storage, with a focus on its virtual inertia adaptive control. Conventionally, a synchronous generator has a large inertia from its rotating rotor, and thus its kinetic energy can be used to damp out fluctuations from the grid. However, DFIGs do not provide such a mechanism as their rotor is disconnected with the power grid, owing to the use of back-to-back power converters between the two. In this paper, a hydrogen energy storage system is utilized to provide a virtual inertia so as to dampen the disturbances and support the grid’s stability. An analytical model is developed based on experimental data and test results show that: (1) the proposed method is effective in supporting the grid frequency; (2) the maximum power point tracking is achieved by implementing this proposed system; and, (3) the DFIG efficiency is improved. The developed system is technically viable and can be applied to medium and large wind power systems. The hydrogen energy storage is a clean and environmental-friendly technology, and can increase the renewable energy penetration in the power network.

Hydrogen energy leads us in an important direction in the development of clean energy, and the comprehensive utilization of hydrogen energy is crucial for the low-carbon transformation of the power sector. In this paper, the demand for hydrogen energy in various fields is predicted based on the support vector regression algorithm, which can be converted into an equivalent electrical load when it is all produced from water electrolysis. Then, the investment costs of power generators and hydrogen energy equipment are forecast considering uncertainty. Furthermore, a planning model is established with the forecast data, initial installed capacity and targets for carbon emission reduction as inputs, and the installed capacity as well as share of various power supply and annual carbon emissions as outputs. Taking Gansu Province of China as an example, the changes of power supply structure and carbon emissions under different scenarios are analysed. It can be found that hydrogen production through water electrolysis powered by renewable energy can reduce carbon emissions but will increase the demand for renewable energy generators. Appropriate planning of hydrogen storage can reduce the overall investment cost and promote a low carbon transition of the power system.

Green hydrogen is used as fuel or raw material in power systems, transportation, and industry, which is expected to curb carbon emissions at the root. First, a unified energy system consisting of clean power generation systems, hydrogen energy systems (HESs), and transmission systems was proposed, and the characteristics of hydrogen load in different fields are analyzed. Possible business models for HESs in industry and transportation are then presented, cost and benefit functions for stakeholders of HES were created, and a business model with multi-party participation was modeled as a multi-objective optimization model. In a power system, the business model of combining two operating modes for hydrogen storage was proposed at the power generation side as well. Finally, three HESs were designed for a chemical plant with a hydrogen demand of 1000 Nm³/h, a hydrogen refueling station with a daily hydrogen load of 600 kg, and a 100% clean power generation system, respectively. The results of the case study show that one or more feasible business models (i.e., all stakeholders are profitable) can be found in both industrial and transportation by the HES planning approach proposed, while the internal rate of return of HES installed on the generation side is less than 5% due to high investment cost at this stage and low utilization rate; nonetheless, the profitable strategies are shown by 3D graphics.

With the increasing penetration of renewable energy in power systems, fluctuation of renewable energy power plants has great influence on stability of the system, and renewable power curtailment is also becoming more and more serious due to the insufficient consumptive ability of local power grid. In order to maximize the utilization of renewable energy, this paper focuses on the generation scheduling optimization for a wind-solar-thermal hybrid system considering that the produced energy will be transmitted over a long distance to satisfy the demands of the receiving end system through ultra-high voltage (UHV) transmission lines. Accordingly, a bilevel optimization based on a non-cooperative game method is proposed to maximize the profit of power plants in the hybrid system. Users in the receiving end system are at the lower level of the bilevel programming, and power plants in the transmitting end system are at the upper level. Competitive behavior among power plants is formulated as a non-cooperative game and the profit of power plant is scheduled by adjusting generation and bidding strategies in both day-ahead markets and intraday markets. In addition, generation cost, wheeling cost, and carbon emissions are all considered in the non-cooperative game model. Moreover, a distributed algorithm is presented to obtain the generalized Nash equilibrium solution, which realizes the optimization in terms of maximizing profit. Finally, several simulations are implemented and analyzed to verify the effectiveness of the proposed optimization method.

This paper presents a wind-methanol-fuel cell system with hydrogen storage. It can manage various energy flow to provide stable wind power supply, produce constant methanol, and reduce CO₂ emissions. Firstly, this study establishes the theoretical basis and formulation algorithms. And then, computational experiments are developed with MATLAB/Simulink (R2016a, MathWorks, Natick, MA, USA). Real data are used to fit the developed models in the study. From the test results, the developed system can generate maximum electricity whilst maintaining a stable production of methanol with the aid of a hybrid energy storage system (HESS). A sophisticated control scheme is also developed to coordinate these actions to achieve satisfactory system performance.