Search

Under the dual-carbon target, hydrogen energy, as a zero-carbon secondary energy source, has great scope for replacing fossil feedstocks in the fields of energy, transportation and industry. However, the current research on the competitiveness of hydrogen energy in various fields is not sufficiently addressed. In this paper, we use the LEAP model to predict the future scale of hydrogen use and the two-factor learning curve to predict the trend of hydrogen price change from 2025 to 2050, using Qinghai Province as the research background. At the same time, considering the carbon emission reduction benefits and raw material costs, the competitiveness of hydrogen energy in energy, transportation, industry and other fields in the future is compared. The results show that: 1) The hydrogen load scale in Qinghai Province will grow fast from 2025 to 2030. From 2030 to 2040, it slows under the steady and basic scenarios but remains high under the accelerated one. By 2040, the consumption scales are 1.057 million, 649,000 and 442,000 tons respectively. 2) The price of hydrogen energy will drop rapidly from the current 28 CNY/kg to about 20 CNY/kg in the next 5 years. By 2040, the price of hydrogen energy will be reduced to about 17 CNY/kg. 3) In terms of hydrogen energy competitiveness, when carbon emissions are not taken into account, hydrogen energy is currently competitive in the transportation field. During 2032-2038, it will be competitive in the field of methanol synthesis. By 2040, hydrogen energy will not be competitive in the fields of ammonia synthesis and power/heating. When considering carbon emissions, the competitiveness of hydrogen energy in the transportation field will become greater. The competitive year in the field of methanol synthesis will be 1-2 years ahead. By 2040, it will not be competitive in the field of synthetic ammonia and power/heating, but the gap will be significantly reduced due to the consideration of carbon emissions. [ABSTRACT FROM AUTHOR]

Against the backdrop of increasingly prominent environmental issues, new energy consumption issues, and energy supply and demand balance issues, the optimization of multi time scale operation of distributed electro hydrogen coupling systems has become a research focus. Based on this, this article optimizes the multi time scale operation of a distributed electric hydrogen coupling system that takes into account grid interaction. By designing a system framework for distributed electro hydrogen coupling systems, operational strategies for each system were proposed. Analyzed the uncertainty and response characteristics of wind and solar power generation units and load demand, and constructed a multiple uncertainty model for distributed electric hydrogen coupling system. At the same time, a three stage, multi time scale operation optimization model of the electric hydrogen coupling system was constructed based on the response characteristics of the distributed electric hydrogen coupling system. The construction of these models reduced scheduling costs by 12.55% and increased clean energy consumption rate by 13.50%. [ABSTRACT FROM AUTHOR]

To optimize the energy supply potential and complementary advantages of distributed energy, this paper focuses on the dispatching optimization of cogeneration virtual power plant considering uncertainty. First of all, wind power, photovoltaic, combined heat and power (CHP) units, electric boilers, and controllable loads are integrated into a CHP virtual power plant. Then, carbon capture and electric-to-gas devices are introduced to realize carbon recycling. Furthermore, quantify the risk of real-time dispatching of virtual power plants through uncertainty scenario generation and conditional value at risk (CVaR) theory, and the multi-objective stochastic dispatching optimization model of virtual power plants is built with the aim at minimizing the operation cost, carbon emissions, and operation risk as the objectives, and the CRITIC weighting method is adopted to solve it. Finally, the calculation results show that: 1) the electric boiler can use wind and photovoltaic power to supply heat for the system, reduce the dependence ofthe virtual power plant (VPP) on the CHP unit, and make the electric output of the unit more flexible. 2) The risk quantification method proposed can fully measure the risk situation in real-time dispatching, arrange the wind and photovoltaic power generation plan and backup plan more reasonably, and enable the VPP to get more benefits while avoiding the risks in real-time dispatching. [ABSTRACT FROM AUTHOR]

Taking an industrial park as an example, this study aims to analyze the characteristics of a distribution network that incorporates distributed energy resources (DERs). The study begins by summarizing the key features of a distribution network with DERs based on recent power usage data. To predict and analyze the load growth of the industrial park, an improved back-propagation algorithm is employed. Furthermore, the study classifies users within the industrial park according to their specific power consumption and supply requirements. This user segmentation allows for the introduction of three constraints: node voltage, wire current, and capacity of DERs. By incorporating these constraints, the study constructs an optimization model for the distribution network in the industrial park, with the objective of minimizing the total operation and maintenance cost. The primary goal of these optimizations is to address the needs of DERs connected to the distribution network, while simultaneously mitigating their potential adverse impact on the network. Additionally, the study aims to enhance the overall energy efficiency of the industrial park through more efficient utilization of resources. [ABSTRACT FROM AUTHOR]

Based on the PM6:Y6 binary system, a novel non-fullerene acceptor material, D18-Cl, was doped into the PM6:Y6 blend to fabricate the active layer. The effects of different doping ratios of D18-Cl on organic solar cells were investigated. The best-performing organic solar cell was achieved when the doping ratio of D18-Cl reached 20 wt%. It exhibited a short-circuit current of 28.13 mA/cm2, a fill factor of 70.25%, an open-circuit voltage (Voc) of 0.81 V, and a power conversion efficiency of 16.08%. The introduction of an appropriate amount of D18-Cl expanded the absorption spectrum of the active layer, improved the morphology of the active layer, reduced large molecular aggregation and defects, minimized bimolecular recombination, and optimized the collection efficiency of charge carriers. These results indicate the critical importance of selecting an appropriate third component in binary systems and optimizing the doping ratio to enhance the performance of ternary organic solar cells. [ABSTRACT FROM AUTHOR]

Summary: With the continuous opening of China's electricity market, a large number of third‐party electricity retailers have poured into the electricity market. Electricity retailers are the bridge between the main player of the electricity market. In view of the large number and variety of electricity retailers in the current electricity market, this paper divides the electricity retailers that have been publicized in China into five categories. In view of the uncertainty of the credit evaluation standard of electricity retailers, this paper determines the cloud model scale of the risk level of the electricity retailers; selects three primary indicators, eight secondary indicators, and 20 tertiary indicators to construct the credit risk evaluation indicator system of the electricity retailer. This paper also builds a computing model combining intuitionistic fuzzy analytic hierarchy process (IFAHP) with cloud model; obtains the final evaluation score by combining the certainty of cloud model with intuitionistic fuzzy weight, the qualitative to quantitative change of the indicator is realized, and makes the fuzzy concept of credit rating of electricity retailers get a quantitative change. From the model results, it can be seen that the risk score of the electricity grid asset retailers is 14.8666, which is the lowest risk; the independent electricity retailers has a risk score of 26.9706, which is the highest risk. Compared with the traditional AHP‐cloud model, this method is not only more objective, but also can obtain more information such as the distribution of index values from entropy and hyper entropy. [ABSTRACT FROM AUTHOR]

As an efficient way to deal with the exhaustion of traditional fossil fuels, new energy power generation has obtained much attention from the Chinese Government. In this context, more and more new energy power generation groups that consist of large numbers of regional enterprises have been founded and developed rapidly. However, researches related to comprehensive benefit evaluation of group-affiliated new energy power generation enterprises is still blank in China, which will hinder the benefit growth and sustainable development of such enterprises. A novel hybrid evaluation indicator system is proposed from both perspectives of sustainability and the internal management within the groups. Considering the preference information given on each of the indicators is featured by multi-source and multi-form, an evaluation framework to integrate the blended and complex evaluation information is designed. In addition, different from previous studies, this paper employs a combined technique of Stochastic Transformation for Blended Information (STBI) method and the Technique for Order Preference by Similar to Ideal Solution (TOPSIS) to simulate the evaluation process and rank the comprehensive benefit of evaluation objects. It can efficiently handle the comprehensive evaluation problems with blended and complex evaluation information and preserve the initial evaluation information to the utmost simultaneously. Finally, this paper applied the evaluation model to empirical research and the results show that the model meets the actual situation of the new energy power generation group and can provide a certain reference value. [ABSTRACT FROM AUTHOR]