In the context of the national strategy of "Dual Carbon"，CNPC innovatively proposes Green and Low-Carbon Action Plan 3.0 and establishes a three-step development strategy of "clean substitution，strategic replacement and green transformation". Supported by the high-quality integrated development of oil and gas and new energy，the strategy focuses on solving the dual challenges of energy industry development and carbon emission reduction and provides a practical path for the construction of a new energy system. As oil and gas and new energy belong to different energy fields，their integrated development is associated with numerous challenges，such as instability of efficient and low-carbon supply of oil and gas，insufficient support to replacement by new energy，and deficient depth of collaborative transformation of oil and gas and new energy. As an important hydrocarbon resource base in China，Xinjiang Oilfield play a key role in ensuring national energy security. It is imperative to leverage the inherent advantages of Xinjiang Oilfield and rely on three major paths，namely strengthening the green and low-carbon development of oil and gas，accelerating the development of new energy industry and enhancing the all-round security of oil and gas，and 12 measures，including energy conservation and efficiency improvement，clean substitution，regional energy supply，large-scale export，and basic research，to explore a green and low-carbon transformation path that is in line with the reality of Xinjiang Oilfield and has oilfield characteristics.

The world is now in a critical period of energy structure transformation，oil and gas fields as large energy consumers are seen with accelerated green and low carbon transition. Electrochemical energy storage，as a vital technical category for steady applications of new energy such as wind and photovoltaic power in oil and gas fields，is considered increasingly important. This paper introduces the working principles and electrochemical characteristics and current research status of various electrochemical energy storage technologies （lithium iron phosphate，lithium titanate，flow batteries，lead-acid batteries，and supercapacitors）. According to their technical characteristics，their favorable scenarios，application scales and typical application cases have been sorted out，in terms of enhancing renewable energy consumption and optimizing traditional energy production and energy use. In view of the harsh environments of oil and gas scenarios featuring high risks，strong corrosion，and wide temperature ranges （-30~60℃），the challenges faced by the system and the problems that need to be solved urgently are analyzed in terms of the system safety，reliability，and environmental adaptability. This paper further elaborates the future development trend of each energy storage technology in oil and gas scenarios from the perspectives of new energy storage material systems，intelligent energy storage system management and equipment development. The findings of this research provide references for promoting the synergistic multi-energy development of wind and photovoltaic power and energy storage，forming a more efficient energy utilization system，and accelerating the green transformation of traditional energy.

With the increasing penetration of photovoltaic （PV） generation into power systems，the randomness and uncertainty of its output have raised higher requirements for the flexible peak regulation capability of grids. To offer more accurate predicted scenarios and facilitate　flexibility oriented dispatch，an intelligent method integrating fuzzy clustering，similar day extraction，and probabilistic prediction was developed. Highly correlated meteorological variables including temperature，humidity，global horizontal irradiance，and tilted irradiance were first identified using the Pearson correlation coefficient. Fuzzy C-means （FCM） clustering was then applied to classify weather types. Feature weights were determined using the CRITIC method，and similar days within each weather category were extracted based on weighted Euclidean distance to construct a high quality training dataset. A quantile regression long short-term memory （QRLSTM） network was subsequently employed to perform short-term probabilistic forecasting of PV output. Simulation results demonstrated that the proposed approach achieved high prediction accuracy　across various weather conditions，with confidence interval coverage rates exceeding 90% and significantly reduced confidence interval ranges compared to those of benchmark models. It was concluded that the proposed method effectively enhances the reliability and robustness of PV power prediction and provides high quality scenario support for uncertainty aware dispatch in multi-energy complementary systems.

As an essential link connecting resource potential and practical applications，the planning and design of microgrid，especially the rational configuration of the models and capacities of wind turbines，photovoltaic （PV） panels，and energy storage systems，is particularly crucial. To meet the load demand and reduce both investment costs and annual average comprehensive costs of microgrid，an economic capacity matching model considering the joint model selection of wind turbines，PV panels and energy storage equipment is proposed. Firstly，a microgrid system model is constructed，which includes wind turbines，PV panels，and energy storage. Secondly，a mixed integer linear programming model is designed with the objective function of minimal comprehensive costs of micro-grids is developed，which incorporates equipment selection constraints，capacity constraints，operation constraints，and power and energy balance constraints. Finally，the optimal equipment model combination and capacity configuration scheme are obtained using a commercial solver. The case study shows that compared with the benchmark schemes 2 and 3，the optimized scheme 1 reduces the investment cost by 21.01% and 17.25% respectively，and the comprehensive cost by 18.6% and 14.81% respectively，while meeting the same load demand. Therefore，the results prove that the proposed model can effectively accomplish the economic selection of equipment and capacity matching，reduce the investment cost and annual average comprehensive cost of microgrid，and provide the theoretical basis and technical support for the planning and design of microgrid.

To mitigate climate change by reducing CO₂ emission，carbon capture，utilization，and storage （CCUS） technologies have garnered significant attention. However，the required large scale investment and inflexibility of CCUS projects have greatly hindered their widespread applications. In this context，systematic source-sink matching has emerged as a key research focus，as scientific and efficient matching can optimize pipeline network design and reduce the overall costs of CCUS implementation. To this end，this study proposes a CCUS pipeline network layout optimization method using Density-Based Spatial Clustering of Applications with Noise （DBSCAN），offering a solution for CCUS pipeline network design. Firstly，the DBSCAN clustering is employed to cluster emission sources and storage sinks. Subsequently，a CCUS source-sink matching model is developed based on the minimum spanning tree method after comprehensively considering source-sink characteristics and cost components across operational phases to generate theoretical CCUS matching schemes. Finally，to address pipeline redundancy caused by multi-sources to one-sink configurations，an improved saving algorithm is applied to optimize the CCUS source-sink matching scheme. A hypothetical planning region is presented for testing of the proposed method，which demonstrates that the model does not only reduce deployment costs but also significantly shortens transportation distances. Compared with traditional methods，the total deployment costs decrease from 130 billion CNY to 98 billion CNY，by a reduction of approximately 24.6%，while the transportation distance is reduced from 4 075 km to 1 008 km，marking a decrease of 75.3%. These findings validate the adaptability and economic efficiency of the proposed method in complex CCUS scenarios，and the proposed method provides a feasible optimization pathway and theoretical foundation for CCUS system planning.

Most of the oil and gas fields in China are located in remote areas with low ambient temperature throughout the year. It is necessary to heat the wellhead to prevent freezing. Micro catalytic burners can be used in many heating scenarios. However，methane alone is difficult to stably catalytically self-ignite at room temperature. By using China's abundant renewable energy such as wind power and photovoltaic power to produce green hydrogen and mix it with methane on precious metal Pt，catalytic self-ignition at room temperature can be achieved. Research on catalytic combustion of green hydrogen and methane mixed fuel is expected to play an important role in developing new techniques for wellhead anti-freezing and accelerate "low-carbonization" of energy. The reaction files of the catalytic reaction mechanism of hydrogen and methane mixed fuel on the surface of Pt catalyst are studied and imported into Fluent 2021R1 to build a three dimensional numerical computation model for the catalytic combustion of hydrogen and methane mixed fuel in micro-channels and explore the effects of the mixing ratio of hydrogen-methane and the synchronous and asynchronous supply of hydrogen and methane on the ignition of catalytic combustion. It is found that a low proportion of hydrogen leads to the deactivation of the catalyst，and a high proportion of hydrogen can trigger catalytic spontaneous combustion at room temperature. The synchronous supply mode is associated with a higher upper limit of the hydrogen proportion for catalyst deactivation and a smaller lower limit of the hydrogen proportion for catalytic spontaneous combustion. The simulation results show that the synchronous supply of hydrogen and methane，an inlet velocity of 1.0 m/s，a hydrogen and methane concentration ratio of 1∶1，and a micro-channel diameter of 1.5 mm are favorable for the catalytic self-ignition of hydrogen and methane mixed fuel. The performed numerical simulation reveals the catalytic self-ignition characteristics of green hydrogen and methane mixed fuel at room temperature and the evolution law of the ignition process，which lays a foundation for the application of such heating processes in oil and gas field production.

In the background of China's goals of "Dual Carbon"，hydrogen，as clean energy，is expected to be widely used；however，it leads to large carbon emissions in the production process. Hydrocarbon Steam Reforming （HSR） is a common pro- cess for hydrogen production in refineries，in which accurate carbon accounting is hard to perform，due to the high fluctuation of feed- stock and low frequency of monitoring of key carbon emissions data. In this paper，the hydrogen production process of a refinery was taken as an example，and the HSR model was built by Aspen Plus to analyze the impact of different process parameters on carbon emis- sions in order to address the lack of accurate carbon measurements. Due to the large variation of some important parameters in the actu- al production process，it is hard for a steady model to produce sufficiently accurate simulation data . This performed experiment inter- connected MATLAB with Aspen Plus and changed model input parameters in accordance with the actual production data to achieve the dynamic simulation of the production process. The experimental results verified that the proposed model can well simulate the actual hydrogen production process and thus，provide data support for accurate carbon accounting.

In the wave of global energy transition，the innovation of energy storage technology is extremely important for ensuring stable energy supply and sustainable development. Deep underground salt caverns have become the preferred storage space for energy resources such as oil，natural gas，and hydrogen，due to their characteristic stability and containment，with extensive applications across the world and significant application results. Compared to the oil blanket method for cavern construction，cavern construction with nitrogen dissolution inhibition is safer and more efficient，environment friendly and cost effective for salt cavern energy storage facilities. This paper focuses on the cavern construction technology with nitrogen dissolution inhibition for salt cavern energy storage and presents a comparative analysis of cavern construction techniques with oil and gas blanket for dissolution inhibition. The cavern construction with nitrogen dissolution inhibition is clarified，including the wellhead workflow modification，on-site nitrogen injection process，and gas-liquid interface monitoring and control technique. It also lists and investigates application cases in both China and other countries. Based on a thorough literature review，this paper concludes the important effects of cavern construction with nitrogen dissolution inhibition on improving the construction efficiency of gas storage，reducing costs，and protecting environment. Moreover，the future development trend of this technology is explored.