With the continuous increase in the scale of new energy installations and their grid integration，the inherent randomness and volatility of new sources exacerbate grid frequency deviations and increase regulation pressure，posing a serious threat to system stability，security，and economic operation. To address this issue，this paper proposes a capacity optimization configuration strategy for hybrid energy storage systems（HESSs）that accounts for energy storage response characteristics and wind power fluctuation smoothing requirements. The method employs a HESS composed of advanced adiabatic compressed air energy storage（AA-CAES）and electrochemical energy storage. First，the input power of the HESS is decomposed using variational mode decomposition（VMD）. To reduce the impact of mode mixing on the accuracy of power decomposition，the parameters of the VMD algorithm are optimized using a differential evolution（DE）algorithm. Next，based on the response speed of AA-CAES，preliminary allocation boundaries are defined. Further，a secondary allocation of the hybrid energy storage power is performed with the goal of minimizing the comprehensive cost of the system. Finally，the proposed method is validated through case simulations. The results show that the proposed method reduces mode mixing during power decomposition，achieves reasonable power allocation among different energy storage systems，leverages the operational characteristics of various energy storage components，smooths wind power fluctuations，optimizes the capacity configuration of the HESS，and enhances the economic efficiency.

To support the construction of a new power system and achieve the Carbon Neutrality and Carbon Peaking goals， it is imperative to clarify the development path of next-generation coal-fired power generation technologies. Through literature review and analysis of technological routes， this study systematically identifies key supporting technologies for the efficient， flexible， low-carbon， and intelligent transformation of coal power. The research findings indicate that high-performance metallic materials are essential for ensuring safe and reliable operation under wide load conditions and frequent start-stop cycles. Technologies such as wide-load combustion combined with nitrogen oxides co-control， chemical looping combustion （CLC）， coal/biomass coupling， and green ammonia co-firing can significantly enhance regulation capabilities while reducing carbon emission intensity—where CLC can achieve carbon capture efficiencies exceeding 95%. The conclusion emphasizes that next-generation coal power must fulfill dual roles in “supply assurance” and “flexible regulation” By fostering multidimensional collaborative innovation across materials， combustion processes， fuels， and control systems， it is possible to ensure energy security while effectively supporting high proportions of renewable energy integration and facilitating a low-carbon transition in the electricity system.

To promote the low-carbon transition of gas turbine combined cycle （GTCC） systems， it is imperative to address key issues such as combustion instability and excessive nitrogen oxide （NOₓ） emissions caused by hydrogen-enriched combustion in gas turbines. This study conducts a systematic analysis through literature review on the differences in physical and chemical properties between hydrogen and natural gas， integrating principles of combustion kinetics and thermodynamics to examine the impact mechanisms of varying hydrogen blending ratios on combustion stability， emission characteristics， and cycle efficiency. Additionally， we outline the current development status of advanced hydrogen combustion technologies such as micro-mixed combustion and rich-hydrogen premixed combustion， while assessing their engineering applicability within typical GTCC systems. Furthermore， by incorporating materials science and structural mechanics considerations， we explore the failure risks associated with hydrogen embrittlement effects on critical components including compressors， turbine blades， and fuel nozzles under high-temperature and high-pressure conditions. Current research findings indicate that when the volumetric fraction of blended hydrogen exceeds 30%， traditional burners are prone to inducing thermoacoustic oscillations and localized hotspots， resulting in a significant increase in NOₓ emissions. However， employing advanced combustion strategies can mitigate NOₓ emissions while enhancing unit load-following capabilities. It is essential for key hot-end components to undergo material upgrades and structural optimizations to meet operational requirements for hydrogen fuels. Therefore， achieving high proportions of hydrogen blending or even pure hydrogen combustion in gas turbines necessitates a coordinated advancement in both innovative combustion technologies and adaptive modifications to overall system design. This approach will provide comprehensive technical pathways supporting the low-carbon transformation of gas turbines.

With the implementation of the “dual carbon” strategic goals，the proportion of offshore renewable energy is gradually increasing，raising higher demands for the integration of renewable energy in coastal power systems. In this context，underwater compressed air energy storage（UWCAES）has emerged as one of the key technologies to address the challenges of high proportions of renewable energy in coastal areas，due to its advantages such as large capacity，zero carbon emissions，and stable operating conditions. This paper proposes a configuration strategy for UWCAES considering multi-level gas storage arrangements. Firstly，based on the spatial distribution characteristics of gas storage in shallow and deep underwater areas，a multi-level compressed air energy storage model is established to enhance the operational flexibility of UWCAES. Secondly，aiming to maximize system benefits，a configuration model for multi-level compressed air storage is proposed，which takes into account constraints related to the operation of multi-level compressed air and system power balance. Subsequently，a genetic algorithm is employed to determine the depth and capacity of gas storage in both shallow and deep water areas，facilitating rapid acquisition of configuration results. Finally，simulation cases validate the effectiveness of the proposed configuration strategy. Compared to UWCAES operating at a single gas storage pressure level，the proposed multi-level UWCAES significantly improves the grid’s capability for renewable energy absorption and economic performance. The multi-level gas storage arrangement effectively enhances the regulation performance and economic advantages of UWCAES under complex operating conditions，and provides a practical technical path for the storage planning of coastal power systems with high proportion of renewable energy.

In the context of electricity market transactions， price forecasting has increasingly become an indispensable component of decision-making mechanisms for energy enterprises and serves as a crucial basis for market participants to formulate bidding strategies. Accurate electricity price forecasts assist various trading entities in the power market in reducing bidding risks and maximizing their interests. Therefore， researching electricity price forecasting holds significant importance. However， due to multiple influencing factors such as meteorological conditions， load demand， line congestion， and policy changes， electricity prices exhibit complex uncertainties and notable volatility. To address this issue， methods for predicting electricity prices have diversified over time. Nevertheless， challenges remain in achieving precise forecasts due to the scarcity of high-quality trading data and inherent flaws in prediction algorithms. This paper reviews relevant research findings on electricity price forecasting both domestically and internationally. Firstly， it analyzes the mechanisms behind price formation along with its influencing factors while summarizing related theoretical research methodologies. Secondly， it provides a detailed overview of recent advancements in electricity price forecasting methods by categorizing them into four main areas： time series prediction models， traditional machine learning models， deep learning models， and hybrid models； each method is discussed thoroughly with critical analysis. Finally， from perspectives including influencing factors， data preprocessing techniques， method selection criteria as well as evaluation metrics， this study anticipates future trends in electricity price forecasting.

In the context of carbon dioxide emission and carbon neutrality， as traditional power systems undergo transformation and upgrading towards new power systems， that has driven the explosive growth of a new generation of active energy agent （AEA） in distribution network， such as “photovoltaics， energy storage， virtual power plants， flexible loads， and electric vehicles”. However， the current electricity spot market is difficult to adapt to the differentiated physical and economic characteristics and diverse trading needs of various AEAs， and it is also challenging to clarify the additional environmental value of transactions. Against this backdrop， to quantify the contribution of AEA power generation and consumption mode to carbon emission reduction， firstly， a reputation evaluation model based on contract completion rate is proposed， with the AEA reputation value and transaction security verification results， the transaction sequence and transaction price are adjusted and updated. Then， allocation mechanism of environmental rights is designed based on regional dynamic carbon emission factors with power flow carbon label and morphological similarity index of user load-new energy resource （UL-NER） curves. Finally， to maximize social welfare， an energy block matching and clearing model is built， and the Gurobi optimization solver is utilized to solve the model. The results of case analysis and scheme comparison show that， trading mechanism not only increases AEA’s revenue and social benefits， but also enhances its ability to reduce carbon emissions.

Against the backdrop of the transition from dual control of energy consumption to dual control of carbon emissions， traditional planning methods based on energy balance are difficult to accurately assess the investment and operational costs of distribution networks. This paper presents a bi-level model of electric-carbon coupled planning for AC/DC distribution network for massive clean energy access. Firstly， this paper introduces an electric-carbon coupled planning methodology for AC/DC distribution networks and develops a upper-level mathematical model that couples AC/DC power flow with carbon emissions. The objective function of the model aims to minimize the combined “electricity + carbon” investment and operational costs， taking into account the full lifecycle carbon accounting of fossil energy consumed by distribution network across extraction， transportation， and combustion stages， as well as dynamic carbon emissions based on real-time network power losses. Secondly， addressing the challenge of carbon tax fluctuations in extreme scenarios， this paper constructs a lower-level mathematical model for carbon tax correction based on conditional value at risk （CVaR）， and proposes a CVaR-based carbon tax correction strategy and investigates a risk measurement approach that accounts for extreme carbon taxes. The corrected carbon tax values are then fed back into the upper-level planning model to further refine the planning strategy， ensuring adaptability to the impacts of extreme carbon tax fluctuations. Simulation results demonstrate that the proposed “electricity + carbon” AC/DC distribution network planning yields more accurate results compared to traditional AC network planning and exhibits superior adaptability to the impacts of extreme carbon tax fluctuations on planning outcomes.

The uncertainty of renewable energy output poses significant challenges to the optimization and scheduling of microgrids. At the same time， traditional optimization methods and scheduling time scales are too single， resulting in large errors in scheduling results， making it difficult to ensure the reliability and economy of system operation. A two-stage optimization operation strategy for microgrids based on K-nearest neighbor （K-NN） algorithm， variational mode decomposition （VMD）， convolutional neural network （CNN）， and bidirectional long short-term memory （BiLSTM） neural network is proposed to address the above issues. Firstly， a power prediction model based on K-nearest neighbor algorithm and hybrid BiLSTM neural network is established to provide accurate wind and solar prediction data for the two-stage optimization scheduling model. Secondly， a two-stage optimal scheduling model is established. In the day ahead scheduling phase， a stepped carbon trading mechanism and incentive demand response are introduced to develop a day ahead scheduling plan with the goal of minimizing the total operating cost of the system； In the intra day scheduling phase， an intra day rolling optimal scheduling strategy based on model predictive control is established to achieve rolling correction of the intra day scheduling plan with the goal of minimizing the adjustment of the intra day scheduling plan， and reduce the power fluctuation caused by the prediction error. Finally， taking a microgrid as an example for simulation analysis， the results show that the proposed method effectively improves the prediction accuracy while enhancing the economic， environmental， and stability of the microgrid.

In the context of actively implementing the " peak carbon dioxide emission and carbon neutrality" goal， building a new energy system and constructing a new power system， accelerating the construction of a more flexible， clean and sustainable low-carbon energy system has become the only way to energy transformation. Based on the analysis of the "five transformations" needed in the energy production and supply system， this paper expounds the connotation and characteristics of low-carbon energy system， clariifies its construction ideas， and discusses the development trends and challenges of key technologies needed to realize low-carbon energy system in detail. On this basis， two practical cases are listed from the perspective of supply side and demand side. Finally， the future development trend of low-carbon energy system is prospected.

In order to enhance the disaster resistance ability of power system， the active prevention strategy of the power grid with high proportion of new energy before disaster is studied. Firstly， combining the accuracy of disaster prediction and the time scale of proactive preventive measures， the length of proactive preventive decision window before disaster is studied. Secondly， a three-layer proactive prevention model with the goal of minimizing the sum of dispatching cost and loss of load is constructed. The upper-layer model determines the access location and time of mobile emergency power supply， while the middle-layer model determines the extreme disaster attack scenario with the greatest loss of load based on the set of natural disaster scenarios. The lower model optimizes the network topology and power output based on the mobile emergency power access scheme and extreme disaster attack scenario. Finally， the effectiveness of the proposed method is verified on the IEEE 69-node simulation system. The results show that the preventive cost of the active preventive strategy is much less than that of the passive preventive measures， and the pre-access time of the mobile emergency power also has a certain impact on the preventive cost of the active preventive strategy.

Exploring the risk spillovers of carbon market and new energy market is of great significance for preventing market risks and maintaining the healthy and stable operation of carbon markets and new energy markets. Tail-event driven network model is used to construct the carbon-new energy system， and the tail risk spilover effect of carbon market and new energy market is analyzed from different perspectives such as system， market and individual. The results show that the overall correlation between carbon and new energy system has obvious cyclical characteristics， and the sudden extreme events will increase the risk correlation degree. During the sample period， the risks absorbed by the carbon market from the new energy market are greater than those transmitted to the new energy market， and the carbon market and the photovoltaic sub-market are more closely related. With the improvement of carbon market and new energy market， the number of associated edges in the window period of local extreme point gradually increases， and the network structure becomes more and more complex. When the overall correlation degree is at the local maximum， the carbon market and photovoltaic sub-market mainly play the role of risk spillover channel， and the wind power and new energy vehicle sub-market have the function of spillover and bidirectional spillover. Finally， suggestions are put forward from the perspectives of risk prevention and control， market construction and supervision and management.

At present, energy is facing three major problems: shortage, pollution and safety. Under the guidance of carbon peak, carbon neutralization and policy constraints, the new round of energy revolution will show four major trends. Combined with the four trends of energy development, this paper deeply analyzes the problems of traditional power system, analyzes the role and positioning of power grid in power system, and expounds the evolution direction of new power system. This paper discusses and predicts the index node, time schedule, important characteristics and evolution process of the new power system, puts forward the development roadmap of the new power system, and discusses the four supporting technical systems of the new power system, including large-scale renewable energy development, power grid peak shaving and frequency modulation, local power grid and microgrid construction, hydrogen energy and its comprehensive utilization, provides a reference for the energy and power industry to build a new power system.

Hydrogen energy is a clean, zero-carbon, flexible and efficient secondary energy with abundant sources. As an important part of modern energy system, it's an important carrier to achieve the goal of carbon peaking and carbon neutralization. With the increasingly severe situation of carbon emission reduction, green hydrogen has received high attention worldwide. Hydrogen production from renewable energy can realize the whole hydrogen energy industry chain green and carbon-free, and solve the problem of renewable energy consumption, which is a very potential development route of hydrogen energy. This paper summarizes and analyzes the latest development trends of hydrogen energy industry at home and abroad, and focuses on the development status and trend of key technologies of green hydrogen energy from each link of the whole industrial chain, including hydrogen production, hydrogen storage, hydrogen transportation, hydrogen filling and application. Then based on the development situation of hydrogen energy industry in China, several typical application scenarios and development suggestions are put forward, which provides reference for the development of green hydrogen energy.

With the proposed goal of "carbon neutrality" , China's energy utilization mode needs to be adjusted. Firstly, it is introduced that the proportion of non-fossil energy in China is about 15% at present, and it will reach about 70% by 2050. Secondly, in addition to increasing the utilization proportion of non-fossil energy, carbon capture and utilization technology must be used to achieve carbon emission reduction in some difficult decarburization fields. Then, carbon capture and utilization technologies are introduced in detail. Carbon capture technologies include carbon dioxide capture before combustion, carbon dioxide capture during combustion and carbon dioxide capture after combustion. Carbon dioxide utilization technology mainly includes physical application, chemical utilization and biomass utilization. Due to the complete decarburization of hydrogen production by water electrolysis with new energy, hydrogen production by water electrolysis with new energy is considered to be the ultimate route of decarburization. Before the complete decarburization is realized, carbon capture technology is needed to cover the bottom.

Hydrogen energy is expected to play an important role in China's energy transformation process due to its low carbon, clean, high energy density and high conversion efficiency. This paper analyzes the research status and development prospect of various technologies in the fields of hydrogen production, hydrogen storage and hydrogen utilization, and then the specific technical path of renewable energy and integrated energy service system coupled hydrogen energy are discussed. Solid polymer electrolyte (SPE) hydrogen production and solid material hydrogen storage are the most potential development direction of hydrogen production and storage. Hydrogen fuel cell and adding hydrogen into natural gas pipeline should be advanced simultaneously. The combination of water electrolysis using abandoning wind/photovoltaic or off-grid hydrogen production and fuel cell power generation, hydrogen station supply, methanol production and natural gas hydrogen mixing will effectively solve the problems of uneconomical and difficult transportation. Hydrogen can also realize the interconnection of multiple energy networks and has a very broad application prospect in the future integrated energy service system.