In view of the dual-carbon goal proposed by the state, increasing the proportion of green power trading is a key initiative to realize the "dual-carbon" goal, but green power and carbon emissions have not yet been fully coupled, and the way of purchasing green power to offset carbon emissions is too single, so how to scientifically calculate the baseline for offsetting carbon emissions from green power and stimulate the consumption of green power on the user side is a problem that needs to be solved at present. First of all, the study from the carbon emissions accounting and green power emission reduction value measurement of two aspects; Secondly, the high carbon emissions of the industrial sector as an example, the use of cluster analysis to assess the emission reduction potential of a number of industries; then based on this, from the industry of total carbon emissions, carbon emissions intensity and the proportion of electricity consumption of the three aspects, to the exploration of constructing the embodiment of the industry differences in the calculation model of the green power to offset the carbon baseline; Finally, through the analysis of the case to validate the Finally, the viability of the model is verified through an example analysis, and the baseline for the mandatory and key emission reduction categories of industrial industries is calculated.

With the proposal of the Carbon-neutral Target and the continuous promotion of the construction of new power systems, the degree of China's power market-oriented reform has been deepening. On the one hand, the number of participating subjects in the user-side power market has increased, and the variety of transactions has been enriched, which puts forward higher requirements for the operation efficiency of power trading centers and other aspects; on the other hand, power trading institutions, as the operators, builders and managers of power trading, should develop in synergy with dispatch centers and load management centers to strengthen the information interactions and business dealings, and at present, the dispatch centers and load management centers have already realized the operation of multi-level organization system. Therefore, this paper firstly analyzes the challenges faced by the trading center under the new power system, and explores the current organizational system of the power trading center, and finally puts forward the innovations of multi-level and grid based on the original organizational structure and management level of power trading centers, which will support the efficient and stable operation of the future market of multi-market subjects and multi-transaction varieties.

The aggregated entity formed by the distributed photovoltaic (DPV) and energy storage system has the capability to offer multiple services in the electricity markets, reaping the advantages of both energy arbitrage and frequency regulation. This paper focuses on developing a bidding strategy and operation plan for an aggregated entity from a profit pursuit perspective. We propose a multi-stage stochastic programming optimization model that divides the original problem into three stages, allowing for feasible and more realistic decision-making while maintaining the relationships among decisions. The proposed model includes a new multi-service portfolio that balances the profit of the two markets and accounts for uncertainties in market prices, DPV output, and regulation signals. To motivate collaboration among stakeholders, we also develop a profit allocation model rooted in the principles of Nash bargaining theory. This model serves as a compelling incentive for all parties involved, encouraging mutually beneficial cooperation. Finally, a numerical case study demonstrates the validity of the proposed models.

With the proposal of "carbon peaking and carbon neutrality" target, the proportion of new energy in China's power generation side is increasing, and it is a general trend for new energy to enter the market and participate in trading. However, there is a big risk for new energy to enter the market, and it is necessary to seek an effective way to avoid the risk and promote the new energy to enter the market, which is a hot and difficult issue in the current research. This paper firstly analyses the risk of high proportion of new energy market transactions; proposes CFDs to help new energy avoid the risk of entering the market, including the multi-factor linkage of government-authorized CFD and the market-based CFD with LMP, and modelled the trading of different types of marketable CFDs; Finally, an example is given to verify the validity of the model and the feasibility of CFDs.

The aggregated system of the distributed solar and energy storage system can provide multi-service in the electric power market, benefiting from both energy arbitrage and frequency regulation. This paper focuses on the bidding strategy in day-ahead markets and the real-time operation plan of the aggregated system. The nature of the problem includes the coupling of multiple markets and the interconnection of different timescales, which could also be the breakthrough points of it. We propose a multi-stage stochastic optimization model to exploit the market potential of optimizing the regulation behavior while taking into account the energy arbitrage income. We divide the original problem into three stages, simplifying the problem and maintaining the relationships among stages at the same time. The multi-stage model is solved by stochastic dual dynamic programming algorithm and the validity of the approach is proved by the case study.

The current electricity market is carried out in a unified bidding mode of various types of power generation resources, resulting in insufficient resource competition and incomplete reflection of the value of different quality power generation resources, hindering the long-term development of renewable energy and reducing the willingness of adjustable conventional power supply to provide flexible adjustment ability. Therefore, this paper proposes the electricity energy classified bidding market, sets different value measurement competition space for different types of power generation resources, promotes the rationalization of resource competition and the authenticity of power supply value, and promotes the benign competition pattern of coordinated development of multiple resources.

With the continuous increase in the penetration rate of renewable energy, renewable energy generation will gradually become the main body of power generation in the power system, occupying a dominant position on the power supply side. It is difficult for conventional generators to recover fixed costs in the electric energy market. At the same time, renewable energy generation needs more traditional power sources as support to ensure system stability due to its randomness, volatility, and intermittency. Therefore, to ensure the adequacy of the power generation capacity of the system, it is urgent to establish a reasonable capacity compensation mechanism to ensure the recovery of the fixed cost of flexible power sources especially thermal power. This paper establishes a systematic analysis framework for the adequacy of power generation capacity, designs a double-differentiated capacity compensation mechanism, and proposes a capacity compensation calculation method, which is based on the traditional calculation method of capacity compensation standard, can fully reflect the capacity value and flexibility value. Finally, based on the IEEE 30-bus system and an actual provincial power grid, case studies validate the rationality and feasibility of the double-differentiated capacity compensation mechanism.

Driven by the "dual carbon" goal, it is an effective market-oriented way to promote renewable energy consumption and carbon emission reduction that users participate in renewable energy trading and carbon trading. This paper first proposes a coordinated transaction mode for load aggregator (LA) between the internal and external two-level markets, which provides a solution for a single user to efficiently participate in the multi-market, and effectively articulates multiple markets of electricity, excess renewable energy consumption, and carbon quota. Then, based on the diversified demands of users, a bi-level decision-making model for LA participating in multi-market is established. On the one hand, users optimize and adjust their own needs through internally distributed adjustment transactions within LA. On the other hand, LA acts as an agent for users to participate in the external electricity market, excess consumption market and carbon quota market, which makes it minimize transaction costs while meeting the diversified needs of users. Finally, this paper concludes that the establishment of an internal and external collaborative transaction decision-making model in which LA participates in multiple markets can effectively promote renewable energy consumption and carbon emission reduction from the user side.

确保发电容量充裕是电力系统安全运行和电力市场稳定的必要条件,是电力工业发展中需要解决的核心问题之一.随着全球能源电力低碳转型,电力系统发电容量充裕性面临着严峻挑战,国际上已实施多种容量机制.文章结合欧洲能源转型及电力市场化改革过程梳理容量机制的建设背景、发展脉络及现状,重点分析欧洲2019/943法案推荐近期适用的战略备用机制,及该机制在芬兰、德国、比利时的设计细节.双碳目标下,我国煤电将由主体电源转变为调节性、支撑性电源,亟需容量机制保障其安全平稳转型.文章梳理了我国煤电容量机制现状及问题,指出战略备用机制具有良好的适用性,分析设计实施该机制的关键问题,为国内容量机制建设提供了决策参考.

China is characterized by uneven distribution of resources and regional economic development. It is necessary to strengthen inter-provincial electricity market construction, break inter-provincial barriers, and promote the optimization of the distribution of electricity resources in a larger area. The inter-provincial market is to promote the optimal allocation of electricity resources on a larger scale in each province and to promote the flow of electricity resources from electricity-rich areas to electricity-scarce areas. Therefore, this paper firstly analyzes the significance of the inter-provincial electricity spot convergence mechanism to play the role of the inter-provincial market in optimizing the allocation of resources on a large scale, and then constructs a model of inter-provincial and intra-provincial spot market transactions, analyzes the convergence mode of the two levels of market transactions under the convergence mechanism, and finally puts forward an outlook on the construction direction of China's future inter-provincial renewable energy market transaction mechanism.

Promoting the large-scale development of the distributed photovoltaic (DPV) industry is the inevitable choice to construct the new power system based on new energy and the urgent need to achieve the carbon peak-and-neutrality goal. At present, domestic DPV mostly adopts "self-generation, self-consumption and surplus power to the grid" mode. The power consumption is highly dependent on the government and lacks a flexible and diversified market-oriented trading mechanism, resulting in a seriously restricted consumption rate. This paper proposes a hierarchical consumption (HC) mechanism of large-scale DPV to promote clean energy consumption. Then, taking the proportions of DPV selfconsumption, sharing, medium-and-long-term transaction and spot transaction electricity as decision variables, the paper establishes a dynamic allocation multi-objective optimization model for DPV prosumer clusters (PCs). The model quantifies and superimposes the double risks of market price fluctuation and DPV prediction deviation; takes the maximum income and the minimum decision risk as the goals; and uses NSGA - Ⅱ algorithm and TOPSIS method to solve. Finally, an example is given to verify the effectiveness of the model in improving the overall benefits of PC and promoting the local consumption of DPV energy.

Accurate short-term load forecasting results can effectively guarantee the safe dispatch and stable operation of power system. However, with the popularization of distributed generation and the increase of user-side flexible resource, the load characteristics of users have changed, which has a certain impact on the accuracy of short-term load forecasting. Therefore, a regional short-term load forecasting model considering dynamic participation of multiple users is proposed in this paper. Firstly, the quantitative indexes of price-based demand response are extracted according to the characteristics of load-to-price, and the incentive-based demand response resources are divided into three categories: curtailment load (CL), transferable load (TL) and optical storage system (OSS). The quantitative models are established respectively considering the uncertainty and diversity of users' response, which are represented by Monte Carlo simulation sampling method. Then, GORUBI solver is used to obtain the results after combining all kinds of resources. After that, on the basis of the historical load data, the above two kinds of indexes are introduced into the multivariate long-short term memory (LSTM) network model. Finally, a case study is carried out to evaluate the performance of the proposed model. The results demonstrate that the short-term load forecasting model with user-side factors can effectively reduce the prediction errors and further improve the prediction accuracy.

With the rapid development of renewable energy industry, the proportion of renewable energy sources has gradually increased. The connection between the large-scale uncertain power and the power grid results in transmission congestion, which affects the safe and stable operation of the system. So far, there are two deficiencies in congestion scheduling: one is the lack of research on the influences of users in scheduling process, the other is the lack of integration between scheduling and market transactions. Therefore, in order to effectively solve the problem of congestion caused by renewable energy sources, the scheduling should be further studied as a research field. This paper makes use of plenty of scheduling resources, including various types of power generation enterprises, demand response users and energy storage systems, to establish an optimal congestion scheduling model of intraday market to promote the consumption of renewable energy sources with the target of minimizing the cost of congestion scheduling and the cost of wind power curtailment and solar power curtailment. Finally, the validity of the model for reducing the cost of congestion dispatching and improving the utilization level of renewable energy is verified by carrying out a modified IEEE 14-bus system.

Spot market is now under construction in China, which enriches the power trade greatly, and makes the power market tend to be multiple and diverse. When participating in the multi-market transaction, it is necessary for generation enterprises to develop a scientific strategy in order to search for profit and avoid risk. Firstly, based on the mean-CVaR theory, a multi-market competition model striking the balance between risks and benefits for generation enterprises is proposed in this paper. Then, considering the status quo and prospect of power market in China, a case of generation enterprise participating in long-term market, spot market and operating reserve market is studied with the model, Finally, the correlations between yield rate and CVaR, electricity distribution proportion are analyzed.

随着降温负荷在负荷结构中占比逐年增大,测算降温负荷对中短期负荷预测意义重大。受经济新常态、去产能等政策影响,基本负荷在月间出现较大差异,传统降温负荷测算方法对该类情况有局限性。构建了一种基于支持向量回归和K均值聚类的降温负荷组合测算模型,包括基于SVR-Winters的变尺度基本负荷预测和EMD-Kmeans降温负荷二次剥离。以西北某省实际数据进行算例分析,结果表明该方法能有效解决基本负荷月间差异较大及日内随机波动等问题,具有较高的测算精度及良好适应性。

Under the background of national requirement to further improve the comprehensive energy utilization efficiency, natural gas distributed energy system, as one of the efficient and clean energy utilization methods, has been incorporated into the national energy development strategy. However, the comprehensive energy utilization efficiency of key natural gas distributed energy enterprises in China can not meet the expectations. Based on the analysis of the energy efficiency of natural gas distributed energy, considering the objective existence of the load cultivation period, this paper establishes the source-load matching degree model and the source-load coordinated growth model, which have guiding significance for the scale of the construction of natural gas distributed energy units, and can help enterprises realize the efficient use of energy as soon as possible. And the validity of the model is verified by an example of a gas distributed energy project in a business district of Shanghai.

Natural gas distributed generation (NGDG) has been widely concerned, promoted, and applied all over the world because it has advantages such as high comprehensive energy efficiency, environmental protection, sustainable and stable power supply, and so on. It also has become an important part of the energy strategy in China. Unfortunately, most NGDG projects on production in China do not operate very well due to several reasons such as high investment and operation cost, long load cultivation period, and so on. Thus it is quite urgent to design one pricing mechanism suitable for NGDG to meet the need in the transition stage before fully power marketization and rationalize and standardize the feed-in tariff of NGDG. This paper proposes a one-part tariff mechanism for NGDG based on classified benchmark price, which solves the problem that most NGDG projects have to refer to the benchmark tariff of local coal power plants due to the absence of NGDG pricing benchmark. Meanwhile, according to the characteristics of energy projects and regions, the mechanism establishes a two-dimensional classification scheme for NGDG, sets up the benchmark data and the method to determine the values, and then put forward the benchmark tariff of NGDG. It also changes the "one plant one price" approach in some areas. Finally, using the tariff mechanism and operating period price model, we calculate the benchmark tariff of all kinds of NGDG in several typical regions. The results can be referenced for research and NGDG tariff mechanism establishment in various countries.

Demand side management has attracted wider and wider attention under the electric power system reform be-cause it conforms to the development tendency of the smart grid.In this paper,the cost indexes and benefit indexes of demand side management are determined to evaluate their impacts on the power grid companies under the power trans-mission and distribution price reform.It is divided into short-term and long-term pricing according to the different forms of the transmission and distribution price.Then short-term and long-term cost-benefit evaluation models are built according to the different accounting methods of total reve-nue.Being applicable to a variety of demand side manage-ment strategies,such variables as 'avoidable peak load ca-pacity'and 'increased transmission and distribution energy' are set in the model.The three-dimensional results of short-term and long-term evaluation together with the change trend of the transmission and distribution price for a region-al grid are obtained from case analysis,which validates the objectivity and effectiveness of the evaluation model.

The medium and long term load forecasting faces problems under the new normal economy,such as S shape load trend,few dependable data sample,etc.,and the accuracy of traditional forecasting method is limited,for which,a medium and long term load forecasting method based on partial least-square regression and scenario analysis method is proposed.With the combination of macroscopic view with the microscopic view,a hierarchical index system of factors influencing power load is built from three macroscopic aspects of new normal economy,i.e.speed,structure and driving force.The partial least-square regression method is adopted to obtain the relation equation between power load and its influence factors.According to the characteristics of economy and power development during the 12th and 13th five-year plan,the scenario analysis method is adopted to set up several scenarios and corresponding parameters,and different load forecasting results under each scenarios are obtained for reducing the forecasting risk.The proposed model is applied for forecasting the yearly electricity consumption of a province during the 13th five-year plan,and the comparison with the forecasting results of existing sophisticated methods and official data verify the effectiveness of the proposed model.

At present,China's subsidy policy on the natural gas distributed energy resource is comparatively deficient that only a small number of provinces and cities have issued the relevant policies which still exist some disadvantages,in which case a subsidy guiding standard is urgently needed.A mechanism of subsidy by stages for the natural gas distributed energy resource is proposed based on a specific project classification method and actual laws for the project development stages.A definition method is also put forward for the development stages of energy programs.Then a subsidy measurement model for the natural gas distributed energy resource is established based on the internal rate of return method,which makes a quantitative analysis on the relationship between the amount of subsidies and the internal rate of return on proj ects.Finally,a subsidy calculation example in Shanghai is made to provide a reference for the subsidy policy making of natural gas distributed energy resource in provinces and cities.