| In response to issues such as energy shortage and environmental pollution,new energy technology has entered a stage of rapid development in the field of power supply.Due to the influence of natural factors on new energy,with a large number of new energy sources such as wind turbines and photovoltaic integrated into the power grid,its volatility and randomness make the power system face severe challenges such as unstable operation,reduced power quality,and insufficient capacity to absorb new energy.In the construction of intelligent source network load,demand side schedulable resources and hydrogen energy storage technology are considered as the key means to solve the above problems.Hydrogen energy storage,due to its clean,low-carbon,and high energy density characteristics,can serve as a power reserve in the context of high proportion of new energy grid connection.This paper also studies the demand response mechanism based on user classification under the background of power system equipped with hydrogen energy storage,which can fully absorb new energy,reduce the volatility of the system,and achieve the goal of win-win between the grid and the demand side by tapping the schedulable potential of the user side and cooperating with the hydrogen energy storage system.The specific research content of this article is as follows:(1)Establish a mathematical model for the operation system of hydrogen containing energy storage load aggregator and analyze the characteristics of the three types of loads on the demand side.The load regulation capability of hydrogen gas turbines and the response delay characteristics of hydrogen fuel cells affected by temperature were analyzed in principle.The demand side load was divided into three categories and corresponding mathematical models were established.By analyzing the load characteristics of the three types of users,a foundation was laid for the subsequent development of reasonable optimization scheduling plans in the article.(2)Establish electricity consumption behavior indicators,screen target users for load aggregators,and classify target users through system clustering and iterative self-organizing data analysis algorithms.A two-level optimization model was constructed with the load aggregator as the upper level decision-maker and the contracted users as the responders.The characteristics of load transfer of various users before and after the implementation of the demand side response project and the capacity of hydrogen storage devices to absorb new energy combined with demand response are studied.The example analysis shows that the above method can effectively screen out user groups with high schedulability potential,and successfully guide users to change their electricity usage habits during peak load,finding the optimal incentive DR strategy for load aggregators.(3)First,under the background of large-scale wind and solar grid connection,the static characteristic voltage models of various loads were established,and the impact of the fluctuation of new energy output on different types of loads was studied.Secondly,taking into account the uncertainty of the load side,the load price volume curve aggregation model was constructed to provide technical support for the bidding of load aggregators.Then,based on the conditional Value at risk theory,the relationship between the investment plan and investment risk of load aggregators was studied,A two-level optimization scheduling model for multi load aggregator operation considering uncertainty has been established.Finally,through numerical examples,it is proven that the above methods can reduce the operational network losses of the system,and the superior power grid and load aggregator can effectively avoid the economic losses caused by user defaults. |
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