Electricity Price Strategy For Large Industrial Users To Promote Clean Energy Consumption And Potential Evaluation Of Peak-shaving

In order to achieve the dual carbon goals of "carbon peak" and "carbon neutrality"proposed by China at the end of 2020,the power industry,as one of the main sources of carbon emissions,has become an inevitable trend to vigorously develop clean energy on the power generation side,and realize electric energy substitution and energy management on the user side.With the large-scale grid connection of clean energy,although the power generation of traditional units has been reduced,the volatility and intermittentness of clean energy have also increased the scheduling pressure of traditional units,the peak shaving of traditional power generating units has been unable to meet the rapid development and large-scale consumption of regional clean energy.Considering that the flexible load on the user side has the characteristics of fast response and high economy,in-depth exploration of the theory and mechanism of user participation in peak shaving adapted to the grid with a high proportion of clean energy will help the management department to take advantage of source-load integration and improve the efficiency of peak shaving decision-making methods.Aiming at the issue of clean energy consumption under the new situation,this paper conducts research from priceguided user participation in peak shaving mechanism research and peak shaving potential evaluation.First,reveal the relationship between price incentives and changes in user-side load characteristics,focusing on the analysis of changes in electricity prices,the relationship between user economy and load characteristics,combined with consumer psychology to construct a load transfer model for industrial users peak shaving,and obtain the results by curve fitting Related parameters.On the basis of traditional user-side peak shaving research,the new energy output and load are combined to form an equivalent load,and on the basis of the traditional time period division,comprehensively consider the degree of subordination of different time periods of load and new energy to the peak and valley of the equivalent load curve Contribution degree,proposed to improve the membership function,so as to divide the time period.Secondly,it has formulated an electricity price strategy to promote the consumption of clean energy.Based on the user load transfer model,the goal is to maximize clean energy consumption and user satisfaction,and introduce relevant time period constraints and traditional unit scheduling constraints,the peak-valley-level time period optimization model and the peak-valley level period electricity price combination optimization model to promote the consumption of new energy have been established respectively.The simulation calculations were carried out by taking large industrial users and new energy sources in a certain area of the power grid as examples.The results show that the time period division method and electricity price strategy proposed in this paper can effectively promote the consumption of clean energy,alleviate the pressure of traditional unit dispatch,and ensure the economic and stable operation of the power system.Finally,an indicator system was constructed from four aspects,including the ability to participate in peak shaving,the promotion of clean energy consumption,economy,and comfort.Interval weighting is used to eliminate the error caused by power user load fluctuations on the evaluation results,and a dynamic evaluation method for user peak shaving potential to promote the consumption of clean energy is proposed.On the one hand,the idea of"acceleration" is introduced to reflect the change trend and magnitude of different time series/day evaluation indicators,which overcomes the difficulty of traditional methods to reflect the time series dynamic process of indicators;On the other hand,the introduction of "incentive"and "punishment" management ideas to users participating in peak shaving can reflect the current status of the evaluated object more objectively and truly.Combining dynamic incentive index values and interval weights can obtain an interval decision matrix,and then rank the potential of various users to participate in peak shaving.Taking the load of multiple types of users in a certain area as an example,the initial observation values of each indicator are obtained through a combination optimization model.The results show that this method can effectively evaluate and score the peak shaving potential of users to promote clean energy consumption.The results obtained not only quantify the completion of users’ participation in peak shaving tasks,but also provide a data basis for the subsequent deployment arrangements of peak shaving on the user side,and promote users to participate in the construction of peak shaving mechanisms.