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Comprehensive Evaluation Method of Virtual Power Plant Based on Hydropower Suppressing Wind Power Fluctuation

In order to assess the effects of the virtual power plants (VPP) participating in power grid regulation, this paper constructs a comprehensive evaluation index system of virtual power plants based on hydropower suppressing wind power fluctuations from three aspects: hydropower regulation ability, grid operation and dispatching, and economy of VPPs. The weight of each index is determined by the combination weighting method based on the entropy weight method (EWM) and the analytic hierarchy process (AHP). To verify the rationality and scientificity of the index and the weighting method in this paper, a regional power grid in Fujian has been taken as an example. Three VPP construction schemes including wind farms and small hydropower stations are selected and then the score of compare each index and total score of each scheme are calculated to determine the optimal scheme. The conclusion indicates that the evaluation index system and method is applied to the VPPs composed of wind power and hydropower and provides a theoretical reference for the construction and planning of VPPs in areas rich in wind and water resources.


Introduction
Renewable power sources such as wind and light have become more and more important in China's energy transition and sustainable development [1]. However, there are still many technical difficulties in large-scale grid connection of renewable energy in China, and the problems of abandoning water, wind and light are serious [2]. The VPP [3][4] integrates various distributed power sources through sophisticated control methods and energy management, and solves the problem of peak shaving and accommodation problems of the power grid caused by the large amount of renewable energy access [5]. Therefore, in order to measure the effect of VPPs participating in grid dispatching, it is necessary to conduct a reasonable and effective comprehensive evaluation of the construction plan of VPPs based on renewable energy.
The current research on the evaluation of VPPs is mainly aimed at using traditional power plants to stabilize wind power fluctuations, and the research on the evaluation indexes of VPPs that are coordinated and complementary to wind and water is imperfect. Ref. [6] established a corresponding index system for the system's peak and frequency modulation capability from multiple time scales. Ref. [7] constructs an evaluation index system from three aspects of reliability, economy and schedulability, and proposes a method of calculating reliability by constructing a three-state transition According to the characteristics of VPP resource distribution, this paper proposes an adjustable small water level to suppress wind power fluctuation evaluation method. The rationality of the index system and evaluation method in this paper is verified by an example of a real power grid in Fujian Province. It plays a guiding role in the construction of VPP based on renewable energy.

Evaluation Index System of VPP
Based on the influence factors of VPP participating in grid dispatching to suppress wind power fluctuation, evaluation indexes are constructed from three aspects: Hydropower regulation ability, grid operation dispatching and VPP economy. Under the data and index quantitative calculation method, a comprehensive evaluation index system of VPP is proposed, which is shown in figure 1.

Index of Small Hydropower Regulation Capacity
Index 1: regulation coefficient of small hydropower capacity. The regulation capacity of small hydropower is determined by the regulation coefficient of its storage capacity, which is equal to the regulation capacity of the hydropower station divided by the average annual runoff of the reservoir. The regulation capacity is the reservoir volume between the normal water level and the dead water level, and its expression is as follows: where Vi is the regulating capacity of hydropower station i, and Qav is the average annual runoff of the reservoir for many years. According to the reservoir capacity coefficient, the adjustable hydropower station can be classified according to the length of time. The larger the capacity regulation coefficient is, the stronger the regulation capacity is. Index 2: maximum output of hydropower unit. The output value of hydropower unit can be calculated according to the optimal regulation model of VPP. The larger the value is, the stronger the regulation ability is.
In the regulation process, the small hydropower with good regulation performance often requires more output and long regulation time, so the length of hydropower output time is also an index to evaluate the power of hydropower regulation, and the hydropower output time can be obtained according to the hydropower output curve.
Index 4: smoothness of hydropower output curve. The output smoothness of the hydropower unit can be reflected by the output change of the adjacent time of the hydropower unit, which needs to meet the climbing constraint of the hydropower unit. The smaller the value is, the smoother the hydropower output is and the stronger the regulation and control ability is are the output power of hydropower station i at time t and time t-1 respectively. Indicator 5: reservoir energy storage rate. The reservoir energy storage rate is positively related to the adjustable storage capacity of the reservoir in a specific period of time. The larger the value is, the better the hydropower regulation ability is. The reservoir energy storage rate of cascade hydropower stations is expressed as where t i V and max i V are the storage capacity of reservoir i at time t and the maximum storage capacity of reservoir i respectively.

Index of Grid Operation and Dispatching
The denominator part is the total output of the VPP, and the numerator part is the wind power consumption value.

Virtual Plant Evaluation Methods
Based on the 9 indexes proposed in the previous chapter, the active power optimal scheduling of VPP is evaluated. First, according to the actual operation data of VPP and power grid, the index value is calculated by the index quantitative calculation formula; then, the objective and subjective weights of each index are determined by AHP and EWM respectively; finally, the comprehensive weights of each index are determined.

EWM
The fundamental idea of EWM to determine the objective weight of an index is: if the data sequence of an attribute has greater variation, the corresponding weight coefficient will be larger [9][10]. The steps of empowerment are as follows: The first step is to calculate the index output information entropy where Zij is the contribution of index j of the project i, and n is the number of indexes. When Zij=0, ZijlnZij=0 is specified.
The second step is to calculate the index weight vector w= ( w1, w2, …, wn) The calculated entropy weight is the objective weight of the evaluation index got by EWM. Compared with subjective weighting method, entropy weighting method has higher accuracy, stronger objectivity and better adaptability, which can be used together with other weighting methods.

AHP
AHP is a multi-criteria decision-making method combining qualitative and quantitative analysis, which decomposes relevant elements of decision-making problem into objective, criterion and scheme levels [11]. The steps of weighting are as follows: The first step is to build a hierarchical analysis structure, which divides the decision-making problem into objective level, index level and criterion level.
The second step is to establish a judgment matrix to judge and compare the relative importance of each index.
The third step is to check the consistency of the judgment matrix where RI is the average random consistency index, which can be got by looking up the table, and CR is the random consistency ratio. The fourth step is to sort in a single hierarchy. The purpose of hierarchical single ranking is to count the relative importance of each index in the judgment matrix. First, each row element of the judgment matrix is normalized, and then each normalized column is added and divided by n to get the final weight.

Combination Weight
In this paper, the decision-making indexes are combined and weighted by the method of multiplication synthesis, that is, firstly, the weight coefficients resolved by the above subjective and objective weighting methods are multiplied correspondingly, and finally, the product is normalized. The specific weighting formula is: 1 , 1,2,...

Calculation Flow Chart of Evaluation Index Weight of VPP
The calculation process of VPP evaluation index weights is shown in figure 2.

Case Study
In order to verify the scientificity and rationality of the proposed indexes and methods, according to the geographical conditions of Ningde area and the installed situation of wind power (table 1) and Huangxilan 5-30  30  8  Wangkeng  10-40  40  9 Shangpei 10-44 44 In this paper, the form of scoring system is adopted, each index gets a full score of 10 points, according to the results of the index system, and the corresponding index scores are obtained (table 3); combined with the combination of AHP and EWM to solve the total score of the scheme. From the perspective of index weight, hydropower regulation ability index has the largest weight and relatively strong importance, while power grid operation and dispatching and economic index have relatively weak importance. From the point of view of the scheme score, the number of adjustable hydropower stations selected in scheme 1 is small and the regulation capacity of hydropower stations is not considered, so the scores of various indicators are the lowest. The score of hydropower regulation capacity and economic index of VPP construction in scheme 3 is higher than that in schemes 1 and 2. And the score of operation and dispatching index in scheme 3 is almost the same as that in scheme 2, which is caused by the similarity of the results of hydropower station selection in scheme 3 and scheme 2. According to the total score of comprehensive evaluation, scheme 3 is the best, and the VPP should be constructed in accordance with scheme 3 to achieve the coordination and complementarity of wind power and hydropower.

Conclusion
In this paper, considering the regulation ability of hydropower, the operation and dispatching ability of power grid, and the economy of VPP, a comprehensive evaluation index system of VPP is proposed. The evaluation index system can comprehensively reflect the construction of VPP and the dispatching effect of power grid. The weight of each index is determined through combination weight method. The case study verifies the scientificity and rationality of the index and method. The results can provide theoretical basis and guidance for the planning and construction of VPPs in water-rich areas.