Evaluation of Energy Storage Station Based on the Optimal Weighting Method

The energy storage station is playing an increasingly important role in supporting new power systems. How to scientifically and effectively evaluate the application effect of energy storage stations is an urgent problem to be solved. In this study, a multi-indicator evaluation model for energy storage stations is established. An improved fuzzy comprehensive assessment (FCA) with optimal weight is applied to actual energy storage stations. Using the energy storage station monitoring platform, comprehensive evaluation scores of demonstrated energy storage stations are obtained. The support effect of energy storage stations on the power grid is evaluated from three aspects: performance, operational reliability, and energy efficiency. The higher the evaluation score, the stronger the energy storage regulation ability, and the more significant the active support to the power grid.


Introduction
In 2021, the National Development and Reform Commission and the National Energy Administration issued the "Guiding Opinions on Promoting the Integration of Power Source Network Load Storage and Multi-energy Complementary Development".The construction and operation of energy storage power stations is an important measure in the power industry, and research related to energy storage power stations is becoming increasingly important.
To implement the spirit of the above guidance, various energy storage demonstration projects are gradually being prepared and constructed in areas with abundant scenic resources throughout China.The energy storage power station has the characteristics of short action time, fast charging and discharging speed, and accurate control.At the same time, the energy storage system has an absolute advantage over traditional thermal power units in terms of smooth power, voltage control, transient stability, etc. [1].However, it is urgent to solve how to measure the support effect of these energy storage power stations and source network load storage demonstration projects on the power system.There are currently many studies on the operational effects of energy storage battery monomers and PCS, mainly considering technological maturity, economy, and other aspects [2].
With the integration of renewable energy and distributed power sources, the structure of traditional power systems has been changed.Furthermore, the active support capability of energy storage stations is becoming increasingly significant, and the comprehensive evaluation system of traditional power systems can no longer meet the evaluation needs of new power systems [3].The comprehensive evaluation and quantifiable evaluation criteria for energy storage power plants are key to research.The operation evaluation of energy storage power stations involves numerous index factors and belongs to the category of multi-criteria comprehensive evaluation [4].The performance index of fire storage combined frequency modulation is studied in [5].From the perspective of reliability constraints, a microgrid containing multiple energy sources is evaluated [6].A scientific evaluation method is necessary for energy storage power plants.In the implementation process of all the above comprehensive evaluation methods, determining the weight of the index is very important to the evaluation results.In recent years, subjective evaluation index methods include AHP, ANP, DEMATEL, etc., while objective evaluation index methods include EWM, CRITIC, PCA, FAM, etc.
In this paper, the comprehensive evaluation system for energy storage power stations has been established, and the calculation of index weights is more reasonable and effective.The application in demonstration projects of energy storage power stations can effectively guide and support the operation and maintenance of energy storage stations.The paper is organized as follows: In Section 2, the Basic performance index, operational reliability index, and energy utilization efficiency index of energy storage power stations are presented.In Section 3, an optimal weighting method for energy storage stations is proposed.In Section 4, data collection and monitoring systems for energy storage stations are applied.Finally, the evaluation conclusions with of energy storage stations are presented in Section 5.

Evaluation index system for an energy storage station
A system evaluation architecture for an energy storage station is shown in Figure 1.The evaluation system for energy storage stations includes a criterion layer and an index layer.The criterion layer consists of energy storage performance, operational reliability, and energy efficiency level.The evaluation index model for energy storage stations is as follows.The dischargeable capacity equation is as follows.The utilization rate equation is as follows.
The availability rate equation is as follows. 100% where UTH represents the operating hours of the energy storage station, PH represents the statistical time hours during the evaluation period, and AH is the available time of the energy storage station during the evaluation period.
The overall efficiency equation is as follows. 100% Self-consumption rate equation is as follows. 100% The energy loss rate equation is as follows. 100% where UP E is the up-power of the energy storage station,

Evaluation method for an energy storage station
The fuzzy comprehensive assessment (FCA) method can evaluate samples through membership theory, effectively solving the problem of nonlinearity and difficulty in evaluating the joint frequency modulation performance index of fire storage.However, the index weights given by the FCA method are subjective.Considering the objectivity of the entropy weight method, this article establishes an optimal weight, achieving a shift from a qualitative evaluation to a quantitative evaluation in the FCA method, making the evaluation results for energy storage stations more objective and effective.
(1) The evaluation index data of each energy storage station was standardized.The standardized evaluation matrix is as follows.x is the m evaluation index of the n energy storage station with standardized data.
(2) The evaluation set is composed of evaluation levels for the performance index, such as excellent, good, medium, and poor.We can build a fuzzy comprehensive judgment matrix as follows: where mv r is the fuzzy result for the m index in the current evaluation process under the v evaluation level, which is determined by the trapezoidal degree function.
(3) According to the entropy weight method (EWM), the information proportion of different indices in the corresponding index system to the entire sample can be calculated.The equation for the proportion matrix of index information is as follows.
(5) The final total evaluation vector for the energy storage station obtained by synthesizing the weighted average matrix of

 
, M  type is as follows.Finally, the scoring results of each energy storage station evaluation will be provided.

Energy storage station monitoring platform
Based on the application architecture and data architecture, we can make full use of the existing control platform architecture, deploy the energy storage monitoring application server in the security III area, and realize the online evaluation function of the energy storage station.The energy storage station transmits remote signaling and telemetry information through a tele control device using the 104 protocol.
The energy storage station monitoring platform application is based on an information model data management architecture, as shown in Figure 2, including device static models and device dynamic models (functional models).The static model of the device mainly includes device appearance, configuration information, etc., which is maintained in the relational database.In real-time data processing, the dynamic model (functional model) of the device is organized and presented in a Kafkathemed manner.In historical data storage, device dynamic models are maintained in the form of Tdengine super tables, mapping the organizational relationships of devices in the system using super table tags.The analysis and evaluation results for the energy storage station monitoring platform support realtime evaluation and display of the overall station and single station, as well as evaluation and statistics by year, month, day, custom cycle, and other methods.It is possible to view the trend of changes in various indexes.To demonstrate the effectiveness of the evaluation method in this article, seven demonstration projects of energy storage stations (due to engineering reasons, the real station name and location have been hidden) are evaluated, as shown in Figure 3.
Based on the values of seven indicators on a single day (February 9, 2023), the indicator evaluation method provided in this article is applied to obtain the scoring value.Furthermore, the first-level evaluation index score matrix is obtained.At the same time, through horizontal comparison and analysis of energy storage power stations in various regions, we can compare the application effectiveness with energy storage power stations across the entire network, as shown in the first row of the data table in Figure 3, which is the comprehensive score of all power grid.From the demonstration interface for evaluation results, the final evaluation scores result is shown in Table 1.The higher the evaluation score is, the stronger the energy storage regulation ability is, and the more significant the active support to the power grid is.It can be concluded that the comprehensive scores of energy storage stations 1, 2, and 6 are above 90 points, and the evaluation result is excellent.In this type of energy storage station, charge-discharge power and dischargeable capacity are abundant, which can effectively supply energy to the surrounding area.Therefore, the energy storage performance is significant.On the other hand, the operational reliability score of such power stations is outstanding, so the utilization rate of the station is high, which can better support the frequency and voltage regulation The comprehensive evaluation results of energy storage stations 3, 4, and 5 are medium.Therefore, for such energy storage stations, emphasis should be placed on improving operational reliability.Due to the unfinished project and it is not connected to the grid for power generation, the evaluation score of the No. 7 energy storage station is relatively low.For such stations with missing and abnormal data, data maintenance should be strengthened to improve the reliability of data communication and channels.
Table 1.Evaluation scores of the energy storage stations based on the optimal weighting method.

Conclusions
Compared with previous evaluations of source network load storage performance, this article proposes a three-layer evaluation system for energy storage performance, operational reliability, and energy efficiency.The Energy storage station monitoring platform has been established.The proposed improved FCA evaluation method is applied to actual energy storage stations.Furthermore, the main research direction for the next step revolves around evaluating the regulatory effectiveness and economic benefits of energy storage systems participating in auxiliary services of the power system in different application scenarios.

Figure 1 .
Figure 1.System evaluation architecture for an energy storage station.
discharge power of the energy storage station, N P represents the rated power of the energy storage station, ADC E is the actual discharge capacity of the energy storage station, and N E is the rated energy of the energy storage station.
down-power of the energy storage station, SE E is the self-consumption power of the energy storage station, C E is the total charging capacity of the energy storage station, and D E the total discharge capacity of the energy storage station.

( 4 )
Based on the information content and differences of the index, the weight matrix is calculated as follows.

Figure 2 .
Figure 2. The information model data management architecture for energy storage platform.

Figure 3 .
Figure 3. Demonstration interface for evaluation results of seven energy storage stations.

Table
of the power grid.It is worth noting that the energy efficiency level of this type of power station is excellent, which is manifested by high overall efficiency and low energy loss rate.