Energy efficiency evaluation of cooling water system based on fuzzy comprehensive evaluation method

In the energy efficiency analysis of cooling water system, the fuzzy comprehensive evaluation method is used to establish the energy efficiency analysis factor system. Firstly, it divides the factors into different levels, quantifies the evaluation indexes of factor sets, establishes the weights of each factor and the membership function by using the analytic hierarchy process (AHP), and constructs a complete fuzzy evaluation system. Then through the description and calculation of a specific example, combined with fuzzy theory, the energy efficiency state of the whole cooling water system and each link is obtained. The feasibility and rationality of the application of fuzzy comprehensive evaluation method to the energy efficiency evaluation of cooling water system are explained by analysis, which provides a new way to solve the problem of energy efficiency evaluation of cooling water system.


Introduction
Cooling water system is common in chemical, electric, metallurgical and other enterprises, but its energy consumption is very large, and the reuse efficiency of cooling water is also low. Zhang Xueli [1] et al. put forward the water temperature comparison method to evaluate the performance of cooling tower, Zhu Jing [2] et al. used fuzzy comprehensive method to evaluate the energy efficiency of heat exchanger. However, due to the interaction of the components of the cooling water system, the energy efficiency evaluation of a single part cannot effectively explain the energy efficiency of the whole system, so this aspect needs to be studied.
In this paper, the fuzzy evaluation method is used to put forward the energy efficiency evaluation system of the whole system, and the energy efficiency index of the components of the cooling water system is evaluated from different angles. On this basis, improvement measures are proposed to improve the utilization efficiency of circulating water, save energy, and save costs for enterprises.

Overview of fuzzy evaluation methods
Fuzzy comprehensive evaluation method is a kind of evaluation method based on fuzzy mathematics. The core of this method is to quantify the mathematical relationship between two or more variables by using fuzzy sets and membership functions. It breaks through the absolute relationship of the traditional classical set theory [3][4], and approximates the accuracy to the fuzziness. Research or solve some vagueness. Because it is impossible to define energy consumption or energy saving quantitatively, the energy efficiency evaluation of cooling water circulation system studied in this paper has strong fuzziness, hierarchy and correlation. Fuzzy comprehensive evaluation method can integrate complex energy efficiency indicators and make effective evaluation by using fuzzy mathematics theory [5].

Analysis of factors affecting cooling water system
3.1. Energy efficiency index of cooling tower (1) Fan efficiency (2) Cooling efficiency of cooling towers (3) Water loss of cooling tower There are four main forms of loss in cooling tower: evaporation loss, wind blowing loss, entrainment loss and water withdrawal loss. The loss of water withdrawal is negligible.

Energy efficiency evaluation index of heat exchanger
(1) Heat flux intensity of heat exchanger surface This index combines the influence of heat transfer coefficient and temperature difference, and is a relatively comprehensive index. The cladding layer should be thicker than the upper cladding layer.
(2) End temperature difference we redefine the performance index of a heat exchanger by using two temperature differences, which is also an indicator of energy efficiency of a direct reaction heat exchanger.

Energy efficiency evaluation index of pipe
(1) Pipeline surplus coefficient There are different pressure losses in each pipeline. These pipes are longer and the pressure loss can not be ignored. Therefore, the pipeline surplus coefficient is introduced to calculate the pressure values at both ends of the pipeline.
(2) Heat loss coefficient of pipeline Heat loss is directly manifested in the internal temperature of the pipeline, and the external environment temperature also directly affects the heat loss of the pipeline. It can be calculated

Energy efficiency evaluation index of valves
Surplus coefficient of valve When the fluid flows through the valve port, pressure loss will occur due to the change of shape. Also select two nodes before and after the valve to calculate the pressure savings coefficient.
3.6. Notation : Evaporation loss : Wind loss : Entrainment loss : Water withdrawal loss F: Heat exchanger surface area, 2 :Refrigerant outlet temperature :Refrigerant inlet temperature :Heat medium inlet temperature : Heat medium outlet temperature : Second flow of pump, 3 / : Lift of pump, n g : Number of pipeline segments

Energy efficiency evaluation factor set
First, determine the set of factors, which is a set of all factors that affect the object to be evaluated [6]. The energy consumption of cooling water system is mainly embodied in the energy consumption of cooling tower, heat exchanger, water pump, pipeline and valve. These five components have different influence weights on the cooling water circulation system, and each component includes different energy efficiency indicators. Therefore, the factors of energy efficiency evaluation are divided into different levels, and the cooling water circulation system has different influence weights. The energy efficiency evaluation index system is shown in Figure.2.

Evaluation of energy efficiency
Secondly, the energy efficiency of the cooling water system is divided into four states: poor, medium, good and excellent, and the fuzzy set for evaluating each energy efficiency index is determined. Expressed as: V={V 1 , V 2 , V 3 , V 4 }, There are many ways to determine membership functions [7]. According to the characteristics of energy efficiency evaluation of cooling water system, the linear membership function is adopted in this paper, as shown in Figure.3.  Figure 3. Membership function.
The membership functions of each fuzzy set are as follows: (1) The membership function of "Bad" and "Excellent" of fuzzy sets is: (2) The membership function of "Medium" and "Good" of fuzzy sets is:

Establishment of fuzzy evaluation matrix
After determining the energy efficiency evaluation factor set and comment set, the evaluator needs to evaluate each single factor according to the calculation of its estimated value and expert experience, and get the comment table. This paper mainly determines the comment form by calculating and searching experts. In addition, some evaluation factors are the larger the better type, and some are the smaller the better type [8]. In order to facilitate calculation, the smaller the better type of evaluation factors are taken as the opposite number, such as table.1. The fuzzy evaluation matrix of every single factor can be obtained by calculating the data and factor sets in the table.

Comprehensive evaluation index weight vector
The weight is the status and importance of the evaluation index. For the factors that need to be evaluated, the proportion is different in the total evaluation index of each level. Therefore, it is necessary to add a proportion to each factor of each level. The sum of the weights of all the evaluation indexes of the first level is 1, and the weight is expressed as: α (i = 1, 2, 3, 4, 5), �( ) = 1
The first level of energy efficiency indicators is divided into cooling towers, heat exchangers, pumps, pipes and valves, according to their energy consumption and scale values, to determine the judgment matrix. Among them, the energy consumption of each part is shown in Table.2, and the index U i represents the scale value of the relative importance of U j , as shown in Table.3. Then the judgment matrix, such as  The i factor is as important as the j factor 3 The i factor is slightly more important than the j factor 5 The i factor is significantly more important than the j factor 7 The i factor is more important than the j factor 9 The i factor is absolutely important than the j factor reciprocal b ji = 1/b ij  The maximum membership degree principle was adopted in the analysis of the evaluation results. It can be concluded that the energy efficiency of the cooling water system is in a "good" state.

Conclusions
(1) The process of applying fuzzy comprehensive evaluation method to cooling water system is described in detail through an example, and the factors affecting the energy efficiency of cooling water system are evaluated effectively.
(2) Through the energy consumption situation of each link of the system, the low energy utilization index can be technically reformed to improve the overall energy efficiency level and save cost.
(3) Through analysis, it can be concluded that the fuzzy comprehensive evaluation method has high rationality and applicability for the energy efficiency evaluation of cooling water system.