Efficiency Assessment Of Malaysian Coal-Fired Power Plant: A Circular Economy Perspective

DEA Method

DEA is a non-parametric method of linear programming which is commonly employed to empirically evaluate the efficiency and relative performance of decision making units (DMUs). The DMUs is homogenous in the sense it uses the same inputs to produce the same outputs (Amin & Toloo, 2007).There are mainly two DEA models which can be divided into CCR model or BCC model (Zeng et al., 2009). In this study, the BCC model is used for measuring the technical efficiency of DMUs, which implies that increases in inputs would leads to changes in outputs in a variable rate, corresponding to the reducing principle of circular economy (Sağlam, 2017). To obtain the best BCC-efficient DMU:

$$\min \left[\theta -\epsilon \left({\hat{e}}^T{s}^{-}+e^T{s}^{+}\right)\right]=V_D$$

$$s.t.\underset{j=1}{\overset{n}{\sum }}{\lambda }_j{x}_j+s^{-}=\theta .x_{j0}$$

$$\underset{j=1}{\overset{n}{\sum }}{\lambda }_j{y}_j-s^{+}=y_{j0}$$

${\lambda }_j\ge 0,j=\mathrm{1,2},\dots ,n;s^{+}\ge 0,s^{-}\ge 0$ Eq. (1)

Suppose the optimal solution of the linear programming (1) is θ*, λ*, s^–*, s⁺*, then:

(a) if θ*=1 and s^–*=s⁺*=0, then MU is DEA effective;

(b) if θ*=1, but s^–* or s⁺* ≠ 0, then DMU is weakly DEA effective;

(c) if θ*<1, then DMU is DEA ineffective.

SBM Model

The BCC model is able to discover the effectiveness of DMUs (Zeng et al., 2009). However, it is not able to rank the DMUs efficiencies. This study deal with 48 DMUs with the input and output matrices X=(x_ij )∈R^mxn and Y=(y_ij)∈R^sxn, respectively. The dataset is assumed positive, X>0 and Y>0. The production possibility set P is defined as:

$P=\left\{(x,y)|x\ge X\lambda ,y\le Y\lambda ,\lambda \ge 0\right\}Eq.\left(2\right)$

Where λ is a non-negative vector in ${\mathbb{R}}^n$. Considering an expression for describing a certain DMU $(x_o,y_o)$ as:

$$x_o=X\lambda +s^{-}Eq.\left(3\right)$$

$$y_o=Y\lambda -s^{+}Eq.\left(4\right)$$

With $\lambda \ge 0,s^{-}\ge 0$ and $s^{+}\ge 0$. The vectors $s^{-}\in {\mathbb{R}}^m$ and $s^{+}\in {\mathbb{R}}^s$ indicate the input excess and output shortfall of this expression, respectively called slacks. Using s^- and s⁺, index ρ can define as follow:

$$\rho =\frac{1-\left(\frac{1}{m}\right){\sum }_{i=1}^m{s}_i^{-}/x_{io}}{1+\left(\frac{1}{s}\right){\sum }_{r=1}^s{s}_r^{+}/y_{ro}}Eq.\left(5\right)$$

To evaluate the efficiency of (x_o, y_o), the fractional program can be formulate in λ, s^- and s⁺. SBM minimize Eq. (5) subjected to Eq. (3) and (4). A DMU (x_o, y_o) is SMB-efficient if ρ* = 1 (Tone, 2011). The first assessment stands to measure their relative efficiency with BCC model. Should DMUs are DEA ineffective, the rank order can be obtained with their relative efficiency. If, on the other hand, DMUs are DEA effective, the SBM will be utilised to evaluate their efficiency. The rest of DMUs can then be ranked in accordance to the SBM efficiency value. Consequently, the ineffective unit of the DMUs can be improved with the SBM evaluation result.

Input-output indicators

The foundation of circular economy evaluation in the coal plant reflects the “3R” standard which are reduce, reuse and recycle (Zeng & Zhang, 2011). The circular economy effectiveness, along with the emission reduction can be evaluated through the consumption intensity, resource productivity, material flow intensity, water discharge rate, and etc. In the efficiency assessment, more output is desired as opposed to emissions (Zeng et al., 2009). The emissions, it is the unavoidable output resulted from the burning of fossil fuels (production factors). From a circular economy viewpoint, emissions, should be minimised under the evaluation. Hence, to run-through the DEA model, the emissions shall be considered as an input DMU’s, rather than output, in the analysis (Zeng et al., 2009).

In China for instance, 12 indicators were used in evaluating circular economy efficiency for coal-fired plant which include among others the water consumption, wastewater emissions, utilization of recycle water, etc. (Zeng & Zhang, 2011). However, due to data limitation in this study, only 6 indicators across the inputs, production, consumption and final discharge of emissions have been investigated. The input and output indicators used are as follows and the descriptive statistics of the data is shown in Table 01 :

Input indicators:

x1:Coal consumption per output unit

x2: Energy consumption per output unit

x3:Sulphur dioxide emissions per output unit

x4: CO₂ emissions per output unit

Output indicators:

y1: Ratio of Resource Output

y2: Total output value per power generation unit

Data isotonicity test of input-output indicators

There are 4 coal power plants operated in Peninsular Malaysia. However, due to data limitation, the study only able to collect data from supercritical coal plant (4 units × 700 MW) located in Peninsular Malaysia. A 12 month data for the year 2016 of the 4 units plant are used in the study which consist of 48 DMUs in the model. In the study, a total of 4 input and 2 output are used as indicators for circular economy measurement. The DEA model entails that the DMUs shall be homogenous with comparability and meet the isotonicity, which implies that the output must not decrease as the input increases (Ruiz & Sirvent, 2016). This can be confirmed using correlation analysis of the 48 DMUs indicators as shown in Table 02 . The result revealed that the input and output indicators are all positively correlated. This indicates that the input and output of the coal plant meet the isotonicity requirement and it reflects the relationship required for implementing the circular economy.

Assessment Result

The survey data of the 48 unit of the plant are listed in Table 03 , with which the efficiencies of the 48 DMUs are calculated by BCC model using DEA software.

The results in Table 04 depicts that the circular economy efficiencies of 11 units plant are equivalent to 1, which implies DEA-effective while another 37 units plant are relatively inefficient such as P13 – P24, P26 – P36, P38-P41, P45, P48, P410 and P411, and > θ*P48 > θ*P39 > θ*P26 > θ*P21, > θ*P41 > θ*P312 > θ*P38 > θ*P45 > θ*P411 > θ*P210 > θ*P34 > θ*33 > θ*P29 > θ*P410 > θ*P18 > θ*P31 > θ*P17 > θ*P110 > θ*P36 > θ*P35 > θ*P28 > θ*P15 > θ*P27 > θ*P310 > θ*P112 > θ*P23 > θ*P22 > θ*P311 > θ*P24 > θ*P211 > θ*P32 > θ*P212 > θ*P14 > θ*P13 > θ*P111 > θ*P16 > θ*P19.

Next, the effective DMUs are further assessed by Slack-based model (SBM), to acquire efficiency for the rest of the plants. The data is evaluated and the results are listed in Table 04 . The result reveals that all the SBM efficiency of the rest 11 units plant are equal to 1, and θ'*P11 > θ'*P12 > θ'*P25 > θ'*P37 > θ'*P42 > θ'*P43 > θ'*P44 > θ'*P46 > θ'*P47 > θ'*P49 > θ'*P412. Hence, the rank order of the 48 units plants for circular economy efficiency are P11 > P12 > P25 > P37 > P42 > P43 > P44 > P46 > P47 > P49 > P412 > P48 > P39 > P26 > P21 > P41 > P312 > P38 > P45 > P411 > P210 > P34 > P33 > P29 > P410 > P18 > P31 > P17 > P110, > P36 > P35 > P28 > P15 > P27 > P310 > P112 > P23 > P22 > P311 > P24 > P211 > P32 > P212 > P14 > P13 > P111 > P16 > P19. It is evident from the result that P11 can be regarded as the benchmark of common best practices in the plant management plan and served as baseline for performance and technical efficiency improvement of other unit of the coal plant.

Improvement of DEA Inefficient Unit Plant

The aim of the evaluation is for improving the inefficient DMUs. From the SBM results indicated in Table 04 , the projected value of ineffective DMUs of P13– P24, P26 – P36, P38-P41, P45, P48, P410 and P411 can be calculated with model in Eq. (5) and the result is shown in Table 05 . Hence, the efficiency of 37 units’ of the plant can be improved according to the projected value. The efficiency performance could be achieved, among others, by upgrading or modifying plant design, increasing heat rate, use better coal type and grade, etc. (Malek et al., 2013).