Efficiency of Power Distribution Companies in Pakistan (Application of Non Parametric Approach)

Efficiency of Power Distribution Companies in Pakistan (Application of Non Parametric Approach)

Nauman Mushtaq1,Dr Moghira Badar2,Dr Faiza Akhtar3, Dr Fatima Batool4,Dr Muhammad Ejaz Sandhu5,Dr Muhammad Imran Khan6,Fahad Saddique7,Salman Sarwar8,Muhammad Ahsan Zia9

1Phd Scholar, The Institute of Management Science Lahore. nauman_mushtaq1@yahoo.com

2(Ph.D),Salar International University Lahore. moghirab@yahoo.com

3(Ph.D),BUITEMS Quetta Balochistan. faizaakhtar42@yahoo.com

4(Ph.D), University of the Punjab,Lahore. fatima.batool@cemb.edu.pk

5(Ph.D,) Director Operations, Shahid Javed Burki Institue of Public Policy at Netsol. Lahore. www.sjbipp.org dr.sandhu@sjbipp.org

6(Ph.D),The Institute of Management Science Lahore. dr.imran@pakaims.edu.pk

7Phd Scholar,The Institute of Management Science Lahore. fahad.sadique@gmail.com

8Phd Scholar, The Institute of Management Science Lahore. salmansarwar333@gmail.com

9University Of South Asia Lahore. ahsan45@gmail.com

ABSTRACT

Electricity is very significant at global level that is used the most useful type of energy in modern world. We will evaluate the distribution system in DISCO. This paper is focused on grounds regarding the grid, through this research of distribution network input & output characteristic, dependent about which is establishing a more objective estimation values and system from the economic aspect and by using the data envelopment analysis for evaluates their relative efficiencies. Using this way we can compare the performance of good company. Finally, by the help of this analysis for power distribution companies, this study provides a range of scientifically evaluation method for the improvements of a distribution system according to different state. Technical Efficiency is by CRS 97.2% by VRS 98.2% and Scale Efficiency is 99.0%.

Keywords- [1] DEA [2] DISCO’s

1. INTRODUCTION

Electric Power usage is the very important, for the locally and commercially utilization and the very much convenient source of energy in modern world. As a specific type of natural resource, electricity that cannot be stored, and its generation, transmission, supply to consumers and utilization is managed at the same stage. Along by the rapid growth of national economy and the increasing demand of the people’s materialistic approach and new living style, social and corporate culture for electricity is increasing. The basic need of the reliability and quality is increasing at high level, which is engaged in promoting the quick development of energy industry, grid expansion and technology advancement developing with continuous flow. The research on the evaluation in construction of grid has vital practical significance and importance for development of its efficiency and improving economic and social impacts on Pakistan.

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2. LITRATURE REVIEW

DEA model is a very effective and ideal to calculate the efficiency of multi input & multi output both decision making units. However, DEA technique is useful in the evaluating about Financial Institutions, Multilateral Agencies, Educational Institutes, Medical Fields, Universities, Public Limited Companies, Banking Sector, Tourism Firms and Stock Market. In previous decades, DEA method has been used to evaluate the efficiency of the power sector. First time this application technique of DEA technique was used for power system and power field. Luo Daoping and Xiao Di (1996) analyzed the all factors on production of eight Chinese grids by using the DEA model and researched the classification and its scale [3]. Some other research scholars Wang Enchuang and Ren Yulong in (2008) worked on empirical study on the input and output effectiveness of grid of Chongqing by indirect and direct layer [4]. Zhou Ming and Zhao Wei in (2008) conducted study of the operating efficiency from the perspectives about the grids enterprise combining DEA and yardstick to compare competition [5]. Despite for the evaluation of efficiency of distribution companies is more important from the grid system planning technique aspect, like as to considering the reliable, safe and the quality of electric power delivery to consumer and industry etc. Even also for the local and international literature probably is regarding less for the analyzing for the scale to economic, scale appropriate condition and input & output integration of performance after doing the planning is accomplished and also converted to operational state.

In all process of electricity industry reform, tackling a lot of uncertain existing factors, about how to generating and designing suitable index about grid company and how to put forward coordinating evaluation method or techniques and procedure have vital practically importance about the companies to make objective, appropriate, clean, fairly and suitable evaluation and for a power distribution company to improvement the stages of managing, promoting efficiency, investing decision and inauguration the new project with scientific method and perfect for the benefits and for restraint the mechanism.

3. THE EVALUATION METHOD OF (DEA)

The DEA stands for data envelopment analysis is actually beneficial decision technique while estimating the relative performance for the homogeneous department or some unit and that can be utilized in all segments of life. In year of 1978, the initial DEA model was introduced which is put forward by many famous operational activities by researchers A. charnes, W.W.Cooper and E.Rhodes is named C2R model and it was fruitful to calcuate the relative efficiency of decision making units [6] and Lewin in 1994 [7]. In study of economic, DEA is also a very useful weapon while researching the boundary manufacturing or productions that have multiple inputs and multiple outputs units However, it can be utilized to research and identify the errors and problems which also relevant with multilateral manufacturing or producing function, like as the rates of progress in technology, the indexes of productivity and scale, the minimum cost problem with maximum benefits.

Since the DEA method does not need to estimate parameters in advance, it has underestimated superiority in avoiding subjective factors, simplifying operations and reducing error, etc. Compared with other methods, the biggest advantage of DEA method is that it is pure technical, need not given an advance known production function with the parameters, it provides excellent model for the comparison of efficiency between different distribution network.

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4. DESIGN OF MODEL MATHEMATICALLY

Efficiency of Disco firms has been calculated by non-parametric (Programming) methods. Charnes et al. (1978-1981) who invented the term DEA apply the same work on multi input and output models. It is mostly used to find the efficiency in all fields of study. To find out the efficiency it works on Decision Making Units (DMU) and selects the best one from all of these decision making units DMUs. The finding of DEA lies between one and zero because it uses the maximum ratio of weighted input and output if the results are one it means the unit is efficient but on the other hand if results are zero or less than one then the unit is inefficient. Most of the researchers considered it to be the best for the small size of observation. P Zhou and Kim Leng Poh in (2008) [8] and jarite and Maria also used DEA in their study (2010).[9]

According to Asghar and Afza (2010)[10] “The input oriented DEA model is used to estimate technical efficiency pure technical efficiency and scale efficiency which if given in figure (1)

Min λ0θ0

s.t. Σ λ 0j yrj ≥ y r0 (r = 1…….s) (1

θ 0 xi0 ≥ Σ n J=1λ0j xij (i = 1…….n) (2

Σ n J=1 λ 0j = 1 (3

λ0j ≥ 0 (j = 1…….n)

1) Σ λ 0j y rj ≥ y r0 (1) is the output constraint.

2) θ 0 x i0 ≥ Σ λ j x 0 is the input constraint.

yrj and xio are the output and input of the nth DMU whereas; λ is the weight. 0 is the DMU which is to be measured and by solving the non-parametric model, we can get the minimum θ0 which is the vector of the efficiency score. The index j specifies DMUs for j=1,…,N. yrj is the rth output of the jth firm for r=1,..,R. xij indicates the ith input of the jth DMU for I = 1,…,I (Mahlberg, 2000).[11] The third constraint introduces variable return to scale (VRS) into the model and if third constraint is dropped, the frontier technology converts from VRS to CRS. Moreover, if (Σλ0j ≤ 1) is applied instead of third constraint, the new model can even determine the reason of scale inefficiency that could be increasing return to scale (IRS) or decreasing return to scale (DRS)”.

5. INDEX SYSTEM FOR EVALUATION DESIGN & OBJECTIVE OF STUDY

DEA model is perfect and ideal to evaluate the efficiency of multi input & output both decision making units know which unit is performing better and find potential area to use for implementation of new reforms.

DETERMINE THE INPUT & OUTPUT INDICATORS (VARIABLES)

Distribution Company is system of supply of electricity to consumer or industry that is consisted of Power Transformer Substation, Power Distribution Substation, Power Transmission Lines (including cable) Relays, Breaker, Towers, Panels, Circuit, Meters, Switches, Power Batteries, Alarms of Safety, Security monitoring Equipments and other Power Supply Equipments & facilities with switch yard and power house or control room. Grid is the main central point and vital component of a power system, the flexibility in system and also robustness interpret the reliability for the complete power system. Operation in Grid fundamentally through the gradually reducing of the voltages and after that delivered to the relevant industry or consumer, some of this specific process is shown in Figure 1 given below:

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60KV 32KV Terminal

(FIG 1) THE CHART OF POWER FOR DISCO

Figure No 1 showed regarding the different levels of voltage of electric power can be further divided into parts of transmission level, distribution level, sale of electricity and other related systems in power sector. 500KV and 220KV in this power supply system are related to part of the NTDC transmission system while and DISCO’s Level this started with 120KV grids and lower are part of distribution system, which is mainly consist about 120KV substation and supply lines even 10KV and lower are for consumer & commercial sector as per their demand..

At the last stage of the power supply system the distribution system connected directly with consumer including the power generation system, transmission system and distribution system is also very important link for contacting consumer, supply of power and distribution of electricity. Normally the system which is stepped down substation second time or the system which is providing power to consumers after the stepping down is called the distribution system.

The distribution system has the greatest impact on supply for users. In fact, the supply of scale, level and the degree of rationality can intensively reflect the system of structure and its operational characteristics. Therefore, this paper will take distribution system as the research object.

Table I Input and Output Variables (Indicators)

Regarding to the above principles for setting targets also combined by the real distribution system, and taking the opinion of experts into account [12][13][14], selected the input & output variables shown in TABLE I.

Static Descriptive Table (II)

6. DATA ANALYSIS

As per to the input & output variables (indicators) Table I, we have investigated 10 DISCO,s Electricity supply Companies 11 years real data and averaging for getting a set of raw as data descriptive Statics. See TABLE II. While Table III displaying The DISCO’S (Power Distribution Companies of Pakistan)

Table IV shows Power All Annually Input-Output Indicators (Slack) for the period of 2014 to 2024.

(Power Distribution Companies of Pakistan) Table III

Summary of Slacks Distribution Companies of Pakistan (2014 to 2024)

empirically analysis of every DISCO and the changes, and searching out the reason, initially, this paper used genuine data [15] of input & output oriented model [16] of (win4deap2 by DEAP 2.1 software) introduced by TIM COELLI CEPA to evaluate the 11-year average result of efficiency and the input redundancy also about the output deficit, which is a type of static analysis. However we used the Malmquist Model at multistage of the DEAP software to analysis of every DISCO DMU at average changes for total factor supply which is dynamic analyzing.

7. RESULT & DISCUSSION

(Table V) The DISCO’s Efficiency of Input & Output Variables

of Pakistan (2014 to 2024)

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About TABLE V when assumed that constant returns to scale Crste represents. The Technical Change (Techch) which is the obtained result depends on the BC 2 Model while not assuming constant returns to scale the Vrste indicted the Efficiency Change (Effch), which is to be be decomposed to Pure Efficiency Change (Pech) and Scale Efficiency Change (Sech). Scale states the returns to scale,

scale=crste / vrste. The Vrste and Scale are the results depending upon C2R Model. And the column at last, IRS & DRS respectively showed the increased, Constant(-) and decreased returns to scale. They are evaluated from ∑λ j , ∑λ j < 1 , This indicates the increased returns to scale, ∑λ j = 1 , this indicates the Constant returns to scale, ∑λ j > 1 , this indicates the decreased returns to scale.

[Note]

CRSTE

Stands for Technical

Efficiency from CRS DEA

VRSTE Stands for Technical

Efficiency from VRS DEA

SE Stands for Scale

Efficiency=CRSTE/VRSTE

RTS Stands for Return to Scale(DRS IRS CRS)

DRS Stands for Decreasing Return to Scale

IRS Stands for Increasing Return to Scale

CRS Stands for Constant Return to Scale (-)*symbol

Malmquist index has an advantage, namely it doesn’t need to involve whether to consider constant returns to scale or not, because when calculating, Malmquist model uses both Crste and Vrste. Malmquist indexes, namely Tfpch, can be decomposed into Efficiency Change (Effch) and Technical change (Techch), and Efficiency change (Effch) can be further decomposed into Pure Efficiency Change (Pech) and Scale Efficiency Change (Sech).

While Effch≥1 meaning about the overall Efficiency has been raised upward, Pech≥1 meaning Pure Efficiency has been incresed, Sech≥1 meaning Scale Efficiency has been enhanced, Techch≥1 meaning the progress in technology, Total Factor Productivity Tfpch is decomposed into Effch and Techch, when Effch and Techch combined operate and make Tfpch increase, then the Tfpch≥1.

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(FIG 2) Power System in Pakistan

TABLE V explained about the results of efficient and no efficient DMUs as below yearly.

In year 2014 DMU 1 & 10 is high efficient and 6 & 7 is lower efficient with decreasing trend and 2 & 4 increasing.

In year 2015 DMU 4 & 5 is high efficient and 3 & 7 is lower efficient with decreasing trend 4 & 10 increasing.

In year 2016 DMU 4 & 5 is high efficient and 6 & 7 is lower efficient with decreasing trend 9 & 10 increasing.

In year 2017 DMU 4 & 5 is high efficient and 6 & 7 is lower efficient with decreasing trend 2 & 9 increasing.

In year 2018 DMU 4 & 5 is high efficient and 2 & 7 is lower efficient with decreasing trend 2 & 9 increasing.

In year 2019 DMU 4 & 5 is high efficient and 3 & 8 is lower efficient with decreasing trend 9 increasing.

In year 2020 DMU 4 & 5 is high efficient and 7 & 8 is lower efficient with decreasing trend 9 increasing.

In year 2021 DMU 4 & 5 is high efficient and 7 & 8 is lower efficient with decreasing trend 9 increasing.

In year 2022 DMU 4 & 5 is high efficient and 6 & 7 is lower efficient with decreasing trend 9 increasing.

In year 2023 DMU 4 & 5 also 4 & 6 is high efficient and 7 & 8 is lower efficient with decreasing trend no increasing.

In year 2015 DMU 4 & 5 also 1 &2 is high efficient and 7 & 8 is lower efficient with decreasing trend 9 increasing.

From TABLE V, compared with the 10 DMUs the efficiency of 4 and 5 are the highest DMUs, namely effective. DMU 9 is increasing while the other 7 and 8 indicated failure to achieve the high innovation efficiency because of the mainly their respective efficiency to scale are at lower stage and returns to scale are at decreasing trends.

At average level of 11 years data the result of Technical Efficiency is by CRS 97.2% by VRS 98.2% and Scale Efficiency is 99.0%.By the achieved result, we can judge the result that each DMU should focus on improvement regarding the Technical Changes for the purpose to raise the Total Factor Productivity.

8. CONCLUSION

At this current stage, we know the effectiveness of power generating companies has been paid wide level attention for research. Also a lot of researchers used the DEA techniques to examination of this subject of Generation while the distribution companies are rarely selected as main research purpose. There are still few important fields which are required for new findings. However, by purpose to adapt to the new reforms and latest development of the electricity distribution sector, this research is a small try to understand the input & output effectiveness of distribution companies from more critical aspect.

The explained result indicated that Technical Efficiency is by CRS 97.2% by VRS 98.2% and Scale Efficiency is 99.0%. While the input redundancy existed, so it is necessary for the management to made better distribution system plans and investing management technology, and to save the excessive wastage of available precious resources. In specifically as for the ineffective & lower level DMUs, under the premise of emphasizing its operational procedures and for economic society coordination on development the management should take general consideration, as per the direction of redundancy and its amounts for grasp out the direction of DISCO grid system performance. Specially for

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diminishing the line losses (distribution & Transmission) rate & improvement of technology in each level there has a big space for management should put enough good effort in these potential areas.

9. REFERENCE

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[2] Soonhu Soh & Md Tamzid Parves, “An Efficiency Analysis of Combine Cycle Power Plants using DEA Models: A case study in Bangladesh” International Journal of Mechanical and Production Engineering Research and Development (IJMPERD) ISSN (P): 2249-6890; ISSN(E): 2249.

[3] Luo Daoping and Xiao Di, “The application of data envelopment analysis (DEA) in electric power industry”, System Engineering Theory and Practice, Apr.1996, pp.60-65.

[4] Wang Enchuang, Ren Yulong and Liu Zhen, “Input-output efficiency assessment of Chongqing distribution network by using DEA”,East China Power, vol.36,Jun.2008, pp.34-37.

[5] Zhou Ming, Zhao Wei, Wang Peng and Li Gengyin, “A hierarchical yardstick competition approach to assessing operation performance of distribution utilities”, Electrical power system automation, vol.32, Apr.2008, pp.20-24.

[6] Charnes A, Cooper W W and Rhodes E, “Measuring the efficiency of decision making units”, European Journal of Operational Research, Feb.1978, pp.429-444.

[7] Charnes A, Cooper W W and Lewin A, “Data envelopment analysis: theory, methodology and application”, Kluwer Acdemic, 1994.

[8] Zhou, P., Ang, B. W., & Poh, K. L. (2008). A survey of data envelopment analysis in energy and environmental studies. European Journal of Operational Research, 189(1), 1–18. https://doi.org/10.1016/j.ejor.2007.04.042.

[9] Jaraite, J., & Di Maria, C. (2012). “Efficiency, productivity and environmental policy: A case study of power generation in the EU. Energy Economics, 34(5). https://doi.org/10.1016/j.eneco.2011.11.017

[10] Afza, T., & Asghar, M. J. A. (2012). “Financial reforms and efficiency in the insurance companies of Pakistan. African Journal of Business Management”, 6(30), 8957–8963. https://doi.org/10.5897/AJBM11.1821

[11] B Mahlberg, M Luptacik system, European Journal of Operational Research 234 (3), 885-897.

[12] Wang Enchuang, Ren Yulong and Zhu Chunbo, “The overall efficiency study of distribution network based on fuzzy DEA method”, Industrial Engineering and Management, vol.14, Feb.2009, pp.81-87.

[13] Wang Enchuang, Ren Yulong and Zhu Chunbo, “The evaluation study of electrical energyenvironment coordinated development based on DEA”, Technology Management Research, Mar.2009, pp.164-166.

[14] Teng Fei and Wu Zongxin, “Performance Analysis of China Electric Power Enterprises”, Quantitative and Technical Economics Research. Jun.2003,pp.127-130.

[15] Survey Reports of DISCO’s in Pakistan published by Ministry of Energy Power Division Pakistan.

[16] Mushtaq, N & Saddique,F, “Efficiency of Power Generation Companies in Pakistan: Application of Non-Parametric Approach” Ilkogretim Online - Elementary Education Online, 2020; Vol 19 (Issue 4): pp. 3486-3504 http://ilkogretim-online.orgdoi::10.17051/ilkonline.2020.04.764735.

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