DOI: https://doi.org/10.14710/ijred.2023.48487

Performance Assessment of Malaysian Fossil Fuel Power Plants: A Data Envelopment Analysis (DEA) Approach

1Department of Defence Science, Faculty of Defence Science and Technology, Kem Sungai Besi, 57000 Kuala Lumpur, Malaysia

2Department of Computer Science, Faculty of Defence Science and Technology, Kem Sungai Besi, 57000 Kuala Lumpur, Malaysia

Received: 24 Aug 2022; Revised: 15 Oct 2022; Accepted: 27 Dec 2022; Available online: 8 Jan 2023; Published: 15 Mar 2023.
Editor(s): H Hadiyanto
Open Access Copyright (c) 2023 The Author(s). Published by Centre of Biomass and Renewable Energy (CBIORE)
Creative Commons License This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

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Abstract

This paper investigated the performance of Malaysian power plants from the year 2015 to 2017 using Malmquist Total Factor Productivity (TFP) index, which is based on Data Envelopment Analysis (DEA). This approach offers substantial advantages as compared to other existing methods as it can measure productivity changes over time for a variety of inputs and outputs. Moreover, it comprises two primary components: the technical efficiency change and the technological change indexes that provide clearer insight into the factors that are responsible for shifts in total factor productivity. This study uses a single input, installed generation capacity (MW), and two outputs, average thermal efficiency (%) and average equivalent availability factor (%). These output-input data included ten main power plants: TNB Natural Gas, SESB Natural Gas, SESB Diesel, SEB Natural Gas, SEB Coal, SEB Diesel, IPP Semenanjung Natural Gas, IPP Semenanjung Coal, IPP Sabah Natural Gas, and IPP Sabah Diesel. The results have two significant implications for fossil fuel power plants in Malaysia. First, technological change was the primary factor in boosting the TFP performance of the fossil fuel power plants in Malaysia. Meanwhile, the decline in TFP performance in Malaysian fossil fuel power plants may be attributed, in part, to a lack of innovation in technical components as the results found that the average technical efficiency changes in 2015 – 2016 were at 146% and then dropped significantly to 2% in 2016 – 2017. Second, the average scale efficiency changes rose dramatically from -53% to 3% providing a significant contribution to the improvement of technical efficiency changes. The fossil fuel power plants become efficient as the power plants’ size increases. This indicates that the size of a power plant positively impacts the performance of the TFP.

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Keywords: energy; data envelopment analysis; efficiency; productivity; power plants; electricity

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Section: Original Research Article
Language : EN
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  1. Abdul Latif, S. N., Chiong, M. S., Rajoo, S., Takada, A., Chun, Y. Y., Tahara, K., & Ikegami, Y. (2021). The Trend and Status of Energy Resources and Greenhouse Gas Emissions in The Malaysia Power Generation Mix. Energies, 14(8), 2200. https://doi.org/10.3390/en14082200
  2. Azhar Noraini (2021) Malaysia’s Voluntary National Review (VNR) 2021. United Nations. https://sustainabledevelopment.un.org/memberstates/malaysia. Accessed on 18 October 2022
  3. Babatunde, K. A., Said, F. F., Nor, N. G. M., & Begum, R. A. (2018). Reducing Carbon Dioxide Emissions from Malaysian Power Sector: Current Issues and Future Directions. Engineering Journal, 1(6), 59-69. https://doi.org/10.17576/jkukm-2018-si1(6)-08
  4. Bahman Z., & Patrick M. (2021). Chapter 9 - Energy Insight: An Energy Essential Guide. In Introduction to Energy Essentials. Academic Press, 321-370. https://doi.org/10.1016/B978-0-323-90152-9.00009-8
  5. Charnes, A., Cooper, W., & Rhodes, E. (1978). Measuring the Efficiency of Decision-Making Units. European Journal of Operational Research, 2(6), 429–444. https://doi.org/10.1016/0377-2217(78)90138-8
  6. Cooper, W.W., Seiford, L.M., Zhu, J. (2004). Data Envelopment Analysis. In Cooper, W.W., Seiford, L.M., Zhu, J. (eds) Handbook on Data Envelopment Analysis. International Series in Operations Research & Management Science. Springer. https://doi.org/10.10 07/1-4020-7798-X_1
  7. Du, M., Liu, Y., Wang, B., Lee, M., & Zhang, N. (2021). The Sources of Regulated Productivity in Chinese Power Plants: An Estimation of the Restricted Cost Function Combined with DEA Approach. Energy Economics, 100, 105318. https://doi.org/10.1016/j.eneco. 2021.105318
  8. Fare, R., Grosskopf, S., Norris, M., & Zhang, Z. (1994). Productivity Growth, Technical Progress, and Efficiency Change in Industrialized Countries. The American economic review, 66–83
  9. Fare, R., Shawna, G., Bjorn, L., & Ross, P. (1989). Productivity Development in Swedish Hospitals: A Malmquist Output Index Approach. In Charnes, A., Cooper, W.W., Lewin, A., & Seiford, L. (Eds), Data Envelopment Analysis: theory, Methodology and Applications. Kluwer Academic Publisher. https://doi.org/10.1007/978-94-011-0637-5_13
  10. Hannah R., Max R. and Pablo R. (2020) Energy, OurWorldInData.org. https://ourworldindata.org/energy. Accessed on 18 October 2022
  11. IEA (2019). Electricity Information Overview, Technical Report IEA
  12. James D. (2022). What is Thermal Efficiency? https://www.aboutmechanics.com/what-is-thermal-efficiency.htm. Accessed on 18 October 2022
  13. James J. (2019). Power Plant Explained, Working Principles. https://realpars.com/power-plant/. Accessed on 13 October 2022
  14. Khanjarpanah, H., Jabbarzadeh, A., & Seyedhosseini, S. M. (2018). A Novel Multi-Period Double Frontier Network DEA to Sustainable Location Optimization of Hybrid Wind-Photovoltaic Power Plant with Real Application. Energy Conversion and Management, 159, 175-188. https://doi.org/10.1016/j.encon man.2018.01.013
  15. Khanjarpanah, H., & Jabbarzadeh, A. (2019). Sustainable Wind Plant Location Optimization using Fuzzy Cross-Efficiency Data Envelopment Analysis. Energy, 170, 1004-1018. https://doi.org/10.1016/j. energy.2018.12.077
  16. Li, A., Zhang, A., Huang, H., & Yao, X. (2018). Measuring Unified Efficiency of Fossil Fuel Power Plants Across Provinces in China: An Analysis Based on Non-Radial Directional Distance Functions. Energy, 152, 549-561. https://doi.org/10.1016/j.energy.2018.03.164
  17. Linda D. (2017) EIA projects 28% Increase in World Energy Use by 2040. U.S. Energy Information Administration. https://www.eia.gov/todayinenergy/detail.php?id=32912. Accessed on 18 October 2022
  18. Mahmoudi, R., Emrouznejad, A., Khosroshahi, H., Khashei, M., & Rajabi, P. (2019). Performance Evaluation of Thermal Power Plants Considering CO2 Emission: A Multistage PCA, Clustering, Game Theory and Data Envelopment Analysis. Journal of Cleaner Production, 223, 641–650. https://doi.org/10.1016/j.jclepro.2019.03.047
  19. Mariano, J. R. L., Liao, M., & Ay, H. (2021). Performance Evaluation of Solar PV Power Plants in Taiwan Using Data Envelopment Analysis. Energies, 14(15), 4498. https://doi.org/10.3390/en14154498
  20. Ministry of Energy, Green Technology and Water (KeTTHA) (2017) Green Technology Master Plan Malaysia 2017 – 2030. https://www.pmo.gov.my/wp-content/uploads/2019/07/Green-Technology-Master-Plan-Malaysia-2017-2030.pdf. Accessed on 13 October 2022
  21. Munisamy, S., & Arabi, B. (2015). Eco-efficiency Change in Power Plants: Using A Slacks-Based Measure for the Meta Frontier Malmquist Luenberger Productivity Index. Journal of Cleaner Production, 105, 218–232. https://doi.org/10.1016/j.jclepro.2014.12.081
  22. Mushtaq, F., Maqbool, W., Mat, R. & Nasir Ani, F. (2013). Fossil Fuel Energy Scenario in Malaysia-Prospect of Indigenous Renewable Biomass and Coal Resources. In 2013 IEEE Conference on Clean Energy and Technology (CEAT), 232 -237. https://doi.org/10.1109/ceat.2013.6775632
  23. Mustapa, S. M., & Majid M. B. (2017). Efficiency Assessment of Malaysian Coal-Fired Power Plant: A Circular Economy Perspective. In 8th International Economics and Business Management Conference (IEBMC 2017). https://doi.org/10.15405/epsbs.20 18.07.02.66
  24. Nattanin U., Shu-Yi L., Anupong W. (2015). The Technical Efficiency of Rice Husk Power Generation in Thailand: Comparing Data Envelopment Analysis and Stochastic Frontier Analysis. Energy Procedia, 75, 2757-2763. https://doi.org/10.1016/j.egypro.2015.07.518
  25. NS Energy Staff Writer (2020). What are the Different Types of Power Plants Used to Generate Energy? NS Energy. https://www.nsenergybusiness.com/features/newsmajor-types-of-power-plants-to-generate-energy-151217-6004336y/. Accessed on 13 October 2022
  26. Petronas Annual Report 2019 (2019). Petronas. https://www.petronas.com/sites/default/files/Media/PETRONAS-Annual%20Report-2019-v2.pdf. Accessed on 23 October 2022
  27. Pritish B. and Francis E. H. (2022). Malaysia’s Oil and Gas Sector: Constant Expectations despite Diminishing Returns. ISEAS Yusof Ishak Institute. https://www.iseas.edu.sg/wp-content/uploads/2022/01/ISEAS_Perspective_2022_21.pdf. Accessed on 23 October 2022
  28. Rentizelas, A., Melo, I. C., Junior, P. N. A., Campoli, J. S., & do Nascimento Rebelatto, D. A. (2019). Multi-criteria efficiency assessment of international biomass supply chain pathways using Data Envelopment Analysis. Journal of Cleaner Production, 237, 117690. https://doi.org/10.1016/j.jclepro.2019.117690
  29. Resource Adequacy Planning (2020) PJM Manual 22: Generator Resource Performance Indices. PJM. https://pjm.com/~/media/documents/manuals/m22.ashx . Accessed on 18 October 2022
  30. Rezaee, M. J., & Dadkhah, M. (2019). A Hybrid Approach Based on Inverse Neural Network to Determine Optimal Level of Energy Consumption in Electrical Power Generation. Computers & Industrial Engineering, 134, 52-63. https://doi.org/10.1016/j.cie.2019.05.024
  31. Sahoo, N. R., Mohapatra, P. K., & Mahanty, B. (2018). Examining the Process of Normalising the Energy-Efficiency Targets for Coal-based Thermal Power Sector in India. Renewable and Sustainable Energy Reviews, 81, 342–352. https://doi.org/10.1016/j.rser.2017.08.005
  32. Samsudin, M. S. N., Rahman, M. M. & Wahid, M. A. (2016). Power Generation Sources in Malaysia: Status and Prospects for Sustainable Development. Journal of Advanced Review on Scientific Research, 25(1), 11-28
  33. Sarica, K., & Or, I. (2007). Efficiency Assessment of Turkish Power Plants using Data Envelopment Analysis. Energy, 32(8), 1484–1499. https://doi.org/10.1016/j.energy.2006.10.016
  34. Sözen, A., Alp, ˙I., & ozdemir, A. (2010). Assessment of Operational and Environmental Performance of the Thermal Power Plants in Turkey by Using Data Envelopment Analysis. Energy Policy, 38(10), 6194–6203. https://doi.org/10.1016/j.enpol.2010.06.005
  35. Şeyma, E. M. E. Ç., Tuba, A. D. A. R., Akkaya, G., & Delice, E. K. (2019). Efficiency Assessment of Hydroelectric Power Plant in Turkey by Data Envelopment Analysis (DEA). Avrupa Bilim ve Teknoloji Dergisi, 34-45. https://doi.org/10.1016/j.eneco.2011.04.001
  36. Sharvini, S. R., Noor, Z. Z., Chong, C. S., Stringer, L. C., & Yusuf, R. O. (2018). Energy Consumption Trends and Their Linkages with Renewable Energy Policies in East and Southeast Asian Countries: Challenges and Opportunities. Sustainable Environment Research, 28(6), 257-266. https://doi.org/10.1016/j.serj.2018.08.006
  37. Sueyoshi, T., Li, A., & Gao, Y. (2018). Sector Sustainability on Fossil Fuel Power Plants Across Chinese Provinces: Methodological Comparison among Radial, Non-Radial and Intermediate Approaches Under Group Heterogeneity. Journal of Cleaner Production, 187, 819-829. https://doi.org/10.1016/j.jclepro.2018.03.216
  38. Sueyoshi, T., Liu, X., & Li, A. (2020a). Evaluating the Performance of Chinese Fossil Fuel Power Plants by Data Environment Analysis: An Application of Three Intermediate Approaches in a Time Horizon. Journal of cleaner production, 277, 121992. https://doi.org/10.1016/j.jclepro.2020.121992
  39. Sueyoshi, T., Qu, J., Li, A., & Xie, C. (2020b). Understanding the Efficiency Evolution for the Chinese Provincial Power Industry: A New Approach for Combining Data Envelopment Analysis-Discriminant Analysis with an Efficiency Shift Across Periods. Journal of Cleaner Production, 277, 122371. https://doi.org/10.1016/j.jclepro.2020.122371
  40. Sun, C., Liu, X., & Li, A. (2018). Measuring Unified Efficiency of Chinese Fossil Fuel Power Plants: Intermediate Approach Combined with Group Heterogeneity and Window Analysis. Energy Policy, 123, 8-18. https://doi.org/10.1016/j.enpol.2018.08.029
  41. Suruhanjaya Tenaga Malaysia (2020) Performance & Statistical Information on the Malaysian Electricity Supply Industry 2018. https://meih.st.gov.my/
  42. Suruhanjaya Tenaga Malaysia (2021) Malaysia Energy Statistics Handbook 2020. Energy Data and Research Unit. https://meih.st.gov.my/
  43. Tajbakhsh, A., & Hassini, E. (2018). Evaluating Sustainability Performance in Fossil-Fuel Power Plants Using a Two-Stage Data Envelopment Analysis. Energy Economics, 74, 154-178. https://doi.org/10.1016/j.eneco.2018.05.032
  44. Tapia, J. F. D., Promentilla, M. A. B., Tseng, M. L., & Tan, R. R. (2017). Screening of Carbon Dioxide Utilization Options using Hybrid Analytic Hierarchy Process-Data Envelopment Analysis Method. Journal of Cleaner Production, 165, 1361-1370. https://doi.org/10.1016/j.jclepro.2017.07.182
  45. U.S. Energy Information Administration (2017) International Energy Outlook 2017. https://www.eia.gov/outlooks/ieo/pdf/0484(2017).pdf . Accessed on 18 October 2022
  46. U.S. Energy Information Administration (2021) International Energy Outlook 2021. https://www.eia.gov/outlooks/ieo/ Accessed on 13 October 2022
  47. U.S. Energy Information Administration (2021) Country Analysis Executive Summary: Malaysia. https://www.eia.gov/international/content/analysis/countries_long/Malaysia/malaysia.pdf. Accessed on 12 October 2022
  48. Wang, C. N., Dang, T. T., & Wang, J. W. (2022). A Combined Data Envelopment Analysis (DEA) and Grey Based Multiple Criteria Decision Making (G-MCDM) for Solar PV Power Plants Site Selection: A Case Study in Vietnam. Energy Reports, 8, 1124-1142. https://doi.org/10.1016/j.egyr.2021.12.045
  49. Wang, C. N., Dang, T. T., & Bayer, J. (2021). A Two-Stage Multiple Criteria Decision Making for Site Selection of Solar Photovoltaic (PV) Power Plant: A Case Study in Taiwan. IEEE Access, 9, 75509-75525. https://doi.org/10.1109/access.2021.3081995
  50. Wang, Z., Li, Y., Wang, K., & Huang, Z. (2017). Environment-Adjusted Operational Performance Evaluation of Solar Photovoltaic Power Plants: A Three Stage Efficiency Analysis. Renewable and Sustainable Energy Reviews, 76, 1153-1162. https://doi.org/10.1016/j.rser.2017.03.119
  51. Wang, C. N., Nguyen, V. T., Thai, H. T. N., & Duong, D. H. (2018). Multi-Criteria Decision Making (MCDM) Approaches for Solar Power Plant Location Selection in Vietnam. Energies, 11(6), 1504. https://doi.org/10.3390/en11061504
  52. Wu, Y., Ke, Y., Xu, C., Xiao, X., & Hu, Y. (2018). Eco-efficiency Measurement of Coal-Fired Power Plants in China Using Super Efficiency Data Envelopment Analysis. Sustainable Cities and Society, 36, 157–168. https://doi.org/10.1016/j.scs.2017.10.011
  53. Zhang, N., Zhao, Y., & Wang, N. (2022). Is China's Energy Policy Effective for Power Plants? Evidence from The 12th Five-Year Plan Energy Saving Targets. Energy Economics, 112, 106143. https://doi.org/10.1016/j.eneco.2022.106143

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