Investigating the Efficiency of Combined Cycle Power Plants with the Data Envelopment Analysis Process (with an Emphasis on Air Pollution)

• Autorzy: Sanjaranipour Noushin , Atabi Farideh , Momeni Mansour , Ghodousi Jamal , Lahijanian Akramolmolok

Identyfikatory

DOI

10.7494/geom.2022.16.2.111

• Języki publikacji: EN

Abstrakty

EN

Performance management is one of the most significant strategies in promoting the efficiency of organizations and is highly sensitive. It is important to check the efficiency of combined cycle power plants because of their major contribution to power generation and air pollution. This study was conducted to evaluate the economic and environmental efficiency of Combined Cycle Power Plants (CCPPs). The inputs and outputs required to evaluate the performance of the power plants were determined according to expert opinions. Then, the 7-year statistics and information of the Qom, Neishabour, Shahid Rajaee, Yazd and Kerman power plants were collected as the desired CCPPs in Iran. The Window Data Envelopment Analysis (WDEA) method was used for evaluating the efficiency of the power plants. The 3-year window length showed that most of the power plants were efficient. Only the Rajaee, Neishabour and Yazd power plants were ineffective in some years. The mean efficiency of the power plants in the 4-year window length showed that the plants were efficient from 2008 to 2010.

Słowa kluczowe

EN

efficiency; Combined Cycle Power Plants; DEA; air pollution

• Wydawca: AGH University of Science and Technology Press
• Czasopismo: Geomatics and Environmental Engineering
• Rocznik: 2022
• Tom: Vol. 16, no. 2
• Strony: 111--125
• Opis fizyczny: Bibliogr. 16 poz., tab.

Twórcy

autor

Sanjaranipour Noushin

• Islamic Azad University, Science and Research Branch, Faculty of Natural Resources and Environment, Department of Environmental Management, Tehran, Iran

• https://orcid.org/0000-0002-9740-3900

autor

Atabi Farideh

• Islamic Azad University, Science and Research Branch, Department of Environmental Engineering, Tehran, Iran

• https://orcid.org/0000-0002-8192-2976

autor

Momeni Mansour

• University of Tehran, Department of Management, Tehran, Iran

• https://orcid.org/0000-0002-9157-5584

autor

Ghodousi Jamal

• Islamic Azad University, Science and Research Branch, Faculty of Natural Resources and Environment, Department of Environmental Management, Tehran, Iran

• https://orcid.org/0000-0002-2610-9886

autor

Lahijanian Akramolmolok

• Islamic Azad University, Science and Research Branch, Faculty of Natural Resources and Environment, Department of Environmental Management, Tehran, Iran

• https://orcid.org/0000-0002-8452-4324

Bibliografia

• 1. Key World Energy Statistics 2017. International Energy Agency, Paris 2017.
• 2. Samadi S.: The Social Costs of Electricity Generation – Categorising Different Types of Costs and Evaluating Their Respective Relevance. Energies, vol. 10(3), 2017, 356. https://doi.org/10.3390/en10030356.
• 3. Amani N., Bagherzadeh Valami H.: Efficiency Evaluation of regional electronic companies in Iran by Network DEA: A based on the Conversion of the Structures into a uniform structure. Journal of Decisions and Operations Research, vol. 3(3), 2018, pp. 249–280. https://doi.org/10.22105/dmor.2018.81213.
• 4. Shoghli A., Roshenas K.: Application of Balance Score Card (BSC) and Analytic Hierarchical Process (AHP) in assessment of academic departments: A case study in Zanjan School of Pharmacy. Journal of Medical Education Development, vol. 9(22), 2016, pp. 53–63.
• 5. Wen Z., Meng F., Chen M.: Estimates of the potential for energy conservation and CO2 emissions mitigation based on Asian-Pacific Integrated Model (AIM): the case of the iron and steel industry in China. Journal of Cleaner Production, vol. 65, 2014, pp. 120–130. https://doi.org/10.1016/j.jclepro.2013.09.008.
• 6. Fallah Shams lialestanei M., Raji R., Khajeh Poor K.: Performance Evaluation by Using Hybrid Method: BSC, TOPSIS and AHP. Industrial Management Journal, vol. 5(1), 2013, pp. 81–100. https://doi.org/10.22059/imj.2013.35684.
• 7. Adabi Firouzjah J., Mozafari S.A.A., Hadavi F.: Measuring the efficiency of provincial administrations of the ministry of sport and youth by using data envelopment analysis. Research in Sport Management and Motor Behavior, vol. 3(6), 2014, pp. 61–78.
• 8. Zhou Z., Xiao H., Jin Q., Liu W.: DEA frontier improvement and portfolio rebalancing: An application of China mutual funds on considering sustainability information disclosure. European Journal of Operational Research, vol. 269(1), 2018, pp. 111–131. https://doi.org/10.1016/j.ejor.2017.07.010.
• 9. Amiri M., RamezanZadeh S., Khatami FirozAbadi M., Sadaghiani J.: Performance Evaluation of Amin Olum-e-Entezami University Departments by Common Weights Approach in Data Envelopment Analysis and Fuzzy Principal Component Analysi. Resource Management in Police, vol. 1395(14), 2016, pp. 11–36.
• 10. Pourghafar Maghfertay A., Pishgar F., Gharakhani D.: Providing a conceptual model to evaluate the performance of R&D departments of manufacturing companies with the approach of DEA/AHP (case study: Gilan province). Journal of Industrial Management, vol. 9 (special issue on management and accounting), 2014, pp. 25–40.
• 11. Bagheri F.: Evaluation and measurement of energy efficiency in one of the thermal power plants of Iran. Case study (Shahid Rajaei Power Plant). Tehran Science and Research Branch, Islamic Azad University, 2015.
• 12. Manzoor D., Rahimi A.: A Comparative Analysis of the National Iranian Oil Company (NIOC) Articles of Association during 1954–1978: Proposing a Number of Principles of the New Articles of Association. Iranian Energy Economics, vol. 4(14), 2015, pp. 191–215. https://doi.org/10.22054/jiee.2015.1067.
• 13. Wang K., Yu S., Zhang W.: China’s regional energy and environmental efficiency: A DEA window analysis based dynamic evaluation. Mathematical and Computer Modelling, vol. 58(5), 2013, pp. 1117–1127. https://doi.org/10.1016/j.mcm.2011.11.067.
• 14. Cooper W.W., Seiford L.M., Tone K.: Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-Solver Software. Vol. 2. Springer, 2007.
• 15. Asmild M., Paradi J.C., Aggarwall V., Schaffnit C.: Combining DEA Window Analysis with the Malmquist Index Approach in a Study of the Canadian Banking Industry. Journal of Productivity Analysis, vol. 21(1), 2004, pp. 67–89. https://doi.org/10.1023/B:PROD.0000012453.91326.ec.
• 16. Banker R.D., Charnes A., Cooper W.W.: Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis. Management Science, vol. 30(9), 1984, pp. 1078–1092. https://doi.org/10.1287/mnsc.30.9.1078.

Uwagi

PL

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu „Społeczna odpowiedzialność nauki” - moduł: Popularyzacja nauki i promocja sportu (2022-2023)