journal article·2020-04-08Open access

Development of an ESCO Risk Assessment Model as a Decision-Making Tool for the Energy Savings Certificates Market Regulator: A Case Study

Mohsen Ahmadi, Mohsen Hatami, Peyman Rahgozar, Salar Shirkhanloo, Shahriar Abed, Hossein Kamalzadeh, Ian Flood

Applied Sciences· Volume 10· Issue 7

Abstract

This article is focused on developing an Energy Service Company (ESCO) risk assessment model for use by energy savings certificates (ESC) market regulators. This model enables market regulators to determine the appropriate point in time for ESCOs to sell their certificates with the aim of minimizing risk as well as maximizing economic gain yet remain motivated for reducing the cost of energy efficiency technologies. To this end, the interactions between an ESCO and other parties (such as suppliers) in the market in addition to the principles of the energy efficiency performance contract are taken into consideration. Then, appropriate probability distributions have been fitted to the stochastic variables to be applied in the Net Present Value (NPV) function, based on sampled company data. A case study considers a one MW Organic Rankine Cycle (ORC) implementation in Iran’s petrochemical industry. The finding of this study shows if the ESCO is allowed to sell the certificates during the first seven years as well reduce 30% of the investment cost, the expected Net Present Value over Investment Cost (NPV/I) savings will cover more than one cycle.
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Research context

OpenAlex topics: Energy Efficiency and Management · Capital Investment and Risk Analysis · Global Energy and Sustainability Research

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Energy Engineering, Sharif University of Technology, Tehran, P.O. Box 14565-114, Iran

M. E. Rinker Sr. School of Construction Management, University of Florida, P.O. Box 115703, Gainesville, FL 32611, USA

CUIRE, Department of Civil Engineering, The University of Texas at Arlington, P.O. Box 19308, Arlington, TX 76019, USA

SWIS, Department of Civil Engineering, The University of Texas at Arlington, P.O. Box 19308, Arlington, TX 76019, USA

Lyle School of Engineering, Southern Methodist University, P.O. Box 750339, Dallas, TX 75275, USA

References (43)

Show source-provided references
1. Evaluating project level investment trends for the U.S. ESCO industry: 1990–201710.1016/j.enpol.2019.03.061 ↗
2. Energy efficiency barriers in commercial and industrial firms in Ukraine: An empirical analysis10.1016/j.eneco.2017.01.013 ↗
3. Energy efficiency investments in small and medium sized manufacturing firms: The case of California energy crisis10.1016/j.eneco.2017.12.006 ↗
4. Hansen, S.J., Langlois, P., and Bertoldi, P. (2009). ESCOs Around the World: Lessons Learned in 49 Countries, CRC Press. [1st ed.].
5. Public-private partnerships for energy efficiency projects: A win-win model to choose the energy performance contracting structure10.1016/j.jclepro.2017.09.151 ↗
6. A review of energy performance contracting business models: Status and recommendation10.1016/j.scs.2017.06.018 ↗
7. Risks in Energy Performance Contracting (EPC) projects10.1016/j.enbuild.2015.01.054 ↗
8. Developing an Iranian green building assessment tool using decision making methods and geographical information system: Case study in Mashhad city10.1016/j.rser.2016.09.004 ↗
9. Jozaghi, A., Alizadeh, B., Hatami, M., Flood, I., Khorrami, M., Khodaei, N., and Ghasemi Tousi, E. (2018). A Comparative Study of the AHP and TOPSIS Techniques for Dam Site Selection Using GIS: A Case Study of Sistan and Baluchestan Province, Iran. Geosciences, 8, Available online: https://www.mdpi.com/2076-3263/8/12/494.10.3390/geosciences8120494 ↗
10. Koosha, R., and Shahsavari, F. (2020, March 21). An Uncertainty and Sensitivity Analysis Tool for Building Thermal Energy Consumption: A Performance Comprehension of Static and Dynamic Response Analyses. American Society of Mechanical Engineers Digital Collection. Available online: https://nondestructive.asmedigitalcollection.asme.org/IDETC-CIE/proceedings/IDETC-CIE2019/59179/V001T02A077/1069690.
11. A multi-stakeholder analysis of the economic efficiency of industrial energy efficiency policies: Empirical evidence from ten years of the Italian White Certificate Scheme10.1016/j.apenergy.2019.02.047 ↗
12. Energy savings certificates: A market-based tool for reducing greenhouse gas emissions10.1016/j.enpol.2007.10.001 ↗
13. Turkey’s energy efficiency assessment: White Certificates Systems and their applicability in Turkey10.1016/j.enpol.2013.10.036 ↗
14. White certificate trading: A dying concept or just making its debut? Part I: Market status and trends10.1016/j.tej.2018.03.002 ↗
15. Analysis of barriers and drivers for the development of the ESCO markets in Europe10.1016/j.enpol.2017.04.023 ↗
16. Hatami, M., Flood, I., Franz, B., and Zhang, X. (2019). State-of-the-Art Review on the Applicability of AI Methods to Automated Construction Manufacturing. Computing in Civil Engineering, American Society of Civil Engineers. Available online: http://ascelibrary.org/doi/10.1061/9780784482438.047.10.1061/9780784482438.047 ↗
17. Kamalzadeh, H., and Hahsler, M. (2020, April 07). POMDP: Introduction to Partially Observable Markov Decision Processes. Package ‘pomdp’. Available online: https://rdrr.io/cran/pomdp/f/inst/doc/POMDP.pdf.
18. Kouchesfehani, Z.K., Tehrani, A.D., Najafi, M., Syar, J.E., and Kampbell, E. (2019, January 21–24). Adding Additional Reinforcement to Improve the Structural Performance of Spray Applied Pipe Lining Rehabilitation Technology: A Review. Proceedings of the Pipelines 2019: Multidisciplinary Topics, Utility Engineering, and Surveying, Nashville, TN, USA.10.1061/9780784482506.002 ↗
19. Analysis of regulatory instruments promoting building energy efficiency10.1016/j.egypro.2018.07.090 ↗
20. (2020, March 30). A Guide to Energy Performance Contracting in Public Buildings. Available online: https://www.codema.ie/images/uploads/docs/A_Guide_to_Energy_Performance_Contracting_in_Public_Buildings.pdf.
21. Interactions of a tradable green certificate market with a tradable permits market10.1016/S0301-4215(00)00133-6 ↗
22. “White and Green”: Comparison of market-based instruments to promote energy efficiency10.1016/j.jclepro.2004.12.013 ↗
23. Tradable certificates for renewable electricity and energy savings10.1016/j.enpol.2004.08.026 ↗
24. Market behaviour and the to-trade-or-not-to-trade dilemma in ‘tradable white certificate’ schemes10.1007/s12053-008-9026-6 ↗
25. Transaction costs of Tradable White Certificate schemes: The Energy Efficiency Commitment as case study10.1016/j.enpol.2007.02.029 ↗
26. Multi-item production planning with carbon cap and trade mechanism10.1016/j.ijpe.2013.01.024 ↗
27. Renewable Energy Certificate and Perform, Achieve, Trade mechanisms to enhance the energy security for India10.1016/j.enpol.2012.12.072 ↗
28. The price of energy efficiency in the Spanish housing market10.1016/j.enpol.2016.03.032 ↗
29. Monte Carlo Simulation approach for economic risk analysis of an emergency energy generation system10.1016/j.energy.2019.01.145 ↗
30. Performance risks of lighting retrofit in Energy Performance Contracting projects10.1016/j.esd.2018.07.004 ↗
31. Moud, H.I., Shojaei, A., Flood, I., Zhang, X., Hatami, M., and Rinker, M.E. (2018, January 22–26). Qualitative and Quantitative Risk Analysis of Unmanned Aerial Vehicle Flights over Construction Job Sites. Proceedings of the Eighth International Conference on Advanced Communications and Computation (INFOCOMP 2018), Barcelona, Spain.10.5220/0006868804510458 ↗
32. A shape-based adaptive segmentation of time-series using particle swarm optimization10.1016/j.is.2017.03.004 ↗
33. Engineering Risk Management Planning in Energy Performance Contracting in China10.1016/j.sepro.2011.08.032 ↗
34. A multi-criteria decision-making framework for risk ranking of energy performance contracting project under picture fuzzy environment10.1016/j.jclepro.2018.04.169 ↗
35. Selecting an Appropriate Strategy to Increase Petrochemical Product Sales (Case Study: Iranian Petrochemical Industry)10.11114/bms.v3i1.2247 ↗
36. Kamalzadeh, H., Sobhan, S.N., Boskabadi, A., Hatami, M., and Gharehyakheh, A. (2019). Modeling and Prediction of Iran’s Steel Consumption Based on Economic Activity Using Support Vector Machines. arXiv, Available online: http://arxiv.org/abs/1912.02373.
37. Numerical simulation on flow field in circumferential overlap trisection helical baffle heat exchanger10.1016/j.applthermaleng.2012.07.031 ↗
38. The effects of the energy price reform on households consumption in Iran10.1016/j.enpol.2015.01.012 ↗
39. High Temperature ORC Systems10.1016/j.egypro.2017.09.160 ↗
40. Electricity Generation and Energy Cost Estimation of Large-Scale Wind Turbines in Jarandagh, Iran10.1155/2014/613681 ↗
41. Turnaround maintenance in petrochemical industry: Practices and suggested improvements10.1108/13552510410553235 ↗
42. A Time Preference Measure of the Social Discount Rate for Iran10.1186/s40008-018-0127-x ↗
43. Zhuang, J., Liang, Z., Lin, T., and Guzman, F.D. (2007). Theory and Practice in the Choice of Social Discount Rate for Cost-Benefit Analysis: A Survey, Asian Development Bank (ADB). ADB Economics Working Paper Series, Asian Development Bank (ADB).