A Compound Real Option Approach for Determining the Optimal Investment Path for RPV-Storage Systems

Abstract

The use of residential Photovoltaic-Storage systems may produce large benefits to owners and has expanded rapidly in recent years. Nonetheless, large uncertainties regarding the profitability of these systems make it necessary to incorporate flexibilities in their economic evaluations. This paper offers a new method to evaluate the compound flexibility of both the option of delaying investments and the option of further expanding the capacity of solar photovoltaic modules and batteries during the investment horizon. Flexibility is modeled as a compound real option, whose value is computed using a novel method that we call Compound Least Squares Monte Carlo (CLSM). The model is applied to the investment decisions associated to a residential Photovoltaic-Storage system. Results suggest that investors should use the proposed CLSM method in the economic valuation of multi-stage projects, since considering only a single flexibility could promote sub-optimal decisions. Moreover, in our case study, we show that it is optimal to break the investment down into two steps or more in 36% of future scenarios, on average.

Keywords

Batteries Least Squares Monte Carlo Optimal Investment Path Real Options;RPV-Storage Systems Solar Power

Get full access to this article

View all access options for this article.

References

Barbour

Edward

Gonzalez

Marta C.

(2018). “Projecting Battery Adoption in the Prosumer Era.” Applied Energy 215 (August 2017): 356-70. https://doi.org/10.1016/j.apenergy.2018.01.056.

Black

Fischer

Scholes

Myron

(1973). “The Pricing of Options and Corporate Liabilities.” Journal of Political Economy 81(3): 637-54. https://doi.org/10.1086/260062.

Bloomberg NEF (2019). “A Behind the Scenes Take on Lithium-ion Battery Prices | Bloomberg NEF”. Retrieved from https://about.bnef.com/blog/behind-scenes-take-lithium-ion-battery-prices/.

Boyle

Phelim P.

(1977). “Options: A Monte Carlo Approach.” Journal of Financial Economics 4(3): 323-38. https://doi.org/10.1016/0304-405X(77)90005-8.

Chilean Government (2019). “Inflacion histórica Chile - IPC.”. Retrieved from https://es.inflation.eu/tasas-de-inflacion/chile/inflacion-historica/ipc-inflacion-chile.aspx.

Cucchiella

D’Adamo

Gastaldi

(2017). “The economic feasibility of residential energy storage combined with PV panels: The role of subsidies in Italy.” Energies 10: 1434. https://doi.org/10.3390/en10091434.

ENEL (2019). “Tarifas Históricas - enel.cl.” Retrieved from https://www.enel.cl/es/clientes/informacion-util/tarifas-y-regla-mentos/tarifas/tarifas-historicas.html.

ENEL X (2019). “Energía solar, paneles solares - Enel X.” Retrieved from https://www.tiendaenel.cl/63-energia-solar.

Fatone

Mariani

Recchioni

M. C.

Zirilli

(2015). “The Barone-Adesi Whaley Formula to Price American Options Revisited.” Applied Mathematics 06(02): 382-402. https://doi.org/10.4236/am.2015.62036.

10.

Flatley

Giulietti

Grossi

Trujillo-Baute

Waterson

(2016). “Analysing the Potential Economic Value of Energy Storage.” The Energy Journal 39: 101-122. https://doi.org/10.2139/ssrn.2744679.

11.

Fuentes

van der Weijde

Sauma

(2020). “The promotion of community energy projects in Chile and Scotland: An economic approach using biform games.” Energy Economics 86: 104677. https://doi.org/10.1016/j.eneco.2020.104677.

12.

Gahrooei

M.R.

Zhang

Ashuri

Augenbroe

(2016). “Timing residential photovoltaic investments in the presence of demand uncertainties.” Sustainable Cities and Society 20: 109-123. https://doi.org/10.1016/j.scs.2015.10.003.

13.

Hesse

H.C.

Martins

Musilek

Naumann

Truong

C.N.

Jossen

(2017). “Economic optimization of component sizing for residential battery storage systems.” Energies 10(7): 835. https://doi.org/10.3390/en10070835.

14.

Hoppmann

Volland

Schmidt

T.S.

Hoffmann

V.H.

(2014). “The economic viability of battery storage for residential solar photovoltaic systems - A review and a simulation model.” Renewable and Sustainable Energy Reviews 39: 1101–1118. https://doi.org/10.1016/j.rser.2014.07.068.

15.

Hull

J.C.

(1946). Options, Futures, and other Derivatives (10th ed.).

16.

Loncar

Milovanovic

Rakic

Radjenovic

(2017). “Compound real options valuation of renewable energy projects: The case of a wind farm in Serbia.” Renewable and Sustainable Energy Reviews 75(November 2016): 354-367. https://doi.org/10.101/j.rser.2016.11.001.

17.

Longstaff

F. A.

Schwartz

E.S.

(2001). “Valuing American options by simulation: A simple least-squares approach.” Review of Financial Studies 14(1): 113-147. https://doi.org/10.1093/rfs/14.L113.

18.

Mamkhezri

Thacher

Chermak

(2020). “Consumer Preferences for Solar Energy: An Experimental Study.” The Energy Journal 41(5): 135-161. https://doi.org/10.5547/01956574.41.5.jmam.

19.

Mariscal

Reyes

Sauma

(2020). “Valuing flexibility in transmission expansion planning from the perspective of a social planner: A methodology and an application to the Chilean power system.” The Engineering Economist 65(4): 1712509. https://doi.org/10.1080/0013791X.2020.1712509.

20.

Martinez-Cesena

E. A.

Azzopardi

Mutale

(2013). “Assessment of domestic photovoltaic systems based on real options theory.” Prog. Photovolt: Res. Appl. 17: 250-262. https://doi.org/10.1002/pip.2208.

21.

Möllendorff

C. von

Welsch

(2017). “Measuring Renewable Energy Externalities: Evidence from Subjective Well-being Data.” Land Economics 93(1): 109-126. https://doi.org/10.3368/le.93.L109.

22.

Moon

Baran

(2018). “Economic analysis of a residential PV system from the timing perspective: A real option model.” Renewable Energy 125: 783-795. https://doi.org/10.1016/j.renene.2018.02.138.

23.

Pindyck

R.S.

(1999). “Long-Run_Evolution.” The Energy Journal 1-27. Retrieved from papers2://publication/uuid/B420CAEC-D4F6-47DE-9D10-DBBD68C55887.

24.

Sioshansi

Ramteen

(2010). “Welfare Impacts of Electricity Storage and the Implications of Ownership Structure.” The Energy Journal 31(2): 173-198. https://doi.org/10.5547/ISSN0195-6574-EJ-Vol31-No2-7.

25.

Rios

Blanco

Olsina

(2019). “Integrating Real Options Analysis with long-term electricity market models.” Energy Economics 80: 188-205. https://doi.org/10.1016/j.eneco.2018.12.023.Servicio

26.

Nacional de Aduanas (2019). “Ser-vicio Nacional de Aduanas - Viajeros Internacionales.” Retrieved from https://www.aduana.cl/viajeros-internacionales/aduana/2007-02-28/143620.html.

27.

Shaw-Williams

Susilawati

Walker

(2018). “Value of residential investment in photovoltaics and batteries in networks: A techno-economic analysis.” Energies 11(4). https://doi.org/10.3390/en11041022.

28.

Sunrun . (2019). “Repowering Clean Gigawatt-Scale Potential for Residential Solar & Battery Storage in Los Angeles.” Retrieved from https://www.sunrun.com/sites/default/files/repowering-clean-sunrun.pdf.

29.

Tang

Wang

Guo

(2014). “Remaining useful life prediction of lithium-ion batteries based on the wiener process with measurement error.” Energies 7(2): 520-547. https://doi.org/10.3390/en7020520.

30.

Tervo

Agbim

DeAngelis

Hernandez

Kim

H.K.

Odukomaiya

(2018). “An economic analysis of residential photovoltaic systems with lithium ion battery storage in the United States.” Renewable and Sustainable Energy Reviews 94(June): 1057-1066. https://doi.org/10.1016/j.rser.2018.06.055.

31.

Tesla (2019). “Powerwall | The Tesla Home Battery. “. Retrieved from https://www.tesla.com/powerwall?redirect=no.

32.

Truong

Naumann

Karl

Muller

Jossen

Hesse

(2016). “Economics of Residential Photovoltaic Battery Systems in Germany: The Case of Tesla’s Powerwall.” Batteries 2(2): 14. https://doi.org/10.3390/batteries2020014.

33.

Uddin

Gough

Radcliffe

Marco

Jennings

(2017). “Techno-economic analysis of the viability of residential photovoltaic systems using lithium-ion batteries for energy storage in the United Kingdom.” Applied Energy 206(June): 12-21. https://doi.org/10.1016/j.apenergy.2017.08.170.

34.

Zhang

M.M.

Zhou

D.Q.

(2016). “A real options model for renewable energy investment with application to solar photovoltaic power generation in China.” Energy Economics 59: 213-226. https://doi.org/10.1016/j.eneco.2016.07.028.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.15 MB