Real Option Valuation Methodology for Household-Scale Renewable Energy Systems

Abstract

Installing household-scale renewable energy (RE) assets, such as solar home systems, micro-wind turbines, pico-hydro systems, biomass space heaters, and improved cook-stoves, offers a range of benefits to householders. These include the possibility of working longer hours, enhancing the efficiency of production processes, improving the quality of life, and gaining greater control over their immediate environment. In several settings, artisans pursuing the same vocation are known to work from homes located in clusters. Consequent to procuring and deploying the RE asset, the community of individual investors bestows upon itself the option to derive incremental money incomes. This is subject to each member’s access to working capital credit and raw material, skill levels and levels of effort, productivity, and more. This paper argues that householders assess the option to derive incremental incomes and go on to make the investment decision in RE micro-infrastructure based on the estimated value of such options. The model so developed is applied to a community of silk weavers in southern India to estimate the premiums that investors pay to opt into deriving incremental incomes. This study could estimate that by installing a solar home system, a weaver could derive an economic benefit of 17.36% and an intangible benefit of 82.64% of the amount invested into the asset.

Received: 15 June 2023 | Revised: 1 September 2023 | Accepted: 10 November 2023 

Conflicts of Interest

The authors declare that they have no conflicts of interest to this work.

Data Availability Statement

Data available on request from the corresponding author upon reasonable request.

Author Statement Contribution

Sunderasan Srinivasan: Conceptualization, Methodology, Validation, Writing - review & editing, Visualization, Supervision, Project administration, Funding acquisition. Vamshi Krishna Reddy Kottam: Software, Formal analysis, Investigation, Resources, Data curation, Writing - original draft.