Making Optimal Location-Sizing Decisions for Deploying Hybrid Renewable Energy at B&Bs

The adoption of renewable energy (RE) is a promising business strategy for bed and breakfasts (B&Bs) to mitigate climate change while maintaining a competitive edge. However, there is still a lack of analytical studies to determine an optimal RE mix for tourism accommodations. This study thus proposes a practical approach to enable all B&Bs to make optimal RE decisions for their facility. A mixed-integer programming (MIP) model is developed and tested in a case study. The model successfully identifies an optimal hybrid energy system for two scenarios, the base case that generates 116,942 kWh of electricity annually at the cost of USD 21,499, and the unconventional technology case that generates 114,474 kWh of electricity annually at the cost of USD 24,670. Compared to purchasing all the required electricity from the power grid, both scenarios can save more than 26 tons of CO(2)e/year. The analysis provides valuable information for B&Bs to initiate a smooth energy transition with affordable costs. This study considers various energy components, including hybrid RE, batteries, the power grid, self-sufficiency targets, and various RE technologies. Therefore, B&Bs can choose a preferred self-sufficiency target where RE satisfies a specific portion of the energy demands and the power grid satisfies the rest. The model can also evaluate the tradeoff between investing in RE technologies and purchasing larger batteries. These findings will assist B&Bs in accelerating the adoption of RE globally.

Automated summary

This study proposes a practical approach to enable all B&Bs to make optimal renewable energy decisions for their facility. A mixed-integer programming (MIP) model is developed and tested, successfully identifying an optimal hybrid energy system for two scenarios, both of which can save significant carbon emissions compared to purchasing electricity from the power grid.