# Making Optimal Location-Sizing Decisions for Deploying Hybrid Renewable Energy at B&Bs
## 6 Conclusions  
This study aims to provide a practical approach for all B&B businesses to make optimal location-sizing decisions on deploying hybrid RE technologies. An MIP model is developed and applied in a case study with realistic B&B settings and energy data. The case study contains two scenarios, the base case and the unconventional technology case. The MIP model successfully solves both scenarios to optimality, identifying an optimal RE system that can generate an annual 116,942 kWh of RE for the base case (at the cost of USD 21,499) and an annual 114,474 kWh of RE for the unconventional technology case (at the cost of USD 24,670), respectively. This would result in an emissions saving of 26,715 kgCO\({}_{2}\)e/year (compared to purchasing the required electricity from the power grid). Although the annual cost of hybrid RE is 14.6% less than solar-only, it is still significantly higher than the annual cost of the power grid. In addition to the cost difference between RE technologies and the power grid, overproduction due to time differences in energy generation and energy consumption also contributes to the high cost of hybrid RE. Therefore, simulating the energy transition by sharing the energy demand between RE and the power grid (based on a specific share) would allow B&Bs to initiate the energy transition with affordable costs and acceptable emissions. With 50% self-sufficiency as the baseline, annual costs would increase from 11.8% to 94.0% if self-sufficiency is increased from 60% to 100%. The annual costs in the unconventional technology case are 14.7% higher than in the base case. However, the area needed to install REGDs in the unconventional technology case is 14.2% less than the base case. As B&Bs can make smart decisions in the RE mix, the performance reliability of REGDs becomes critical as they are exposed to outdoor conditions. Therefore, considering age-related performance degradation on RE technologies would enhance the value of future research. Future studies may also investigate emission reduction targets as, in reality, the maximum emissions allowed by policymakers become a critical challenge in energy planning. Conceptualization, C.-T.W. and Y.-J.H. ; methodology, C.-T.W. and Y.-J.H. ; software, L.T. ; validation, C.-T.W. and L.T. ; formal analysis, C.-T.W. and L.T. ; investigation, L.T. ; resources, C.-T.W. ; data curation, C.-T.W. ; writing--original draft preparation, C.-T.W. and L.T. ; writing--review and editing, C.-T.W. and L.T. ; visualization, L.T. ; supervision, C.-T.W. ; project administration, C.-T.W. ; funding acquisition, C.-T.W. All authors have read and agreed to the published version of the manuscript. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Comparison** & **Base Case** & **Unconventional Technology Case** \\ \hline Energy generation (kWh/year) & 116,942 & 114,474 \\ Unused energy (kWh/year) & 66,725 & 64,257 \\ Annual costs (USD/year) & 21,499 & 24,670 \\ Area required (m\({}^{2}\)) & 1017 & 873 \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Comparison between the base case and unconventional technology case. **Funding:** This research received financial support from two organizations at National Central University: The Office of International Affairs and the Graduate Institute of Industrial Management. **Institutional Review Board Statement:** Not applicable. **Informed Consent Statement:** Not applicable. **Data Availability Statement:** This study only uses publicly available data, with sources all clearly indicated in the paper. **Acknowledgments:** The authors wish to express a special thanks to Aiyuan Homestay, a family-run B&B situated in Fangyuan Township, Changhua County, Taiwan, for their generous sharing of practical experience in onsite renewable energy generation. **Conflicts of Interest:** The authors declare no conflict of interest.