# Making Optimal Location-Sizing Decisions for Deploying Hybrid Renewable Energy at B&Bs
## 2 Literature Review
This study proves the importance of oil tanks used as energy storage to regulate the fluctuating solar energy supply. [PERSON] et al. [59] confirmed the critical role of a battery in balancing the intermittency of renewables. Using TRNSYS, their results highlight that the battery can reduce the purchased electricity from the power grid by up to 61%. In addition to simulation, heuristic algorithms are also a popular tool for solving RE problems in accommodation facilities. [PERSON] et al. [60] developed a multi-objective particle swarm optimization (PSO) algorithm to minimize costs, land requirements, and CO\({}_{2}\) emissions for an Iranian hotel. According to their results, an integrated RE system for cooling, heating, and power generation is less costly than a separate system. [PERSON] et al. [61] showed that occupancy fluctuations between weekends and weekdays can significantly affect energy demand. Therefore, generating synthetic time series data of energy demand based on simulated occupancy and weather data would be useful in providing a realistic setting. The levelized cost of electricity (LCOE) is also used to evaluate RE configurations from a financial perspective as it is able to capture long-term economic sustainability. Table 1 presents the key features of tourism accommodation papers on the system optimization of RE systems. It also includes the cost of energy for comparing the average cost per kWh for energy generation. From this table, findings and proposed contributions can be summarized as follows. * Most prior studies do not determine the optimal location for deploying REGDs. Although [PERSON] et al. [60] investigate the total area required, they do not investigate which locations are suitable for each RE technology. This study proposes the optimal location-sizing decisions on deploying a hybrid RE system at the B&B location to fill this gap. To the author's knowledge, this is the first study in tourism accommodations that determines the optimal size of the RE system for each suitable location. * While simulation often provides suboptimal solutions, all of the prior studies use simulation-based optimization using software [47; 48; 49; 50; 53; 58] and heuristic algorithms (PSO) [60; 61]. Therefore, the MIP model is developed in this study as a proposed method to solve the problem. * Since the cost of implementing 100% RE is relatively high for some B&Bs, integrating the RE system with the power grid would be an attempt to bridge the high costs of RE and the affordability for B&Bs. Based on the literature, only the research of [49; 61] include the power grid in the RE system. This integration also offers more flexibility in evaluating the conflicting objectives of energy planning (costs vs. emissions). Interestingly, almost half of the prior studies do not consider the volume of emissions that can be reduced in the RE system [48; 49; 58; 59; 61]. This study attempts to fill this gap by integrating the power grid into the RE system to eventually reach 100% RE. Therefore, the model would allocate a specific portion of energy demands that RE must meet and the power grid supplies the rest (e.g., 50% RE, 60% RE,..., 100% RE). * All prior studies use a specific type of solar panel and/or wind turbine for the RE system. They neglect the existence of various REGDs on the market, especially new-generation RE technologies, which may provide higher energy generation at higher costs. This study evaluates various types of solar and wind REGDs, both conventional and unconventional, to assist B&Bs in investing in RE technologies. * With regards to energy demand, only [PERSON] et al. [61] consider that higher occupancy on weekends creates a higher energy demand than on weekdays. This study uses this finding when establishing energy demand data for the B&B. In summary, various energy components are integrated into a model to ensure smooth energy transition, including hybrid RE, batteries, the power grid, different self-sufficiency targets, and different RE technologies.