Framework to Develop Electric School Bus Vehicle-to-Grid (ESB V2G) Systems Supplied with Solar Energy in the United States

Abstract

Federal and state governments in the United States (US) are promoting the transition from traditional Diesel School Buses to Electric School Buses (ESBs). This would prevent the emission of deleterious air pollutants that affect students and communities while simultaneously contributing to a reduction in greenhouse gases, aiding in the fight against climate change. However, due to their significant size and long routes, ESBs require large batteries with significant electricity demand. If this additional electricity demand is supplied to hundreds of thousands of EBSs at peak consumption times, the strain on the grid may be detrimental, while transportation costs for schools could dramatically increase. Furthermore, if EBSs are charged using traditional hydrocarbon generation, the environmental benefits of these projects may be significantly reduced. Therefore, applying renewable energy presents a host of synergistic opportunities to reduce emissions while providing inexpensive electricity to schools. Solar energy is abundant in large portions of the US, potentially providing many schools with ample inexpensive and sustainable electricity to power their transportation equipment and meet other requirements at their facilities. This research developed a novel framework to integrate publicly available big data provided by federal and state agencies in the US, as well as National Laboratories, to provide stakeholders with actionable information to develop EBS grid-to-vehicle (V2G) systems across the US. Geographic Information Systems, data analytics and Business Intelligence were applied to assess and characterize solar energy generation and consumption patterns. The novel integration of the systems in the proposed framework provided encouraging results that have practical implications for stakeholders to develop successful and sustainable ESB V2G facilities. These results identified many schools across the US that would significantly benefit from the use of solar energy and be able to supply their local communities during idle times with renewable energy through V2G. The renewable energy resource would be capable of charging ESBs at a low cost for operational availability as required. The results indicate that the proposed ESB V2G system will provide significant benefits to both schools and their local communities. The feasibility of the proposed endeavor was validated by the results of the study, providing both school and solar energy stakeholders with insights into how to better manage such a complex system.

1. Introduction

Almost twenty-five million students use school buses every day in the United States (US) [1,2]. Most of the almost half a million buses used in this endeavor are diesel-based, emitting air pollutants that affect the health of students and their communities while simultaneously contributing to greenhouse gas emissions, which exacerbate climate change [3,4]. Air pollution from school buses is considered to be worse than emissions from other vehicles for several reasons. School buses are older than other road vehicles, on average 9 years, increasing the emission of air pollutants per mile by nearly double when compared with other trucks [5]. The five to six billion miles of school bus routes takes them primarily through residential areas, creating a more serious community impact than other transport vehicles that mainly use highways [6,7]. Additionally, it has been shown that air pollutants penetrate the passenger cabin of the school bus, with much higher concentrations than for other locations, impacting the health of students, considering that, on average, a student rides the bus for forty-five minutes per day [1,6]. Many schools’ locations have shown higher concentrations of air pollutants due to school buses idling while loading or unloading, impacting students and even parents, faculty and staff who do not use them [8,9].

To help ameliorate these health and environmental challenges while simultaneously providing significant financial benefits, governments in the United States are promoting the transition from traditional Diesel School Buses to Electric School Buses (ESBs) [2,10,11]. Although ESBs have a higher purchasing price, manufacturers have indicated that the lower fuel and maintenance costs would help offset the initial investment [12,13]. Furthermore, the federal government, through the Clean School Bus Program, funded through the Bipartisan Infrastructure Law, is providing USD 5 billion through 2026 to replace current school buses with low-emission or zero-emission equipment [11,14]. States also offer financial incentives to achieve this goal. The Texas Clean School Bus (TCSB), for instance, provides grants from the Texas Commission on Environmental Quality (TCEQ) to replace or retrofit school buses to reduce air pollution exposure to students [10,15].

Due to ESBs’ significant size and long routes, the required batteries are much larger than those for smaller vehicles, with significant electricity demand [16]. If this additional electricity demand is supplied to thousands of EBSs with existing electricity generation, the strain on the grid may be detrimental, while transportation costs for schools could dramatically increase [17,18]. Furthermore, if EBSs are charged using hydrocarbon-generated electricity, the environmental benefits of these projects would be significantly reduced. Therefore, applying renewable energy presents a host of synergistic opportunities to reduce emissions while providing inexpensive electricity to schools [19,20]. Significant portions of the United States have high solar energy availability, creating opportunities for schools to install solar panels to locally power their transportation and operational needs. Additionally, considering the significant number of wind farms in many rural locations across the US, this resource may be additionally incorporated to provide energy to this novel transportation system [21,22,23]. This will generate considerable benefits for educational institutions as well as grid managers, which will not need to build additional expensive transmission capabilities [24,25]. Furthermore, considering that schools have their vacation during summer, which is the period of the year with the highest solar production, schools may sell surplus energy to the grid in a vehicle-to-grid (V2G) scheme. Solar harvesters and EBS batteries that are idle during the summer months can generate significant income for school districts across the US [16,26].

This research evaluates big data provided by federal and state agencies in the US to assess the feasibility of developing ESB V2G projects for diverse school locations across the United States. Previous research has not provided stakeholders with a holistic framework to evaluate the feasibility of solar-powered ESB V2G. Currently, school districts lack comprehensive decision parameters to maximize the success of these projects, which has hindered the deployment of this new technology. The proposed framework addresses challenging factors for ESB V2G systems, such as the large territorial extension of the US, the dispersed distribution of schools and the high variability of solar energy in both the geographical and temporal dimensions. To achieve these objectives, the novel framework integrates data for solar potential and utility-scale solar projects to better understand the potential growth of this synergetic partnership between schools and the renewable industry. The integrated data are all publicly available, allowing for the development of a low-cost and flexible framework to assess and optimize the placement and operational parameters of ESB V2G systems across large territories. Advances provided by this holistic framework include the assessment of the required electricity for diverse geographical areas in the US and for diverse seasons, evaluating the sufficiency of the solar power generated to determine the required equipment capacity. The proposed novel framework will allow stakeholders to evaluate the whole array of synergistic benefits for both schools and their local communities while simultaneously reducing the carbon footprint from electricity generation all across the US. The novel framework will supply stakeholders with critical information on the most advantageous strategies to develop the ESB V2G systems in optimal locations at a national level.

2. Materials and Methods

The aim of the proposed framework is to provide stakeholders with the relevant information to optimize the development of solar-powered ESB V2G systems. The project has the potential to furnish significant benefits to both local communities and school districts. The framework integrates a wide array of publicly available big data sources provided by US federal, state and local agencies, National Laboratories and private industries. The data were managed and incorporated into the system by applying algorithms from data analytics, Business Intelligence (BI) and GIS. The data were uniformized into schemes capable of being incorporated into and operating in the systems and algorithms used in the proposed framework. These systems provide outputs consistent with BI, capable of generating actionable knowledge for stakeholders to develop successful ESB V2G systems. Figure 1 presents the diverse tasks required for the implementation of the proposed framework, supplying stakeholders with a reference system to identify the optimal locations to maximize the success potential for the proposed scheme. The first two major initial tasks involve the assessment of the ESB inventory and the solar energy potential across the nation. The last two major activities comprise the comparison of actual solar energy assessments across all schools in the continental US and the potential use of this energy to supply local communities after assessing individual demand patterns.

In the first major activity, ESB Assessment, databases from the National Center for Education Statistics (NCES), Institute of Education Sciences (IES) and U.S. Department of Education [27] were incorporated with data on diverse geographical features from the US Census Bureau [28]. Data on school bus usage and characteristics per state were integrated into the system from school bus industry publications [29,30]. A geospatial analysis was performed by applying the integrated databases to characterize both schools and their transportation inventories across the continental US. The second major activity in the framework, Solar Energy Assessment, involves the integration of solar energy data across the continental US into the geospatial database for the system. Data from the National Solar Radiation Data Base (NSRDB) provided by the National Renewable Energy Laboratory (NREL) considering yearly and monthly averages were integrated [31]. Geospatial transformations were applied to these data to be overlaid in the framework, developing diverse assessments and characterizations to evaluate solar energy harvesting per location and season. An assessment of the US continental average Direct Normal Irradiation (DNI) availability per month and per three-consecutive-month period was performed, as shown in the box plot chart presented in Figure 2. This allows for an initial evaluation of the feasibility of developing the proposed framework and highlights the significantly higher potential during the summer months (June to August).

For the framework’s third major activity, School Energy Harvesting, determining the available solar energy radiation and equipment sizing for each monthly period is required. As shown in Figure 3, solar radiation has a high variability all across the US, and this will determine the area for the required solar panels to supply the yearly minimum electric charge for the ESB. The high-producing areas, located in the southwest of the nation, will require smaller PV equipment, while the northern regions will incorporate larger panels to supply their transportation energy demand. The minimum required power for the transportation demand will depend on how many ESBs each school has and the size of their batteries. For instance, a school with two ESBs with 220 kWh batteries will require a daily minimum charge of 440 kWh from their solar panels. If the location has low winter solar radiation, it would require a larger PV than a location or time period with higher solar radiation to achieve the required 440 kWh. However, when solar radiation increases during the summer months, these larger solar panels will be able to capture more than the original 440 kWh, potentially more than doubling the power output. This would allow for two or more charge–discharge daily cycles for the ESB V2G system. Furthermore, many ESB V2G systems will incorporate battery modules on school grounds to capture solar radiation during busy days, when ESBs are on the road, to charge them when they finish delivering students. The combination of large solar panels, multiple charging–discharging ESB cycles during the day, battery modules on school grounds and three-month summer vacations (when ESBs are not used) will create great potential for ESB V2G systems. Locations with low-producing months will therefore have larger equipment that will aid them in capturing more energy during the summer months, when their buses are idle. This will generate the potential to have outstanding performing ESB V2G systems in some of these locations.

The required power for ESB batteries was defined during the framework’s third major activity. Battery sizes vary significantly depending on the vehicle model, range and passenger capacity. Type A ESBs have a capacity of 24 to 30 passengers, a range of 100 to 150 miles and a battery size between 89 and 160 kWh. Alternatively, the capacity for Type C ESBs is between 48 and 81 passengers, with ranges from 105 to 115 miles and battery sizes between 127 and 220 kWh. Type C ESBs have a range capability of 170–250 miles with a battery size of up to 321 kWh. Finally, Type D ESBs have a capacity of 83–84 passengers, a range of 120–155 miles and battery sizes from 155 to 220 kWh [32]. Different schools are expected to have a mixture of buses with diverse capacities, ranges and capabilities. For this study, we consider a 220 kWh battery size, as it is the most frequent maximum battery size for large-capacity buses. This allows this study to reflect the maximum potential demand from school districts in the US. Additionally, this framework will evaluate the extent to which school buses will be charged while not on the road, applying both direct solar energy capture and on-site batteries that capture solar energy when ESBs are away, assessing the coverage that this energy provides for its daily required routes [33,34].

Equation (1) was applied to calculate the area required for each PV system in all the schools for the framework. The required power (P) was calculated considering the potential ESB inventory for each school with a 220 kWh battery with one daily charge.

$$A=\frac{P}{DNI\ast S_e\ast \left({1-S}_l\right)}$$

(1)

The proportion of DNI that the PV system can extract (System Efficiency—S_e) was set at 15.36% for this framework, considering the current state of technology equipment [35,36]. Transmission and generation losses for the equipment are identified as S_l and set at 14.08% as a recommended value for commercial equipment [35,36,37].

During the fourth and last stage of the framework, Community Requirements, the integrated data sources and analysis are integrated with the electricity demand. Electricity consumption data per county were obtained from the 2023 SLOPE: State and Local Planning for Energy system, provided by the National Renewable Energy Laboratory (NREL) [38]. Historical performance per month from January 2001 to January 2024 on the average retail sales and retail price of electricity data was obtained from the Energy Information Administration (EIA) Electricity Data Browser [38]. This integrated geospatial database was applied through geospatial analysis, data analytics and Business Intelligence (BI) to develop the EBS V2G framework. BI allows the transformation of the data, analysis, assessments and optimization tools into meaningful insights, recommendations and plans that have practical applications for stakeholders to develop a successful EBS V2G system [39,40]. BI has been considered in previous research for renewable energy and V2G applications, but its application to ESB systems integrated with geospatial analysis has been limited [41,42,43]. The incorporation of BI into the novel framework will provide stakeholders with significant insight to make sound business decisions that allow for the development of sustainable ESB V2G systems.

3. Results

The student distribution across public schools in the US is very dispersed, as shown in Figure 4. This is relevant for evaluating the requirements and impact that the proposed framework will have on each individual facility. Locations with a larger number of students will potentially be required to capture higher solar energy values by applying larger areas for solar harvesters or possessing better solar potential. Figure 4a indicates that 17% of US states contain more than half of all students in the US, with California, Texas and Florida occupying the first three spots. These states, which make up almost 30% of all US students, have some of the best solar potential in the nation. Figure 4b showcases the student population per county, indicating an even higher spatial concentration of students. Less than 2% of the counties, accounting for less than 8% of the area of the US, contain more than 30% of all students. Furthermore, 5% of the counties, covering 13% of the area of the nation, contain more than half of all students. On the other hand, 81% of the counties, representing 70% of the US territory, only have 20% of the students. These results showcase the relevance of performing a granular analysis of solar energy availability, resource potential and individual facility requirements.

Figure 5 showcases public schools assessed according to the geographic distribution per state and their segmentation according to enrolled students at each institution. Figure 5a indicates a high geographical divergence in the number of public schools per state. Five states comprise one-third of all institutions, 20% of the states contain half of the public schools, and just one-third have 65% of educational institutions. On the other hand, 30% of the states with the lowest number of schools only account for less than 8% of them. This is relevant, considering that it is important to invest in ESB V2G projects at the locations that will generate the biggest benefit for the schools and the students. Figure 5b provides a more nuanced perspective on the locations better suited for ESB V2G investments. It allows for the identification of schools that have an adequate number of students to create an initial balance investment for these novel projects to have the best opportunity for success. Thirteen percent of schools have fewer than a hundred students and less than one percent of the students in the continental US. Schools in the range of 200–600 students constitute more than half of all institutions, with 40% of all students in the nation. Conversely, institutions in the range 600–1200 make up 20% of the institutions but have more than one-third of all students in the country. A relevant factor is that the schools with the greatest number of students, more than 3000, represent 0.3% of all institutions at the national level but contain almost 3% of students in the country. The analyzed segments indicate that schools in the 600–1200 range would allow a focus on a limited number of institutions while serving the greatest number of students. The largest institutions, with more than 3000 students, would also create a more focused investment while benefiting a significant number of students and their local communities. Serving institutions with a significant number of students will allow stakeholders to transition to ESBs in a deliberate fashion, with prudent investments in this transformation.

Evaluating the number of students that use school buses and the proportion of students out of the total student population that use this service [29,30], as shown in Figure 6, provides stakeholders with additional insight into the development of the ESB V2G project. In this case, the proportion of students using school buses has a critical impact on the school vehicular inventory, power requirements and potential energy storage capability. For instance, California is the state with the highest number of enrolled students but is ranked eleven for students transported by bus, considering that only 11% of its students use this service, potentially reducing solar energy storage capabilities. On the other hand, the state of New York jumps from the fourth position when considering the number of students to the first spot when ranked for students using this service, with a utilization rate of 71%. Some states have utilization rates higher than 90%, while fifteen states have usage by more than 60% of the students, and two of these states (New York and Pennsylvania) transport more than one million students. This analysis will aid stakeholders in the identification of the most promising locations to initiate ESB V2G projects according to each region’s requirements.

Assessing the number of school buses per state and per school size category, it is possible to provide stakeholders with additional insight into the viability of ESB V2G investment projects, as shown in Figure 7. Data from available public sources were integrated, considering the proportionality of the school bus distribution in terms of the percentage of students using it, school enrollment and vehicular inventory per state [27,29,30]. The results in Figure 7a indicate that the five states with the highest number of school buses (New York, Texas, Illinois, California and Pennsylvania) comprise 34% of the national inventory. Furthermore, ten states hold 51% of all of the nation’s school buses, making them good locations to evaluate potential ESB V2G projects, pending solar energy optimality assessments. On the other hand, half of the states in the lower-ranking section comprise less than 20% of this vehicular inventory, and one-quarter of the states have just 5% of the nation’s school buses. It will be important to evaluate the locations with the highest number of vehicles to improve success opportunities for investment projects. However, the size of the school in regard to its enrollment is also important, as the results in Figure 7b show. The enrollment range with the highest number of school buses is in the 400–500 segment, with 13% of the national inventory, 67% of which is in states where the proportion of students transported per school is in the 41–80% range. In fact, almost all schools with sizes from 100 to 2100 enrolled students are in states where 41–80% of students use school buses, which provides a very good insight to stakeholders on the institutions where the development of this project should be focused. It is relevant to indicate that 70% of current vehicular parking is concentrated in schools with enrollment between 200 and 1000 students. Institutions with fewer than 200 students or more than 3000 have a higher presence in locations with lower utilization rates and account for less than 6% of all national school buses.

Assessing the monthly and seasonal availability of solar energy over the US to better understand the ESB V2G renewable energy potential is a critical component of this study. Figure 8 shows the solar energy potential, indicating the average DNI in watts/m² for each trimester. This analysis provides relevant insight into the resource availability over time and criteria to determine equipment size. The analysis was performed by applying Natural Breaks (Jenks) segmentation, with variable color bar criteria, to provide a better contrast for the continental US. These results indicate great similitude between the first and fourth quarters, with half of the area (54% and 48%) of the continental US having an average DNI potential of less than 200 watts/m², while 42% and 49%, respectively, of the nation’s area corresponds to the range between 200 and 300 watts/m². For the second quarter, the DNI availability increases for most locations, with almost 70% in the range between 200 and 300 watts/m² and 27% of the area in the 300 and 400 watts/m² segment. The third trimester is the one with the highest availability of solar energy, with 55% in the 200–300 watts/m² domain and 42% of the continental US in the 300–400 watts/m² range. For both the second and third quarters, 3% of the nation is in the higher range between 400 and 440 watts/m². Since, during the school period, the power required to fuel the EBS remains constant, the equipment sizing will be based on the period in which energy harvesting is lowest. Identifying locations and periods in which their energy generation is lowest will be relevant to determining the required solar energy collection infrastructure.

Figure 9 assesses the DNI that each school in the US receives both per month and per trimester. This provides a general outlook on the feasibility of developing the proposed system to power EBSs through solar energy. There is significant seasonal variability both per month and per trimester. These results showcase the highest solar potential for most of the schools from April to September, with the lowest availability from October through March. For the period from October to March, all of the minimum values are below 100 watts/m², and those in the first quartile are between 100 and 200 watts/m². The median for this lower-availability period is in the 140–210 watts/m² segment, while the third quartile only exceeds 200 watts/m² during March, October and November. The maximum level for the first and fourth quarters is lower, with a 25–40% proportion, when compared with the highest value from all the months in the year. On the other hand, in the period in which energy availability is highest, from April to September, the values are all higher than 130 watts/m², the first quartiles are all higher than 200 watts/m², and the median is in the range of 215–255 watts/m². For the third quartile, the solar average potential is in the 240–290 watts/m² tranche, with four of these highest months having values above 400 watts/m². Furthermore, there is a significant number of schools that are located in the upper-limit outlier sections for the months with the best solar generation, indicating the high energy-harvesting potential for these institutions. This analysis provides powerful insight into the solar equipment sizing required for each facility to generate sufficient energy during the whole year to supply each individual school’s EBS fleet.

Considering that each of the ESBs in this study has a 220-kWh battery and that one daily charge is required per vehicle harvesting solar energy, it is possible to calculate the required area for the panels in the equipment. The economic analysis for the implementation of the proposed system is complex and depends on the characteristics and location of each school. Future research in this project will undertake an in-depth financial analysis of the proposed ESB V2G system, expanding the framework described in this paper. However, a brief economic analysis is able to furnish important insights into the benefits that the proposed system can provide. The Total Cost of Ownership (TCO) of school buses includes capital investment, fuel, insurance and maintenance. When comparing the TCO of ESBs with that of diesel vehicles, the former is 28% higher, considering that ESBs’ capital investment is significantly higher, while long-term costs, including fuel and maintenance, are much lower. However, when federal, state and private financial incentives are incorporated into the economic analysis, the TCO of ESBs becomes significantly lower than that of traditional diesel equipment: 50% lower over the lifetime of the equipment. Furthermore, forecasts indicate that as ESB technology improves and costs decrease, there will be a significant reduction in the ESB TCO over the next decade, even without financial assistance. These economic benefits do not consider the revenue that the ESB V2G systems can provide for each school, which will create much larger incentives to implement these projects [44,45,46,47,48].

Figure 10 presents results on the required area of PV, considering the lowest DNI month for each individual school. This will satisfy the minimum energy requirement for that particular month and will allow for an energy surplus in the remaining months, creating the potential to charge ESBs several times per year. This will have significant implications for the ESB V2G projects, particularly during the summer months. Figure 10a shows that for most schools, the month that would require the largest PV panels would be December, with only 10% requiring 500 m² or smaller panels, 52% of schools requiring less than 2000 m² in area and 90% requiring panels smaller than 5000 m². In contrast, for June and July, PV panels smaller than 500 m² would be required for 24% of schools, and 2000 m² area or smaller will be adequate for 81% of schools, while 5000 m² would supply 98% of the schools. This is supplemented by Figure 10b, confirming that December is the month with the highest area requirement for most schools to be able to fully supply ESBs, with a first quartile of 779 m², a median of 1627 m² and a third quartile of 2692 m². On the other hand, June and July are confirmed as the months with the lowest area requirement, with a median of 999 m², a first quartile of 458 m² and a third quartile of 1640 m². This clearly indicates that as school PV systems are sized for the months with the least harvesting, the summer months with higher production will generate a significant energy surplus that schools can provide to their local communities through the ESB V2G systems.

4. Discussion

Figure 11 presents results for the potential daily power output (kWh) that each school ESB V2G system could generate, classified per month, considering that its solar harvesting system was sized to correspond to each school’s lowest-solar-production month. This figure highlights the potential for the summer months to generate much higher power output than the winter months. For instance, half of the schools are able to generate 1000 kWh or less for December and January, while 72% of schools have the potential to generate more than 1000 kWh for June and July. Furthermore, less than 11% of schools can generate more than 2000 kWh during December, while 35% of schools can exceed this value during June and July. For power output higher than 3000 kWh per day, the results indicate that 10–13% of the schools in the continental US generate this output in the period from April to September. This is a good indicator for the development of the ESB V2G systems.

Figure 12a supplements the results of the previous analysis, highlighting the adequacy of high-power output in the summer months from schools to be applied in ESB V2G systems. The three highest median values over the year take place during the summer, from June to August, ranging from 1690 to 1800 kWh. Furthermore, the third quartile’s maximum monthly values also exist between June and August, in the range of 2925–3115 kWh. Figure 12b provides results from the monthly average retail sales and retail prices of electricity from January 2001 to January 2024, as provided by the Energy Information Administration [49]. These results highlight the higher demand for electricity during the summer months, as well as the higher average price of this resource throughout this period. The potential for schools to supply their local communities from their ESB V2G systems is reinforced, coupled with the potential to obtain significant financial benefits from the sale of electricity in higher-price periods.

Figure 13 shows the potential average daily power generation and storage that could be provided from V2G by applying the cumulative inventory of ESBs per county and the solar energy generation for each location. The results indicate that the counties with the highest potential for this system align well with the largest urban areas. This is coherent with the proportional sizes of schools depending on the location’s population. However, some locations that have a lower number of students using this service or have lower solar potential present lower energy availability. Figure 13a aids stakeholders in identifying locations that may provide the best potential outlook for the successful development of the proposed V2G system. For instance, one of the counties with high potential for the project is Cook County, Illinois, which is ranked fourth nationally in terms of the number of students, behind Los Angeles, California; Maricopa (Phoenix), Arizona; and Harris (Houston), Texas. These three locations have higher solar potential than Cook County, as shown in Figure 13a. The deciding factor in ranking Cook County in a higher position corresponds to the proportion of students using school buses, which, for Illinois, is more than 50%, which significantly surpasses the less than 20% for California and Texas and the less than 30% for Arizona. The summer months, as shown in Figure 13b, are of critical importance for this project, providing higher solar energy generation potential and full availability for ESB storage, considering their idle schedule during summer school vacations. The increase from the yearly average to the summer (June–August) average is significant for many counties. For instance, 46% of all counties in the continental US could experience an increase between 20% and 30% in energy availability from their ESB V2G systems when comparing the yearly average with the summer average. Furthermore, 21% of the counties could experience an increase in their systems of 30–50% between the yearly and summer averages. The analysis should be performed at a granular level in a case-by-case scenario, considering the significant variability generated by the factors relevant to this system. For instance, when the summer months are considered, Cook and Harris Counties continue to be among those generating higher energy in the nation, with the first one experiencing a summer variability of 33% and Harris just 13%. However, due to summer variability, King County (Seattle, WA, USA) climbs from the number 9 ranking based on yearly averages to the number 3 ranking based on summer averages, surpassing Los Angeles (California) and Maricopa (Arizona) due to its 62% variability during the summer months. This is an example of the benefits that the proposed framework can provide to stakeholders. It can effectively aid them in the selection of the best locations for the development of the proposed ESB V2G systems, considering diverse periods and locations, maximizing benefits for local communities and schools.

Figure 14 presents county-level daily average electricity consumption obtained for 2023 from the National Renewable Energy Laboratory SLOPE: State and Local Planning for Energy [38]. The daily averages shown in Figure 14a are calculated for 2023, indicating that there is a very strong connection between the highest-electricity-consuming counties and the top ESB V2G counties for the project. Out of the top ten electricity-consuming counties, five (representing 7% of national electric consumption) coincide with the first, second, fourth, fifth and eighth highest ESB V2G output in yearly averages. A correlation analysis including all the counties with potential ESB V2G systems results in a 0.84 value, indicating a strong positive correlation, highlighting the potential to develop the proposed system across the US. The summer monthly averages per county shown in Figure 14b were calculated by applying the monthly average retail sales of electricity from January 2001 to January 2024 [49], which indicates that during this timespan, June to August account for, on average, 28% of the yearly electricity consumption. A stronger connection is observed in this figure, considering that most electricity consumption and ESB V2G power output increase during the summer months. Furthermore, during this period, the ESB availability is very high, creating the potential for a second or a third charge for the buses, increasing the potential supply of the stored energy to local communities. This provides the opportunity to develop an energy hub, incorporating the storage capabilities from the ESBs and the battery modules on school grounds, as described in the Materials and Methods Section, to maximize the local solar energy potential. The developed system will allow for the maximization of renewable energy integration into the grid and optimize the management of the local energy hubs that will develop as a result of the proposed ESB V2G systems [50,51].

The solar energy harvested and stored by the ESBs, as proposed in this framework, could be applied in a V2G system to supply the electricity requirements of the counties where each school is located. Figure 15 indicates the proportion of each county’s daily electricity consumption that the ESB V2G scheme could provide. The results indicate a median of 1.71%, a third quartile of 2.6% and a maximum of 4.83%, excluding outliers, for the yearly daily average electricity consumption per county. For the summer months (June to August), the contribution is even larger, with a median of 1.85%, third quartile of 3.01% and maximum, excluding outliers, of 5.78%. Electricity demand is highly variable during the day, requiring supplemental generation for the highest-consumption hours, which is generally provided by fuels that have a larger carbon footprint, such as coal. These are the time periods where the ESB V2G system would provide the most benefit by supplying this additional required electricity and replacing more deleterious fuels. Furthermore, there are a significant number of schools that are able to provide a much higher proportion of electricity consumption for each county, reaching almost 15% for the yearly average analysis and more than 21% during the summer months. The highest proportional results during the summer months are very significant, considering that, across the nation, summer is the period with the highest electricity demand and hourly variability.

Performing a geospatial analysis of the distribution per county of the ESB V2G contribution to electricity consumption is very important for stakeholders, allowing them to make decisions on the optimal locations to implement the proposed system. Figure 16 shows the electricity contribution per county for both (a) the yearly daily average and (b) the summer-month average for 2023. These results are relevant because they highlight the locations where benefits to local communities would be optimized by supplying the required electricity at peak times. As previously indicated, factors impacting solar energy availability from the system relate to the local solar radiation availability and the number of ESBs. Some rural locations with excellent solar potential, a high percentage of students using school buses and medium to low energy consumption have some of the highest proportional coverage. However, some large urban areas with significant solar potential and large school systems provide good proportional coverage for the system. For instance, in the state of New York, several counties with high electricity consumption would be able to provide a proportion ranging from 4 to 6% based on both yearly and summer month averages. This analysis confirms the potential to provide local communities with sustainable electricity while generating significant financial benefits for their local school districts.

5. Conclusions

The results of this study indicate that there are significant benefits for both schools and local communities across the US using the framework to develop ESB V2G systems supplied with solar energy. Local communities can have access to sustainable energy in close proximity to satisfy their energy demand at peak times. Schools, in addition to providing their students with healthier transportation options at lower operational costs, can receive significant financial benefits from selling excess energy stored in their ESBs at high-demand/price times.

Schools are proportionally distributed all across the US according to local populations, which correspond very well with the local electricity demand. Larger schools, which have a higher inventory of ESBs, will be located in communities with higher electricity demand. The framework, therefore, helps stakeholders identify schools that may benefit a larger number of students and local populations from the sustainable energy generated by ESB V2G systems. On the other hand, the results also indicate that some smaller communities, with smaller schools and outstanding summer solar energy potential, may provide a higher proportion of the electricity consumed by this community, opening them to good investment opportunities for the proposed system.

These results allow stakeholders to identify the main factors that maximize the benefits of this framework. As indicated, larger student populations and significant electricity demand are relevant parameters. However, divergence in the proportion of students using school transportation in each location creates a variable inventory of ESBs in each county, impacting the potential storage capacity. Additionally, solar energy availability changes depending on the geographical and seasonal settings, creating diverse opportunities for these systems. It was determined, for instance, that high-variability locations require larger-sized PV harvesting equipment, which leads to greater capture values during the summer months. This provides the opportunity to supply their local communities with higher energy levels at high sales prices, creating a positive synergetic cycle between educational institutions and local communities.

This framework can be expanded to other geographical locations with the inclusion of the required databases. Future research will include assessing specific financial benefits that diverse schools may obtain from the proposed system, considering the cost of equipment, historical and forecasted values of variable electricity prices and consumption per location and per sector, and seasonal solar potential per location, and incorporating current and future technologies for solar harvesting.