© V. Bhuva et al., Published by EDP Sciences, 2026

1 Introduction

In April 2021, the White House announced new decarbonization goals for the United States, which included achieving a 50–52% reduction from 2005 levels in economy-wide net greenhouse gas (GHG) pollution in 2030 and reaching Net Zero emissions economy-wide by no later than 2050 [1]. While decarbonization is not among the priorities of the U.S. Administration elected in November 2024, there is a broader international push to curb emissions under frameworks like the Paris Agreement, with the residential sector emerging as a pivotal arena for action. According to the Energy Information Administration (EIA), the residential sector contributed 953.8 million metric tons of carbon dioxide equivalent-15% of U.S. emissions-and consumed 12.3 quadrillion BTUs, or 7% of total energy usage in 2021 [2,3]. Electricity and natural gas dominate its energy profile, supplying 85% of needs, while renewables account for a mere 7%, exposing significant room for improvement when it comes to emissions reduction [3].

The access to renewable energy is an issue for most residents in LMI communities, where high energy burdens (around 6%, triple that of wealthier counterparts) compound socio-economic challenges [4]. However, there are strategies to deploy solar at the neighborhood level in a way most residents can benefit from it.

The U.S. Department of Energy (DOE) defines community solar as a solar project or buying program for a geographic area where multiple customers (individuals, nonprofits, businesses, or other groups) receive benefits. They either pay a subscription fee or own a portion of the energy generated and receive credit on their electric bills for the energy generated by their share of the plant. This application is a great option for residential end users who cannot install solar on their homes due to factors such as inadequate roof conditions, outdated electrical systems, or rental housing situations. The lack of space onsite is a common factor when it comes to deploying solar in urban areas. Therefore, most of the community solar plants are at a different location than the consumers [5]. The energy generated is supplied directly to the local utility and the utility credits each subscriber with a portion of revenue generated by the community solar [6]. The financial mechanism existing between the utility and the community solar plant is usually a Power Purchase Agreement (PPA) [7].

Community solar can effectively lower the monthly cost of electricity along with reducing the electricity demand from the grid during daylight hours [8], reducing and offsetting the environmental emissions of the users [9–11]. Additionally, community solar offers an option to keep receiving benefits even if the owner moves to a different house or location. Typically, community solar is installed on leased land having the ability to return it back to its original state [12], brownfield, private land [13] or even as part of existing solar farms [14].

With five new community solar projects being deployed in California, community solar is already a viable option for LMIs [15]. The innovation of the approach presented by this paper resides in the location of the photovoltaic plants: none of the existing community solar plants serving LMIs are located inside the detention basins serving the communities. This study investigates the feasibility of deploying community solar photovoltaic (PV) systems in stormwater detention basins owned and maintained by Homeowner Associations of LMI communities across Texas, Oklahoma, New Mexico, and Louisiana, offering a novel pathway for solar to provide environmental, energy, and cost savings in urban areas.

Stormwater detention basins as shown in Figure 1, are engineered infrastructures ubiquitous in the U.S., designed to manage runoff during storm events and safeguard communities from flooding, erosion, and pollutant dispersion [16–20]. Typically situated outside housing developments and maintained by homeowners' associations, these basins capture stormwater from surrounding properties, slowing discharge rates to mitigate downstream impacts [19,20]. Ranging from 10 to 12 feet in depth, they serve as stormwater control measures, yet their extensive area present a unique opportunity for renewable energy development [21,22]. Two main configurations that adjust to water fluctuations are viable: ground-based solar elevated above the flood level or floating PV systems. This dual-purpose potential reimagines detention basins as assets able to provide different sources of revenue, particularly for LMIs where traditional solar options like rooftop installations are hindered by structural deficiencies, renting status, or financial constraints, necessitating innovative site alternatives.

There are three PV solar projects deploying carport-type PV plants inside detention basins in the U.S. One of the projects is a 422 kW plant installed and serving a dairy product warehouse [22] and the other is a 297 kW system supplying energy for a school [23], both located in New Jersey. The third one is a 419 kW racking system which was installed in August 2023 in California serving mobile park residents [24]. Two analyses of 32.6 MW and 101 kW of floating PV system in Taiwan [25,26] show the feasibility of their deployment in detention basins. These cases suggest detention basins can support significant energy generation, yet their application for community solar in LMIs lacks systematic quantification. Existing research predominantly explores rooftop solar, large-scale floating PV in reservoirs, ground-based systems, carport designs, or agrivoltaics, often overlooking the potential of smaller, community-adjacent basins [6,27–31]. This study fills this gap, leveraging these precedents to assess whether detention basins can serve as energy assets providing cost savings and reducing the environmental emissions of the residential sector, while helping offset the maintenance costs of the flood control infrastructure.

A review of the research literature reveals a spectrum of perspectives on solar PV deployment. Advocates of floating PV emphasize efficiency gains-estimated at 5–10% over land-based systems-due to water cooling effects that reduce panel temperatures, alongside co-benefits like evaporation reduction (30–50%) in water-scarce regions such as Texas and Oklahoma [32,33]. Critics, however, caution against ecological trade-offs, including shading impacts on aquatic ecosystems, altered dissolved oxygen levels, or water quality degradation, urging detailed environmental assessments [34]. Community solar, where multiple users share benefits via subscription or ownership, offers a distinct model, reducing grid demand and emissions while bypassing individual installation barriers [9,10,12,35]. Recent deployments on leased land, brownfields, or farms-and five new projects in California LMIs-support its viability, yet none utilize detention basins near communities, highlighting this study's innovation [15,36–38]. These debates underscore the need for region-specific analyses to balance energy gains with ecological and social outcomes, particularly in LMIs where equity is paramount.

In Texas, Oklahoma, New Mexico, and Louisiana-states with significant LMI populations and diverse climatic conditions-this approach could transform residential energy access, leveraging detention basins to provide cost efficiency, environmental emissions savings and, when properly designed, grid resilience.

This study tests two hypotheses: (1) community solar in detention basins can offset 100% of residential emissions in LMIs, helping them achieve the Net-Zero Energy status, and (2) economic viability requires incentives beyond current federal provisions, such as the 40% Investment Tax Credit. The primary aim is to evaluate the technical, economic, and environmental feasibility of this approach across four states, contributing to the residential sector's decarbonization-15% of U.S. emissions-and advancing energy justice. Preliminary findings indicate floating PV systems reduce costs by 52–54% compared to carport designs, only Louisiana and New Mexico basins meet spatial demands, and profitability hinges on enhanced incentives. These results position detention basin solar as a scalable, equitable solution, bridging research gaps and supporting national climate targets, with implications for policy and community planning in LMIs.

2 Material and methods

The analysis was structured into four stages: energy and emissions assessment, technical feasibility, financial feasibility, and sensitivity analysis, as depicted in a flowchart in Figure 2. The methodology relied on collecting data on energy consumption, space availability, and environmental emissions factors, to be used in techno-economic models that will assess the system‘s performance and profitability.

The energy and emissions analysis begins with the calculation of the average electricity and natural gas consumption per household in LMIs for each state, distinguishing between traditional households (using both electricity and natural gas) and all-electric households. This data was sourced from the U.S. Department of Energy's Low-Income Energy Affordability Data Tool for average energy costs and the U.S. Energy Information Administration's 2023 residential rates [39,40].

$$\begin{array}{l}\mathit{Electricity}\mathit{Usage}\mathit{per}\mathit{traditional}\mathit{household}\mathit{in}\mathit{LMI}\mathit{Community}\mathit{of}\mathit{a}\mathit{State}\left[\mathit{kWh}\right]=\\ \mathit{}\frac{\mathit{Average}\mathit{annual}\mathit{electricity}\mathit{cost}\mathit{per}\mathit{household}\mathit{of}\mathit{a}\mathit{State}[\$]}{\mathit{Average}\mathit{residential}\mathit{electricity}\mathit{rate}\mathit{of}\mathit{a}\mathit{State}\mathit{in}2023\left[\frac{\$}{\mathit{kWh}}\right]}\end{array}$$(1)

$$\begin{array}{l}\mathit{Natural}\mathit{Gas}\mathit{Usage}\mathit{per}\mathit{traditional}\mathit{household}\mathit{in}\mathit{LMI}\mathit{Community}\mathit{of}\mathit{a}\mathit{State}\left[\mathit{MMBTU}\right]=\\ \mathit{}\frac{\mathit{Average}\mathit{annual}\mathit{natural}\mathit{gas}\mathit{per}\mathit{household}\mathit{cost}\mathit{of}\mathit{a}\mathit{State}[\$]}{\mathit{Average}\mathit{residential}\mathit{natural}\mathit{gas}\mathit{rate}\mathit{of}\mathit{a}\mathit{State}\mathit{in}2023\left[\frac{\$}{\mathit{MMBTU}}\right]}& .\end{array}$$(2)

To generate the “All Electric” residential profile, the natural gas usage is converted to the equivalent electricity usage and added to the electricity usage calculated using electricity cost data.

$$\begin{array}{l}\mathit{Electricity}\mathit{Usage}\mathit{per}\mathit{all}\mathit{electric}\mathit{household}\mathit{in}\mathit{LMI}\mathit{Community}\mathit{of}\mathit{a}\mathit{State}\left[\mathit{kWh}\right]=\\ \mathit{}\frac{\mathit{Average}\mathit{annual}\mathit{electricity}\mathit{cost}\mathit{per}\mathit{household}\mathit{of}\mathit{a}\mathit{State}[\$]}{\mathit{Average}\mathit{residential}\mathit{electricity}\mathit{rate}\mathit{of}\mathit{a}\mathit{State}\mathit{in}2023\left[\frac{\$}{\mathit{kWh}}\right]}+\\ \left(\mathit{Natural}\mathit{Gas}\mathit{Usage}\mathit{per}\mathit{tradtional}\mathit{household}\mathit{in}\mathit{LMI}\mathit{Community}\mathit{of}\mathit{a}\mathit{State}\left[\mathit{MMBTU}\right]\times 293.07107\right)& .\end{array}$$(3)

Consumption trends over a 25 yr period (2025–2050) were projected using historical data from the Residential Energy Consumption Survey (1997–2020), calculating annual percentage changes for the West South Central (Texas, Oklahoma, Louisiana) and Mountain (New Mexico) regions [41,42]. The emissions factors for the electricity coming from the grid were derived from the National Renewable Energy Laboratory's Cambium dataset, modeled as polynomial regressions from 2025 to 2050 at 1 yr intervals, while natural gas emissions were held constant at 53.06 kg CO₂/MMBTU [43,44]. The total community emissions and the theoretical electricity required to offset them were computed annually for both household types.

$$\begin{array}{l}\mathit{Electricty}\mathit{Usage}\mathit{per}\mathit{Household}\mathit{in}\mathit{Region}\left[\mathit{kWh}\right]=\\ \mathit{Average}\mathit{household}\mathit{electricty}\mathit{consuption}\mathit{in}\mathit{Region}\left[\mathit{MMBTU}\right]\mathit{}\times \mathit{}293.071\end{array}$$(4)

$$\begin{array}{l}\mathit{Natural}\mathit{Gas}\mathit{Usage}\mathit{per}\mathit{Household}\mathit{in}\mathit{Region}\left[\mathit{MMBTU}\right]=\\ \mathit{Average}\mathit{household}\mathit{Natural}\mathit{gas}\mathit{consuption}\mathit{in}\mathit{Region}\left[\mathit{MMBTU}\right]\end{array}$$(5)

$$\frac{\left(\begin{array}{c}\hfill \text{Percentrage Change in Electricity or Natural Gas Per Report}\mathit{Electricity}\mathit{or}\mathit{Natural}\mathit{Gas}\mathit{Usage}\mathit{per}\mathit{household}\mathit{for}\mathit{year}\mathit{n-}\hfill \\ \hfill \mathit{Electricity}\mathit{or}\mathit{Natural}\mathit{Gas}\mathit{Usage}\mathit{per}\mathit{household}\mathit{for}\mathit{year}\mathit{n-1}\hfill \end{array}\right)}{\mathit{Electricity}\mathit{or}\mathit{Natural}\mathit{Gas}\mathit{Usage}\mathit{per}\mathit{household}\mathit{for}\mathit{year}\mathit{n}-1}\times 100$$(6)

$$\begin{array}{l}\mathit{Average}\mathit{change}\mathit{in}\mathit{electricty}\mathit{or}\mathit{natural}\mathit{gas}\mathit{per}\mathit{year}=\\ \frac{\sum \frac{\mathit{Percentrage}\mathit{Change}\mathit{in}\mathit{Electricity}\mathit{or}\mathit{Natural}\mathit{Gas}\mathit{Per}\mathit{Report}}{100\times \#\mathit{of}\mathit{years}\mathit{per}\mathit{Report}}}{\#\mathit{of}\mathit{reports}\mathit{from}\mathit{RECS}}\end{array}$$(7)

$$\begin{array}{l}\mathit{Electricty}\mathit{or}\mathit{natural}\mathit{gas}\mathit{of}\mathit{a}\mathit{household}\mathit{year\; n}\mathit{-1}=\mathit{Electricty}\mathit{or}\mathit{natural}\mathit{gas}\mathit{of}\mathit{a}\mathit{household}\mathit{year}\mathit{n}\\ -1\times \left(1+\mathit{Average}\mathit{change}\mathit{in}\mathit{electricty}\mathit{or}\mathit{natural}\mathit{gas}\mathit{per}\mathit{year}\right)\end{array}$$(8)

$$\begin{array}{l}\mathit{Total}\mathit{Carbon}\mathit{Emissions}\mathit{of}\mathit{Community}\mathit{with}\mathit{Traditional}\mathit{Characteristics}\mathit{for}\mathit{year}\mathit{n}\left[kg.\right]\\ =((\mathit{Electricity}\mathit{Usage}\mathit{per}\mathit{traditional}\mathit{household}\mathit{in}\mathit{LMI}\mathit{Community}\mathit{of}\mathit{a}\mathit{State}\mathit{for}\mathit{year}\mathit{n}\left[\mathit{kWh}\right]\\ \times \mathit{Grid}\mathit{Emissions}\mathit{Factor}\mathit{of}\mathit{a}\mathit{State}\mathit{for}\mathit{year}\mathit{n}\left[\frac{\mathit{kg}.}{\mathit{kWh}}\right])\\ +(\mathit{Natural}\mathit{Gas}\mathit{Usage}\mathit{per}\mathit{traditional}\mathit{household}\mathit{in}\mathit{LMI}\mathit{Community}\mathit{of}\mathit{a}\mathit{State}\mathit{for}\mathit{year}\mathit{n}\left[\mathit{MMBTU}\right]\\ \times \mathit{Natural}\mathit{Gas}\mathit{Emissions}\mathit{Factor}\left[\frac{\mathit{kg}.}{\mathit{MMBTU}}\right]))\times \#\mathit{of}\mathit{Homes}\mathit{in}\mathit{Selected}\mathit{Communit}\end{array}$$(9)

$$\begin{array}{l}\mathit{Total}\mathit{Carbon}\mathit{Emissions}\mathit{of}\mathit{Community}\mathit{with}\mathit{All}\mathit{Electric}\mathit{Characteristics}\mathit{for}\mathit{year}\mathit{n}\left[kg.\right]\\ =(\mathit{Electricity}\mathit{Usage}\mathit{per}\mathit{all}\mathit{electric}\mathit{household}\mathit{in}LMI\mathit{Community}\mathit{of}\mathit{a}\mathit{State}\mathit{for}\mathit{year}\mathit{n}\left[kWh\right]\\ \times \mathit{Grid}\mathit{Emissions}\mathit{Factor}\mathit{of}\mathit{a}\mathit{State}\mathit{for}\mathit{year}\mathit{n}\left[\frac{kg.}{kWh}\right])\times \#\mathit{of}\mathit{Homes}\mathit{in}\mathit{Selected}\mathit{Communit}\end{array}$$(10)

$$\begin{array}{l}\mathit{Theoretical}\mathit{electricity}\mathit{required}\mathit{to}\mathit{fully}\mathit{offset}\mathit{Total}\mathit{Carbon}\mathit{Emissions}\mathit{of}\mathit{Community}\mathit{for}\mathit{year}\mathit{n}\left[\mathit{kWh}\right]=\\ \frac{\mathit{Total}\mathit{Carbon}\mathit{Emissions}\mathit{of}\mathit{Community}\mathit{for}\mathit{year}\mathit{n}\left[\mathit{kg}.\right]}{\mathit{Grid}\mathit{Emissions}\mathit{Factor}\mathit{of}\mathit{a}\mathit{State}\mathit{for}\mathit{year}\mathit{n}\left[\frac{\mathit{kg.}}{\mathit{kWh}}\right]}\end{array}$$(11)

$$\begin{array}{l}\mathit{Total}\mathit{Carbon}\mathit{Emissions}\mathit{off\; set}\mathit{for}\mathit{year}\mathit{n}\left[\mathit{kg}.\right]=\\ (\mathit{Estimated}\mathit{Electricity}\mathit{generated}\mathit{by}\mathit{PV}\mathit{system}\mathit{for}\mathit{year}\mathit{n}\left[\mathit{kWh}\right]\times \\ \mathit{Grid}\mathit{Emissions}\mathit{Factor}\mathit{of}\mathit{a}\mathit{State}\mathit{for}\mathit{year}\mathit{n}\left[\frac{\mathit{kg.}}{\mathit{kWh}}\right])\end{array}.$$(12)

As mentioned in the previous section, the technical analysis is focused on sizing community solar plants to offset 100% of each community's emissions over 25 yr, defining Net Zero Energy Emissions as a state where the emissions associated with the annual energy purchases are lower than the emissions reductions generated by the renewable energy exports [45]. Four LMI communities (one per state) were selected based on proximity to a detention basin, with household counts ranging from 82 (Texas) to 1,353 (Oklahoma) and basin areas measured via Google Maps (e.g., 6,172 m² in Texas, 87,464 m² in Oklahoma). The solar PV capacities were estimated using the National Renewable Energy Laboratory (NREĹs) System Advisor Model (SAM) (version 2025.4.16, SSC 302), incorporating site-specific weather data, a 0.5% annual degradation rate, and a 190 W/m² power density to convert capacity (kWDC) to required area [46]. The technical feasibility was confirmed if the calculated area fit within the basin's available space. Only the technically viable cases advance to the financial analysis.

The financial analyses are focused on the economic feasibility of community solar installations, considering a lifespan of 25 yr (both for carport and floating PV systems). Costs included modules, inverters, balance-of-system components, installation labor, and operations and maintenance (set at $19/kW/yr), with state-specific inputs like power purchase agreement prices (e.g., $0.06/kWh in New Mexico, $0.02782/kWh in Louisiana), state income tax, and sales tax [47,48]. A 40% Investment Tax Credit was applied universally, reflecting federal incentives for LMIs. The Net Present Value (NPV) served as the primary indicator, with positive values denoting profitability. Default SAM parameters supplemented site-specific data where applicable, ensuring consistency across scenarios.

A sensitivity analysis was conducted on cases failing financial feasibility, examining two variables: power purchase agreement prices and external incentives. Starting points used base simulation values (e.g., $0.02782/kWh for Louisiana), while endpoints were determined by setting the Internal Rate of Return equal to the nominal discount rate (9.06%/yr) for price adjustments yielding near-zero NPV, and a trial-and-error method for incentives achieving the same. Twenty-five combinations per case were simulated, normalizing NPV and incentives by household count to enable cross-state comparisons. The capital cost per kilowatt per home was also calculated to assess incentive impacts on investment needs.

$$\begin{array}{l}\mathit{Capital}\mathit{Cost}\mathit{per}\mathit{Home}\mathit{per}\mathit{kW}[\$]=\\ \frac{\left(\mathit{Capital}\mathit{Cost}\mathit{of}\mathit{the}\mathit{project}[\$]-\mathit{External}\mathit{Incetive}\mathit{for}\mathit{the}\mathit{Case}[\$]\right)}{\#\mathit{of}\mathit{Homes}\mathit{in}\mathit{Selected}\mathit{Community}\times \mathit{Estimated}\mathit{Solar}\mathit{PV}\mathit{Capacity}\mathit{per}\mathit{Home}\left[\left({\mathit{kW}}_{\mathit{DC}}\right)\right]}\end{array}$$(13)

where,

$$\mathit{Estimated}\mathit{Solar}\mathit{PV}\mathit{Capacity}\mathit{per}\mathit{Home}\left[{\mathit{kW}}_{\mathit{DC}}\right]=\frac{\mathit{Estimated}\mathit{Solar}\mathit{PV}\mathit{Module}\mathit{Capacity}\mathit{from}\mathit{SAM}\left[{\mathit{kW}}_{\mathit{DC}}\right]}{\#\mathit{of}\mathit{Homes}\mathit{in}\mathit{Selected}\mathit{Community}}.$$(14)

Fig. 1 Stormwater detention basin [18].

Fig. 2 Analysis flowchart.

3 Results

This study investigated the potential for community solar photovoltaic systems installed in stormwater detention basins to help LIM communities achieve Net Zero Energy across Texas, Oklahoma, New Mexico, and Louisiana. The initial phase of the analysis determined the annual household energy consumption to estimate the scale of solar systems required. Energy usage was evaluated for two household profiles: traditional, utilizing both electricity and natural gas, and all-electric, depending entirely on electricity, represented in Tables 2 and 3. These profiles, informed by state-specific residential energy patterns, revealed varied consumption trends shaped by regional differences in fuel mix and pricing structures, setting the stage for subsequent technical and financial evaluations [41]. Each community varied in household count and basin size, measured using Google Maps, presented in Table 1 along with number of cooling and heating degree days for the nearest major city. Figures 3–6 present the boundaries of the selected housing communities.

The annual energy usage per household and location with traditional characteristics is calculated in Table 2, and with all electric characteristics is calculated in Table 3. The electricity and natural gas usage are in relation to CDD and HDD specified in Table 1, New Mexico which has more HDD has higher natural gas consumption for heating whereas Texas and Louisiana with more CDD causes more electricity consumption for HVAC compared to natural gas consumption for heating.

Using equations (1)–(8), the energy usage per household is plotted bellow in Figures 7–10. The figures depict how the usage profile of electricity and natural gas for LMI household in each state for both traditional and all electric households. Each state's electricity and natural usage vary at different rate.

As mentioned in previously, Net Zero Energy is used as a design target for the community solar. The total carbon emissions from household energy use in LMI Communities across Texas, Oklahoma, New Mexico, and Louisiana, along with the theoretical electricity needed to offset these emissions through community solar photovoltaic systems are:

– Calculated using grid emissions factors, sourced from a national energy dataset, and a natural gas emissions factor of 53.06 kg CO₂ per MMBTU, derived from established environmental data.

– Applied across the analysis period to quantify community emissions and corresponding solar requirements [44,49].

Using equations (9)–(12), Figures 11–14 below depicts the emissions and the theoretical electricity needed. The electricity and natural gas usage along with grid emissions factor affects the theoretical electricity needed. Traditional households require more theoretical electricity compared to all electric as the emissions factor natural gas remains constant compared to electricity. LMI community in Oklahoma, which consist of higher number of homes accounts for more natural gas consumption; as emissions factor of natural gas is constant and with grid emissions factor reducing, more electricity is needed. In contrast Texas LMI community with lower natural gas usage and lower home count allows for lower electricity requirements.

As previously mentioned, the technical feasibility is assessed by estimating the optimal capacity of community solar photovoltaic systems required to offset a 100% of the energy-related carbon emissions in the nearby LMI community (resulting into a Net Zero Energy Emissions status), an approach aligned with renewable energy sizing studies [49]. A standard annual degradation rate for solar modules, set at 0.5% to reflect performance over time, was incorporated into capacity calculations using established modeling tools [46]. To verify space availability, the estimated system capacity was converted to required surface area using a power density ratio of 190 watts per square meter, enabling comparison with available detention basin areas in each community. This analysis provided critical insights into whether the dimensions of the basin could accommodate the solar infrastructure required to offset 100% of the energy-related environmental emissions of the community. Table 4 shows the optimal solar PV size and percentage of carbon offset.

Technical feasibility assessments revealed that only three of eight possible combinations of community characteristics (traditional and all electric households) and solar photovoltaic system designs in LMI Communities across Texas, Oklahoma, New Mexico, and Louisiana met the spatial requirements for achieving Net Zero Energy emissions. This is consistent with findings in community-scale renewable energy studies [49]. As presented in Table 5, these feasible cases indicated that available detention basin areas could accommodate the estimated solar capacities, whereas the remaining communities required basin areas exceeding the available space. The state with higher electricity required to fully offset emissions, which is dependent on grid emissions factor and number of homes when paired with lower basin area causes them to be not technically feasible. Table 6 summarizes additional metrics, including the solar capacity and the corresponding basin area per household for each state and household type, enabling comparisons of energy requirements and identifying regional factors influencing system feasibility, such as basin availability and community size.

The analysis of the solar photovoltaic capacity requirements revealed variations in per-household energy needs across LMI Communities in Texas, Oklahoma, New Mexico, and Louisiana, driven by factors such as total energy demand, 25 yr consumption trends, emissions factors, household characteristics, and local solar irradiation. As shown in Figure 15, Texas requires the least solar capacity per home, while Oklahoma demands the most, reflecting differences in emissions profiles and energy usage patterns. This difference can be observed as a pronounced peak for traditional households in Oklahoma compared to smoother trends in Texas, as seen in Figures 7, 8, 11, and 12. For all-electric households, capacity needs varied within a 5 kW range. Commercial solar panels offers a capacity of approximately 410 watts per panel, necessitating between 52 and 128 panels per home for traditional households and 37 to 49 for all-electric households [50]. These panel counts pose challenges in LMI Communities, where older homes often lack sufficient roof space, proper orientation, or structural integrity for rooftop solar, and low-income families may face barriers in maintaining systems post-warranty, reinforcing the suitability of community solar for decarbonization.

Following confirmation of technical feasibility for three of eight cases, as detailed in Table 5, the financial feasibility was evaluated for carport and floating photovoltaic systems in the technically viable cases: Louisiana traditional, Louisiana all-electric, and New Mexico all-electric. Six financial analyses (for each technical feasible case, a carport and floating PV system case) were conducted using established modeling tools, incorporating location-specific parameters such as power purchase agreement prices, state income tax, and sales tax, as presented in Table 10. New Mexico's agreement price was set at 0.06 dollars per kilowatt-hour, and Louisiana's at 0.02782 dollars, with an annual increase of 1% as a standard assumption [47,48]. System costs, outlined in Tables 7–9, included an operations and maintenance cost of 19 dollars per kilowatt per year, reflecting post-installation equipment and service expenses [51]. The type of system affects the capital cost, Carport systems faced challenges such as soft soils and sloping terrain, addressable through engineering solutions, while floating systems required robust designs to manage fluctuating water levels and adaptive anchoring [24,52]. Financial indicators such as the NPV and the capital cost of the investment were calculated using location-specific weather data and installation costs, with all other parameters held at default, providing insights into the economic viability of these systems for decarbonizing LMI Communities.

The results of the financial feasibility assessments, detailed below in Table 11, indicate that only one of six evaluated cases in LMI Communities across Louisiana and New Mexico achieved a positive Net Present Value over a 25 yr period, showing profitability for the all-electric community in New Mexico utilizing a floating photovoltaic system. The remaining cases did not show positive profitability indicators under the current conditions in Tables 7–10, such as PPA Price, State Income Tax and State Sales Tax, Solar Module Variables, highlighting economic barriers to achieving Net Zero Energy Emission strictly through solar deployment in detention basins. Factor such as higher capital cost due to larger system requirements which is dependent on energy usage and emissions factor for electricity when accompanied with lower PPA price causes no financial feasibility. A sensitivity analysis was conducted to identify viable scenarios by examining two key variables: PPA prices, which influence revenue, and external incentives, which reduce capital costs, both adjustable based on location-specific policies. The analysis set the Internal Rate of Return equal to a nominal discount rate of 9.06 % per year, a standard assumption for a 25 yr period, to determine breakeven agreement prices, while a trial-and-error approach established incentive levels yielding near-zero Net Present Value at base prices, providing insights into pathways for economic feasibility. Table 12 below shows the maximum and minimum values for the two sensitive variables in each of the communities.

The sensitivity analysis explored combinations of PPA prices and external incentives to identify financially viable solutions for LMIs community solar systems across Louisiana and New Mexico, simulating twenty-five cases per community to assess the different Net Present Value outcomes. These simulations, detailed in Figures 16–20, revealed transition points where the NPV shifted from negative to positive for each case, indicating thresholds for profitability. To account for varying household counts, the Net Present Value and incentive values were normalized per household, as shown in Figures 21–25, illustrating the incentive required per home at different agreement prices and the corresponding profitability, while providing a standardized comparison across communities.

Findings highlighted that the Louisiana community with all-electric characteristics and a floating photovoltaic system required the smallest per-home incentive to achieve a profitable project, yielding the highest profitability at a PPA price of 0.06 dollars per kilowatt-hour with comparable incentives. Conversely, the Louisiana community with traditional characteristics and a carport system demanded the highest incentive, reflecting greater financial barriers. Figures 21–25 offer a framework to estimate agreement prices and incentives needed for new communities to achieve Net Zero Energy Emission status. Additionally, Figure 26 illustrates variations in capital cost per kilowatt of solar capacity as incentives change, with Louisiana's all-electric floating system requiring the lowest investment and the traditional carport system the highest, indicating that all-electric households and floating systems generally necessitate lower incentives and capital costs compared to traditional households and carport-type systems.

Fig. 3 82-Home LMI community in Texas.

Fig. 4 1,353-Home LMI community in Oklahoma.

Fig. 5 260-home LMI community in New Mexico.

Fig. 6 101-home LMI community in Louisiana.

Fig. 7 Energy usage per household in Texas with traditional and all electric characteristics.

Fig. 8 Energy usage per household in Oklahoma with traditional and all electric characteristics.

Fig. 9 Energy usage per household in New Mexico with traditional and all electric characteristics.

Fig. 10 Energy usage per household in Louisiana with traditional and all electric characteristics.

Fig. 11 Emissions and electricity required for LMI community in Texas with traditional and all electric characteristics.

Fig. 12 Emissions and electricity required for LMI community in Oklahoma with traditional and all electric characteristics.

Fig. 13 Emissions and electricity required for LMI community in New Mexico with traditional and all electric characteristics.

Fig. 14 Emissions and electricity required for LMI community in Louisiana with traditional and all electric characteristics.

Fig. 15 Solar and detention pond area required per home with traditional and all electric characteristics.

Fig. 16 NPV of sensitivity analysis of Louisiana with traditional characteristics and carport system.

Fig. 17 NPV of sensitivity analysis of Louisiana with traditional characteristics and FPV system.

Fig. 18 NPV of sensitivity analysis of Louisiana with all electric characteristics and carport system.

Fig. 19 NPV of sensitivity analysis of Louisiana with all electric characteristics and FPV system.

Fig. 20 NPV of sensitivity analysis of New Mexico with all electric characteristics and carport system.

Fig. 21 Per home NPV of sensitivity analysis of Louisiana with traditional characteristics and carport system.

Fig. 22 Per home NPV of sensitivity analysis of Louisiana with traditional characteristics and FPV system.

Fig. 23 Per home NPV of sensitivity analysis of Louisiana with all electric characteristics and carport.

Fig. 24 Per home NPV of sensitivity analysis of Louisiana with all electric characteristics and FPV system.

Fig. 25 Per home NPV of sensitivity analysis of New Mexico with all electric characteristics and carport system.

Fig. 26 Variation in capital cost per home in response to incentives.

4 Discussion

The deployment of community solar PV plants in stormwater detention basins with the goal to reduce costs and environmental emissions to the Net Zero Energy emissions evel in LMI Communities across Texas, Oklahoma, New Mexico, and Louisiana reveals a complex interplay of technical feasibility, and economic viability, shaped by regional energy dynamics, socio-economic and geospatial constraints. Household energy demand profiles emerged as a pivotal determinant of PV system sizing. All-electric households community in Texas (1,125 kW_DC), Oklahoma (27,350 kW_DC), New Mexico (4,050 kW_DC), and Louisiana (1,850 kW_DC) required significantly less capacity than their traditional (electricity + natural gas) counterparts (1,750 kW_DC, 71,000 kW_DC, 7,800 kW_DC, and 3,600 kW_DC, respectively), reflecting lower annual energy demands (e.g., 28,682.8 kWh in New Mexico all electric vs. 7,973.2 kWh + 70.7 MMBTU for traditional) and alignment with grid decarbonization trends projected by NREL's Cambium (2025–2050). Traditional households, reliant on natural gas with a static emissions factor of 53.06 kg CO₂/MMBTU [44], faced a steeper challenge as grid emissions decline, necessitating oversized PV systems to offset peak emissions years-most starkly in Oklahoma, where a 71,000 kW_DC system dwarfed the 87,464 m² basin by 427%. This underscores the fact that using solar energy technologies to offset fossil fuel use increases the capacity required in regions where natural gas remains prevalent, like the Southcentral U.S.

Technical feasibility hinged on detention basin spatial capacity, revealing stark regional disparities.

Texas's 6,172 m² basin fell short of the 9,210 m² (149%) and 6,447 m² (104%) required for traditional and all-electric systems, respectively, constrained by its small footprint relative to an 82-home community.

• Oklahoma's 87,464 m² basin, despite its size, could not accommodate the 373,684 m² (427%) or 143,947 m² (164%) needed, reflecting the scale of its 1,353-home community and high per-home solar PV size required (52.48 kW_DC traditional, 20.21 kW_DC all-electric).

• In contrast, New Mexico's 40,672 m² basin supported the 21,315 m² (52%) for all-electric but not the 41,052 m² (101%) for traditional homes.

• Louisiana's 46,623 m² basin efficiently housed 18,947 m² (40%) and 9,737 m² (21%) for traditional and all-electric cases.

Economically, floating PV systems consistently outperformed carport-type systems, slashing capital costs by 52–54% (e.g., $7,047,000 vs. $16,750,000 for New Mexico all-electric homes; $3,619,000 vs. $7,768,000 for Louisiana all-electric homes). This cost differential, driven by reduced structural and land preparation expenses [53], positions floating PV as a scalable solution for community solar in LMIs, where high initial investment barriers compounded by poor housing conditions preclude rooftop solar.

The financial and sensitivity analyses underscores state-specific challenges and profitability thresholds:

• Louisiana's traditional floating PV yielded a −$2,901,000 NPV at $0.02782/kWh, requiring $3,735,000 ($36,980/home) or a PPA hike to $0.07950/kWh, while its all-electric floating PV needed $2,215,000 ($21,931/home) or $0.08745/kWh.

• New Mexico's all-electric floating PV achieved a $127,000 NPV at $0.06/kWh with 40% ITC, yet its carport-type variant demanded $6,370,000 ($24,500/home) or $0.11825/kWh.

• Texas and Oklahoma, lacking PPA data, likely face similar hurdles given their system sizes (e.g., 1,750 kW_DC and 71,000 kW_DC traditional), with sensitivity analyses suggesting Louisiana's traditional carport extreme ($0.15872/kWh or $9,460,000, $93,663/home) as a benchmark.

The approach delivered robust emissions offsets-116% for the Texas, 214% for Oklahoma, 143% for New Mexico, and 169% for the Louisiana traditional LMI communities. Floating PV's water-cooling effect, boosting efficiency by 5–10%, and evaporation reduction (30–50%) [32,33], offer co-benefits in water-scarce Texas and Oklahoma, though ecological trade-offs-e.g., shading impacts on aquatic ecosystems-require further study, as noted in FPV literature [38]. Deployment challenges, such as carport-type foundation costs (3% contingency) and floating PV's anchorage for fluctuating levels (5.87% contingency in Louisiana), elevate the expenses by 5–10%, yet state-specific incentives (e.g., Texas property tax exemptions, New Mexico SRECs) and federal ITC mitigate these. For LMIs, where rooftop solar is stymied by structural and financial barriers, detention basin PV offers a community-scale alternative, by reducing burdens [57] and leveraging EO 14008's 40% benefit previously mandate. However, Texas and Oklahoma's spatial deficits, Louisiana's PPA constraints, and Oklahoma's outsized energy demand necessitate nuanced policy interventions-higher PPA rates, targeted grants (e.g., EPA Solar for All [58]), and basin expansion-to achieve feasibility across these states.

5 Conclusion

This paper analyzes the feasibility of using the stormwater detention basins owned and maintained by LMI Communities to host PV solar plants that able to:

• Offset 100% of the community's environmental emissions (Net Zero Emissions communities).

• Help its residents reduce their energy burden.

The paper considers a community solar business model in four different states in the Southcentral region of the U.S.

According to the analysis, the characteristics of the household play a major role in the basin area (and PV system size) required to offset the emissions of the community during the lifespan of the technology. Traditional household communities require additional solar deployment because the natural gas emissions factor is constant (in contrast to the declining grid emissions factor over the project lifespan). This results in larger PV capacity and space requirements than in all-electric communities. As the forecasted grid emissions factor declines, the capital required to fully offset the emissions from traditional household communities increases, opening an opportunity to deploy other technologies or reduce the fuel's emissions factor in traditional households. Other geospatial factors that affect the PV capacity to be deployed are the energy usage and grid emissions trends in each state.

When it comes to deployment, floating solar offers lower investment costs than a carport system due to the higher installation costs of the latter. The deployment of floating and carport solar in detention basins will require more planning than a typical ground-based PV system.

The community showing positive financial and technical feasibility was the all-electric community in New Mexico with floating solar in its detention basin. The system has a positive NPV at the current PPA price and energy cost, and the annual emissions are fully offset over the 25 yr analysis period.

Common barriers to deploying community solar in detention ponds to reduce costs and emissions in LMI Communities are:

• The high initial investment is usually a barrier for homeowners in LMI Communities.

• More space is needed than is available in the detention basin for the community, especially for traditional household communities.

• Selling the power generated to the local utility usually generates lower economic savings than self-consuming it, making the feasibility more challenging. PPA prices would need to be higher to make the project financially feasible with no incentives.

• Incentives, either from federal, state, or non-governmental organizations, are needed for LMIs to achieve the Net Zero Energy emissions status using PV solar.

Some of the advantages of deploying community solar in detention ponds to decarbonize LMI Communities are:

• Damaged roofs are a common barrier in LMI Communities, preventing them from accessing solar technologies. Community solar can help avoid the expensive cost of repairing roofs to bring them up to the required standards for installation of solar panels.

• In addition to that, deploying solar in detention ponds has higher aggregated power generation potential than residential rooftop solar costs than deploying solar on roofs.

• Community solar can help improve the value of the properties in the communities.

• Incentives are available for LMIs to implement these community solar projects. They include:

  • Investment Tax Credits (ITC) via the Inflation Reduction Act (IRA) for all states.

  • Implementation grants like EPA's Solar for All and others from other agencies [59].

  • Property Tax exception in Texas, New Mexico, and Louisiana.

  • Solar Renewable Energy Credits (SRECs) in New Mexico, Solar Installation Sales Tax Exemption in New Mexico, Louisiana Solar Sales Tax Exemption, Net Metering is offered in New Mexico and Louisiana. The National Community Solar Partnership (NCSP) for all the states [60].

  • Various incentives and policies are also available in DSIRE. Along with this some incentive opportunity currently available or can potentially be available [61].

The analysis described the PPA prices and incentives required per home for NPV outcome for a typical community situated in LMI, which can be used to scale to determine the incentives required as per PPA price for a new community being designed or an existing community in LMI. These methods and results can be used by community planners and policymakers to go one step forward on the decarbonization goals for the residential sector.

The next steps should involve obtaining more granular energy demand profiles from the targeted communities along with considering new policies and incorporating actual vendor quotes for installation cost for PV solar in detention basins; comparing the feasibility with deployment of PV solar on rooftop for similar LMI Communities and to deploy pilot projects in some of the locations showing positive techno-economic feasibility to monitor; study the ecological and hydrological impacts, along with operation challenges and validate results with the techno-economic analysis. Along with this, additional steps will be required when deploying this method in a full-scale project, like interconnection which could include reaching out to the local utility early in the process to discuss their conditions for interconnection and other factors, similar than for traditional solar. And permitting, comprising of reaching out to the local government to learn more about local regulations and permitting requirements for PV solar plants to be deployed in detention basins.

Funding

This research received no specific grant, award, or external funding. The work was conducted as part of the authors? professional activities at the Houston Advanced Research Center (HARC).

Conflicts of interest

The authors declare that there are no conflicts of interest regarding the publication of this work.

Data availability statement

The authors have data supporting the findings of this study. These data are available from the corresponding author upon reasonable request.

Author contribution statement

Conceptualization, CG and V.B.; Methodology, V.B and C.G.; Software, V.B.; Validation, V.B and C.G.; Formal Analysis, V.B.; Investigation, V.B.; Resources, V.B.; Data Curation, V.B.; Writing − Original Draft Preparation, V.B., C.G.; Writing − Review & Editing, V.B., C.G., E.E. and P.G.; Visualization, V.B.; Supervision, C.G.

References

All Tables

All Figures

	Fig. 1 Stormwater detention basin [18].
In the text

	Fig. 2 Analysis flowchart.
In the text

	Fig. 3 82-Home LMI community in Texas.
In the text

	Fig. 4 1,353-Home LMI community in Oklahoma.
In the text

	Fig. 5 260-home LMI community in New Mexico.
In the text

	Fig. 6 101-home LMI community in Louisiana.
In the text

	Fig. 7 Energy usage per household in Texas with traditional and all electric characteristics.
In the text

	Fig. 8 Energy usage per household in Oklahoma with traditional and all electric characteristics.
In the text

	Fig. 9 Energy usage per household in New Mexico with traditional and all electric characteristics.
In the text

	Fig. 10 Energy usage per household in Louisiana with traditional and all electric characteristics.
In the text

	Fig. 11 Emissions and electricity required for LMI community in Texas with traditional and all electric characteristics.
In the text

	Fig. 12 Emissions and electricity required for LMI community in Oklahoma with traditional and all electric characteristics.
In the text

	Fig. 13 Emissions and electricity required for LMI community in New Mexico with traditional and all electric characteristics.
In the text

	Fig. 14 Emissions and electricity required for LMI community in Louisiana with traditional and all electric characteristics.
In the text

	Fig. 15 Solar and detention pond area required per home with traditional and all electric characteristics.
In the text

	Fig. 16 NPV of sensitivity analysis of Louisiana with traditional characteristics and carport system.
In the text

	Fig. 17 NPV of sensitivity analysis of Louisiana with traditional characteristics and FPV system.
In the text

	Fig. 18 NPV of sensitivity analysis of Louisiana with all electric characteristics and carport system.
In the text

	Fig. 19 NPV of sensitivity analysis of Louisiana with all electric characteristics and FPV system.
In the text

	Fig. 20 NPV of sensitivity analysis of New Mexico with all electric characteristics and carport system.
In the text

	Fig. 21 Per home NPV of sensitivity analysis of Louisiana with traditional characteristics and carport system.
In the text

	Fig. 22 Per home NPV of sensitivity analysis of Louisiana with traditional characteristics and FPV system.
In the text

	Fig. 23 Per home NPV of sensitivity analysis of Louisiana with all electric characteristics and carport.
In the text

	Fig. 24 Per home NPV of sensitivity analysis of Louisiana with all electric characteristics and FPV system.
In the text

	Fig. 25 Per home NPV of sensitivity analysis of New Mexico with all electric characteristics and carport system.
In the text

	Fig. 26 Variation in capital cost per home in response to incentives.
In the text