Solar Energy Utilization Potential in Urban Residential Blocks: A Case Study of Wuhan, China

Abstract

In dense, energy-demanding urban areas, the effective utilization of solar energy resources, encompassing building-integrated photovoltaic (BIPV) systems and solar water heating (SWH) systems inside buildings, holds paramount importance for addressing concerns related to carbon emission reduction and the balance of energy supply and demand. This study aimed to examine the interplay between urban residential blocks and their solar energy potential, with the objective of promoting environmentally sustainable development within urban residential areas. The primary focus of this study was the hot summer and cold winter zone of China, which serves as a representative case study. Methodologically, we employed Rhinoceros and Grasshopper (GH) software version GH6.0 tools to simulate the solar radiation potential within residential blocks and translated this information into the potential utilization of BIPV and SWH systems. Subsequently, our focus was directed towards identifying optimal locations for mounting BIPV modules and water heaters on roofs and building façades. The study results revealed the following: (1) The floor area ratio (FAR), building density (BD), average building height (ABH), and space layout (SL) exerted substantial influences on the solar potential of a residential block, with correlations of up to 75%, 71%, 78%, and 50%, respectively, concerning the overall solar potential of the entire plot. (2) It is essential to emphasize that, with regard to the BIPV installation potential, façades account for 80% of the overall residential block potential, whereas rooftops contribute only 20%. Both south- and west-facing façades exhibited a BIPV installation ratio of approximately 34%. (3) In the realm of solar water heating, the potential for installations on building façades accounted for 77% of the total living area of the residential blocks, 23% on the rooftops, and 35% on the south-facing façades. This study furnishes practical guidelines for harnessing the potential of BIPV and SWH systems within residential blocks, thereby contributing to the advancement of sustainable urban development practices.

1. Introduction

At present, the development of renewable energy is a common goal, and there is a global consensus among countries around the world. By 2023, the global cumulative power generation will reach 77,620 terawatt-hours (TWh), of which coal will account for 67.0% (6123 TWh), while renewable energy will account for 20.3% (4983.14 TWh), with solar power accounting for a large proportion of the total [1,2]. Solar energy has become one of the most important clean energy sources and has been widely welcomed due to its safety, cleanliness, and ease of utilization [3]. As a renewable energy technology, the construction of BIPV integration and installation of SWH are important measures for promoting energy conservation and low-carbon urban development [4].

In China’s “14th Five-Year Plan” for renewable energy development, the targeted annual capacity for photovoltaic power generation is 124.5 billion kilowatt-hours. In this context, effective development of the solar energy potential in urban residential neighborhoods has a broad development prospect [5]. Here remains untapped potential for the utilization of renewable energy resources. In terms of the application of BIPV technology in China, 75.8% of BIPV systems are currently installed on industrial buildings and 20% are deployed on public buildings, while the utilization rate of solar BIPV technology in residential areas is only 3.9% [6]. It is essential to emphasize that urban residential blocks in China encompass a diverse array of functional components, including residential, commercial, office, and industrial spaces, with residential blocks constituting the predominant share. However, there is a lack of theoretical research on the integration of BIPV modules into these specific environments [7].

In terms of SWH, more than 80% of the newly installed capacity in the world comes from China [4], so the Chinese SWH market has great potential. However, the penetration of SWH applications in urban residential blocks is low, and there is still room for improvement in the system’s performance and reliability. Therefore, it is imperative to conduct a comprehensive study to assess the solar potential associated with different residential configurations and explore strategies for the large-scale installation of BIPV modules and the installation of SWH in residential areas. Both urban BIPV installations [8] and SWH systems [9] have great potential for development in terms of both scale and quantity.

In the realm of the research content, notable contributions have been made by various scholars and projects. For instance, Solar Cities in Berlin, Germany [10], Brito et al. [11], Groppi [12], Horváth [13], and Verso [14], among others, have conducted extensive investigations into solar energy applications in residential blocks within European countries. However, it is important to note that these studies have primarily concentrated on low-rise residential block roofs [15], with fewer instances of solar energy applications in high-rise residential block areas. Consequently, research findings on solar energy potential derived from Europe and the United States may not be directly applicable to the context of Chinese residential blocks. In contrast, research in China has focused mainly on the urban and building levels, with less research on the solar potential of residential blocks. In terms of research, scholars such as Ming [16], Sun [17], Yang [18], Nan [19], and Chao [20] have conducted extensive research into the application of solar energy technologies at the residential block and building levels. Huang [21] proposed a new method for detecting the city’s solar energy potential using image segmentation and deep learning techniques, and determined that the annual photovoltaic (PV) potential of Wuhan’s urban rooftops is 17,292.30 × 106 kWh per year. Xu [22] calculated the city-scale solar radiation by quantifying the relationship between urban residential block types and building roof shading coefficients in Wuhan, thus providing rapid access to solar radiation based on 2D urban roof images. Xu [23] investigated the effect of the residential block type on solar radiation by simulating solar irradiation in real urban industrial, commercial, and residential blocks. In existing studies, neither the scale of the study nor the selection of the study object are suitable for residential neighborhoods. The study of urban-scale solar power generation potential is conducive to predicting the regional solar power generation capacity on the macro scale.

Given this context, it becomes essential to delve into the solar energy distribution characteristics at regional points within the broader regional scale. This involves translating the diverse shading relationships encountered in actual Chinese residential block floor areas into quantifiable morphological parameters. This approach facilitates the investigation of the relationship between these quantified morphological parameters and the potential for solar energy utilization. Moreover, it facilitates the development of installation strategies for building-integrated photovoltaic (BIPV) modules, both on the roofs of distinct residential blocks and on various building façades. The ultimate goal is to foster the widespread adoption of BIPV and SWH [24] technologies within the Chinese urban environment.

In terms of the research methodology, evaluating the potential for solar energy utilization necessitates a critical examination of the building envelope area. Several statistical calculation methods have been developed for assessing the area of roofs and façades in urban buildings. These methodologies have been advanced by researchers such as Izquierdo [25], Wiginton [26], Lehmann [27], Julieta [28], and Karteris et al. [29]. These approaches encompass various techniques, including stratified sampling, GIS sample identification [30], site or building classification, and simulation methods employing software such as ECOTECT and Radiance. These approaches employ spatial categorization, which is subsequently processed through modeling within the GIS 10.4 or SketchUp 2018 software platforms. They rely on empirical values to determine the total available area on roofs and façades for solar energy utilization. However, it is crucial to acknowledge that the potential for solar energy application is influenced by a myriad of factors [31]. Therefore, it has become imperative to conduct a comparative analysis of the solar energy resources available for photovoltaic and photothermal applications across different building types, configurations, and heights within urban residential blocks. This comprehensive assessment enables the optimization of the analysis pertaining to the potential for solar energy utilization within these buildings.

This study aims to overcome these limitations by dissecting the intricate relationship between urban residential blocks and the exploitation of solar energy potential. Furthermore, it offers a comprehensive planning strategy for the allocation of the solar energy usable space, utilizing the main urban area of Wuhan as an illustrative example. The principal aim of this research is to proffer strategies for the integration of BIPV and SWH technologies into diverse residential blocks. This goal is attained through a thorough analysis of the solar energy potential across various residential block typologies within the city. In terms of research concepts, this study advances an analytical framework based on the solar energy potential of distinct residential block types. This framework serves as a foundational research basis for the planning and layout design of multifaceted residential blocks. It aims to overcome the constraints associated with traditional design and optimization processes, which are often reliant on empirical judgments. Consequently, the study seeks to establish a design strategy that is applicable to the optimization of residential block configurations. Methodologically, the research determines the simulated solar radiation potential of residential blocks using GH in Rhinoceros. This potential is then translated into BIPV and SWH utilization. A subsequent analysis primarily concentrates on the optimal selection of BIPV installation sites and SWH placement locations on roofs and façades, guided using simulated solar radiation data. The analysis subsequently assesses the impacts of varying parameter ranges on the BIPV installation potential, BIPV installation ratios, and BIPV power generation potential across residential blocks. Ultimately, the study provides optimal installation strategies for BIPV integration and solar water heaters within diverse residential block typologies, thus furnishing a research foundation for residential block layout design methodologies.

This study is organized into four main sections: In the first section, the significance of solar energy within the context of renewable energy is thoroughly examined through a comprehensive review of the relevant literature. Additionally, instances of solar energy applications, particularly in the fields of BIPV and SWH, are provided to underscore its importance. The second section employs Wuhan, an area in China that is characterized by a hot summer and cold winter climate zone, as a representative case study. This section takes into consideration the spatial layout of Wuhan and classifies the region into six categories: low-floor-area ratio low density (LFARLD), low-floor-area ratio high density (LFARHD), medium-floor-area ratio low density (MFARLD), medium-floor-area ratio high density (MFARHD), high-floor-area ratio low density (HFARLD), and high-floor-area ratio high density (HFARHD). The third section is dedicated to the establishment of 24 distinctive case studies, representing the six aforementioned types of residential blocks. It involves an in-depth analysis of their solar radiation potential, encompassing aspects such as the BIPV installation ratios, BIPV installation potential, BIPV power generation potential, as well as the SWH installation potential and SWH heating. Part four offers specific research recommendations tailored to each individual case.

2. Thinking and Methodologies

2.1. Framework Ideas

To comprehensively investigate the pivotal factors influencing solar energy utilization, this study initiated a multi-phase research approach: An initial survey encompassing 24 representative residential blocks was conducted to collect data regarding the typical layout patterns of residential blocks in Wuhan. These data provided fundamental insights into the spatial configurations of residential blocks within different regions of the study. Subsequently, 3D modeling software tools, including Rhinoceros, GH, and the Ladybug plug-in, were employed to simulate the solar potential. By leveraging these tools, the solar energy receiving capacity of diverse residential blocks could be effectively simulated and analyzed. During the third phase, an in-depth analysis of the simulation data was conducted to investigate a range of factors influencing solar radiation. These factors included parameters such as the floor area ratio, building density, average height, and spatial layout. The primary objective of this phase was to establish the correlations between these factors and the potential for photovoltaic power generation. Drawing from the results of each data analysis, we formulated research strategies tailored to different types of residential blocks. These categories included LFARLD, LFARHD, MFARLD, MFARHD, HFARLD, and HFARLD. These strategies are intended to offer precise guidance for the comprehensive utilization of BIPV and SWH technologies within mass housing areas, presenting practical and feasible measures and recommendations. By completing these five research phases, this study provides an in-depth understanding of the BIPV potential and SWH within Wuhan’s residential blocks in Figure 1. Importantly, it offers pragmatic and effective guidance strategies. These comprehensive strategies are poised to facilitate the advancement and adoption of renewable energy solutions within urban settings, ultimately contributing to the attainment of sustainable urban development objectives [32].

2.2. Sample Selection and Analysis

Wuhan, representing a typical region in a hot summer and cold winter zone of China, was the primary focus of this study. Specifically, the study’s scope centered on the main urban area of Wuhan, which encompasses a total land area of 678 km². Within this area, residential blocks occupy approximately 147.88 km². To delineate the characteristics of residential areas, this study employed BD and FAR as the principal indicators for classifying residential areas into high, medium, and low categories (

Table 1. Characterization of the spatial distribution of different types.

Habitat Category	Area/km2	Percentage/%	Regional Description
LFARLD	0.36	0.24	Distributed along the lakeshore, characterized by a favorable ecological environment, and primarily comprising villa districts.
LFARHD	1.47	0.99	Small, clustered groups, point distribution, concentrated in the historical city center of Wuchang and the Qing tai Annex community in Hanyang. These areas were constructed in the earlier years, exhibiting a high building density and a lower proportion of green spaces.
MFARLD	17.62	11.92	Scattered distribution, primarily concentrated in the vicinity of Ink Lake and South Lake, mainly comprising newer residential blocks characterized by a higher-quality living environment.
MFARHD	13.73	9.28	Circular and ribbon-like distribution patterns prevail, with circular layouts being predominant in Hankou and ribbon-like configurations occurring along the Second Ring Road in Wuchang and Hanyang. The architectural typology is predominantly multi-rise, featuring a mix of high-rise structures.
HFARLD	30.11	20.36	A clustered distribution is primarily observed in newly constructed residential blocks situated outside the Second Ring Road. These areas predominantly consist of high-rise buildings arranged in a point-like pattern, offering a superior living environment.
HFARHD	29.45	19.91	It is distributed in a ring and belt configuration, characterized by low-rise, multi-rise, or high-rise building structures, featuring a high building density, high population density, and limited open spaces.

). These classifications serve to elucidate features that convey varying levels, textures, and environmental qualities. Within the urban area, these various categories of residential block spaces are distributed in roughly equal proportions. However, as one moves farther away from the old city center, their distribution gradually diminishes, forming a pattern of polycentric zoning. It is noteworthy that a substantial percentage of spaces (95.6%) within the primary urban area exhibit an FAR that exceeds 1.5, with 63.4% of these spaces surpassing an FAR of 2.5. This trend underscores a clustered high-density distribution characteristic within the main urban area, emphasizing the efficient utilization of spatial resources. This distribution pattern highlights the general high FAR characteristics of residential block spaces within the main urban area, showing the utilization characteristics of spatial resources. By examining the residential block density and building FAR within the main urban area, we gain insights into the spatial characteristics and ground-level layout of urban development. These insights are instrumental in facilitating the city’s future sustainable development. Moreover, given Wuhan’s designation as a region in China within a hot summer and cold winter zone, the findings of these studies also hold practical significance by providing guidance and data for the planning and development of residential blocks in similar climatic regions.

Figure 2 shows that the analysis of the comprehensive layout characteristics revealed that the distribution of residential blocks in the primary urban area of Wuhan is exceptionally diverse, with high FAR residential blocks being predominant. Notably, the “high FAR, low-rise” type of residential block stood out as a distinctive and prevalent category. These residential blocks typically exhibit a high population density and building density, emphasizing the compactness of the living spaces. Collectively, mid-rise and high-rise residential blocks offer high-quality living environments throughout the city. Conversely, “low FAR, high-rise” residential blocks are mainly situated in older urban areas, including some designated historic preservation zones. These residential blocks are characterized by lower construction ratios and relatively taller building heights, preserving historical elements and traditions. Various types of residential blocks are widely distributed across the primary urban area of Wuhan. High-rise residential blocks typically embody contemporary architectural styles, mid-rise and high-rise residential blocks contribute to high-quality living environments, and low-rise residential blocks are primarily located in the older city areas, often carrying historical preservation value. The diversity among these residential block types, spanning the urban scale and historical contexts, enriches the development of Wuhan’s primary urban area. Through researching six types of residential blocks, 24 representative residential blocks were quantified as the study sample (

Table 2. Sample of 24 residential blocks.

Type of Space	Case 1		Case 2	Case 3	Case 4
LFARLD	Residential Block Patterns
	SL	combinatorial	determinant	faulty presentation	determinant
	FAR	1.34	1.14	1.36	1.37
	BD (%)	16	14	19	17
	ABH (m)	31	24	21	24
LFARHD	Residential Block Patterns
	SL	combinatorial	determinant	determinant	faulty presentation
	FAR	1.38	1.39	1.44	1.48
	BD (%)	20	20	23	25
	ABH (m)	15	21	49	12
MFARLD	Residential Block Patterns
	SL	combinatorial	faulty presentation	determinant	combinatorial
	FAR	2.37	1.93	2.28	1.69
	BD (%)	16	18	17	11
	ABH (m)	64	68	41	20
MFARHD	Residential Block Patterns
	SL	determinant	encompassing	combinatorial	encompassing
	FAR	2.37	2.3	2.19	2.1
	BD (%)	28	30	27	35
	ABH (m)	31	27	114	18
HFARLD	Residential Block Patterns
	SL	determinant	encompassing	determinant	encompassing
	FAR	2.68	2.74	3.84	3.87
	BD (%)	9	18	11	15
	ABH (m)	117	57	125	117
HFARHD	Residential Blocks Patterns
	SL	encompassing	encompassing	determinant	determinant
	FAR	2.68	2.8	3.16	3.5
	BD (%)	25	28	28	25
	ABH (m)	24	36	33	46

), and an in-depth examination of their layout characteristics and patterns was conducted. These findings offer valuable references and guidance for the utilization of solar energy in urban contexts.

2.3. Model Creation and Parameter Setting

Each layout pattern analyzed in the parametric study adhered to the relevant requirements outlined in Document 248 of “Wuhan Construction Engineering Planning and Management Technical Provisions” [33] and “the Wuhan Residential Daylight Distance Specification” [34]. These requirements encompass various aspects, including building fire prevention, daylight distance, and other planning and design conditions. The design process included the GIS location of the residential area, obtaining accurate roof areas and floor area ratios, and creating a map of the area using Computer Aided Design (CAD) software version 2014, which was then imported into Rhinoceros. A radiation simulation was initiated by importing the Chinese Standard Weather Data (CSWD) into Rhinoceros. Then, a 3D model of the block was built. The solar radiation simulation of the building was carried out using Ladybird and Bee software version ladybug1.5, and the visualization results of the solar radiation intensity distribution on the building surface were obtained. In the simulation, the simulation period was set to 1 year, and the building surface was divided into a 2 × 2 m grid to calculate the annual accumulated solar radiation at each test point. The model of the residential area was measured in meters, and the building height was set at 3 m as the universal height setting obtained by researching the data from the residential area. At the same time, the distribution of building heights followed the principle of minimizing the obstructions between buildings. Additionally, the floor height of the buildings increased progressively from south to north. The simulation software’s parameter settings were configured as follows:

(1)

Meteorological file settings, specifically climatic conditions, play a pivotal role in determining the available solar radiation resources. This study conducted experiments to evaluate different meteorological files, and the findings indicated that the radiation values simulated using the CSWD meteorological file were closely aligned with the measured values. Consequently, in this study, the CSWD meteorological file was selected as the preferred choice [35];

(2)

Regarding the run cycle setting, it is essential to note that the final radiation value obtained in this study represents the annual average. Therefore, the simulation cycle spans one year, encompassing the period from 1 January to 31 December.

GH serves as a graphical algorithm editor that is seamlessly integrated with Rhinoceros’s 3D modeling tools, making it a popular choice among building professionals and students for parametric modeling. Numerous plug-ins are readily available to facilitate the requisite BIPV simulations [36]. Additionally, solar simulation tools such as Ladybug and Bee, which are designed for Rhinoceros and GH, were employed [37]. These tools are well-established and have undergone validation based on radiation data, having been used in prior research to simulate the solar resource availability [38]. When conducting radiation calculations, a substantial number of representative 3D residential blocks were meticulously modeled within Rhinoceros using GIS data. A simulation workflow was subsequently established using the Ladybird plugin for GH [39]. This workflow encompassed various EPW-validated models, enabling the simulation of the solar radiation distribution across selected representative residential block structures. EPW data are in a format used by Energy Plus, the U.S. Department of Energy’s open access professional weather analysis software. EPW validation is the process of confirming the accuracy and completeness of an EPW (EnergyPlus Weather) meteorological data file, while EPW synthesis is the process of generating or editing an EPW file to meet specific building performance simulation requirements. The estimation procedures were grounded in Rhinoceros-generated geometries, GH-derived input data, and EPW-synthesized climate data sourced from SWERA data. Upon the completion of modeling for both the buildings and their 3D urban surroundings, the necessary input parameters and data required for conducting solar irradiation simulations were determined. These included the Wuhan climate EPW dataset, a year-round analysis period, the average grid cell size used for the radiation analysis of the surfaces under scrutiny (roofs and façades), and vector data representing the true north direction. In cases where BIPV panels were simulated as frameless custom modules, they occupied approximately 90% of the surfaces in question. The total radiation values, as well as the radiation per unit area, are expressed in kilowatt-hours (kWh) and kilowatt-hours per square meter (kWh/m²).

2.4. Calculated Analysis of the Solar Energy Potential

2.4.1. Calculation of the Solar Radiation Thresholds and Radiation Potential

(1)

Solar radiation threshold

By referring to data published by the China General Social Survey (CCSS) in early 2019, it can be ascertained that the range for BIPV system installation lies between 3.5 and 6.5 Renminbi per Watt (RMW). In this study, we set the system installation cost, denoted as Csu, at 4 RMW/W, while establishing the annual system maintenance factor, denoted as RAn, at 2%. The parameter PD represents the power density of PV modules. Based on research findings regarding polycrystalline silicon BIPV module products from relevant domestic PV enterprises, we set the power density of polycrystalline silicon PV modules, represented as PD, at 270 W/m². By calculating the solar radiation thresholds, we derived the solar radiation thresholds for the PV system under different life cycles [40]. In the solar energy field, the life cycle of solar energy equipment usually includes the stages of manufacture, transportation, installation, use, maintenance, and disposal, which becomes the life cycle of solar energy. The solar radiation threshold usually refers to a minimum level of light intensity, i.e., the light intensity must reach a specific value for solar equipment to operate properly or perform optimally, allowing us to analyze the relationship between these thresholds and the system’s life cycle [41,42]. In this study, the radiation threshold of solar PV was calculated according to the current situation in Wuhan. First, Formula (2) for the solar radiation threshold t was obtained based on the input–output balance Equation (1) for the PV system over the whole life cycle.

$$C_{sys}=t\times {\eta }_i\times K\times C_{ele}\times {{\displaystyle \sum }}_1^N{(1-R_d)}^{N-1}$$

(1)

$$t=\frac{C_{sys}}{{\eta }_i\times K\times C_{ele}\times {{\displaystyle \sum }}_1^N{(1-R_d)}^{N-1}}$$

(2)

where $N$ denotes the life cycle of the PV system, ${\eta }_i$ is the photovoltaic conversion efficiency of the PV system, and $R_d$ denotes the decay rate of the PV system. Polycrystalline silicon PV modules were used in this study, and according to research conducted on the market, their conversion efficiency ${\eta }_i$ was set to 19.1%, while the attenuation rate $R_d$ was set to 1.4%. $K$ is the integrated efficiency coefficient, which is a comprehensive evaluation parameter that is used to measure the performance of the PV system, and according to related research by Kumar et al., in this study the $K$ value was set to 86% [43]. $C_{ele}$ is the feed-in tariff, which is closely related to the PV subsidy policies of national and local governments [44]. According to the subsidies of national and Wuhan-related policies, we set it to 0.9861 RMB/Kwh.

Thus, based on the calculation of the solar radiation thresholds, this study obtained the solar radiation thresholds of PV systems in different life cycles in order to analyze the relationship between the thresholds and the systems’ life cycles (Figure 3). Each symbolic point in the figure indicates a different solar radiation threshold corresponding to a different cycle. The results showed that the solar radiation threshold gradually decreased with an increase in the system’s life cycle. In this study, a system’s life cycle of 20 years was used as the standard to determine the solar radiation threshold t in Wuhan. The solar radiation threshold t in Wuhan is 530.6 kWh/m²∙y [45].

(2)

Solar radiation potential

The radiation values for the buildings within the selected residential area were initially generated through software simulations. Subsequently, the radiation potential was computed based on the solar radiation threshold of 530.6 kWh/m²∙y. The resulting percentage was obtained by subtracting the solar radiation threshold from the average annual radiation for instances where the radiation exceeded this threshold.

2.4.2. BIPV Calculation Analysis

(1)

BIPV installation potential

According to the national specification “Design Code for Photovoltaic Power Plants” [39] for the calculation model of the BIPV installation potential, the BIPV installation potential, represented by $P_{roof}$, $P_{facade}$, and $P,$ was calculated as follows.

$$C_{ri}=C_{ra}\times C_f\times C_{st}{\times C}_S\times C_{rt}\times C_{cov}$$

(3)

$$C_{fi}=C_w\times C_{sf}$$

(4)

$$P_{roof}=\frac{A_r\times C_{ri}\times A_{r>t}}{A_b}$$

(5)

$$P_{facade}=\frac{A_f\times C_{fi}\times A_{f>t}}{A_b}$$

(6)

$$P=P_{roof}+P_{facade}$$

(7)

The BIPV installation potential refers to the proportion of the available BIPV area on the building surface [46]. When calculating the roof installation coefficient, $C_{ra}$ is the roof area coefficient, which is the ratio of the roof area to the floor area, and has a value of 0.9. $C_f$ is the facility coefficient, which indicates the proportion of the roof that is not occupied by HVAC equipment, chimneys, etc., and has a value of 0.7. $C_{st}$ is the solar thermal coefficient, which refers to the proportion of the roof that is not occupied by the solar hot water system. Since almost all residential neighborhoods in China have solar hot water systems installed, the $C_{st}$ was set to 0.9. $C_{rt}$ is the roof coefficient. In this research, the $C_{rt}$ was set to 1 for flat-roofed buildings and 0.5 for sloped-roofed buildings. $C_{cov}$ is the effective area coefficient of the BIPV modules, i.e., the ratio of the surface area of the BIPV modules to the surface area of the roof. It takes into account the gap between BIPV modules to avoid reflections caused by mutual shielding. The $C_{cov}$ was set to 0.53 [47]. For the calculation of the façade mounting coefficient, it is mainly affected by the window opening coefficient ($C_w$) and the structural coefficient ($C_{sf}$). They represent the proportion of the area that is not occupied by doors, windows, balconies, structures, etc. We set the $C_w$ and the $C_{sf}$ to 0.78 and 0.9, respectively.

For $P,P_{roof}$, $R_{facade}$, and $P$ represent the BIPV installation potential of the roof, façade, and cell, respectively. $A_r$ and $A_f$ denote the areas of the roof and façade, respectively, and $C_{ri}$ and $C_{fi}$ denote the roof and façade installation factors. $A_{r>t}$ and $A_{r>t}$ are the proportions of the roof and façade whose radiation values exceed a predetermined threshold. The definition of the radiation thresholds makes it possible to evaluate the BIPV-available area of a building per unit of the site area, allowing parallel comparisons between different types of residential blocks.

(2)

BIPV installation ratio

Based on the calculation of the BIPV installation potential, the BIPV installation ratio for each building surface was further calculated. This indicates the mounting positions of BIPV modules on different surfaces and can be calculated as follows:

$$R_{roof}=\frac{P_{roof}}{A_{roof}}$$

(8)

$$R_{facade}=\frac{P_{facade}}{A_{facade}}$$

(9)

where $R_{roof}$ and $R_{facade}$ denote the BIPV installation ratio of the roof and the façade; $P_{roof}$ and $P_{facade}$ denote the BIPV usable area of the roof and the façade; and $A_{roof}$ and $A_{facade}$ denote the BIPV usable area of the roof and the façade. The façade is the area of the roof and the façade.

(3)

BIPV power generation potential

According to the national specification “Design Code for Photovoltaic Power Plants” [39] for the calculation model of the BIPV system power generation, the formula for the BIPV system power generation ($E_p$) can be obtained as follows:

$$E_p=H_A\times A_{pv}\times {\eta }_i\times K\times {(1-R_d)}^{N-1}$$

(10)

where $H_A$ is the annual cumulative solar radiation value of the building surface, $A_{pv}$ is the mountable area of the BIPV module, and N is the life cycle of the BIPV system. ${\eta }_i$, K [43], and $R_d$ are the photovoltaic system photovoltaic conversion efficiency, the integration period efficiency coefficient, and the decay ratio of the BIPV system, respectively, which were set to 19.1%, 86%, and 1.4% [25] in the previous section [48]. As a result, the power generation capacity of the BIPV system could be obtained. On this basis, the BIPV technical potential of the building was evaluated in terms of the average annual power generation of the BIPV system per unit of land area in order to compare the BIPV power generation of different types of residential blocks in parallel.

2.4.3. SWH Calculations

(1)

SWH Installation Potential

The solar energy utilization potential solar energy utilization potential evaluation involves the calculation of the average annual solar energy production on the surface of the building on the basis of the comprehensive consideration of the installation potential of solar energy, the radiation potential, and the efficiency of the system. In this research, the efficiency of SWH was taken as 50% [49].

(2)

SWH heating

According to the national specification “Technical standard for solar water heating system of civil buildings” [50] for the calculation model of the SWH solar collector, the formula for the SWH solar collector $Q_p$ can be obtained as follows:

$Q_p$ is the heat available for hot water from SWH systems throughout the year [51] in GWh/y; $R$ is the total annual amount of solar radiation received by solar collectors per unit area in GWh/m²; $A_c$ is the SWH collector area in m² [52]; $\beta$ is the annual utilization factor of solar radiation, where β = 69.9% [53]; and ${\eta }_s$ is the SWH system efficiency, where ${\eta }_s$ = 50% [49]. Their calculation formula is as follows:

$$Q_p=R\times A_c\times \beta \times {\eta }_s$$

(11)

The amount of heat that can be supplied by an SWH system in a residential block throughout the year, as calculated by the formula described above, can be applied to the optimal installation strategy for the amount of heat produced by roof-mounted and façade-mounted installations in residential blocks.

3. Results and Analysis

3.1. Solar Radiation Values

3.1.1. Calculations of Solar Radiation in Residential Blocks

The annual mean solar radiation data from Wuhan (Figure 4) were used as the basis of the study. A software simulation study was carried out for 24 study samples, and the solar radiation data in the study were typical annual average solar radiation data.

The results of the analysis of solar radiation on roofs and façades across various types of residential blocks (Figure 5) depicted the annual cumulative solar radiation received by building surfaces. As indicated in

Table 3. Solar radiation potential.

Building Surface Radiation Potential (%)
Type of Space		Case 1	Case 2	Case 3	Case 4
LFARLD	Roof	56.1	118.2	58.2	49.7
	South façade	108.1	58.5	106.1	92.2
	North façade	7.9	17.0	10.8	13.9
	West façade	68.2	49.7	73.2	62.0
	East façade	86.2	52.6	88.1	79.8
LFARHD	Roof	73.7	51.8	147.7	35.7
	South facade	115.1	73.6	69.4	121.8
	North facade	4.7	31.6	12.8	17.5
	West facade	105.3	65.1	68.5	108.2
	East facade	70.9	48.3	73.7	108.2
MFARLD	Roof	86.9	34.6	20.3	50.2
	South façade	56.7	52.3	96.1	83.9
	North façade	54.7	1.1	52.1	1.1
	West façade	69.4	76.9	153.3	68.1
	East façade	76.9	80.9	118.1	81.2
MFARHD	Roof	81.7	106.9	23.4	81.8
	South façade	55.1	32.1	148.8	28.9
	North façade	26.7	14.5	41.3	16.4
	West façade	71.5	41.9	87.3	28.4
	East façade	103.9	43.5	111.6	26.5
HFARLD	Roof	49.3	100.0	58.9	100.0
	South façade	50.5	41.7	107.4	74.1
	North façade	95.3	43.1	1.5	60.9
	West façade	92.5	61.1	107.6	81.5
	East façade	102.2	68.4	67.5	60.9
HFARHD	Roof	48.1	70.5	111.6	47.7
	South façade	73.1	57.9	61.2	113.4
	North façade	35.9	70.3	6.4	32.2
	West façade	75.1	100.2	67.6	95.8
	East façade	102.4	117.2	67.5	106.1

, the average annual cumulative solar radiation on roofs within different residential areas ranged from 872.08 KWH/m²∙y to 1281.44 KWH/m²∙y. However, when considering the façades of buildings, the solar radiation was attenuated, resulting in an average annual cumulative solar radiation ranging from 946.99 KWH/m²∙y to 1026.38 KWH/m²∙y. Among the residential blocks, the HFARLD area exhibited the highest overall solar radiation values, with average annual cumulative solar radiation values of 1281.44 KWH/m²∙y for roofs and 1031.15 KWH/m²∙y for façades. Conversely, the MFARLD area displayed relatively lower solar radiation values, with average annual cumulative solar radiation values of 872.08 KWH/m²∙y for roofs and 959.01 KWH/m²∙y for façades.

Figure 6 and Figure 7 illustrate the variation in solar radiation across LFARLD, LFARHD, MFARLD, MFARHD, HFARLD, and HFARHD blocks. In LFARLD regions, roof solar radiation contributed 57% of the total solar radiation, while in HFARLD areas, façade solar radiation comprised 76% of the total solar radiation. These findings suggest that LFARLD regions have a greater solar potential on roofs, whereas HFARLD regions exhibit higher solar potential on elevations. Regarding a comparison among façades, the southern façade boasted the highest solar radiation, ranging from 906.46 KWH/m²∙y to 1102.67 KWH/m²∙y. Following closely was the west elevation, with solar radiation levels ranging between 902.99 KWH/m²∙y and 1152.96 KWH/m²∙y. In contrast, the north elevation exhibited lower solar radiation, ranging from 634.94 KWH/m²∙y to 978.26 KWH/m²∙y and is typically not a primary consideration when assessing the solar potential.

3.1.2. Solar Radiation Potential

The values of the solar radiation quantities used to simulate the buildings in the selected residential blocks were first chosen, and then the radiation potential was calculated based on the solar radiation threshold value of 530.6 kWh/m²∙y. By subtracting the solar radiation threshold from the annual average radiation, the percentage of radiation above the solar threshold was obtained. This gave us the solar potential values of the residential blocks studied below.

The results of the analysis of the solar radiation potential on roofs and façades across different types of residential blocks (Table 3) indicated the proportion of the annual cumulative solar radiation values on building surfaces that exceeded the threshold value. The findings from this study (Figure 8 and Figure 9) revealed that the highest solar radiation potential was observed in residential blocks characterized by LFARHD, with more than half of the rooftop solar radiation potential captured in both low- and high-rise residential blocks.

Conversely, Figure 10 showed that residential blocks with HFARHD primarily absorb the solar radiation potential through their building façades. Specifically, LFARLD residential blocks exhibited an overall solar radiation potential of 61%, with rooftops contributing 66% of this potential. HFARHD blocks exhibited an overall solar radiation potential of 70%, of which 71% was attributed to the façade. In contrast, MFARHD residential blocks showed a lower solar radiation potential, with 55% attributed to low-rise buildings and 51% to the façade. This disparity can be explained by the minimal shading impact between buildings in low-rise residential blocks, leading to increased solar radiation above the threshold on building surfaces and thus an overall boost in the solar radiation potential. On the other hand, medium- and high-rise residential blocks experience shading from neighboring buildings and natural solar radiation attenuation on vertical surfaces, resulting in a reduced area of building surfaces that surpass the solar radiation threshold.

3.1.3. BIPV Installation Ratio

According to Equations (8) and (9), the BIPV installation rate on the roofs and façades of the residential blocks could be calculated, and, therefore, the optimal installation surface for BIPV could be derived.

Table 4. BIPV Installation Ratio.

BIPV Installation Ratio (%)
Type of Space		Case 1	Case 2	Case 3	Case 4
LFARLD	Roof	100.0	100.0	100.0	100.0
	South façade	91.7	99.6	74.6	90.3
	North façade	0.0	0.0	0.0	0.0
	West façade	84.5	30.6	86.3	66.8
	East façade	0.6	0.7	13.2	1.5
LFARHD	Roof	100.0	100.0	100.0	100.0
	South façade	51.8	50.1	53.1	65.5
	North façade	0.0	0.0	0.0	0.0
	West façade	55.5	51.8	65.4	61.3
	East façade	0.0	0.0	0.0	1.4
MFARLD	Roof	98.9	100.0	100.0	100.0
	South façade	41.6	23.5	43.1	29.3
	North façade	0.0	0.0	0.0	0.0
	West façade	75.5	52.4	83.5	79.5
	East façade	0.0	0.0	0.0	0.0
MFARHD	Roof	100.0	100.0	100.0	100.0
	South façade	45.6	37.1	71.1	46.1
	North façade	0.0	0.0	0.0	0.0
	West façade	66.7	47.7	24.3	45.3
	East façade	7.7	0.0	20.0	0.0
HFARLD	Roof	100.0	100.0	98.7	100.0
	South façade	25.1	58.9	57.0	45.2
	North façade	0.0	0.0	0.0	0.0
	West façade	53.2	46.9	54.0	53.8
	East façade	0.2	0.3	5.0	0.0
HFARHD	Roof	97.8	100.0	100.0	98.9
	South façade	54.6	59.9	58.1	45.8
	North façade	0.0	0.0	0.0	0.0
	West façade	23.4	52.9	54.8	53.4
	East façade	0.0	0.3	5.3	0.0

and Figure 11 present the BIPV installation ratios on surfaces of various types of residential blocks, representing the proportion of each building surface area with a solar radiation value exceeding the threshold value of 530.6 KWH/m²∙y. Across all residential block types, the average roof BIPV installation ratio exceeded 99%. Notably, the south-facing façades exhibited a significant BIPV installation potential, with an average BIPV installation ratio of 34% or more for all residential block types (Figure 12). Remarkably, the LFARLD south façades achieved an exceptionally high average installation ratio of 89.5%. The west façades also demonstrated a substantial BIPV installation potential, with an average BIPV installation ratio that exceeded 46% for all residential block types. Notably, the MFARLD façades reached an average installation ratio of 72.73%. Conversely, the BIPV installation ratio on the north façades of nearly all residential blocks was zero. A limited number of residential blocks possessed some BIPV-available area on their east façades, but the average BIPV installation ratio remained below 4.0% for all such cases (Figure 13).

In summary, the south and west façades of residential blocks exhibited a favorable BIPV installation potential, while the east and north façades are unsuitable for BIPV module installation due to their shading and orientation. Additionally, it was observed that, for south-facing façades, LFARLD residential blocks had higher BIPV installation ratios, and these ratios tended to decrease as the building height increased, resulting in increased shading between buildings. In contrast, for west-facing façades, residential blocks with MFARL displayed higher west façade BIPV installation ratios.

3.1.4. BIPV Installation Potential and BIPV Power Generation Potential

This study presents the results of an analysis conducted on the BIPV installation potential and BIPV generation potential of roofs and façades to enhance the BIPV availability on building surfaces per unit area. The roof and façade installation factors can be calculated from Equations (3) and (4), and the calculated data can be applied to Equations (5) and (6) to calculate the roof and façade BIPV installation potentials of the residential blocks. Based on the calculated BIPV installation potential values, it is possible to determine the optimal PV installation strategy for roofs and façades in residential blocks.

The findings, as summarized in

Table 5. BIPV installation potential and BIPV power generation potential.

		BIPV Installation Potential (m2)				BIPV Generation Potential (KWH/m2·y)
Type of Space		Case1	Case2	Case3	Case4	Case1	Case2	Case3	Case4
LFARLD	Roof	0.02	0.05	0.03	0.02	8.34	17.70	4.42	3.14
	Façade	0.36	0.28	0.36	0.24	11.33	52.18	53.12	34.66
	Residential block	0.38	0.33	0.39	0.26	19.67	69.88	57.54	37.80
LFARHD	Roof	0.04	0.03	0.11	0.03	5.85	4.56	28.31	3.47
	Façade	0.25	0.11	0.16	0.29	30.94	11.72	18.29	35.25
	Residential block	0.29	0.14	0.27	0.31	36.79	16.28	46.60	38.72
MFARLD	Roof	0.04	0.02	0.01	0.02	8.05	2.33	1.01	2.92
	Façade	0.12	0.22	0.33	0.36	12.12	22.55	35.68	46.58
	Residential block	0.16	0.24	0.34	0.38	20.17	24.88	36.69	49.50
MFARHD	Roof	0.07	0.11	0.02	0.09	10.86	31.90	2.05	17.68
	Façade	0.70	0.36	0.73	0.27	98.30	53.58	113.36	32.30
	Residential block	0.77	0.47	0.75	0.36	109.16	85.48	115.41	49.98
HFARLD	Roof	0.01	0.07	0.02	0.07	1.37	18.16	2.92	20.08
	Façade	1.08	0.94	1.37	1.46	189.22	143.11	216.75	248.87
	Residential block	1.09	1.01	1.39	1.53	190.59	161.27	219.67	268.95
HFARHD	Roof	0.04	0.06	0.10	0.04	5.53	7.75	22.47	5.23
	Façade	0.32	0.48	0.68	0.38	39.59	52.95	101.23	42.18
	Residential block	0.36	0.54	0.78	0.42	45.12	60.70	123.70	47.41

, revealed a correlation between the BIPV installation potential and the solar radiation potential, with high-rise residential blocks exhibiting a greater installed BIPV capacity compared to low-rise residential blocks. The variation in the roof BIPV installation potential among residential blocks was relatively minor, with fluctuations primarily ranging from 0.03 m² to 0.11 m². Notably, the prevalence of low BIPV installation potential on the roofs of medium- and high-rise residential areas was observed in various types of residential blocks. This was attributed to the substantial differences in individual buildings within low-rise residential blocks, which exhibit higher building densities and, consequently, greater BIPV installation potential on their roofs. However, distinctions in the façade BIPV installation potential emerged across different types of residential blocks. High-rise residential areas consistently demonstrated higher BIPV installation potential than their low-rise counterparts. Specifically, high-rise residential areas characterized by HFARLD residential blocks exhibited the highest BIPV installation potential of 1.37 m², including a façade BIPV installation potential of 1.46 m². Conversely, LFARLD residential blocks exhibited BIPV installation potentials ranging from 0.26 m² to 0.38 m², with BIPV roof installation potentials ranging from 0.02 m² to 0.05 m² (Figure 14).

The results of the analysis pertaining to the BIPV roof potential, representing the average annual BIPV power generation per unit land area across various categories of residential block instances, were as follows. Based on Equation (7), the power generation potential of the roof and façade BIPV in residential blocks could be calculated, thus providing clear power generation data for PV power generation in residential blocks. The overall simulation outcomes revealed minor disparities in the average roof technical potential among different categories of residential block instances, with fluctuations typically ranging from 3.14 to 28.31 KWH/m²∙y. In contrast, there was a notable increase in the façade BIPV potential of residential blocks, which was amplified in tandem with the building height. Specifically, the highest façade BIPV potential was observed in the HFARLD zone, with values fluctuating between 189.22 and 248.87 KWH/m²∙y. Conversely, the lowest façade BIPV potential was identified in the low-rise residential block, where values ranged from 11.33 to 53.12 KWH/m²∙y (Figure 15).

3.2. Parameter Patterns Influencing the BIPV Utilization Potential in Residential Block

The results of the analysis pertaining to the BIPV roof potential, representing the average annual BIPV power generation per unit land area across various categories of residential block instances, were as follows. The overall simulation outcomes revealed minor disparities in the average roof technical potential among different categories of residential block instances, with fluctuations typically ranging from 3.14 to 28.31 KWH/m²∙y. In contrast, there was a notable increase in the façade BIPV potential of residential blocks, which was amplified in tandem with the building height. Specifically, the highest façade BIPV potential was observed in the HFARLD zone, with values fluctuating between 189.22 and 248.87 KWH/m²∙y. Conversely, the lowest façade BIPV potential was identified in the low-rise residential block, where values ranged from 11.33 to 53.12 KWH/m²∙y (Figure 16, Figure 17, Figure 18 and Figure 19).

Based on the results of the regression analysis, shown in

Table 6. p-Values of the linear regression relationships between the morphological parameters and solar power potential of the roof, façade, and residential blocks.

Building Surface	FAR		BD		ABH		SL
	R2	p	R2	p	R2	p	R2	p
Roof	0.949	0.026	0.758	0.129	0.289	0.463	0.259	0.281
Façade	0.172	0.585	0.106	0.674	0.702	0.162	0.704	0.147
Residential block	0.747	0.04	0.71	0.017	0.75	0.029	0.503	0.167

, which include the correlation coefficient (R²) and significance analysis (p-value), we were able to discern the parameters that exert the most substantial impacts on the solar energy utilization potential within the residential blocks. The R² value indicates the fit of the analytical simulation, as shown in Table 6, where FAR has an R² value of 0.949. Thus, we can understand that the relationship between FAR and the potential of BIPV on the roofs of residential blocks is 94.9%. p-values of less than 0.05 or 0.01 indicate that there is an influential relationship between FAR and residential blocks. Our calculations revealed that FAR, BD, and ABH were the parameters with the most pronounced influences on the solar energy utilization potential across the entire residential block. These three morphological parameters exhibited varying degrees of influence on the BIPV technical potential of both roofs and façades within the neighborhood. However, they all demonstrated a correlation with the technical potential of the overall neighborhood that exceeded 70%, and their respective p-values were less than 0.05, signifying statistical significance. The correlation between SL and the technical potential was 50%. Furthermore, when FAR, ABH, and the building layout varied across different residential block categories, the technical potential experienced a corresponding increase. Conversely, as BD escalated, the roof’s technical potential rose, while the overall residential block’s technical potential also increased accordingly.

3.3. SWH Calculations

3.3.1. SWH Installation Potential

This study aimed to enhance the SWH installation potential per unit area on building surfaces. Thus, we conducted an analysis of the SWH installation potential on both roofs and façades. Based on the calculated data for the solar radiation potential, BIPV and SWH were used for the same types of residential settlements, so the efficiency of SWH was taken as 50%; furthermore, Equations (3) and (4) use the same installation factor for roofs and façades. Therefore, the SWH installation potential per square meter on the roofs of the settlements and on each facade could be derived to give the optimal installation strategy for installing SWH. The study’s findings shown in

Table 7. SWH Installation Potential.

SWH Installation Potential (m2)
Type of Space		Case1	Case2	Case3	Case4
LFARLD	Roof	0.02	0.05	0.03	0.02
	South façade	0.21	0.02	0.40	0.03
	West façade	0.10	0.01	0.13	0.02
	East façade	0.14	0.01	0.15	0.02
	Residential block	0.47	0.09	0.71	0.09
LFARHD	Roof	0.04	0.03	0.11	0.03
	South façade	0.23	0.07	0.11	0.30
	West façade	0.05	0.06	0.05	0.07
	East façade	0.08	0.03	0.04	0.07
	Residential block	0.4	0.19	0.31	0.47
MFARLD	Roof	0.04	0.02	0.01	0.02
	South façade	0.67	0.84	0.29	0.24
	West façade	0.78	0.99	0.10	0.04
	East façade	0.86	1.06	0.15	0.06
	Residential block	2.35	2.91	0.55	0.36
MFARHD	Roof	0.07	0.11	0.02	0.09
	South façade	0.10	0.08	0.19	0.09
	West façade	0.08	0.04	0.11	0.04
	East façade	0.09	0.05	0.08	0.05
	Residential block	0.34	0.28	0.4	0.27
HFARLD	Roof	0.01	0.07	0.02	0.07
	South façade	0.16	0.13	0.21	0.23
	West façade	0.09	0.13	0.15	0.17
	East façade	0.10	0.11	0.09	0.13
	Residential block	0.36	0.44	0.47	0.6
HFARHD	Roof	0.04	0.06	0.10	0.04
	South façade	0.28	0.32	0.31	0.05
	West façade	0.09	0.41	0.09	0.01
	East façade	0.06	0.35	0.09	0.02
	Residential block	0.47	1.14	0.59	0.12

and Figure 20 revealed a positive correlation between the SWH installation potential within residential blocks and their solar radiation potential. Specifically, MFARLD residential blocks exhibited a higher SWH installation potential. The variation in the roof SHW installation potential among different residential blocks was relatively insignificant, with values fluctuating between approximately 0.03 m² and 0.06 m². In contrast, there was a substantial discrepancy in the façade SWH installation potential across residential areas, ranging from 0.25 m² to 1.52 m².

Notably, MFARLD residential block areas exhibited the highest SWH façade installation potential of 1.52 m². Among the different façades, the south-facing ones possessed the highest installation potential compared to the other façade orientations, followed by the east-facing façades, which had a lower potential, while the north-facing façades were not considered to have any installation potential. For LFARLD and LFARHD residential areas, the range of solar water heater façade installation potential values spanned from 0.09 m² to 0.47 m², with corresponding solar water heater roof installation potential values ranging from 0.02 m² to 0.11 m². MFARLD and MFARHD residential areas exhibited an SWH installation potential range from 0.32 m² to 1.54 m², coupled with an SWH roof installation potential range spanning from 0.32 m² to 1.54 m². Finally, HFARLD and HFARHD residential areas had an SWH installation potential range of 0.46 m² to 0.58 m², alongside an SWH roof installation potential ranging from 0.01 m² to 0.17 m² (Figure 21 and Figure 22).

3.3.2. SWH Quantity

This study was conducted to enhance the efficiency of water heating through SWH on building surfaces per unit area. According to Equation (11), the efficiency of heating water using SWH on the roofs of the residential blocks and on each façade could be calculated. Therefore, the water heating capacity of the solar water heaters on the roof and façade was analyzed, so that we could provide the optimal installation strategy for SWH in the residential blocks. The findings of the study (

Table 8. SWH floor area of water heated by solar water heaters.

SWH Building Average Annual Water Heating (GWh/y)
Type of Space		Case 1	Case 2	Case 3	Case 4
LFARLD	Roof	5.81	38.21	9.55	6.78
	South façade	81.17	9.43	171.25	14.12
	West façade	31.21	4.28	45.87	7.54
	East façade	48.40	4.43	58.03	8.64
	Residential block	166.59	56.35	284.70	37.08
LFARHD	Roof	12.63	9.85	61.12	7.49
	South façade	89.45	27.18	39.51	121.55
	West façade	18.58	21.87	17.85	26.64
	East façade	24.86	9.55	14.80	26.65
	Residential block	145.52	68.45	133.28	182.33
MFARLD	Roof	17.38	5.03	2.18	6.31
	South façade	233.07	240.10	99.36	96.94
	West façade	299.96	329.86	43.57	14.50
	East façade	349.13	361.22	56.74	23.80
	Residential block	899.54	936.21	201.85	141.55
MFARHD	Roof	23.46	68.87	4.43	38.16
	South façade	28.61	25.40	78.80	24.25
	West façade	25.31	14.32	35.19	10.72
	East façade	33.82	18.22	28.59	13.13
	Residential block	111.20	126.81	147.01	86.26
HFARLD	Roof	2.95	39.20	6.29	43.36
	South façade	64.21	38.60	88.53	87.47
	West façade	35.53	45.34	63.32	68.00
	East façade	41.68	40.53	30.05	44.95
	Residential block	144.37	163.67	188.19	243.78
HFARHD	Roof	11.94	16.73	48.52	11.29
	South façade	100.06	83.91	108.39	20.80
	West façade	38.39	179.68	33.02	3.80
	East façade	21.71	119.32	32.99	8.02
	Residential block	172.10	399.64	399.64	43.91

and Figure 23) indicated that MFARLD residential blocks exhibit a higher capacity for water heating through solar water heaters. The potential for SWH installation on roofs showed relatively minor variation across residential blocks, with values fluctuating within the range of approximately 7.27 GWh/y to 33.73 GWh/y. In contrast, there was a significant disparity in the potential for SWH installation on façades among different residential blocks, spanning from 56.36 GWh/y to 936.22 GWh/y. Specifically, MFARLD residential blocks possessed the highest water heating capacity from SWH on façades, reaching 936.22 GWh/y, while LFARLD blocks exhibited the lowest capacity at 56.36 GWh/y (Figure 24). This variation arose because façades are typically perpendicular to the ground, allowing them to capture solar radiation more effectively over different periods of the day. SWH areas on vertical surfaces receive prolonged exposure to sunlight, leading to the absorption of more solar energy. Unlike sloped roofs, which may reflect some sunlight, SWH systems installed on façades are generally more efficient at converting light energy into heat.

As depicted in Figure 25, the south elevation exhibited a range of water heating capacity values from SWH, varying between a minimum of 39.27 GWh/y and a maximum of 78.29 GWh/y, in comparison to other elevations. The east elevation demonstrated a lower range, fluctuating between 18.96 GWh/y and 45.51 GWh/y, while the potential for installations on the north elevation was not considered. The spectrum of solar water heater façade heating water capacities for LFARLD and LFARHD residential blocks ranged from 109.62 GWh/y to 121.10 GWh/y. Within this category, the SWH roof heating water capacity spanned from 15.08 GWh/y to 22.77 GWh/y. For MFARLD and MFARHD residential areas, the SWH façade heating water capacity fell within the range of 84.09 GWh/y to 537.06 GWh/y. Correspondingly, the SWH roof heating water capacity ranged from 7.72 GWh/y to 33.73 GWh/y. In HFARLD and HFARHD residential areas, the SWH façade heating water supply varied between 162.06 GWh/y and 187.53 GWh/y. Simultaneously, the SWH roof-mounted heating water supply ranged from 22.95 GWh/y to 22.12 GWh/y.

4. Conclusions

This study investigated the influences of morphological parameters on solar radiation in residential blocks in Wuhan and characterized the distribution of the solar potential in the environments of different residential blocks. Given the low-density layout and high-intensity development of China’s residential blocks, China’s residential communities have great potential for solar energy development. However, while BIPV and SWH technologies have been applied on a large scale, related theoretical studies are relatively insufficient. Therefore, it is necessary to study the solar potential of different residential block environments and provide design strategies for BIPV projects. We evaluated the solar radiation of 24 typical residential blocks, including six types of residential blocks. In this research, we investigated the effects of different parameter ranges on the BIPV installation ratio, BIPV installation potential, BIPV power generation potential, SWH installation potential, and SWH quantity. In the study, we propose the optimal installation strategies for BIPV integrated systems and SWH in each residential block.

(1)

Residential block layouts of various configurations exhibit distinct characteristics concerning their solar radiation potential, which can be quantified based on the proportion of the annual cumulative solar radiation values that exceed a specified threshold on building surfaces. Specifically, LFARLD residential blocks exhibited an overall solar radiation potential of 61%, with rooftops contributing 66% of this potential. HFARHD blocks exhibited an overall solar radiation potential of 70%, of which 71% was attributed to the façade. In contrast, MFARHD residential blocks showed a lower solar radiation potential, with 55% attributed to low-rise buildings and 51% to the façade. This phenomenon arises from the escalation in the building height, which fosters greater inter-building shading. When coupled with the natural attenuation of solar radiation on vertical surfaces, this leads to a reduction in the surface area exposed to solar radiation exceeding the threshold value.

(2)

When considering the factors influencing solar energy installation, it was evident that parameters such as FAR, BD, and ABH exert the most significant influences on the solar energy potential of the residential block. Their correlations with the overall solar energy potential of the entire floor area attained values of 75%, 71%, and 75%, respectively. Moreover, the correlation between the building SL and the solar energy potential was estimated to be 50%, with the row-type layout demonstrating the highest solar energy potential. It was evident that optimizing parameters such as the floor area ratio, building density, average building height, and building layout can lead to the maximization of the BIPV installation potential, BIPV installation ratio, and BIPV power generation potential.

(3)

In the context of the solar BIPV installation potential, HFARLD row-type residential blocks exhibited the highest BIPV potential among the high-rise residential blocks, closely followed by the MFARLD blocks. It is essential to emphasize that, with regard to the BIPV installation potential, façades accounted for 80% of the overall residential block potential, whereas rooftops contributed only 20%. Both south and west façades exhibited a BIPV installation ratio of approximately 34%. In terms of the BIPV generation capacity, HFARLD residential areas possess the greatest potential, with MFARLD residential areas ranking second. Regarding BIPV generation, façades contributed significantly, accounting for 87% of the total BIPV potential within the residential block, while rooftops contributed merely 13%. Consequently, high-rise residential areas should focus not only on the comprehensive installation of BIPV modules on roofs but also on harnessing the development and utilization of the BIPV power generation potential offered by the building façades.

(4)

Concerning the installation potential of SWH, MFARLD residential blocks exhibited the highest installation potential, closely followed by HFARHD blocks. In terms of the heating area covered by SWH, the installation potential for SWH on façades accounted for 77% of the total residential area, whereas rooftops contributed 23%. The installation potential for SWH on the south façade was consistent at approximately 35% in both cases. Regarding the amount of hot water supplied by SWH, MFARLD residential blocks offer the largest volume of solar hot water, followed by HFARHD residential blocks. SWH covers a considerable portion of the hot water area, with SWH on façades contributing to 71% of the entire residential block area, while rooftops contribute 29%. Therefore, when implementing SWH in residential block designs, it is crucial to fully exploit the potential of SWH for supplying hot water on both the roofs and façades of residential blocks.

The existing study was based only on the climatic conditions of Wuhan city, and future studies can improve the applicability of the study by quantifying the effects of different climatic conditions on the solar potential of the plot. The large number of BIPV modules and SWH installation schemes proposed in this study can be widely adopted, and these are particularly applicable to residential blocks. The established methodology and workflow provide a reliable reference for solar potential evaluations at the residential block scale. Depending on the building layout and parameters, the derived results can be used for solar potential utilization in existing residential blocks. However, the integration of solar energy with existing power generation systems and strategies to increase the PV penetration need to be further considered in future work. Thus, this study provides urban decision makers with prospects and starting points for renewable energy residential block applications.