Integration of Photovoltaic Systems for Energy Self-Sufficient Low-Rise Multi-Family Residential Buildings in Republic of Korea

Abstract

Globally, building energy consumption has been rising, emphasizing the need to reduce energy usage in the building sector to lower national energy consumption and carbon dioxide emissions. This study analyzes the applicability of photovoltaic (PV) systems in enhancing the energy self-sufficiency of small-scale, low-rise apartment buildings. The analysis is based on a case study using Republic of Korea’s Zero-Energy Building Certification System. By employing the ECO2 simulation program, this research investigates the impact of PV system capacity and efficiency on the energy self-sufficiency rate (ESSR). A series of parametric analyses were carried out for various combinations of building-attached photovoltaic (BAPV) roofs and building-integrated photovoltaic (BIPV) facades, considering the initial cost of BIPV facades. The simulations demonstrate that achieving the target ESSR requires a combination of BAPV roofs and BIPV facades, due to limited roof areas for PV systems. Additionally, this study reveals that BIPV facades can be cost-effective when their unit price, relative to BAPV roofs, is below 62%. Based on the ECO2 simulations, a linear regression formula is proposed to predict the ESSR for the case study building. Verification analysis shows that the proposed formula predicts an ESSR of 74.1%, closely aligned with the official ESSR of 76.9% certified by the Korean government. Although this study focuses on the case of a specific apartment building and lacks actual field data, it provides valuable insights for future applications of PV systems to enhance energy self-sufficiency in small-scale, low-rise apartment buildings in Republic of Korea.

1. Introduction

Globally, the building sector constitutes a substantial portion of national energy consumption. According to the International Energy Agency (IEA), the building sector accounts for over 40% of energy consumption in North America, more than 37.3% in Europe, and above 24% in Asia. Specifically, residential buildings represent over 17% in North America, 25% in Europe, and 19% in Asia, in terms of the total energy consumption [1]. The U.S. Energy Information Administration (EIA) similarly reports that the building sector represents approximately 21% of total energy consumption in the United States, with residential buildings accounting for about 11% [2]. The Korea Energy Economics Institute (KEEI) indicates that the building sector comprises about 22% of national energy consumption, with residential buildings making up about 11% [3]. According to the KEEI, the important fact is that energy consumption in the building sector is continuously increasing [3].

The government in Republic of Korea introduced the Zero-Energy Building Certification (ZEBC) System in 2017, aiming to reduce energy consumption in the building sector. Since 2020, the ZEBC requires public buildings to achieve an energy self-sufficiency rate (ESSR) of at least 20%. Starting in 2023, this mandate has been extended to public multi-family residential buildings with 30 or more dwelling units [4]. The ESSR is the ratio between the source energy generation and the source energy consumption of a building. It serves as the basis for determining the Zero-Energy Building Grade; Grade 5 requires an ESSR from 20% to less than 40%, Grade 4 requires an ESSR from 40% to less than 60%, Grade 3 requires an ESSR from 60% to less than 80%, Grade 2 requires an ESSR from 80% to less than 100%, and Grade 1 requires an ESSR from 100% or higher [4].

However, as mentioned earlier, in Republic of Korea, multi-family residential buildings with 30 or more dwelling units are required to comply with the Zero-Energy Building Certification [4]. This highlights a lack of standards or systems for achieving zero energy in small-scale, low-rise, multi-family residential buildings in Republic of Korea. Consequently, there is also a scarcity of research focused on achieving energy self-sufficiency for these low-rise residential buildings.

According to the Korea Statistical Information Service (KOSIS), as of 2022, multi-family housing accounted for 79% of the total number of dwellings in Republic of Korea [5]. Data from the Korea Energy Agency indicates that since the implementation of the Zero-Energy Building Certification in 2017, only 20 out of 975 certified buildings are residential buildings, representing just 2.1% of the total number of certified buildings [4]. Among the certified residential buildings, 11 buildings are multi-family residential buildings, showing no significant difference in proportion compared to single-family homes. However, when comparing the ZEB grades, 45% of single-family homes achieved a ZEB Grade 3 or higher, while only 33% of multi-family residential buildings reached this level. Therefore, given the high prevalence of multi-family residential buildings in Republic of Korea, it is crucial to enhance the energy self-sufficiency of these buildings to achieve significant energy savings in the building sector.

Research aimed at improving the energy performance and energy self-sufficiency of housing has been actively conducted worldwide, including in Republic of Korea. Some previous studies have performed research using case studies on various net-zero energy buildings, demonstrating the necessity of applying diverse energy reduction technologies and renewable energy sources to achieve net-zero energy buildings [6,7,8,9]. Notably, these studies identified that photovoltaic (PV) systems have been employed in most cases. This underscores that PV systems are considered the primary renewable energy solution for achieving net-zero energy buildings. Furthermore, various pieces of global research on implementing net-zero energy buildings have consistently shown that both PV (including building-attached photovoltaic or BAPV and building-integrated photovoltaic or BIPV) systems and solar thermal systems are considered as energy sources in many of these types of studies [10,11,12,13,14,15,16,17,18,19,20,21,22].

In Republic of Korea, various studies have also been conducted to implement net-zero energy residential buildings, as summarized in Table 1 [23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48]. Unlike international studies, Korean research has predominantly focused on energy reduction technologies and the analysis of building energy policies and their effectiveness, rather than the implementation of zero energy multi-family residential buildings. This suggests that there is a lack of research on application strategies and capacity estimation methods for PV systems, which are essential for achieving nearly or net-zero energy residential buildings in Korean studies. Furthermore, Korean research has primarily focused on high-rise apartments, reflecting the predominant residential culture in Republic of Korea. Consequently, there is a notable deficiency in the research aimed at improving energy performance and achieving nearly or net-zero energy in small-scale, low-rise, multi-family residential buildings, with fewer than 30 dwelling units, in Republic of Korea.

Table 1. Summary of previous research on energy-efficient buildings in Republic of Korea.

Author	Method	Building Type	Indicator	Variables	Type of Renewable Energy	Conclusion
Bo Rang Park et al. [23]	Simulation	Residential building	Energy use intensity	Infiltration Lighting power density Heating system efficiency Plug-load density	-	Achieving carbon neutrality requires a comprehensive approach beyond regulating individual technology elements.
Jihye Choi et al. [24]	Survey	Residential building	Choice probability	Respondents Subsidy Building energy level		Cost-related factors are the most significant in terms of public acceptance of zero-energy residential building.
Changyoon Ji et al. [25]	Statistics	Non-residential building	Energy use intensity	Building Energy Efficiency Certification (BEEC)	-	Improving BEEC is suggested to better account for all energy uses and enhance its effectiveness in reducing greenhouse gas emissions.
Changyoon Ji et al. [26]	Statistics	Residential building	Greenhouse gas (GHG) emissions	Building type Year it was built Climate region Thermal conductivity of the envelope	-	Strengthening BEEC has reduced greenhouse gas emissions from heating energy use in new buildings, but it has not significantly impacted on baseload and cooling energy emissions.
KyungSoo Kim et al. [27]	Survey Statistics Simulation	Residential Building	Energy consumption	Building Type Building Size Built Year Window-Wall-Ratio Building Orientation Aspect Ratio	-	The developed standard building model showed a high level of efficiency and reliability in predicting energy consumption, with a total energy consumption error rate of 12.67%.
Yujun Jung et al. [28]	Simulation	Residential building	Energy and economic metrics; life cycle performance	Air tightness Occupants Window–wall ratio	Hydropower Solar power	The electricity-based energy scenario has better energy and environmental performance compared to the hydrogen-based scenario, achieving energy savings of 62% and 53%, respectively.
Changyoon Ji et al. [29]	Statistics	Residential building	Energy use intensity	Climate region Floor area Building energy certificate	-	The BEEC effectively reduces heating energy consumption, but its impact on electricity use is insignificant.
Munkhbat Undram et al. [30]	Simulation	Residential building	ESSR	Photovoltaic (PV) area Building area	Solar power	District heating apartments can achieve Zero-Energy Building (ZEB) Grade 5 with rooftop PV installations alone, but individual apartments require additional measures to reduce primary energy consumption.
Seongjo Wang et al. [31]	Simulation	Non-residential building	ESSR	Building size Cooling/heating capacity Renewable energy capacity	Solar power Fuel cell Geothermal	ESSR prediction formulas are proposed to design optimal renewable energy systems for zero-energy buildings.
Hyomun Lee et al. [32]	Field test	Residential building	Energy generation	Season	Solar power Solar thermal	The house consumed 7368.95 kWh/yr and generated 11,439.68 kWh/yr through roof-integrated photovoltaics (RIPVs), achieving a 35.58% annual energy surplus.
Sungwoong Yang et al. [33]	Survey simulation	Residential building	Energy consumption	Air tightness Lighting power density Thermal conductivity of the envelope Heating system efficiency	-	Applying energy-saving technologies can lead to substantial energy savings and improved energy efficiency in low-rise residential buildings.
Yeweon Kim et al. [34]	Review	Residential and non-residential buildings		-	-	Ground-source heat pumps generally showed higher self-sufficiency rates than water-source heat pumps.
Byung Chang Kwag et al. [35]	Simulation	Residential building	Heat loss form factor; energy load; energy use intensity	Building size Envelope thermal conductivity Household location Lighting power density Heating system efficiency	-	Improving the boiler efficiency is the most effective measure for reducing energy consumption, while enhancing the building envelope has the least impact.
Joohyun Lee et al. [36]	Simulation	Residential building	Energy load; energy use intensity	Passive house Conventional house	-	It is important to consider the local climate and construction practices in achieving energy efficiency of a passive house.
Hye Soo Suh et al. [37]	Simulation	Community building	Energy consumption	Thermal conductivity of the envelope Air tightness Lighting power density Ventilation efficiency Cooling/heating system efficiency	Solar power Geothermal Solar thermal	Combining passive and active design strategies with renewable energy systems can significantly improve energy performance and achieve nearly zero-energy targets for community buildings.
Jeonghun Song et al. [38]	Simulation	Residential and non-residential buildings	Building energy performance	Building type Renewable energy type	Solar power Fuel cell Geothermal Solar thermal	Integrating renewable energy sources like photovoltaics, ground-source heat pumps, and fuel cells can reduce electricity and gas supply from the grid by 17% and 3%, respectively.
Jiyoung Eum et al. [39]	Simulation	Residential building	Total net present cost	Energy storage system (ESS) capacity/price PV capacity/price Grid price	Solar power	ESS prices should decrease significantly to be economically viable, especially with government support and the implementation of time-of-use (TOU) rates.
Tae-Hyoung Kim et al. [40]	Statistics	Residential and non-residential buildings	Greenhouse gas emissions	Climate region Energy source Year	-	This study suggests that the building sector has significant potential for energy efficiency improvements and greenhouse gas emission reductions.
Sung-Yul Kim et al. [41]		Residential building	Optimum solar power generation	Building design Subsidy Initial cost Operation cost	Solar power	Economic analyses show that connecting solar power generation capacity from a zero-energy perspective is more effective than maximizing the capacity based on the building structure.
Kwon Sook Park et al. [42]	Statistics	Residential building	Energy consumption	Number of family members Building type Climate condition	-	Improving energy performance in existing buildings, strengthening building design criteria, and revitalizing Korea’s energy-saving policies are essential to reduce energy demand and GHG emissions in the residential buildings sector.
Jeongyoon Oh et al. [43]	Review	Residential and non-residential buildings		Passive strategies Active strategies	-	This study proposes integrating and optimizing the passive and active strategies in the early phase of a building’s life cycle and real-time monitoring during the usage phase to achieve net-zero energy buildings.
Chang Heon Cheong [44]	Simulation	Residential building	Energy reduction	Locations of PV panels Building story	Solar power	To achieve net-zero energy in apartment buildings, an advanced energy mix is necessary. The policy for zero-energy buildings may only be feasible for detached houses.
Jin-Hee Kim et al. [45]	Statistics	Residential and non-residential buildings	Energy generation	Energy demand PV installation type PV cell type	Solar power Solar thermal	PV systems are essential for achieving net-zero energy in buildings, but their application requires careful consideration of the economic viability, architectural integration, and surrounding environment.
Duk Joon Park et al. [46]	Review	Residential and non-residential buildings		Number of energy certified buildings Energy performance	-	The BEEC has influenced gas and district heating consumption in residential buildings and shown a decreasing trend in primary energy consumption for non-residential buildings since its implementation.
Lim Jae-Han et al. [47]	Simulation	Residential building	Energy load	Thermal conductivity of the envelope Air tightness Ventilation efficiency Heating system efficiency	-	Enhancing insulation, window performance, ventilation, and air tightness can significantly reduce energy consumption in apartment buildings.
Kyoung-ho Lee et al. [48]	Field test	Residential building	Energy generation	Thermal demands Outdoor air temperature Solar irradiance	Solar power Solar thermal	It is important to integrate solar energy systems in buildings to achieve energy savings and improve the overall energy efficiency. The total annual solar fraction of the solar heating system was 69.7%.

In general, achieving net-zero energy buildings with PV systems can be easier for single-family homes compared to multi-family residential buildings. This is because the energy generated by PV systems installed on the same roof area only needs to cover the energy load of a single household in a single-family home. In contrast, in multi-family housing, PV systems must cover the energy load of multiple households. Consequently, achieving energy self-sufficiency solely through rooftop PV systems could be challenging for multi-family residential buildings.

This study aims to analyze how PV systems can be applied to achieve energy self-sufficiency in a small-scale, low-rise, multi-family residential building in Republic of Korea, particularly during the schematic design process. For this research, an actual low-rise residential building with 28 dwelling units that achieved ZEB Grade 3 will be used as a case study.

2. Methodology

The main purpose of this research is to analyze the integration of PV systems into low-rise residential buildings to achieve energy self-sufficiency in Republic of Korea, particularly during the schematic design process. This study analyzes the energy performance of buildings and conducts a sensitivity analysis of the impact of PV systems using building energy simulation, as shown in Figure 1.

Figure 1. Flowchart of the research.

The target ESSR of 60% was set based on the requirements of the city government of Sejong City for public rental housing. Subsequently, using the Korean building energy code and other criteria, the baseline building was modelled in the ECO2 building energy simulation and the building energy performance was evaluated to calculate the required source energy generation needed to achieve the target ESSR.

To understand the contributions of the BAPV roof and BIPV facade towards achieving the target ESSR, a sensitivity analysis of the PV system’s capacity and efficiency was conducted using the ECO2 simulation. Additionally, this research carried out parametric analysis to analyze the different combinations of BAPV roofs and BIPV facades, as well as the impact of the initial cost of a BIPV facade on the different combinations of PV systems. Based on the ECO2 simulation results and regression analysis, this research proposed a calculation formula for predicting the ESSR.

The energy performance analysis of the baseline buildings was conducted using ECO2, the official building energy analysis program in Republic of Korea, as illustrated in Figure 2. Internationally, various building energy simulation tools, such as EnergyPlus, TRNSYS, and DOE-2 based EQUEST, are commonly used to assess and evaluate building energy performance. However, in Republic of Korea, the ECO2 simulation program serves as the official tool for analyzing building energy loads and consumption in the context of the Zero-Energy Building Certification. The ECO2 program calculates building energy loads and consumption, aiming to evaluate the overall energy performance [30,34,35,49,50]. Previous studies have shown that the ECO2 simulation program yields energy usage trends consistent with the reference data [51,52,53]. In this research, the ECO2 simulation program is employed to analyze building energy performance and assess the impact of PV systems on achieving energy self-sufficiency rates.

Figure 2. Flowchart of ECO2 building energy simulations.

3. Building Energy Modeling

3.1. Baseline Building Energy Modeling

The case study building is a small-scale five-story multi-family public housing building with 28 dwelling units located in Sejong, Republic of Korea. Excluding the first floor, which is a public space, including a lobby and monitoring room, the second to fifth floors consist of seven dwelling units per floor, as shown in Figure 3. This public apartment aims to achieve an energy self-sufficiency rate of over 60% and obtain at least ZEB Grade 3 certification. Each dwelling unit is planned to have an area of 39 m². The description of the case study building is summarized in Table 2.

Figure 3. Schematic drawings of the case study building: (a) floor plan, (b) elevation (unit: mm).

Table 2. Description of the case study building.

Category	Specification
Floor to Ceiling	2.3 m
Floor to Floor	3.2 m
Dwelling Unit Area	Total 1092 m2 39 m2/unit × 7 units/floor × 4 floor
Roof Area	306 m2
Front Exterior Wall Area	530 m2
Front Exterior Wall Window Area of a Dwelling Unit	(Living Space) Window 1: 3.8 m2/Window 2: 2.9 m2 (Mechanical Room) Louver Window: 1.6 m2
Number of Floors	Five-Story Building First floor: Parking Lots, Lobby, Monitoring Room Second~Fifth Floor: Dwelling Units (Seven Units Per Floor)
Main Building Material	Reinforced Concrete
Target ESSR	Over 60% (ZEB Grade 3)

The ECO2 building energy simulation inputs are summarized in Table 3. These inputs are primarily based on reference data from the Energy Saving Design Standards for Buildings of the Korean Government [49]. According to the Energy Saving Design Standards for Buildings of the Ministry of Land, Infrastructure, and Transport of Republic of Korea, residential buildings can exclude the cooling system from the evaluation criteria for the Zero-Energy Building Certification [54]. Therefore, the baseline building in this study does not consider the cooling system and has excluded space cooling from the ZEB certification evaluation criteria.

Table 3. Baseline modeling inputs.

Element	Category	Specification
Exterior Wall	Thermal Transmittance (U-value)	0.167 W/(m2K)
Window	Thermal Transmittance (U-value)	1.00 W/(m2K)
Slab on Grade Floor	Thermal Transmittance (U-value)	0.17 W/(m2K)
Roof	Thermal Transmittance (U-value)	0.15 W/(m2K)
Space Heating	Type	Radiant Floor Heating
	Water Temperature	Supply 80 °C/Return 60 °C
	Efficiency [%]	91% (Decentralized Natural Gas Condensing Boiler)
Domestic Hot Water	Type	Natural Gas Condensing Boiler
	Water Temperature	Supply 80 °C/Return 60 °C
Ventilation	Type	Energy Recovery Ventilator
	Capacity (Air Change per Hour)	0.5
	Efficiency	Heating 70% Cooling 45%
Lighting	Lighting Power Density	7 W/m2
Infiltration	Air Change per Hour	6

3.2. Parameters for the Sensitivity Analysis

The study applied BAPV on the roof and BIPV on the facade of the baseline building and conducted a sensitivity analysis to assess the impact of the BAPV roof and BIPV facade on the building’s ESSR. The parameters investigated in this study included the installation area and efficiency of the BAPV roof and BIPV facade, as outlined in Table 4.

Table 4. Description of the options for the sensitivity analysis.

Parameter		Options
BAPV Roof	Area [m2]	30, 60, 90, 120, 150, 180, 210, 240, 270, 300
	Efficiency [%]	10, 12, 14, 16, 18, 20, 22, 24
BIPV Facade	Area [m2]	16, 32, 48, 64, 80, 96, 112, 128, 144, 160
	Efficiency [%]	10, 12, 14, 16, 18, 20, 22, 24

4. Building Energy Simulation Results

4.1. Energy Performance of the Baseline Model

Table 5 presents the results of the ECO2 simulation for the baseline model. Heating accounted for approximately 54.2% of the total building energy load, followed by domestic hot water at 32.3%, and lighting at 13.5%. When considering site energy consumption, calculated taking into account the equipment efficiency and operating hours, heating energy consumption represented 60.2% of the total, domestic hot water 21.0%, lighting 7.9%, and ventilation 10.8%. In terms of source energy consumption, space heating represented 48.0%, domestic hot water 16.3%, lighting 15.1%, and ventilation 20.6%. Overall, heating dominated the building energy performance, highlighting its significant contribution to energy consumption.

Table 5. Simulation results of the baseline model.

Category	Space Heat	Space Cool	Hot Water	Lighting	Ventilation	Total
Building Energy Load [kWh/m2· yr]	51.5	0.0	30.7	12.8	0.0	95.0
Site Energy Consumption [kWh/m2· yr]	97.4	0.0	34.0	12.8	17.5	161.7
Source Energy Consumption [kWh/m2· yr]	111.9	0.0	37.9	35.1	48.1	233.0

4.2. Results of the Sensitivity Analysis

4.2.1. Impact of PV System Capacities

This study analyzed the impact of capacity changes in the BAPV roof and BIPV facade on the ESSR for the case study building. In the ECO2 simulation, the BAPV roof efficiency and installation angle was fixed at 20% and 30 degrees, respectively, while the BIPV facade efficiency was assumed to be 15%. Notably, when conducting simulations for the BAPV roof or BIPV facade, each type of PV system was simulated independently. In other words, the BIPV facade was not applied during the simulations for the BAPV roof. The simulation results, as shown in Figure 4 and Figure 5, revealed that the ESSR increases linearly as the installation area of both systems increases and the installed capacity increases.

Figure 4. Source energy intensity for variations in the BAPV roof area.

Figure 5. Source energy intensity for variations in the BIPV facade area.

The simulation analysis results indicate that achieving the target ESSR of 60% solely with either a BAPV roof or a BIPV facade is challenging due to installation area limitations. Specifically, a BAPV roof would need to cover more than 280 m², while a BIPV facade would require at least 560 m², according to the linear regression equation. However, local government regulations in Republic of Korea restrict solar panel installation to a maximum of 70% of the flat roof area [55,56]. Given the total roof area of 300 m² in the case study building, a BAPV roof can be installed on up to 210 m² of the horizontal flat roof surface. Applying an installation angle of 30°, the maximum installable area for the BAPV roof is 243 m². Therefore, achieving the target ESSR necessitates combining both a BAPV roof and a BIPV facade.

4.2.2. Impact of PV System Efficiencies

This study conducted simulations to analyze the impact of changes in the efficiency of the PV system on the ESSR of the case study building. When simulating the BAPV roof, it was assumed that it would be installed on 300 m² of the roof, with no installation of a BIPV facade. For the BIPV facade, it was assumed that it would cover 160 m², corresponding to about 30% of the front wall area of 530 m², without a BAPV roof. As a result of the analysis, it was observed that the change in the building’s ESSR due to efficiency changes followed a linear trend, as shown in Figure 6 and Figure 7. Specifically, for the BAPV roof, an efficiency saving of at least 16% was necessary to achieve the target ESSR for the case study building. However, in the case of the BIPV facade, regardless of how high the efficiency was, the target ESSR of 60% could not be reached. The limitation arises from the BIPV facade installation area being restricted to 30% of the front wall.

Figure 6. Source energy intensity for variations in the BAPV roof efficiency.

Figure 7. Source energy intensity for variations in the BIPV facade efficiency.

5. Analysis

5.1. Impact of Combining PV Systems on Achieving the Target ESSR

Since the source energy demand of the baseline model is 233 kWh/(m²·yr), achieving the target ESSR of 60% requires a source energy generation of at least 139.8 kWh/(m²·yr). This study analyzed various combinations of BAPV roofs and BIPV facades to meet the target ESSR, as summarized in Table 6. For this analysis, the PV efficiencies of 20% and 15% were used for the BAPV roof and BIPV facade, respectively. As shown in Table 6, an area of 280 m² for the BAPV roof alone is sufficient to achieve the target ESSR of 60%. However, due to regulatory constraints, which allows only up to 270 m² for the BAPV roof installation in the case study building, achieving the target ESSR solely with a BAPV roof is not feasible. Therefore, a combination of a BAPV roof and a BIPV facade is necessary to achieve the target ESSR of 60% for the case study building.

Table 6. Simulation results for various combinations of BAPV roofs and BIPV facades.

CASE	Surface Area [m2]		PV Capacity [kW]		Source Energy Generation [kWh/m2·yr]			ESSR [%]
	BAPV Roof	BIPV Facade	BAPV Roof	BIPV Facade	BAPV Roof	BIPV Facade	Total
Case 1	30	500	6	78	15.0	124.8	139.8	60.0%
Case 2	60	440	12	68	30.0	109.8	139.8	60.0%
Case 3	90	380	17	59	44.9	94.9	139.8	60.0%
Case 4	120	320	23	50	59.9	79.9	139.8	60.0%
Case 5	150	260	29	40	74.9	64.9	139.8	60.0%
Case 6	180	200	35	31	89.9	49.9	139.8	60.0%
Case 7	210	140	41	22	104.8	35.0	139.8	60.0%
Case 8	223	114	43	18	111.4	28.5	139.8	60.0%
Case 9	240	80	46	12	119.9	19.9	139.8	60.0%
Case 10	270	20	52	3	134.9	4.9	139.8	60.0%
Case 11	280	0	54	0	139.8	0.0	139.8	60.0%
Case 12	300	0	58	0	149.9	0.0	149.9	64.3%

5.2. Impact of BIPV Facade Initial Costs

This study examined the combination of a BAPV roof and a BIPV facade to achieve the target ESSR, considering the installation costs. As shown in Table 7, the baseline installation cost for PV systems was obtained from the Korea Energy Agency’s 2021 report [57]. Since there are no recent official cost estimates for BIPV facade panels from the Korea Energy Agency (KEA), this research used the cost difference ratio between BAPV roofs and BIPV facades from the 2011 and 2012 KEA reports [58,59]. Specifically, the cost of BIPV facade panels was assumed to be approximately 2.0 times that of BAPV roof panels, estimated at KRW 2724 per kW.

Table 7. Standard price per 1 kW for PV systems released by KEA.

Type of PV System		Year
		2011	2012	2021
BAPV Roof	1000 KRW/kW	5650	4972	1816
	USD/kW	4238	3729	1362
BIPV Facade	1000 KRW/kW	13,055	9553	-
	USD/kW	9791	7165	-

(Exchange rate: KRW 1000 = USD 0.75, Google Finance, 8 March 2024).

To evaluate the effect of the initial cost of a BIPV facade, this study conducted ECO2 simulations for various combinations of BAPV roof and BIPV facade installations needed to achieve the target ESSR of 60%. Different initial costs for a BIPV facade were then applied, as shown in Table 8. Throughout the analysis, the installation areas for BAPV roof and BIPV facade panels, as well as the cost of a BAPV roof, remained constant, while the cost of the BIPV facade was varied.

Table 8. Unit cost options for a BIPV facade.

Unit Cost Option	Option 1	Option 2	Option 3	Option 4	Option 5	Option 6	Option 7
BAPV Roof [USD]	1362	1362	1362	1362	1362	1362	1362
BIPV Facade [USD]	681	845	953	1362	2043	2724	4086
Ratio	0.5	0.62	0.7	1.0	1.5	2.0	3.0

Table 9 presents the initial cost associated with different combinations of BAPV roofs and BIPV facades for various implementation surfaces. The minimum initial cost is highlighted in yellow. Notably, for Option 1 and Option 2, a higher utilization of the BIPV facade results in a lower initial cost for implementing PV systems. In contrast, other options achieve the minimum initial cost by using only a BAPV roof. These results indicate that applying a BIPV facade is cost-effective when its initial price, relative to a BAPV roof, is below 62%. Therefore, to promote the extensive adoption of BIPV facades, reducing the initial installation cost through financial support systems, such as government subsidies, is crucial.

Table 9. The resulting initial cost for various combinations and cost options, with the minimum total value highlighted in yellow.

Case	BAPV Roof [USD]	Option 1		Option 2		Option 3		Option 4		Option 5		Option 6		Option 7
		BIPV Facade [USD]	Total Cost [USD]	BIPV Facade [USD]	Total Cost [USD]	BIPV Facade [USD]	Total Cost [USD]	BIPV Facade [USD]	Total Cost [USD]	BIPV Facade [USD]	Total Cost [USD]	BIPV Facade [USD]	Total Cost [USD]	BIPV Facade [USD]	Total Cost [USD]
Case 1	7900	52,924	60,824	65,631	73,530	74,082	81,982	105,848	113,748	158,773	166,672	211,697	219,597	317,545	325,445
Case 2	15,786	46,569	62,354	57,750	73,535	65,186	80,972	93,138	108,923	139,707	155,492	186,276	202,061	279,413	295,199
Case 3	23,685	40,245	63,930	49,908	73,593	56,334	80,019	80,490	104,175	120,735	144,421	160,981	184,666	241,471	265,156
Case 4	31,585	33,869	65,454	42,000	73,585	47,409	78,994	67,737	99,322	101,606	133,191	135,475	167,060	203,212	234,797
Case 5	39,484	27,513	66,998	34,119	73,603	38,513	77,997	55,027	94,511	82,540	122,025	110,054	149,538	165,080	204,565
Case 6	47,370	21,158	68,528	26,238	73,608	29,617	76,987	42,316	89,686	63,474	110,845	84,632	132,003	126,948	174,319
Case 7	55,270	14,824	70,094	18,383	73,653	20,750	76,020	29,648	84,918	44,471	99,741	59,295	114,565	88,943	144,213
Case 8	58,687	12,070	70,757	14,968	73,655	16,896	75,582	24,140	82,827	36,210	94,897	48,281	106,967	72,421	131,107
Case 9	63,170	8458	71,627	10,489	73,658	11,839	75,009	16,916	80,085	25,374	88,543	33,832	97,001	50,747	113,917
Case 10	71,056	2071	73,127	2568	73,624	2899	73,954	4142	75,198	6213	77,269	8284	79,340	12,426	83,482
Case 11	73,687	0	73,687	0	73,687	0	73,687	0	73,687	0	73,687	0	73,687	0	73,687

5.3. ESSR Prediction Models for PV Systems

5.3.1. ESSR Prediction Model Regression Analysis

Table 10 shows variations in the PV capacity, source energy consumption, and ESSR for changes in the BIPV facade area, based on different BAPV roof areas. As shown in Table 10, since the trend of increasing the ESSR with an increase in the BIPV facade area is linear, the required installation area of the BIPV facade for the case study building to achieve net-zero energy can be estimated through linear regression.

Table 10. Simulation results for various installation areas of the BAPV roof and BIPV facade.

Category	BAPV Roof Area [m2]	BIPV Facade Area [m2]
		100	150	200	250	300	350	400	450	500
Total PV Capacity [kW]	150	45	52	60	68	76	83	91	99	107
	180	51	58	66	74	82	89	97	105	113
	210	57	64	72	80	88	95	103	111	119
	240	62	69	77	85	93	100	108	116	124
Total Source Energy Generation [kWh/m2. yr]	150	99.9	112.3	124.8	137.3	149.8	162.3	174.8	187.2	199.7
	180	114.9	127.3	139.8	152.3	164.8	177.3	189.8	202.2	214.7
	210	129.8	142.2	154.7	167.2	179.7	192.2	204.7	217.1	229.6
	240	144.9	157.3	169.8	182.3	194.8	207.3	219.8	232.2	244.7
ESSR [%]	150	42.9	48.2	53.6	58.9	64.3	69.7	75.0	80.4	85.7
	180	49.3	54.7	60.0	65.4	70.7	76.1	81.4	86.8	92.2
	210	55.7	61.1	66.4	71.8	77.1	82.5	87.9	93.2	98.6
	240	62.2	67.5	72.9	78.2	83.6	88.9	94.3	99.7	105.0

Figure 8 shows that the trend of the ESSR variation with respect to changes in the BIPV facade area remains consistent regardless of the BAPV roof area, indicating only a shift in the y intercept. Figure 9 further demonstrates that the y intercept linearly correlates with the BAPV roof area. By combining these linear regression relationships, Equation (2) could be derived, suggesting that it is feasible to predict the ESSR based on variations in both the BAPV roof and BIPV facade areas for a specific building.

$$ESSR\left[\%\right]=0.001071\times A_{BIPV}+0.002142\times A_{BAPV}+0.000199$$

(1)

Figure 8. ESSR variations according to the BIPV facade area and BAPV roof area.

Figure 9. Relationship between the BAPV roof area and the y intercept in Figure 8.

However, this equation only considers the influence of the installation areas of the BAPV roof and BIPV facade, failing to adequately reflect the direct correlation with the source energy consumption for ESSR calculations. In other words, Equation (1) may show high predictive accuracy for the case study building used to derive Equation (1), however it can lack accuracy when building loads and source energy consumption vary. Therefore, to address such limitations and account for source energy consumption, this study used the correlation between the PV capacity and building source energy consumption to assess the achievable ESSR through PV system implementation.

As shown in Figure 10, the ESSR variation relative to the ratio of the PV capacity to the source energy consumption follows a linear trend. The slope of the change, which varies based on the BAPV roof area, remains consistent, while the y intercept differs. Figure 11 shows that the y intercept linearly correlates with changes in the BAPV roof area. By combining these linear regression equations, depicted in Figure 10 and Figure 11, this study derived Equation (2), which can predict the building’s ESSR.

$$ESSR\left[\%\right]=1.6066\times {\displaystyle \frac{TotalSolarPowerCapacity}{AnnualPrimaryEnergyConsumption}}+0.000833\times A_{BAPV}-0.005180$$

(2)

Figure 10. ESSR variations for the ratio between total PV capacity and source energy consumption.

Figure 11. Relationship between BAPV roof area and y intercept in Figure 10.

5.3.2. Verification of the ESSR Prediction Models

The case building studied in this research was built in August 2023, as shown in Figure 12, along with the floor plan shown in Figure 13. While the main design remained consistent with the conceptual design, the dwelling unit area was expanded beyond the initial plans. Notably, mechanical ventilation was not implemented in the final design. The photographs and specifications of the completed building are presented in Figure 12 and Table 11.

Figure 12. Images of final design of the case study building: (a) elevation, (b) BIPV facade, (c) BAPV roof.

Figure 13. Floor plan of the final design of the case study building (unit: mm).

Table 11. Details of the final design specifications of the case study building.

Energy Efficiency Measure			Options
Dwelling Unit Information		Floor Area of Units [m2]	49	48	43	39	36
		Number of Dwelling Units	2	3	3	16	4
Passive System	Building Envelop: Opaque Element	Thermal Transmittance (U-value)	0.137 W/(m2K)
	Building Envelop: Window	Thermal Transmittance (U-value)	0.693 W/(m2K)
	Infiltration	Air Change per Hour	5.50
Active System	Interior Lighting	Lighting Power Density	4.67 W/m2
	Space Cooling	Type	Space Cooling Not Installed
	Space Heating	Type	Radiant Floor Heating
		Efficiency	91.1% (Natural Gas Boiler)
	Domestic Hot Water	Type	Natural Gas Boiler
		Water Temperature	Supply 80 °C/Return 60 °C
	Ventilation	Type	Mechanical Ventilator Not Installed
Energy Generation System	BAPV Roof	Area	240 m2 (52 kW = 500 Wp × 104 panels
		Efficiency	21.6%
	BIPV Facade	Area	138 m2 (17.2 kW = 123 Wp ∗ 140 panels)
		Efficiency	12.3%

Based on the specifications of the building shown in Table 11, the official results of the Zero-Energy Building Certification of Republic of Korea are presented in Table 12, indicating the final ESSR of 76.9%. This exceeds the target ESSR of 60%. The variation is attributed to changes in the boundary conditions, including envelope U-values, the infiltration rate, and lighting power density, as well as adjustments to the floor area compared to the initial plans.

Table 12. The official simulation results of the Zero-Energy Building Certification for the case study building.

Category	Space Heat	Space Cool	Hot Water	Lighting	Ventilation	Total	Energy Generation
Building Energy Load [kWh/m2.yr]	63.6	0	30.7	8.5	0	102.8	0
Site Energy Consumption [kWh/m2.yr]	126.2	0	32.7	8.5	0	167.4	56.9
Source Energy Consumption [kWh/m2.yr]	145.9	0	34.3	23.4	0	203.6	156.6

The ESSR predictions were made using Equations (1) and (2), considering the final building specifications, source energy consumption, and PV capacity. The calculated ESSR prediction from Equation (1) was 66.2%, whereas Equation (2) predicted an ESSR of 74.1%. This discrepancy highlights that Equation (2) provides a more accurate prediction.

The reason lies in that Equation (1) focuses solely on variations in the installation area of PV systems, without directly considering the building’s source energy consumption. While Equation (1) suited the sample data used for its derivation, it exhibited significant errors when the building’s energy usage changed. In contrast, Equation (2) accounts for both PV capacity and source energy consumption, resulting in a more reliable ESSR prediction.

6. Conclusions

This study analyzed various factors related to implementing PV systems for achieving nearly zero energy in small-scale, low-rise, multi-family residential buildings. The analysis was based on a case study building located in Republic of Korea, a newly constructed five-story multi-family residential building with 28 dwelling units. The research investigated the impact of PV capacity and efficiency variations, BIPV facade costs, and the combined effects of a BAPV roof and BIPV facade on the building’s ESSR. Based on these analyses, the study proposed equations to predict the ESSR when implementing PV systems in small-scale, low-rise, multi-family residential buildings in Republic of Korea.

During the conceptual design process, the case study building set a target ESSR of 60%, excluding space cooling and plug loads. To achieve this target ESSR, this study analyzed the impact of PV capacity and efficiency. The simulation results showed that achieving the target ESSR using only a BAPV roof or a BIPV facade would be challenging due to the limited roof area for BAPV systems in multi-family residential buildings and the lower efficiency of BIPV facades compared to BAPV roofs. Therefore, a combination of a BAPV roof and BIPV facade emerges as a viable strategy to achieve the desired ESSR.

Due to the initial cost of a BIPV facade being twice as high as that of BAPV roof, it was more cost-effective to use more BAPV roof panels than BIPV facade panels. To enhance the cost-effectiveness of the BIPV facade, the sensitivity analysis revealed that its initial cost should be 62% lower than that of a BAPV roof. This difference primarily stems from the lower energy performance of BIPV facades compared to BAPV roofs.

Based on the simulation results for various combinations of BAPV roofs and BIPV facades, this study derived equations using linear regression analysis to predict the ESSR for a small-scale, low-rise, multi-family residential building. By utilizing the final design details of the case study residential building, the proposed equation, which considers both the PV capacity and building source energy consumption, was validated to predict the ESSR, which was closely aligned with the actual ESSR.

However, it is important to acknowledge that this study has limitations. Conducted on a specific case study building, further analysis is necessary to determine whether the results can be generalized to multi-family residential buildings of varying scales and locations. Additionally, since this study primarily relied on simulation analysis, future validation using real building energy performance data and PV system-generated energy data is essential.

Despite these limitations, this study differs from previous research by investigating the application of PV systems as a strategy to achieve the ESSR in small-scale, low-rise, multi-family residential buildings in Republic of Korea. This research could be useful for future studies exploring strategies for achieving zero-energy, multi-family residential buildings using PV systems.