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Abstract To address the energy consumption problem in the building sector, this study sought to develop a prototype of the multi-function smart window as a combination of the photovoltaic (PV) blinds and the ventilation system by considering two perspectives: (i) design of the multi-function smart window; and (ii) operation strategy for the multi-function smart window. The main findings can be summarized as follows. First, a comprehensive performance analysis of the multi-function smart window according to the application location of the ventilation system and the PV cell types was conducted to determine the optimal configuration of the multi-function smart window. Second, the hardware prototype of the multi-function smart window was implemented considering the PV cell type, PV tracker type, ventilation type, and filter. Finally, this study developed a software prototype that can monitor and control the multi-function smart window in real time based on the NI LabVIEW software program. Through the application of a novel building envelope system developed based on this study, it is expected that zero-energy buildings can be realized and buildings' indoor environmental quality can be improved. Highlights • Smart window combined with PV blinds and a ventilation system was proposed. • This study focused on the design and operation strategy of the smart window. • Integrated performance analysis was conducted to define the optimum configuration. • Hardware prototype of the PV blinds and the ventilation system were developed. • Software prototype was developed based on the real-time operation system. [ABSTRACT FROM AUTHOR]

Highlights • The economic potential of the rooftop solar PV system was estimated in South Korea. • The spatial and temporal diversity of the solar PV technology were considered. • The rooftop solar PV profitability was calculated based on a bottom-up approach. • The economic potential was 36-fold the installed capacity of the study area in 2016. • This study took one step farther towards the rooftop solar PV potential estimation. Abstract To successfully deploy distributed solar generation in urban environments, it is essential to investigate the potential to generate electricity from the rooftop solar photovoltaic (PV) system within a region. While various interpretations are possible for the rooftop solar PV potential, most of the previous studies focused on estimating the technical potential, not considering the economic viability and market dynamics. Therefore, it is necessary to estimate the economic potential of the rooftop solar PV system to quantify the amount of economically viable solar PV energy within a region and to evaluate the impact of the various factors affecting market access. Towards this end, this study proposed a bottom-up approach for estimating the economic potential of the rooftop solar PV system considering the market dynamics by adoption year. Accordingly, the economic potential of the rooftop solar PV system was estimated for the Gangnam district in Seoul, South Korea from 2008 to 2016. In terms of power capacity, it was analyzed that as of 2016, the actual installed capacity of the solar PV system in the Gangnam district was only 3% of the maximum economic potential of the rooftop solar PV system (i.e., economic potential for electricity business purposes), showing a high potential for additional rooftop solar PV adoption. In terms of electricity generation, it was shown that as of 2016, the annual economic potential of the rooftop solar PV system could supply up to 4.48% of the annual electricity consumption in the Gangnam district, while only 0.12% could be supplied from the annual electricity generation of the actual installed solar PV system. This study has significant contributions in that it took one step farther towards the rooftop solar PV potential estimation process, from the technical potential to the economic potential, considering the spatial and temporal diversity of the solar PV technology. [ABSTRACT FROM AUTHOR]

The successful deployment of distributed solar generation in urban areas involves the evaluation of how suitable a building is for installing the rooftop solar photovoltaic (PV) system within a region. When evaluating the rooftop solar PV suitability of a building, it is crucial to consider not only its technical but also its economic performance as the difference in technical performance can lead to different financial returns for rooftop solar PV adopters. Towards this end, this study aimed to propose a method for developing a rooftop solar PV rating system using cluster analysis based on the technical and economic suitability criteria. As a result, a rooftop solar PV rating system was developed for 21,681 buildings in the Gangnam district in Seoul, South Korea by dividing them into four grades according to their rooftop solar PV potential, return on investment, and payback period. The effectiveness of the proposed rating system was validated by comparing it with the rating systems developed using the classification method and suitability criteria from the previous studies. This study has significant contributions in that it can provide the rooftop solar PV suitability information on a grade scale for intuitive decision-making based on scientific evidence and reasonable criteria. [ABSTRACT FROM AUTHOR]

The government rebate has become one of the important drivers for implementing the photovoltaic (PV) system. However, it is not as effective for the multi-family housing complexes (MFHCs) in South Korea due to the constant government rebate without considering the electricity generation of the PV system by region and the electricity consumption by MFHC. Thus, this study aimed to estimate the optimal government rebate that guarantees the economic profitability of the PV system within the 4-year target payback period set by the South Korean government to encourage the installation of the PV system in MFHCs. Towards this end, based on the 16 administrative divisions in South Korea and the three types of electricity consumption, this study established 48 scenarios for analyzing the life cycle cost and life cycle CO 2 . When the annual electricity generation of the PV system decreased from 357,300 to 302,090 kWh, and when the monthly average electricity consumption per household by MFHC increased from 200 to 600 kWh, the ranges of the optimal government rebate decreased from US$1,406-1479/kW to US$649–838/kW. When the target payback period increased, the optimal government rebate, which guarantees the economic profitability of the PV system within the 4-year target payback period, decreased. This study may be useful for decision-makers (i.e., residents, construction managers, etc.), or policymakers to determine the optimal government rebate that meets the economic profitability of the PV system in terms of the life cycle cost and life cycle CO 2 . [ABSTRACT FROM AUTHOR]

To promote the deployment of the solar photovoltaic (PV) system from the long-term perspective, the solar PV industry in many countries still needs the financial support from the government despite its remarkable growth and price reductions in the last decade. Many countries with this financial burden on their government budget, however, are planning to reduce or to expire the financial support step by step. To bring the solar PV market to its full maturity, it is crucial to improve the solar policies and to sustain the financial support with acceptable and reasonable prices, which can maximize the benefits for the investors while minimizing the incentive budget for the government. Towards this end, this study aimed to develop an integrated multi-objective optimization (iMOO) model for determining the optimal solar incentive design from the perspectives of the investor and the government. A Microsoft Excel-based iMOO model was developed using life cycle cost analysis, genetic algorithm, and Pareto optimal solutions. The developed Microsoft Excel-based iMOO model was applied to six target regions to verify its effectiveness in determining the optimal solar incentive design. As a result, it was shown that depending on the various characteristics (e.g., solar radiation, electricity price, and installation cost) of a region, the optimal solar incentive design can be differently determined with a reasonable and acceptable level using the developed iMOO model. Among the six target regions, Newark required the lowest incentive budget of $US10,648.41 whereas Oklahoma City required the highest incentive budget of $US20,648.73 to offer their optimal solar incentives. The model developed in this study can help both the investor and the government in a decision-making process and provide some solutions and insights for planning solar policies and strategies. Copyright © 2017 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This study aimed to develop a simplified estimation model for determining the optimal rooftop PV system for gable roofs that can evaluate life cycle economic and environmental assessment, by considering the type of installation to be used for such rooftop PV system. The military facilities located in three regions (i.e., Gimpo (northern part), Deajeon (middle part), and Pohang (southern part)) in South Korea were selected for the case studies. The results of this study are as follows. First, in terms of NPV 25 (net present value in 25 years), for the roofs with a lower orientation, ToI-2 opt. was selected as the optimal rooftop PV system, and for the roofs with a higher orientation, ToI-2 ext. or ToI-3 opt. was selected as the optimal rooftop PV system. Second, in terms of SIR 25 (savings-to-investment ratio in 25 years), for the roofs with a lower orientation, ToI-1 ext. was selected as the optimal rooftop PV system, and for the roofs with a higher orientation, ToI-3 opt. was selected as the optimal rooftop PV system. The simplified estimation model may be useful for decision makers, including experts and non-experts (i.e., architects, owners, construction managers, etc.), or policymakers in determining the optimal rooftop PV system for a gable roof. [ABSTRACT FROM AUTHOR]

Solar Renewable Energy Certificates (SREC) in the United States (U.S.) have become an important driver for promoting the solar photovoltaic (PV) system. However, the SREC price volatility is considered the major barrier for installing the solar PV system due to the uncertainty of the revenue from selling the SREC. To address this challenge, this study aimed to establish a base price for SREC in order to encourage the installation of residential solar PV systems in the U.S. Toward this end, this study conducted the life cycle cost analysis to establish the minimum SREC prices required for reaching the target payback period of the residential solar PV system in the U.S. In addition, this study conducted the comparative analysis from the perspectives of residents and state governments by considering the SREC prices. This study was conducted in four steps: (i) target selection; (ii) data collection; (iii) defining assumptions; and (iv) establishing the minimum SREC prices. The results showed that Massachusetts and New Jersey are the most superior state from the perspective of both residents and state governments. This study can help both residents and state governments to get financial advice for installing solar PV system and improving the SREC-related policies. [ABSTRACT FROM AUTHOR]

The solar photovoltaic (PV) system is known as one of the most outstanding new renewable energy systems for achieving the nearly zero energy building (nZEB). For the continuous deployment of the solar PV system in urban environments, it is crucial to estimate the rooftop solar PV potential. Urban areas, however, where high-rise buildings abound, are not always suitable for solar PV installation. Therefore, it is important to accurately estimate the available rooftop area considering the shadows from the surrounding buildings for reliable rooftop solar PV potential estimation. Therefore, this study proposed a method for estimating the rooftop solar PV potential by analyzing the available rooftop area through Hillshade analysis. Toward this end, the rooftop solar PV potential was estimated through the following hierarchical process: (i) calculation of the physical potential; (ii) calculation of the geographic potential; and (iii) calculation of the technical potential. For accurate estimation of the rooftop solar PV potential, the geographic potential (i.e., the available rooftop area) was explored in detail by analyzing the shadow based on the location of the sun through Hillshade analysis. By applying the proposed method to the Gangnam district in Seoul, South Korea, this study estimated the physical, geographic, and technical potentials on hourly, monthly, and annual bases. Overall, the physical, geographic, and technical potentials in the Gangnam district were found to be 9,287,982 MW h, 4,964,118 m 2 , and 1,130,371 MW h, respectively. These rooftop solar PV potential results can be used in establishing solar policies by analyzing the different levels of the rooftop solar PV potential on hourly, monthly, and annual bases. [ABSTRACT FROM AUTHOR]

With the increasing use of front windows such as curtain walls, the application of semi-transparent photovoltaic (STPV) systems is effective in producing renewable energy, reducing cooling load via solar radiation control, and improving visual comfort. However, in STPV, the visibility of the view from a window decreases, and this can have a negative impact on the occupants' satisfaction (i.e., psychological satisfaction, task performance, and task load). Therefore, this study sought to present the optimal visible light transmittance (VLT) of STPV that simultaneously considers energy performance and the occupants' satisfaction according to the azimuth of a building. To this end, a residential building in South Korea was selected, and energy performance according to the VLT of STPV (amorphous Si thin film PV) was analyzed using DesignBuilder and EnergyPlus for STPV with three VLTs (i.e., 10%, 20%, and 30%). In order to analyze the occupants' satisfaction according to the VLT of STPV, 31 participants were recruited, and an experiment using virtual reality (VR) was carried out. Multi-objective optimization was performed using the energy performance, psychological satisfaction, and task load. The results showed that as the weight of energy performance was adjusted to 0.33, 0.5, and 0.6, the optimal VLT of STPV was 25.53%, 22.65%, and 20.85% on average, respectively. It is expected that the findings of this study can allow the building owner or building designer to predict the energy performance, the occupants' psychological satisfaction and task load according to the VLT of STPV. • The energy performance according to VLT of STPV was analyzed using EnergyPlus. • The occupants' satisfaction according to VLT of STPV was measured by VR experiment. • As the VLT of STPV increased, energy performance of building tended to decrease. • As the VLT of STPV increased, the occupants' satisfaction tended to improve. • The optimal VLT was presented by energy performance and the occupants' satisfaction. [ABSTRACT FROM AUTHOR]

The photovoltaic (PV) system has been highlighted as a sustainable clean energy source. To successfully implement the PV system in a real project, several impact factors should be simultaneously considered. This study aimed to develop an integrated multi-objective optimization (iMOO) model for determining the optimal solution in implementing the rooftop PV system. This study was conducted in six steps: (i) establishment of database; (ii) generation of the installation scenarios in the rooftop PV system; (iii) energy simulation using the software program ׳ RETScreen ׳; (iv) economic and environmental assessment from the life cycle perspective; (v) establishment of the iMOO process using a genetic algorithm; and (vi) systemization of the iMOO model using a Microsoft-Excel-based VBA . Two criteria were used to assess the robustness and reliability of the developed model. In terms of effectiveness, the optimal solution was determined from a total of 399,883,120 (=91×49×19×80×59) possible scenarios by comprehensively considering various factors. In terms of efficiency, it was concluded that the time required for determining the optimal solution was 150 s. The developed model makes it possible for final decision-maker such as construction managers or contractors to determine the optimal solution in implementing the rooftop PV system in the early design phase. [ABSTRACT FROM AUTHOR]

The Ministry of National Defense (South Korea) promotes its Defense Green Growth policy to reduce greenhouse gas emissions. Based on this background, this study aimed to conduct the life cycle economic and environmental assessment for establishing the optimal implementation strategy for rooftop photovoltaic system in military facility. Considering three factors (i.e., the orientation of the gable roof, the installation area of the PV system, and the slope of the installed panel), 12 implementation scenarios of PV system were established. The detailed results by prototype are summarized in terms of the two perspectives (i.e., the absolute and relative investment values): (i) Prototype 1 (south-north): P1-S/N (opt.) in terms of the NPV 25 (net present value at year 25) and P1-S (opt.) in terms of the SIR 25 (savings-to-investment ratio at year 25); (ii) Prototype 2 (southeast-northwest): P2-SE/NW (opt.) in terms of the NPV 25 and P2-SE (ext.) in terms of the SIR 25 ; and (iii) Prototype 3 (east-west): P3-E/W (ext.) in terms of the NPV 25 and P3-E (opt.) in terms of the SIR 25 . The results of this study can help decision-makers to determine the optimal strategy for implementing rooftop PV systems on the gable roof of military facilities through life cycle economic and environmental assessment. [ABSTRACT FROM AUTHOR]

ABSTRACT New renewable energy is attracting considerable attention as a future energy source. The photovoltaic (PV) market, in particular, has grown significantly during the past decade. The use of the rooftop PV system in buildings in urban environments is being actively promoted. This research was conducted to develop a framework for the analysis of the potential of the rooftop PV system to achieve the net-zero energy solar buildings in terms of energy supply. To verify the feasibility of the proposed framework, a total of 5418 elementary school facilities located in 16 administrative divisions in South Korea were selected as case studies. This research (i) collected information on the elementary school facilities, the rooftop PV system, and the meteorological and geographical characteristics by region; (ii) conducted an energy supply analysis by applying the rooftop PV system; (iii) conducted an energy demand analysis; (iv) analyzed the energy substitution effect; (v) presented the current status of the energy supply and demand in each region using the geographical information system; (vi) analyzed the causal relationship between the energy supply and demand by region; and (vii) proposed an energy supply and demand strategy by region. This research can help elementary school facility managers or policymakers conduct an energy supply and demand analysis as well as propose an energy supply and demand strategy. It can be used as part of an educational facility improvement program. The framework proposed in this research can also be applied to any other country or sector in the global environment. © 2013 The Authors. Progress in Photovoltaics: Research and Applications published by John Wiley Ltd. [ABSTRACT FROM AUTHOR]

Abstract: The global PV (photovoltaic) generation market has been rapidly growing. In the introduction of a PV system, the electricity generation efficiency of the PV system depends on regional factors and on-site installation factors. It has a significant effect on the returns on investment. Therefore, this study conducted a sensitivity analysis on how the impact factors of the rooftop PV system affect its electricity generation. Based on the results of the sensitivity analysis, this study aimed to ultimately develop a GIS-based optimization model for estimating the electricity generation of the rooftop PV system. Several impact factors were used in the sensitivity analysis. The result of this study showed that there were 1.12-, 1.62-, and 1.37-fold differences in the annual electricity generation of the rooftop PV system in South Korea due to the regional factor, the azimuth of the installed panel, and the slope of the installed panel, respectively. Using a GIS-based optimization model, final decision-maker could easily and accurately estimate the electricity generation of the rooftop PV system in a preliminary feasibility study. [Copyright &y& Elsevier]

• Economic assessment of PV system was estimated considering government solar subsidy. • Optimal installation strategy of PV system was derived using GA and Pareto optimum. • The nine scenarios were established for analyzing life-cycle assessment. • Optimal government solar subsidy program was estimated based on nine scenarios. • The results will help policymakers to establish the solar subsidy program scheme. Since the current government solar subsidy does not consider the economic effect that varies depending on the operating entity of the government solar subsidy program, the implementation of photovoltaic (PV) in multi-family housing complexes (MFHCs) has limitations. Thus, this study aimed to establish the optimal government solar subsidy program for promoting the installation of PV in MFHCs. Toward this end, this study established nine scenarios considering government solar subsidy programs and MAECH and conducted a life-cycle economic assessment. When installing the optimal power capacity of PV in MFHC, the range of the net present value in 25 years increase from US$8,873.54 to US$588,626.83 when the MAECH increased from 200 to 600kWh. When installing the maximum power capacity of the PV in MFHC, the shorter the target breakeven point is, the greater the government solar subsidy the government must support for the MFHC becomes. Government solar subsidies of up to US$966.46/kW and US$938.99/kW, respectively, are required to meet the economic profitability of the PV within 4 and 5 years of breakeven point. The results of this study make it possible for policymakers to establish a government solar subsidy scheme and for residents to determine the optimal government solar subsidy program. [ABSTRACT FROM AUTHOR]

This study was conducted to ascertain how the use of recycled materials instead of virgin materials affect the installation of renewable energy systems for the energy transition of buildings. LCA was used to estimate the life cycle energy use and GHG emissions of building and renewable energy systems with and without using recycled materials. For the case study, a public building and four representative photovoltaic (PV) systems were selected. National recycling standards and processes were considered for suggested recycled materials. In general, replacing virgin material with recycled counterpart reduced embodied GHG emissions more than embodied energy. However, due to high carbon intensity of operation energy and building materials without available counterparts, using recycled materials reduced the life cycle energy use and GHG emissions of the case building by 4.9% and 3.3%. Among four PV systems, using recycled materials was most significant in the single crystalline-silicon (sC-Si) PV system, 44.5% reduction of energy use and 41.3% reduction of GHG emissions. Therefore, when recycled materials are used for achieving the energy transition of the case building with the sC-Si PV system, the PV system requirements could be reduced by a maximum of 9.6% for energy payback and 4.9% for GHG payback. This study demonstrated that the use of recycled materials is effective at reducing the embodied energy and GHG emissions of PV systems as well as buildings. To achieve carbon-neutral buildings, particularly, the use of recycled materials based on a thorough LCA should be considered in addition to renewable energy system. • Analyzing recycled materials' impact on building energy conservation and transition. • Life cycle assessment for building and PV system was conducted through a case study. • National recycling standard and process were applied for practical recycled material. • Impact of recycled materials was determined by carbon intensity of material and grid. • This study can help to consider an important factor for a carbon-neutral buildings. [ABSTRACT FROM AUTHOR]

Installing the battery energy storage system (BESS) and optimizing its schedule to effectively address the intermittency and volatility of photovoltaic (PV) systems has emerged as a critical research challenge. Nonetheless, some existing studies still have limitations in terms of the efficiency of the BESS scheduling due to the lack of comprehensive consideration of diverse user objectives. As a response to this gap, this study aimed to develop a reinforcement learning (RL)-based optimal scheduling model to better reflect the continuous behaviors in the complex real world. To this end, focused on residential buildings connected to the grid and equipped with a BESS and PV system, its optimal scheduling models were developed using four algorithms from among the various RL techniques according to training methods. The results of the case study showed that the developed RL-based optimal scheduling model using Proximal Policy Optimization (PPO) can be applied to effectively operate the BESS with a PV system, considering possible uncertainties in the real world. The case study demonstrated the effectiveness and feasibility of the developed RL-based optimal scheduling model. Compared to other algorithms, the PPO-based RL model has better decision-making for optimal BESS scheduling strategies to maximize their self-sufficiency rate and economic profits by coping with changing variables in the real world. Therefore, the RL-based BESS scheduling model will offer an optimal solution, specifically tailored for use within a virtual power plant, where numerous buildings continuously share electricity. [Display omitted] • Reinforcement learning-based scheduling model of battery energy storage system was developed. • Multi-objective optimization for the scheduling of battery energy storage was conducted. • Proximal policy optimization-based scheduling model outperformed the other three algorithms. • The developed model can provide an optimal solution for prosumers in microgrid. [ABSTRACT FROM AUTHOR]

Reducing peak demand and enhancing self-sufficiency have made the battery energy storage system (BESS) essential in microgrids when combined with photovoltaic (PV) systems. Previous studies have shown that BESS usage remains expensive, and it is more practical to share it within a community rather than installing individual systems. Therefore, this study aimed to propose a framework for BESS sizing and scheduling in an energy-sharing community based on reinforcement learning. To validate the proposed framework, a case study was conducted based on the BESS ownership scenarios (i.e., individual-owned BESS (IOB) and community-shared BESS (CSB)) considering the following purposes of potential stakeholders: (i) enhancing SSR; (ii) reducing peak demand; and (iii) increasing economic profit. The maximum SSR of CSB was 12.4% higher than IOB, while the peak load of CSB was 0.07% lower than IOB. As the BESS size increased, the total cost of BESS increased, and the total profits on electricity decreased. The economic profit increased by about 38% when CSB was used compared to IOBs. The proposed framework offers more promise for a broader range of building loads and PV generation within the energy-sharing community. Ultimately, this study would allow prosumers, community practitioners, and policymakers to better understand the sharing mechanisms in the community and provide decision guidelines for ownership types, operational strategies, and sizing of BESS and PV systems. • This study proposes a framework for sizing and real-time scheduling of the BESS. • Reinforcement learning is used to conduct multi-objective optimization in this study. • A case study conducts at different battery ownership scenarios in energy communities. • Sharing a battery for economic gain proves more beneficial than individual ownership. • This study facilitates determination of the optimal schedule and capacity for BESS. [ABSTRACT FROM AUTHOR]

• Psychological satisfaction by VLT of thin film PV was measured using VR experiment. • Psychological satisfaction results were verified through physiological response. • The energy and economic performance by VLT of thin-film PV were analyzed. • Psychological satisfaction and economic performance determined the optimal VLT. • The optimal VLT can range between 15.8 and 22.6% depending on the house type. Despite the recent growth in installing photovoltaic (PV) systems in buildings, densely populated cities with high-rise buildings have limited space for rooftop PV systems, leading to semi-transparent PV systems being considered an alternative. However, thin-film PV can reduce visibility from windows, potentially negatively impacting satisfaction and visual comfort of occupants. Therefore, this study aims to experimentally verify the efficiency of cadmium-telluride (CdTe) thin-film solar cells with different visible light transmittance (VLT) values and find the optimal VLT of thin-film PV that can be applied to building windows. To this end, this study measured the psychological and physiological responses of occupants through VR experiments and analyzed the energy performance and economic feasibility using energy simulation tools and life cycle cost analysis. Consequently, the optimal VLT varied between 15.8% and 22.6% based on factors such as psychological satisfaction and economic performance. Additionally, the physiological response demonstrated that the level of psychological satisfaction with the implemented changes was influenced by the VLT of thin-film PV. Hence, this study recommends guidelines for VLT when developing thin-film PV, which can contribute to determining the optimal VLT of thin-film PV, considering both psychological satisfaction of occupants and economic performance targeted by potential decision-makers. [ABSTRACT FROM AUTHOR]

• The technical & economic performance of the window-integrated PV system was evaluated. • The analysis was conducted on a 3rd generation PV panel with transparency. • In South Korea, window-integrated PV system with 3rd generation PV panel is feasible. • The 3rd generation PV panel is also economical and can open up a new market. • The window-integrated PV system is one of the strategies for net-zero energy building. To reduce the energy consumption of buildings by installing PV panels therein, it is important to accurately predict the technical and economic performance of the PV panels to be installed and to determine whether their installation will result in profits. In this study, a window-integrated PV system was proposed that combines the exterior window of a building with PV panels, and its technical and economic performance was analyzed. To this end, a residential building in Seoul, the most populous area in South Korea, was used as a reference model, and third-generation PV panels were analyzed. The main findings are as follows. First, with respect to the technical performance of the PV panels, the window-integrated OPV system installed in household type B generated the most annual electricity (923.34kWh). However, the window-integrated OPV system installed in household type C generated the most annual electricity per unit area (36.64 kWh/m2). Second, the NPV 20 and SIR 20 increased as the household's monthly electricity consumption increased and the closer to the south the orientation of the PV panel was. These results show that the window-integrated PV system that used the third-generation PV panel is expected to be one of the active strategies for achieving net-zero-energy buildings. [ABSTRACT FROM AUTHOR]

• The optimal scheduling model of ESS with PV in residential buildings is developed. • Multi-objective optimization is conducted from economic and environmental aspects. • The trade-off between the economic and environmental benefits was confirmed. • Economic and environmental benefits can be increased by the optimal scheduling model. • It is not feasible to adopt the residential ESS under the reduced REC weight. In terms of sustainable development, the Energy Storage System (ESS) with a photovoltaic (PV) is an efficient technology for residential distributed generation to raise its economic and environmental benefits, which are differentiated by charge and discharge scheduling of ESS. Accordingly, it is essential to optimize the scheduling of ESS with PV to maximize economic and environmental benefits for residential buildings. Therefore, this study developed an optimal scheduling model of ESS with PV in residential buildings considering the economic and environmental aspects. The optimal scheduling model was developed in the following two steps: (i) definition of the variables; and (ii) development of the optimal scheduling model of ESS with PV. Despite the rule-based scheduling could only raise lifecycle environmental benefit by sacrificing economic benefit, the optimal scheduling could raise both lifecycle economic and environmental benefits increasing the net income and self-sufficiency rate by up to US$2.8 per month and 2.7%, compared to the case of applying the PV system without ESS. This study has significant contributions in facilitating the wide use of ESS with PV by not only improving its economic and environmental benefits for the ESS owner but also reducing the cost for constructing additional power plants for the government. [ABSTRACT FROM AUTHOR]