A framework for analyzing city-wide impact of building-integrated renewable energy

Song, Jeonghun; Song, Seung Jin

doi:10.1016/j.apenergy.2020.115489

Cited by 21 publications

(4 citation statements)

References 46 publications

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“…Many studies have shown that the technical components for adoption and fast penetration of renewables in households are important as well [52]. Building-integrated renewable energy and smart digitalized home technologies with integrated energy management systems can considerably enlarge the penetration of renewable energy in residential buildings, as well as increase the willingness to pay for renewables in households [53][54][55].…”

Section: Policies To Overcome Barriers Of Renewable Energy Technologi...mentioning

confidence: 99%

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Renewable Energy Acceptance by Households: Evidence from Lithuania

et al. 2022

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Although renewable energy adoption in the residential sector has increased significantly in the EU due to the governmental policies, aiming to reduce the barriers of renewable energy penetration, the full potential of renewable energy deployment in households is still not realized due to the behavioral and other barriers. One of the most important factors in the adoption of renewable energy technologies in households is the decision-making to implement renewables; therefore, the behavioral economics insights should be taken into account during the analysis of renewable energy acceptance by households. The paper provides a systematic literature review on renewable energy use in households by analyzing policies and measures, which could increase the use of renewable energy in households by overcoming the major barriers. The dynamics of renewable energy consumption in EU households was performed by applying Eurostat data, and the empirical case study was conducted in Lithuania to understand the main reasons of renewable energy acceptance by the household. Even though the use of renewable energy sources has increased significantly in the EU member states during the recent years, the study has found the following most common barriers that the traditional policies are unable to overcome: (1) high upfront cost and long pay-back period, (2) a lack of information and knowledge, (3) low priority of environmental concern, (4) resistance to change; human habits. The case study shows that the majority of Lithuanian households would like to use renewable energy technologies in their homes, but they encounter financial difficulties and lack of infrastructure. The policy recommendations were developed based on the results of the conducted study.

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Section: Policies To Overcome Barriers Of Renewable Energy Technologi...mentioning

confidence: 99%

“…Policies and measures to promote renewables in households, linking them to the main barriers[48][49][50][51][52][53][54][55][56][57][58].…”

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confidence: 99%

Renewable Energy Acceptance by Households: Evidence from Lithuania

et al. 2022

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“…Viable RE systems for buildings typically include photovoltaic (PV) panels, wind turbines, solar thermal energy, combined heat and power systems (CHPs), and ground source heat pumps (GSHPs) [18]. These RE sources can be exploited for on-site or distributed energy supply to buildings [20,21] and can be utilized to provide electricity, heating, and cooling [22]. The utilization of RE sources is integral to the achievement of green buildings and green communities, as evidenced by various studies [19,[23][24][25].…”

Section: Introductionmentioning

confidence: 99%

Challenges and Strategies for Achieving High Energy Efficiency in Building Districts

Chen,

Vand,

Baldi

2024

Buildings

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Achieving climate neutrality requires reducing energy consumption and CO2 emissions in the building sector, which has prompted increasing attention towards nearly zero energy, zero energy, and positive energy communities of buildings; there is a need to determine how individual buildings up to communities of buildings can become more energy efficient. This study addresses the scientific problem of optimizing energy efficiency strategies in building areas and identifies gaps in existing theories related to passive design strategies, active energy systems, and renewable energy integration. This study delineates boundaries at the building and community scales to examine the challenges of attaining energy efficiency goals and to emphasize the intricate processes of selecting, integrating, and optimizing energy systems in buildings. The four boundaries describe: (B1) energy flows through the building envelope; (B2) energy flows through heating, ventilation, air conditioning and energy systems; (B3) energy flows through individual buildings; (B4) energy flows through a community of buildings. Current theories often treat these elements in isolation, and significant gaps exist in interdisciplinary integration, scalable frameworks, and the consideration of behavioral and socioeconomic factors. Achieving nearly zero energy, zero energy, and positive energy communities requires seamless integration of renewable energy sources, energy storage systems, and energy management systems. The proposed boundaries B1–B4 can help not only in analyzing the various challenges for achieving high energy efficiency in building communities but also in defining and evaluating these communities and establishing fair methods for energy distribution within them. The results demonstrate that these boundaries provide a comprehensive framework for energy-efficient designs, constructions, and operational practices across multiple buildings, ensuring equitable energy distribution and optimized performance. In addition, the definition of boundaries as B1-B4 contributes to providing an interface for energy-efficient designs, constructions and operational practices across multiple buildings.

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“…Due to the increasing cost and carbon emission of conventional fossil energy, renewable energy has gradually gained increasing interest in the research community (Leirpoll, et al, 2021), including architecture (Song & Song, 2020). As the representation of renewable energy sources, solar energy has great potential capacity to building energy management (Guermoui, Melgani, & Danilo, 2018).…”

Section: Introductionmentioning

confidence: 99%

Solar radiation nowcasting through advanced CNN model integrated with ResNet structure

Chen¹,

Li²,

Du³

et al. 2021

Building Simulation Conference Proceedings

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Although a range of solar radiation forecasting methods have been developed for predicting photovoltaic generation, only a few of them focus on solar radiation forecasting for building energy demand. From the perspective of building performance modelling, solar radiation forecasting needs to meet several critical requirements including high spatial resolution (1m-2km) and high temporal resolution (5-60mins), the accurate value of Direct Normal Irradiance (DNI) and Diffuse Horizontal Irradiance (DHI), which differs the requirement for predicting photovoltaic generation. As the geometric sum of DNI and DHI, accurate prediction of Global Horizontal Irradiance (GHI) with high spatialtemporal resolution tends to be the prerequisite for precise prediction of DNI and DHI. This research aims to construct a hybrid nowcasting model to predict GHI in high spatial-temporal resolution. In this article, the authors adopt an advanced Convolutional Neural Network (CNN) model with Residual Neural Network (ResNet) structure to identify the cloud image information and predict the GHI at 10 minutes intervals merely using cloud images captured by a ground-based sky camera. On this basis, several ResNet structures are compared to achieve the optimal nowcasting model for GHI. The results present that the ResNet structure can efficiently capture the cloud information and the ResNet-152 achieves better performance than other alternative structures on the nowcasting of GHI. Finally, the authors discussed the calculation of synchronous DNI and DHI using the predictive GHI and Dirint model, and the application of DNI and DHI as the input for the simulation of building energy management. Key Contributions• Classifying solar radiation forecasting methods and reviewing recent representative articles. • Proposing a hybrid method using CNN-ResNet models to nowcast solar irradiance. • Only using ground-based cloud images as input to predict solar irradiation. • Comparing several ResNet structures to achieve the optimal nowcasting model for GHI. Practical ImplicationsThis study makes it possible for relevant researchers to utilise predictive solar radiation data in a convenient manner, taking only cloud images as input instead of other difficult-to-obtain weather data.

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A framework for analyzing city-wide impact of building-integrated renewable energy

Cited by 21 publications

References 46 publications

Renewable Energy Acceptance by Households: Evidence from Lithuania

Renewable Energy Acceptance by Households: Evidence from Lithuania

Challenges and Strategies for Achieving High Energy Efficiency in Building Districts

Solar radiation nowcasting through advanced CNN model integrated with ResNet structure

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