• Energy Research

The transition towards energy efficiency in households is advancing slowly despite the increasing number of incentive policy interventions. It is imperative to assess the effectiveness of these interventions to prevent wasting resources or even jeopardizing the energy transition. An agent-based model was developed using the results of two discrete choice experiments to simulate the diffusion of 1) energy-efficient appliances and 2) heating & cooling systems among households. Policy interventions (information campaigns, engaging sales agencies, and providing district heating) on the diffusion of these two types of energy-efficient products have been simulated. The simulation results indicate that energy-efficient heating & cooling systems have the potential for widespread adoption, while appliances do not exhibit the same level of scalability. The results show that information campaigns targeting households' environmental attitudes have limited impacts on energy-efficient appliance diffusion while engaging sales agencies has a greater impact on energy-efficient appliance diffusion than information campaigns. Simulation results also show that district heating can achieve large-scale diffusion, and the main barrier to the diffusion is the accessibility of the infrastructure. This study contributes to designing effective strategies for accelerating energy transition in the residential sector.

The transition towards energy efficiency in households is advancing slowly despite the increasing number of incentive policy interventions. It is imperative to assess the effectiveness of these interventions to prevent wasting resources or even jeopardizing the energy transition. An agent-based model was developed using the results of two discrete choice experiments to simulate the diffusion of 1) energy-efficient appliances and 2) heating & cooling systems among households. Policy interventions (information campaigns, engaging sales agencies, and providing district heating) on the diffusion of these two types of energy-efficient products have been simulated. The simulation results indicate that energy-efficient heating & cooling systems have the potential for widespread adoption, while appliances do not exhibit the same level of scalability. The results show that information campaigns targeting households' environmental attitudes have limited impacts on energy-efficient appliance diffusion while engaging sales agencies has a greater impact on energy-efficient appliance diffusion than information campaigns. Simulation results also show that district heating can achieve large-scale diffusion, and the main barrier to the diffusion is the accessibility of the infrastructure. This study contributes to designing effective strategies for accelerating energy transition in the residential sector.

Abstract Despite strong governmental support, microalgae biodiesel has failed to report rapid growth in China. Thus, it is imperative to conduct an economic analysis on microalgae biodiesel so that useful inputs could be provided for policy making. The analysis is based on a model with a 100-ha production facility. In addition, a sensitivity analysis is performed in this study to determine critical factors contributing to the economic feasibility of microalgae biodiesel. Furthermore, a learning curve is employed to predict the production cost from 2019 to 2022. The production cost is estimated as USD 2.29/kg, which is significantly higher than that of commercial diesel. The findings highlight that biodiesel projects lack economic feasibility and the main barriers are microalgae productivity, annual operating days and product benefits. According to the learning curve prediction, these issues cannot be alleviated within a short period, particularly considering the limitations associated with the current policies. The study concludes with policy implications e.g. a policy system to facilitate the development of microalgae biodiesel.

Abstract Despite strong governmental support, microalgae biodiesel has failed to report rapid growth in China. Thus, it is imperative to conduct an economic analysis on microalgae biodiesel so that useful inputs could be provided for policy making. The analysis is based on a model with a 100-ha production facility. In addition, a sensitivity analysis is performed in this study to determine critical factors contributing to the economic feasibility of microalgae biodiesel. Furthermore, a learning curve is employed to predict the production cost from 2019 to 2022. The production cost is estimated as USD 2.29/kg, which is significantly higher than that of commercial diesel. The findings highlight that biodiesel projects lack economic feasibility and the main barriers are microalgae productivity, annual operating days and product benefits. According to the learning curve prediction, these issues cannot be alleviated within a short period, particularly considering the limitations associated with the current policies. The study concludes with policy implications e.g. a policy system to facilitate the development of microalgae biodiesel.

The built environment is responsible for a significant amount of energy consumption. Energy transition in the built environment is necessary for both sustainable development and energy security. Digital twin technologies are regarded as potential solutions for energy transition as they contribute to better energy management in buildings, communities, and cities. A literature review is conducted to investigate digital twin studies in the field of the built environment. It has been found that there has been significant growth in the number of digital twin studies since 2018. The keyword co-occurrence analysis was adopted to investigate the research topic and research trend. It is found that the studies of the digital twin in the context of built environment energy transition are insufficient, especially at the community level. The city-level digital twin studies either focus on transportation or buildings, and there is a limited number of studies about digital twin applications, especially at the city level. Moreover, studies failed to connect various aspects of a city system. More studies are needed to tackle digital twin application challenges and contribute to the energy transition.

The built environment is responsible for a significant amount of energy consumption. Energy transition in the built environment is necessary for both sustainable development and energy security. Digital twin technologies are regarded as potential solutions for energy transition as they contribute to better energy management in buildings, communities, and cities. A literature review is conducted to investigate digital twin studies in the field of the built environment. It has been found that there has been significant growth in the number of digital twin studies since 2018. The keyword co-occurrence analysis was adopted to investigate the research topic and research trend. It is found that the studies of the digital twin in the context of built environment energy transition are insufficient, especially at the community level. The city-level digital twin studies either focus on transportation or buildings, and there is a limited number of studies about digital twin applications, especially at the city level. Moreover, studies failed to connect various aspects of a city system. More studies are needed to tackle digital twin application challenges and contribute to the energy transition.

PurposeHousing energy consumption is a significant contributor to climate change. Encouraging the adoption of energy-efficient products can be an effective way to reduce energy consumption. The impacts of social influences, such as peer effects and social norms, on energy efficiency adoptions were identified; however, these social influences are not quantified and compared with each other or with other influences. This study aims to investigate the choice of energy-efficient product adoption with different costs and how different social influences affect the choice through different processes and paths.Design/methodology/approachTwo stated choice experiments were employed in Wuhan, China, to examine the impact of social influences on energy-efficient product adoption in low-cost and high-cost scenarios. Appliance packages (including fridges and washing machines) and heating and cooling systems were used for the two cost scenarios, respectively. The social influences are evaluated in three aspects: positive versus negative information, physical versus online social networks and peer effects versus social norms.FindingsThe study revealed how various factors, including social influences, impact energy-efficient product choices. Research results show that: (1) social influences have greater and wider impacts in the low-cost scenario than in the high-cost scenario; (2) negative information decreases the adoption of low-cost energy-efficient products, while positive information boosts high-cost energy-efficient product adoption and (3) people value the information provided by those they know personally and are more influenced by physical social networks.Originality/valueThis study contributes to a better understanding of social influence in energy-efficient product adoption with different costs. This study provides a comprehensive framework to investigate social influences comparing the impact of different processes, paths and types of information. The findings can also provide practical implications for policymakers to accelerate the energy transition in the built environment.

PurposeHousing energy consumption is a significant contributor to climate change. Encouraging the adoption of energy-efficient products can be an effective way to reduce energy consumption. The impacts of social influences, such as peer effects and social norms, on energy efficiency adoptions were identified; however, these social influences are not quantified and compared with each other or with other influences. This study aims to investigate the choice of energy-efficient product adoption with different costs and how different social influences affect the choice through different processes and paths.Design/methodology/approachTwo stated choice experiments were employed in Wuhan, China, to examine the impact of social influences on energy-efficient product adoption in low-cost and high-cost scenarios. Appliance packages (including fridges and washing machines) and heating and cooling systems were used for the two cost scenarios, respectively. The social influences are evaluated in three aspects: positive versus negative information, physical versus online social networks and peer effects versus social norms.FindingsThe study revealed how various factors, including social influences, impact energy-efficient product choices. Research results show that: (1) social influences have greater and wider impacts in the low-cost scenario than in the high-cost scenario; (2) negative information decreases the adoption of low-cost energy-efficient products, while positive information boosts high-cost energy-efficient product adoption and (3) people value the information provided by those they know personally and are more influenced by physical social networks.Originality/valueThis study contributes to a better understanding of social influence in energy-efficient product adoption with different costs. This study provides a comprehensive framework to investigate social influences comparing the impact of different processes, paths and types of information. The findings can also provide practical implications for policymakers to accelerate the energy transition in the built environment.

The potential benefits of adopting PV (photovoltaic) in residential apartments in China, such as reducing peak demand and electricity transmission issues, have been overlooked. Community PV is more applicable for most Chinese cities residents living in apartment buildings. However, existing studies failed to provide comprehensive insight regarding factors influencing community PV adoption and adoption decision strategies. This study utilized a discrete choice experiment performed in Wuhan to examine individuals' community PV adoption preferences and analyze the factors influencing their decisions. The study found that respondents who were well-educated, older than 40, lived in residential buildings constructed earlier than 2006, had a living area >120 m 2, or used AC for more months in the summer were more likely to adopt PV. Three decision strategies (classes) with different PV product preferences were identified. Peer effect is identified to significantly influence the community PV adoption as almost 65% of the respondents are more likely to adopt PV if there are high neighboring PV adoption or installation agreement rates. Cost was not a determining factor for a significant proportion of respondents, who instead focused on revenue. Subsidy policies also had limited influence, affecting only about 43% of respondents. Policy implications are provided based on the research results.