Energy Conservation Awareness Research Articles

An Investigative Study on the Development Strategies for Electric Vehicle Enterprises

With the continuous development of science and technology, cars have become an indispensable means of transportation for human beings in daily travel. More and more cars appear in our life. In recent years, as consumer awareness of energy conservation and environmental protection has increased, global demand for sustainable development has increased, and many new energy vehicles. Because the non-renewable resources such as oil and natural gas needed by traditional fuel cars are consumed faster and faster, the exhaust emissions of traditional cars are polluting the environment increases, so new energy vehicles are the future development trend of the automobile industry. With the international context of the rapid development of new energy trams, the sales volume of electric vehicles in China's automobile market is not good. Through data analysis and industry research, the key factors and reasons affecting the development of electric vehicles are found, make certain suggestions to Chinese new energy electric vehicle companies, in order to change the current situation of low sales of new energy vehicles, the report objectively and truly analyses the future planning of the development of Chinese electric vehicle enterprises and the change of the development trend, as well as the moderate fine-tuning of the sales pricing.

Sustainable Energy Consumption Insights: Understanding Electricity-saving Behaviour Drivers among Young Adults in Ho Chi Minh City

As Vietnam’s population continues to grow, there is a growing need for sustainable societal development. The energy-saving behaviour of every citizen plays a crucial role in achieving this sustainability. Therefore, it is necessary to raise awareness among young adults about energy conservation and environmental protection to promote sustainable social development in Vietnam. Hence, this study aims to examine the key factors influencing electricity-saving and habitual energy-saving behaviour. Data were collected from 431 young adults aged 18 to 30 years old in Ho Chi Minh City. The results indicate the significance of the model studied, with all hypotheses being accepted. The findings demonstrate that several factors, including subjective standards, perceived behavioural control, awareness of consequences, sense of responsibility, personal moral norms and cognition of electricity prices, influence electricity-saving behaviours and habitual energy-saving behaviour related to electricity usage. The findings suggest that young adults are increasingly recognising the importance of conserving electricity in modern life to protect the environment and promote sustainable social development in Vietnam. The management implication suggests that individuals in Ho Chi Minh City have demonstrated an awareness of energy conservation. However, responsible authorities should initiate programmes aimed at promoting electricity-saving practices. This includes the creation of media articles to raise awareness and enhance the understanding of electricity-saving measures, serving as reminders to increase awareness about conserving electricity among every individual. Furthermore, this study offers theoretical and practical implications for researchers and policymakers alike.

Simulation of fishery energy consumption and carbon emissions in Zhoushan City based on the long-range energy alternatives planning system model

To understand the current situation and development trend of energy consumption and carbon emissions in the fishery industry, a Long-Range Energy Alternatives Planning System (LEAP)-fishery model for Zhoushan City was constructed, and the trends of energy consumption and carbon emissions in the Zhoushan City fishery industry were analyzed under the business-as-usual scenario, the low-carbon scenario, and the strengthened low-carbon scenario. The results show that under the business-as-usual scenario, the future energy consumption of Zhoushan City’s fisheries in general shows an increasing trend, and the composition of energy consumption in all scenarios is primarily dominated by fossil energy, with diesel and coal predominating. In terms of the structure of end-use energy consumption, fishing vessels and aquaculture consume the most energy, with energy consumption exceeding 30% of total energy consumption in all scenarios. In terms of the emission reduction contribution rate, which the promotion of clean energy generation, the improvement of energy efficiency, and the reduction of aquaculture production play key roles in the low-carbon development of the fishery industry. From an economic perspective, carbon reduction measures such as reduction of aquaculture production and increased efficiency of energy delivery would have significant economic benefits, but these measures have limitations. Finally, suggestions are made to optimize the energy structure, improve the implementation of energy intensity and total energy control, and strengthen public awareness of energy conservation to reduce carbon emissions from the fishery industry, thus making the research in this paper relevant to real-world situations.

Research on energy efficiency and decarbonization pathway of nearly zero energy buildings based on system dynamic simulation

Accounting for over 40% of the total energy consumption, the global building sector is pivotal for achieving carbon peak and neutrality objectives. The intricate nature of building carbon emissions, influenced by spatial, temporal, and multifactor coupling, poses challenges on implementing carbon-neutral technologies and conservation strategies. This study focuses on nearly zero energy buildings in China and employs system dynamics to predict energy consumption and carbon emissions according to various scenarios, unveiling influencing patterns and viable emission reduction pathways. The results highlight the substantial impact of enhancing energy conservation awareness as this leads to a 36.4% reduction in energy consumption and a 44.2% reduction in carbon emissions. To attain energy efficiency and carbon reduction goals, a comprehensive approach is essential, encompassing improved building performance, heightened resident energy awareness, increased renewable energy use, and energy landscape adjustments. These findings inform future building energy and carbon emission regulations and offer valuable policy insights.

Clustering and prediction of space cooling and heating energy consumption in high-rise residential buildings with the influence of occupant behaviour: Evidence from a survey in Changsha, China

Residential building space cooling and heating energy consumption account for approximately 15% of the total social energy consumption. Occupant behaviour is the primary factor influencing energy consumption for cooling and heating in residential buildings. This study used extensive face-to-face questionnaire surveys and actual measurements for typical households to study the cooling and heating energy consumption of high-rise residential buildings in Changsha. Statistical analysis was conducted on the influencing factors of participant information, architecture, occupant behaviour, and energy conservation awareness in the questionnaire survey. The household energy bills for cooling and heating were clustered, and PCA models were proposed between the influencing factors and the energy consumption, and were verified by measured data of typical households. The results demonstrated that the household energy bills could be divided into five categories. The PCA models show the mode of ventilation during the cooling period and the mode of air conditioner (AC) turning on/off during the heating period are the most important component, accounting for 46.7% and 35.9%, respectively. The statistical parameters provided a reference for the energy consumption simulation software, and the PCA models achieved energy consumption prediction through data of principal components, which are significant for building energy efficiency and carbon reduction.

Review and modeling: Approach to low-carbonize the whole industry chains of integrated energy systems

Industries are undergoing low-carbon evolution with worldwide awareness of energy conservation. As the super key to processing it, integrated energy systems (IESs) are receiving more attention, in terms of cutting carbon emissions actively and passively. Until now, many well-established strategies have been proposed to low-carbonize IESs. However, issues still remain in implementing low-carbonization throughout the whole industry chain. In this context, critical technologies and available flexible resources at different levels of IESs, i.e., the transmission, distribution/district, and residential levels, are reviewed first in this paper. Then, flexible resources in the source, network, load, and storage are remodeled to minimize carbon emissions more directly. In this manner, CO2 in the whole industry chains of IESs can be marked and traced, which is named after the “all-carbon chain” here. Besides, as an original content of this paper, new technologies, i.e., CO2 flooding and Organic Rankine Cycle (ORC), get introductions for low-carbonizing IESs further. Last but not least, an actual large-scale IES is employed to verify the proposed approach from the transmission and distribution/district levels. It is concluded that the all-carbon chain is complex-less when applied in a bi-layer integration process and a weak-convex update formula also could ensure convergence (within 44 iterations). Besides, our approach helps to cut carbon emissions when compared with the traditional IES (by 50.61%) and two low-carbon IESs (by 18.37% and 12.09%). Moreover, our method makes IES enjoy a purposeful evolution for more functions of low-carbonization, source tracing, targeted evolution, and contribution quantification are covered.

Inherent Complexity and Early Warning of Zaozhuang Circular Economy System

Based on China’s green energy development strategy, this paper constructs a basic model of recycling and a channel expansion model for the circular economy foundation of Zaozhuang, Shandong Province, China. Through numerical simulation, it is found that each member of the supply chain should control the rate of price adjustment, otherwise it will cause market disruption. The model is controlled based on a chaos control method. Then, based on the fuzzy comprehensive evaluation method, an early warning system for the circular economy of Zaozhuang City is constructed. It is found that the economic development of Zaozhuang is a serious warning, resources are moderate warning, and the environment is not in an alarm state. In addition to paying attention to energy conservation and emission reduction of enterprises, the government should pay attention to creating awareness of energy conservation and emission reduction in society, and strengthen the technological investment in reducing pollutant emissions. This paper provides a strategic reference for the circular economy model in Zaozhuang, Shandong, China.

A Two-Stage Multi-Agent EV Charging Coordination Scheme for Maximizing Grid Performance and Customer Satisfaction

Advancements in technology and awareness of energy conservation and environmental protection have increased the adoption rate of electric vehicles (EVs). The rapidly increasing adoption of EVs may affect grid operation adversely. However, the increased integration of EVs, if managed appropriately, can positively impact the performance of the electrical network in terms of power losses, voltage deviations and transformer overloads. This paper presents a two-stage multi-agent-based scheme for the coordinated charging scheduling of EVs. The first stage uses particle swarm optimization (PSO) at the distribution network operator (DNO) level to determine the optimal power allocation among the participating EV aggregator agents to minimize power losses and voltage deviations, whereas the second stage at the EV aggregator agents level employs a genetic algorithm (GA) to align the charging activities to achieve customers' charging satisfaction in terms of minimum charging cost and waiting time. The proposed method is implemented on the IEEE-33 bus network connected with low-voltage nodes. The coordinated charging plan is executed with the time of use (ToU) and real-time pricing (RTP) schemes, considering EVs' random arrival and departure with two penetration levels. The simulations show promising results in terms of network performance and overall customer charging satisfaction.

The promotion strategies of heat metering and charging in China’s heating region based on complex network evolutionary game model

Abstract Heat metering and charging can help raise residents’ awareness of energy conservation and save heat consumption in buildings. The heat metering and charging in China, however, was promoted insignificantly. To explore the behavior mechanism of heat-supply enterprises implementing heat metering and charging under the background of complex network in China’s heating region, and put forward the promotion strategies of heat metering and charging, this paper uses the heat-supply enterprises as the sample, improves the utility function of heat-supply enterprises by considering their difference aversion preference and altruistic preference at the same time based on the Difference Averse Surplus Maximizer Model. Then, we establish a complex network evolutionary game model among different heat-supply enterprises, and an empirical analysis is conducted to examine the impact of different factor on heat-supply enterprises in China’s heating region to implement heat metering and charging. The conclusions are as follows: (1) With the current heating cost and income, even if the government subsidizes all environmental benefit generated by heat metering and charging to heat-supply enterprises, the heat metering and charging could not be promoted in different scales of networks. (2) Increasing metering heat price, government fine, environmental protection tax and carbon emission trading price have positive effects on the promotion of heat metering and charging in different scales of networks. (3) The value of metering heat price, government fine, environmental protection tax and carbon emission trading price have no significant impacts on the evolutionary speeds of different scales of networks.

Research on Carbon Emission Characteristics of Rural Buildings Based on LMDI-LEAP Model

Based on the emission factor method and LMDI-LEAP model, this paper systematically studies the current situation, influencing factors and changing trend of carbon emissions from rural buildings in a typical village located in southern China. The results showed that (1) the per capita carbon emissions generated by the energy consumption of rural buildings is 2.58 tCO2/a. Carbon emissions from electricity consumption in buildings account for about 96.07%; (2) the per capita building area, building area energy intensity, population size, population structure and carbon emission coefficient affect rural building carbon emissions, with contribution rates of 70.13%, 31.27%, 0.61%, −1.21% and −0.80%, respectively; (3) from 2021 to 2060, the carbon emissions of rural buildings are expected to increase first and then decrease. In 2021, the base year, carbon emissions from buildings were 2755.49 tCO2. The carbon emissions will peak at 5275.5 tCO2. Measures such as controlling the scale of buildings and improving the utilization rate of clean energy can effectively reduce carbon emissions, in which case the peak can be reduced to 4830.06 tCO2. Finally, the countermeasures and suggestions about rural building energy saving and emission reduction are proposed, including improving the construction management, raising energy efficiency standards in buildings, increasing the proportion of clean energy and raising residents’ awareness of energy conservation.

Air quality assessment based on R/S-SPA composite model: A case study of the Hebei province (China).

Air pollution has been the favorite subject of pollution prevention and control measures with the aim of sustainable development. Therefore, a composite model of rescaled range (R/S) and set pair analysis (SPA) was constructed to evaluate the air pollution situation based on the data from 2013 to 2020 in the Hebei province and then predict its air quality development trend. The results show that (1) the air pollution situation is severe, but the development trend is good and (2) the main pollutants are the core factors affecting air quality, and it is necessary to focus on intervention. The innovation of this paper lies on the combination of R/S and SPA to jointly predict the development trend of air quality in the Hebei province and ensure its scientific prediction. Meanwhile, this paper does not point out the continuation cycle of development state, which is the limitation of this paper. Finally, this study deepens the understanding of air quality evaluation, and the following countermeasures are formed: adherence to the problem- and goal-oriented approach to help the transformation of low-carbon development and enhancing the awareness of energy conservation and environmental protection to practice low-carbon lifestyle.

Awareness on energy conservation: a case study of first-year undergraduate students in Malaysia

PurposeThis paper aims to evaluate the awareness level of university students on energy conservation by focusing on their knowledge, attitude and practice. Energy awareness is a feasible energy conservation measure, but an inappropriate approach can cause the wastage of resources. The current number of reported awareness studies especially among the university student is quite limited, and focus is more given to the awareness on renewable energy, instead of energy conservation.Design/methodology/approachA paper-based survey using a set of questionnaires that involved 2,857 respondents. There are four sections in this questionnaire, which are basic background information of respondents, knowledge (yes/true or no/false choice of responses), attitude (a scale of 1–10, where 10 indicates “strongly agree” and 1 chooses “strongly disagree”) and practices (a scale of 1–10, where 10 indicates “Always” and 1 selects “Never”). The evaluation includes the correlation analysis of all awareness variables with an educational background to disclose the most critical aspects that should be highly considered in the forthcoming awareness campaign.FindingsThis research revealed that university students have a high level of awareness of energy conservation. They hold a high knowledge level and show a positive attitude with very good energy conservation practices. However, some issues require serious attention in preparing energy management plans. Effective approaches should be taken by considering the field of study, gender and family economic status to enhance the awareness level of the university students on energy conservation.Originality/valueThe absence of appropriate references complicates the preparation of energy management plans including the establishment of energy policy and strategies. The findings of this research can contribute some contextual information in the local perspective to ensure the effectiveness of the energy management program and strengthen academic leadership by emphasising the element of sustainability. This is crucial for developing an energy saving culture among the young generation that will be our future scholars and leaders.

Diffusion of Green Building Design Concept in New Housing Construction

With the development of the times and the deepening of environmental pollution, the government has begun to manage and developed energy conservation, and gradually established and improved related legal systems and safeguard systems. At the same time, human beings have begun to turn to protect the environment while feeling that the environment is at risk, and constantly improved their awareness of energy conservation and environmental protection. Therefore, in the process of rapid development of manpower, material resources, and technology, we must strengthen the development of green buildings and protect the environment. This paper discusses the coupling law of green building evaluation system, the development significance of green building and its design concept.

ENERGY EFFICIENCY AWARENESS AND PRACTICES BASED ON ISLAMIC PERSPECTIVES

Currently, the main environmental concerns encountered by most countries are energy and its consumption. A green lifestyle and energy efficiency (EE) could reduce daily energy consumption. Nevertheless, low awareness and knowledge of EE prevent proper green lifestyle practices to save energy and the environment. Thus, the study aims to examine building occupants’ EE and energy conservation awareness and practices based on Islamic perspectives. The study objectives are to examine the level of EE awareness and practices among Malaysian building occupants and incorporate the potential of Islamic teachings from al-Quran concerning energy consumption and conservation in the EE awareness campaigns. The study used the qualitative research method, which involved a literature review, observation, and narrative study. As a result, the significant relevance of EE awareness and practices along with Islamic teachings is explained further in this study. Moreover, instilling knowledge, creating awareness and encouraging occupants to implement EE practices, which consequently reduce energy demand and energy consumption, hence, mitigating the detrimental environmental impacts. The study is crucial in raising public awareness of the Islamic perspectives linked with energy conservation and provides a framework for future development plans that embody EE elements aligned with Islamic teachings.

Influencing factors and paths of direct carbon emissions from the energy consumption of rural residents in central China determined using a questionnaire survey

Rural residents have unique lifestyle characteristics, energy consumption methods, energy-saving behaviors, and awareness. And the direct carbon emission from rural residents is based on the combined effect of multiple factors. In order to address the complexity of factors affecting the direct carbon emissions from rural household, this study used a structural equation model to examine the effect of multi-factor variables on direct carbon emissions from rural households in central China. Data were collected using questionnaires and surveys in six cities in central China to reflect the daily reality of rural residents. The results show that quality of life and awareness of energy conservation can affect the direct carbon emissions of rural residents. Family characteristics and awareness of energy conservation affected carbon emissions indirectly by affecting the daily behaviors and quality of life of the residents; consumption characteristics, energy-saving behaviors, and energy conservation policies are not the main factors contributing to the direct carbon emissions of the residents. Based on the results, future studies can focus on energy conservation education, improvement of the living habits, coal energy use efficiency, and energy consumption structure of residences.

Impact of Climate Change Beliefs on Youths' Engagement in Energy-Conservation Behavior: The Mediating Mechanism of Environmental Concerns.

Global climate change presents a profound threat to the survival and continued development of humanity. The present study featured a survey of 3005 adolescents in China on 13 December 2021, aiming to determine whether climate change beliefs (including recognition of the existence of climate change, cognition of the causes of climate change, and climate change risk perception) influence their engagement in energy-conservation behaviors. Concurrently, the psychological mechanism underlying the influence of environmental concerns on the above relationship was also tested. The results showed that, among youths, climate change belief positively predicts engagement in energy-conservation behaviors. Specifically, awareness of the existence of climate change, knowledge of the causes of climate change, and climate change risk perception all positively predict engagement in energy-conservation behaviors. Further, environmental concerns were found to play a mediating role in the relationship between climate change beliefs and energy-conservation actions. From a practical perspective, the government and education departments should guide young people to develop accurate perceptions of climate change, and should raise their awareness of energy conservation and social responsibility, which should lead to their development of energy-conservation habits.

Optimal selective maintenance scheduling for series–parallel systems based on energy efficiency optimization

With the industry sustainable development and increasing awareness of energy conservation, many manufacturing enterprises prefer to develop the operation and maintenance (O&M) with high production throughput and low energy consumption. In reality, many manufacturing systems are required to conduct a sequence of predefined missions with finite breaks between any two consecutive missions. To successfully complete the next mission production, maintenance actions are arranged and performed on machines during each scheduled break. In this paper, an energy-oriented selective maintenance policy (ESMP) for series–parallel systems is investigated. At each break, multiple maintenance actions with different impacts on machine degradation are available under limited maintenance resources. To obtain the throughput-and-energy based maintenance scheme, we first model the system energy efficiency based on system throughput and energy consumption. Then, we integer the energy efficiency modeling, production throughout analysis, and selective maintenance scheduling into an optimization model. And the model objective is to find the appropriate maintenance action for each machine at each break subject to cost and duration constraints. Numerical examples have been addressed to demonstrate the performance and adaptability of our proposed ESMP in long-term selective maintenance scheduling. Finally, a comparative analysis with traditional reliability-oriented policy shows the significant improvement of energy efficiency.

Impact of Industry 4.0 on Green Decoration Materials in Public Architectural Engineering for Application of Energy Conservation and Environmental Protection

Industry 4.0 is derived from the concept of German industry, and its essence is to use technology for efficient production. However, the evolution in wireless technologies has opened the door to a new class of plant automation architecture that offers adopters a significant strategic advantage. Under the historical background of advocating low-carbon production, energy conservation and environmental protection, and sustainable development in various fields, the awareness of ecological energy conservation and environmental protection has gradually become a mainstream ideology. This paper principally studies the application of energy conservation and environmental protection green decoration materials in public architectural engineering projects to show the advantages of energy conservation and environmental protection green decoration materials in architectural decoration construction and analyzes the future development direction of public architectural decoration in China. Therefore, it is of great significance to improve the public environment and develop new ways of housing renovation with sustainable development goals to create a sustainable Industry 4.0 combining environmental protection and sustainability.

A robust non-intrusive load disaggregation method with roof-top photovoltaics

As a promising technology dealing with electric behavior analysis and energy characteristic mining, non-intrusive load monitoring is popular with these people with energy conservation awareness. Coincidentally, these residents are with strong motivation to install roof-top photovoltaics. Therefore, it is a real challenge to implement non-intrusive load disaggregation considering PV integrations, which is rarely researched. In this paper, this problem is thoroughly investigated with an achievement of a corresponding robust load disaggregation approach. At the first stage, the problem formulation is established based on the evolved dictionary learning scheme, where the special features of PV, e.g., no switching pattern and continuous power variation, are addressed. Secondly, aiming at robustness of monitoring, the steady state disaggregation is enhanced by integrating with event-based detection, forming a hybrid validation strategy. Then, the whole problem is solved following the sparse coding principle. The proposed study is verified by both simulation tests and field measurements, and the results show that the proposed method is accurate and robust in non-intrusive load monitoring with PV consideration. Besides, it is compatible with various load signature utilization, leading to a practical disaggregation solution.

Data-driven dynamic harmonic model for modern household appliances

With the rapid development of power electronics technology and the enhancement of users' energy conservation awareness, the proportion of modern household appliances with power electronic devices is increasing year by year, which has become an important harmonic source. Together with the massive access of home photovoltaic and electric vehicles, the harmonics of the existing residential low-voltage distribution system (RLVDS) show higher distortions and stronger dynamics than ever before. Therefore, an accurate harmonic model of the modern household appliance is necessary for power quality analysis and improvement. This paper proposes a data-driven dynamic harmonic coupled admittance matrix model (HCAMM) based on measured voltage and current data. First, the parameters of the HCAMM are solved by the partial least squares method (PLSM), which can effectively overcome the matrix pathology problem in the solution process, and the HCAMM can reflect the coupling effect between each harmonic. Second, to address the voltage dynamics, the dynamic HCAMM is established by combining the recursive PLSM and the adaptive update strategy, which can accurately characterize the harmonics under different supply voltages. Finally, the accuracy, dynamics, and generality of the proposed harmonic model are verified by simulations and experiments, and the harmonic model is applied to the power quality harmonic evaluation, line power loss calculation with harmonics, and energy saving by reducing the harmonics.