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The study applied the Theory of Planned Behavior - TPB (Ajzen, 1991) and the Norm Activation Model - NAM (Schwartz, 1977) to demonstrate the affecting factors on behavioral intention in energy saving of farmers in the Mekong Delta, Vietnam. Research data were collected from 204 farmer households using electricity in four provinces: Tien Giang, Dong Thap, An Giang, and Kien Giang. Applying the structural equation modeling (SEM), the study has pointed out the affecting factors mentioned above, including personal ethical standards, subjective norms, perceived behavioral control, perceived benefit, attitude, product quality, and energy policy. Besides, the study has shown that the intention to save electricity positively impacts the electricity-saving behavior of farmers

Electricity-saving can be achieved through the efficient use of energy such as turning off lights and electrical appliances when not in use. Therefore this work proposed the smart classroom for electricity-saving with an integrated IoT System to prevent wasting electricity in the classroom. Smart Classroom means that it will detect and count the number of students entering and exiting the classroom by using a sensor system automatically. The main objective of this work is to control the lighting systems and fans by using the IoT application and sensor system. This means that when the sensor is triggered the sensor will send data to the Blynk application software using IoT to display the status of the classroom. This proposed work is also able to detect whether a classroom is available to use or not based on the presence of people. If the classroom is being used the Blynk application software will show the lamp and fan are ON. Otherwise the lamps and fans are OFF if there are no people in the classroom. The result successfully shows that if the first student entering the classroom all the lamps and fans are ON. While if the last student exiting the classroom all the lamps and fans are OFF. This result also indicates that electricity can be saved if all appliances in the classroom are switch OFF at the right time.

Abstract In South Africa, the EDGE certification for green residential buildings, managed by the Green Building Council South Africa (GBCSA), is still developing. The study set out to examine the impact of EDGE-certification on electricity savings of residential buildings and how these savings can be converted into financial benefits. Quantitative research was the overarching research methodology, where a single case study approach was conducted using descriptive statistics. The single case study is situated in Gauteng, South Africa, and consisted of 503 EDGE-certified residential units. The research concluded that EDGE-certified residential units in Gauteng generate electricity savings, which when converted into monetary values can be transformed into real-world savings using different investment vehicles. In this study, real-world savings is defined as the tangible and measurable financial benefits realised from efficiencies associated with green buildings. The study found that such investments, including the use of the hypothetical EDGE Alternative Investment Fund (EAI Fund), result in real-world savings, demonstrating the financial benefits of EDGE certification for owner occupiers in the South African property market.

Energy efficiency opportunities in the industrial sector can reduce air emissions and benefit human health. One national-level energy efficiency program, the Department of Energy (DOE)-funded Industrial Assessment Center (IAC), provides US manufacturing facilities with cost-effective energy efficiency recommendations. However, the effect of the IAC on air quality and human health has not been explored. While several studies have evaluated the health impacts of air emissions reduction associated with energy efficiency, most of them did not consider regional differences in electricity grid profiles. These differences can change both emissions and health outcomes. This study focuses on air quality and health impacts of electricity and natural gas-related recommendations from the IAC program in 2022. It estimates 248 GWh of electricity, and 1.1E6 MMBtu of natural gas savings will result from the recommendations. Using the Environmental Protection Agency (EPA)’s Avoided Emissions and GeneRation Tool (AVERT) to estimate regional electricity emissions, published natural gas emission rates, and EPA’s co-benefit risk assessment (COBRA) tool, the total annual health outcomes associated with these savings range from 4.85 to 16.9 million USD (2023). This range includes different NO x emission rates and high and low COBRA estimates. Additionally, we introduce an energy savings health estimator (ESHE) tool that calculates air emissions and associated health outcomes of energy savings measures. We also apply it to the 2022 IAC recommendations and compare the health outcomes to those calculated using AVERT and COBRA separately. This tool can quickly estimate the health impacts of various energy efficiency projects or programs.

Given the substantial energy use for space cooling in buildings, integrating energy-efficient and sustainable cooling systems into buildings has become increasingly more important. Even though the cooling potential of a near-surface earth-to-air heat exchanger (EAHE) with grass cover was demonstrated in previous studies, the energy savings and environmental benefits resulting from using the EAHE have not yet been quantified. Therefore, in this study, we quantify the energy savings resulting from using a near-surface earth-to-air heat exchanger (EAHE) with grass-covered ground as a precooling unit in hot desert climates. The outlet air conditions of the EAHE during 9 months of the year (March to November), where space cooling is required, are predicted using a 3D transient CFD model, which is validated against field measurements. The EAHE is fabricated from a 1 mm thick aluminum tube with a diameter of 0.15 m and a length of 21.5 m, buried 0.4 m deep. The results showed that the EAHE can cool ambient air by up to 8.5 °C at an air flow rate of 607 m3/h, corresponding to a cooling capacity of 1700 W and a COP of 17. The daily average cooling capacity of the EAHE is about 560 W for an average operation period of 15.1 h per day. When used as a precooling unit for conventional cooling systems, the highest estimated monthly energy savings is 115 kWh, and the estimated annual savings is 741 kWh.

Induction motors account for forty percents of the world’s electricity consumption and for almost seventy percents of total electricity consumption in industry. Therefore, several technical aspects of the construction of induction asynchronous motors—specifically motor length, diameter, and the number of conductors in the stator slots—are analysed, and the impact of each parameter on motor efficiency is examined individually Furthermore, the effect of replacing aluminium rotor bars with copper bars on motor efficiency is examined. The effect of efficiency increasing on electricity savings in correlation to motor operating hours is presented. In addition, a comparative analysis is conducted between the asynchronous motor model exhibiting the highest efficiency and a synchronous line-start motor constructed with identical design parameters. Adequate conclusions on usage of energy efficient motors instead of motors with lower efficiency and their impact on electricity savings are derived.

This paper ascertained the performance of the evacuated tube solar water heater (SWH) coupled with an auxiliary electric heater with reference to the replaced electric water heater with the same storage tank capacity (200 L) in a building. It also examines the influence of the uptake of the SWHs in the community due to different campaign methods. The study evaluated the performance of a 4 kW electric water heater and a 2 kW input SWH with an auxiliary electric heater, and quantified the annual energy and cost savings. A survey using questionnaires was conducted among 150 residences in Dimbaza based on the house representative’s perceptions to replace their electric water heaters with solar water heaters (based on the monetary saving inscribed on the solar water heaters, the sensitization of the target population on the environmental benefits of the solar water heaters and both the monetary savings and environmental benefits). The findings revealed that by replacing the electric water heater with the solar water heater with an auxiliary electric heater, the annual electricity savings due to hot water heating was 4408.99 kWh and the net present value payback period was 4.32 years. The desire of the household representatives to replace their existing electric water heaters with solar water heaters due to the campaign strategies increased from 75 to 126. This study is capable of providing a mechanism to increase the penetration of solar water heaters and justifying the techno-economic viability of solar water heaters.

As technology continues to advance, the demand for electricity increases, and resources become scarcer, awareness of energy saving and related issues is increasingly important and has been the focus of scholarly research in recent times. This study investigates the key factors influencing households' electricity-saving behaviour in Ho Chi Minh City (HCMC), Vietnam, utilizing a convenience sampling approach. A total of 431 data samples were selected for examination. The research factors are attitude, social norms, personal moral norms, responsibility for energy-saving, degree of concern, policy, and social propaganda. These factors are expected to have an impact on perceived benefits and perceived behavioural control, which in turn are expected to positively influence the intention of HCMC householders to save electricity and engage in electricity-saving behaviours. The results show that all my hypotheses are accepted. This study identifies the key factors mentioned above that play important roles, as well as the two further factors of perceived benefits and perceived behavioural control, in shaping intentions for electricity-saving and the impact on electricity-saving behaviours. However, this study found that the degree of concern and policy and social propaganda do not significantly affect perceived benefit, contrary to the initial hypotheses. This study provides evidence and offers insights to policymakers regarding the key factors that influence households' intentions to save electricity and their electricity-saving behaviours. Furthermore, this research lays the groundwork for scholars to develop a comprehensive understanding and conduct further in-depth studies aimed at proposing solutions to enhance awareness of electricity-saving among individuals and organisations. These efforts benefit the community and address environmental concerns, aligning with the UN’s Sustainable Development Goals.

This study aims to analyze vital indicators for urban consumer's behavior regarding electricity saving appliances (ESA) to reduce energy consumption at home in Indonesia. The studied appliances are limited to two, refrigerator and air conditioner, as these appliances are the most dominant in consuming electricity energy. There are two equation models proposed for each appliance by using consumers' perceptions (general and specific perceptions) and external (social environment, weather, and mass media) group variables, usage and habitual behaviors. Using stepwise regression and statistical approaches for 232 surveyed household consumers in Makassar city, the adjusted R 2 value for four composed models is between 52% and 59%. Study findings reveal that specific perception significantly influences the usage of both appliances including the habit of consumers for energy saving. Among the examined external factors, the variable of mass media has significance in almost all models. Implications for policymakers suggest applying a priority approach in promoting energy saving to consumers with low specific perception based on the aspect of installed electric power capacity at home, and giving more information via mass media about attributes of ESA including introducing intervention strategies is essential to support sustainable electricity consumption from the consumer's side.

Electric buses (EBs) are gaining popularity worldwide as a more sustainable and eco-friendly alternative to diesel buses (DBs). Electricity-saving driving plays a crucial role in minimizing an EB’s energy consumption, subsequently leading to an extended driving range. This study proposes a machine learning–based framework for identifying electricity-saving EB driving behaviors during various driving stages, including running on road segments, entering bus stops/intersections, and exiting bus stops/intersections. The proposed random forest (RF) model effectively evaluates the energy consumption level using EB drivers’ historical driving data under different scenarios. Specifically, the electricity consumption factor ( ECF ), as the evaluation index, is divided into three categories to determine the implicit relationship between driving behavior and energy consumption. The results indicate that the classification accuracy of RF models surpasses 90%, which highlights the effectiveness in accurately identifying energy-efficient EB driving behaviors. In addition, the Shapley additive explanations (SHAP) and partial dependency plots (PDPs) are utilized to visualize and interpret the results of RF models. A speed interval of 30–40 km/h is identified as the most energy-efficient range for EB running on a road segment. Findings from this study can be applied to targeted optimization of electricity-saving driving strategies in different driving scenarios to improve the overall efficiency and sustainability of the transportation system.