Design and Implementation of Smart Bench Integrated Solar Cell for Public Space Electricity Saving

The purpose of this research is to design a multifunctional garden bench integrated with solar panels. The bench product is created by utilizing sunlight as a source of electrical energy for the object features of the bench product. The implementation method for producing innovative bench products uses a research and development approach, including concept, design, collection of materials, assembly, and testing. The bench was tested to supply electricity to the LED lights and USB ports. Furthermore, analyzing statistical data the average value of; current, voltage, and power generated by the intelligent bench object. The study results present the primary resources needed for the design and implementation of intelligent bench products. Experiments show that a load of LED lights and USB station chargers depends on the percentage of battery batteries supplied from solar cells. The innovative bench is designed from hollow steel to support product construction efficiency and electronic effectiveness. In this way, we achieved our goal of designing and implementing a portable garden bench that could function in all open areas.

Smart Classroom for Electricity-Saving with Integrated IoT System

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.

Behavioural interventions yield electricity savings among high-income households in Johannesburg, South Africa

The societal benefits of addressing wasteful electricity use practices through behavioural interventions are now well-established. Surprisingly, in South Africa, where the economy is highly dependent on fossil fuel (coal) for electricity generation, this subject remains little studied and understood. The residential sector is a major electricity consumer, and high-income households, in particular, use a substantial proportion of total electricity with serious adverse impacts on grid stability and the environment, which can disproportionately affect the poor. Using a field-based experiment, this study examines the impact of behavioural interventions on household electricity savings and the determinants of success among high-income households in Johannesburg, South Africa. Over the intervention period, households exposed to a combination of electricity-saving information, frequent reminders and feedback on monthly electricity-saving performance showed mean electricity savings of about 1.5%, ranging from 2% to 4% of electricity, while households in the control group showed increased electricity consumption by approximately 11%. Out of all the demographic and personal value factors considered, age, achievement and benevolence promoted electricity savings, while household size, number of rooms, baseline electricity consumption and security inhibited savings. The findings empirically validate the impact of behavioural interventions on, and the positive influence of, personal values in promoting participation in electricity-saving actions within households.

Smart City Management in the Context of Electricity Consumption Savings

According to one definition, Smart City is an administrative unit that uses data and digital technology to improve the decision-making processes and well-being of its inhabitants. Smart Cities use modern, intelligent technologies to forecast future changes, optimize city functions, gain a better understanding of current conditions, and deliver solutions. To make the city smart, multiple connected sensors, smartphones and other IoT devices are needed. As part of the research conducted at the Technical University in Vienna, six key dimensions (categories) of smart cities have been identified and characterized: Smart Economy, Smart Mobility, Smart Environment, Smart People, Smart Living, and Smart Governance. The aim of the paper is to present the concept of the smart cities, the implemented innovative solutions and the issue of electricity saving in Smart Cities. The theoretical considerations were expanded of the presentation of selected smart city projects in Polish cities. The considerations were also supplemented with the results of research conducted on a group of respondents living in large and very large cities in Poland in order to their awareness of the concept of smart cities, awareness on smart projects implemented in their cities of residence, and the possibility of using intelligent technologies to achieve savings in electricity consumption.

Efficiency Power Plant Implementation Decision-Making Based on the Profit Function and Its Numerical Simulation

The efficiency power plant (EPP) is a kind of virtual power plant with zero emission, zero pollution, and low cost and exhibits a high-quality low-carbon production behavior in input-output analysis. In the process of implementing EPP, enterprises not only save electricity but also reduce carbon emissions, while increasing the cost of R&D and equipment. Therefore, it is very necessary to study relationships between carbon quota and EPP implementation decision. In this paper, we build the profit functions of three different types of enterprises implementing EPP and analyze the relationship of main parameters, such as the probability of implementing EPP, electricity saving, income, cost, and carbon quota, and obtain nine relative results. Then, we use ‘Maple’ software to simulate the results by drawing images of parameters, and all the above nine results passed the simulation test verification. At last, we collect the actual survey data and use VC++ programming to carry out an empirical study in China to prove the practicability of the model and the results. The results show that, under the carbon quota trading system, enterprises should tend to implement EPPs and increase investment in R&D and acquisition of EPPs and are needed to adjust the intensity of implementing EPPs according to the change of carbon quota and unit carbon quota income, to obtain higher income.

Decomposition of Industrial Electricity Efficiency and Electricity-Saving Potential of Special Economic Zones in China Considering the Heterogeneity of Administrative Hierarchy and Regional Location

Special Economic Zones (SEZs), an important engine of industrial economic development in China, consume large amounts of energy resources and emit considerable CO2. However, existing research pays little attention to industrial energy usage in SEZs and ignores the heterogeneity of administrative hierarchy and regional location. Considering the dual heterogeneity, this study proposes an improved two-dimension and two-level meta-frontier data envelopment analytical model to decompose the industrial electricity efficiency (IEE) and electricity-saving potential of SEZs in Guizhou Province, China, based on 4-year field survey data (2016–2019). Results show that the IEE rankings of three administrative hierarchies within SEZs are provincial administration SEZs, county administration SEZs, and municipality administration SEZs. The SEZs located in energy resource-rich areas and better ecological environmental areas have higher IEE than those in resource-poor areas and ecology fragile areas, respectively. This study can provide reference for policymakers to formulate effective policies for improving the electricity use efficiency of SEZs in China.

Saving energy in China’s industry with a focus on electricity: a review of opportunities, potentials and environmental benefits

Industry is the largest electricity consuming sector in the world. China consumes about 25% of global electricity demand, and 69% of this is used in industries. The high electricity demand in industry is responsible for 45% of CO2, 25% of SO2, 34% of NOx and 14% of PM emissions in China. This study aims to fill the knowledge gap on the potential for electricity savings in China’s industries, thereby providing important implications for the potential of reducing emissions in electricity-intensive industrial subsectors in general. Available studies are reviewed and compared to identify electricity-saving potentials. The findings show that China’s industrial energy system is shifting to higher electricity and relatively lower fossil fuel use due to accelerated end-use electrification. China’s industry can reduce electricity use by 7–24% in 2040, compared to baseline levels, and generate emission reductions of 192–1118 Mt-CO2, 385–2241 kt-SO2, 406–2362 kt-NOx and 92–534 kt-PM2.5. The iron & steel subsector has the largest contribution to the industrial electricity savings, followed by non-ferrous metals, chemicals, cement and pulp & paper. Policies that combine environmental targets, demand-side efficiency and supply-side retrofits in the power sector should be adopted. Given the different performance of policies in terms of energy savings and emission reduction, sector- and region-specific policies would be preferred.

Assessment of Energy Transition Policy in Taiwan—A View of Sustainable Development Perspectives

Energy transition has become a priority for adaptive policy and measures taken in response to climate change around the world. This is an opportunity and a challenge for the Taiwan government to establish a climate-resilient power generation mixed to ensure electricity security as well as climate change mitigation. This study adopted a sustainable development perspective and applied optimal control theory to establish a cost-effective model to evaluate a long-term (2050), climate-resilient power generation mix for Taiwan. Furthermore, this study applies the STIRPAT approach to predict the demand of electricity by 2050 for the demand side management. The results not only showed the share of various power generation mixed, but also recommended the trajectory of electricity saving by 2050.