Energy Conservation Level Research Articles

Research on Adaptive Control Systems for Building Shading Based on Decision Tree and Random Forest Classification Algorithms

Dynamic shading systems for buildings, due to their variable mechanisms and high adaptability, have the potential to reduce energy consumption in buildings significantly. However, the performance of dynamic shading is largely influenced by the control system employed. This study aims to explore an adaptive control method for building shading based on decision tree and random forest classification algorithms (machine learning), with the objective of minimizing energy demands related to lighting and cooling as much as possible. The adaptive control system model may independently modify the location of building shading in response to input environmental conditions, thereby achieving energy savings for both lighting and cooling. According to the findings, the automated control system model may reduce building energy consumption by 38% overall, which is close to the ideal level of energy conservation.

Multi-objectives occupant-centric control of thermostats and natural ventilation systems in cold climate conditions using real-time occupant-related information

Recently, Occupant-Centric Controls (OCCs) have attracted great attention. Many studies have applied OCCs to mechanical ventilation systems, while natural ventilation systems have gathered much less attention. The natural ventilation effect, driven by opening windows or vents, can be effective in improving indoor air quality, however, result in a leakage of interior heating energy in winter in cold climates. Therefore, the controls of thermostats and natural ventilation systems shall be designed well so that satisfying levels of thermal comfort, air quality and energy conservation can be simultaneously guaranteed. This study proposes an OCC and applies it to thermostats and natural ventilation systems for indoor thermal comfort, air quality and heating energy management. The strategy comprises three controllers: occupancy-based on-off controller, controller of setpoint of indoor air temperature and window openness controller. First, real-time profiles of heat gains from occupants and window openness were collected by employing vision-based detection. Second, a parametric building simulation study was conducted, and then simulation data were generated to develop predictive shallow artificial neural networks for forecasting the indoor conditions and energy performance of the investigated room. Third, the performance of the proposed strategy was examined. Compared to the baselines, the control could offer a decrease in building heating loads by between 43.4% and 63.8 % and an improvement of predicted mean vote levels by 0.36–0.37. The proposed OCC could also maintain indoor CO2 concentrations below 1000 ppm for about 91 % of the studied time, while 84.2 % of the time with several peaks over 3000 ppm in the baseline cases.

The Influence of Technology, Policy, and Environmental Awareness on Energy Efficiency and Conservation in Industrial Estates in Tangerang City

This research investigates the intricate interplay between environmental awareness, policy compliance, technology adoption, and energy efficiency and conservation within the dynamic landscape of the Tangerang City Industrial Estate. Leveraging a quantitative approach, the study surveyed 150 participants to analyze the relationships among these key variables. The results reveal significant and positive associations, indicating that organizations fostering environmental consciousness, adhering to energy-related policies, and embracing advanced technologies exhibit heightened levels of energy efficiency and conservation. The structural model's robust fit, assessed through various indices, underscores the reliability of the identified relationships. The findings offer valuable insights for policymakers, industry stakeholders, and researchers seeking to promote sustainability in industrial practices.

Meta-learning-based multi-objective PSO model for dynamic scheduling optimization

The by-product gas is an important secondary energy in the iron and steel industry. It is important to make the by-product gas’s utilization efficient and reasonable,which is the key to improve the economic efficiency and the level of energy conservation and emission reduction. Aiming at the problems of complex dynamic changes, difficult to accurately model and difficult to predict real-time traffic in gas energy system, this paper proposes an optimal scheduling method based on meta-learning multi-objective particle swarm optimization algorithm. The gas energy optimization scheduling problem is modeled as a multi-objective dynamic scheduling optimization problem. The difficulty of this problem is to comprehensively consider multiple indicators, continuously adapt to the change of the objective function over time, and track the changing Pareto optimal solution set. One of the promising solutions is to build prediction models with better performance under dynamic changes. The model we propose makes full use of the optimization results and the experience information of the optimization process in the historical optimization task. We propose a dynamic parameter initialization method based on meta-learning by starting multiple historical optimization tasks at the same time. Thus,the comprehensive parameters of different tasks are obtained, and a general and best base parameter is learned. Experiments show that the proposed model has better convergence and accuracy than the conventional algorithm.

Multi-parameter optimization design method for energy system in low-carbon park with integrated hybrid energy storage

Low-carbon parks composed of concentrated and contiguous low-carbon buildings has the characteristics of the high proportion of renewable energy penetration and low-carbon operation, requiring the transformation of relevant energy supply systems from being centralized to being centralized and distributed. However, the centralized and distributed energy supply method faces low levels of renewable energy utilization. Therefore, in this study, a low-carbon park energy system is constructed with a core of photovoltaics, wind power, lithium batteries, and heat storage tanks. A multi-parameter collaborative optimization method is proposed with the goals of cost reduction, carbon reduction, and independence by considering the parameters of equipment configuration and operation. The comprehensive benefits of a low-carbon park energy system under each low-carbon park are explored. The advantages of the system in terms of monthly carbon emission intensity, operation cost, maintenance cost, and interactive power are analysed. For the system, the balance of its energy supply and demand on a typical day and the role of energy storage in improving its utilization of renewable energy are analysed. Finally, the feasibility and benefits of the system's energy supply in different climate zones are further studied. The results show that the energy supply cost, carbon emissions, and interactive power are 31.0 CNY/m2, 4.1 kg/m2, and 2.4 kWh/m2, respectively, resulting in the best benefits for a unit area in a low-carbon park energy system in a high-rise residential park (Beijing). Energy storage can effectively improve the levels of renewable energy utilization, energy conservation and carbon reduction in the system. The low-carbon park energy system proposed in this article can significantly contribute to reducing carbon emissions in the construction industry.

A Data-Driven Prediction Model of Blast Furnace Gas Generation Based on Spectrum Decomposition

Blast furnace gas (BFG) is an important secondary energy in the iron and steel industries, and its efficient and reasonable utilization is the key to improving the economic efficiency of enterprises and the level of energy conservation and emission reduction. Aiming at the problems of difficult accurate modeling on the generation process and difficult prediction of real-time flow, this paper proposes a generation prediction model based on spectrum decomposition. Firstly, the major chemical reactions, production process, and data characteristics of blast furnace are analyzed, and the input variables for the prediction model are reasonably selected based on the correlation analysis results. Then, according to the spectrum characteristics, the BFG data is decomposed into low-frequency and medium-frequency parts by two finite impulse response filters. Next, for the low- and middle-frequency components of data, a low-frequency component prediction model based on the support vector regression, and a middle-frequency component prediction model based on the Elman neural network (ENN) are designed respectively. Finally, we decompose the spectrum of the actual industrial production data and find that the spectrum of the decomposed data basically meets the expected target, which verifies the effectiveness of the finite impulse response filters. In addition, we compare the prediction effect of the designed combined model with other models, such as the support vector regression, the back-propagation neural network, and the ENN. The final experimental results show the correctness, effectiveness, and superiority of the combined model and the spectral decomposition method proposed in this paper.

Can green hydrogen and waste heat utilization improve energy conservation and emission reduction of coal-based cogeneration processes?

Power-to-gas offers a new path for carbon emission reduction by integrating renewable energy hydrogen with traditional chemical process. However, its application is limited by the product fluctuation and high cost of green hydrogen. To further improve the level of energy conservation and emission reduction, this research explored the novel integration process of large-scale green hydrogen system and coal-based cogeneration process. The green hydrogen with a low fluctuation was obtained from the wind-solar coupled power equipped with conservative energy storage system. The results showed that the carbon emission was significantly reduced by 9.2%, while the total operating cost was increased by 18.7%. To alleviate the high operating cost caused by green hydrogen, various waste heat utilization systems were introduced to decrease the utilities consumption. It was found that the total site waste heat utilization was capable of further reducing carbon emission by 13.3%, and the increase in total operating cost can be controlled within 15.3%. Economic analysis proved that the expensive cost could be saved by lower hydrogen usage or hydrogen cost. By incorporating waste heat utilization, the cost increase could be as low as 6.0% and 4.8% under 50% green hydrogen flowrate or 40% energy storage system. With the progress of renewable energy hydrogen production and waste heat utilization technology, the proposed integration process will be more environmentally friendly and economically feasible in the future.

RESEARCH OF STARTING MODES OF ASYNCHRONOUS MOTORS AND DEVELOPMENT OF A SOFT START DEVICE

Study of starting modes of asynchronous electric motors. The growth of their demand in industry and everyday life requires an increase in the intensity of use of new systems of the industry existing in the agricultural sector. Currently, there is an aspiration to make the technological process the most automated, as well as to create the most functional and accessible equipment for an ordinary user to understand. Electric drives consume more than 60% of the produced electricity, increasing their energy efficiency is significantly achieved by switching from an unregulated asynchronous electric drive to a regulated one, which contributes to the improvement of the quality characteristics of technological processes, provides the opportunity to automate production, and increases the level of energy and resource conservation. Recently, systems of automated control of technological processes created on the basis of advanced microprocessor equipment have been actively developed, improved and implemented. Nowadays, the method of controlling the start of engines using a frequency converter is becoming more and more common. Until recently, the method of frequency regulation of the electric drive was considered expensive and was used only for a large range of speed regulation, but with the decrease in price and improvement of frequency converters, this control system becomes an almost ideal technical solution from the point of view of controlling the operation of the pump both in the start/stop period and in normal modes. Modernization of traditional control and start-up systems can become a frequency converter with an open software platform, which allows users to refine the software, optimize it for their tasks, including developing and adding their own software modules both at the power inverter control level and at the software-logic level controller for solving local automation tasks. The wide use of asynchronous motors is explained by their advantages compared to other motors: high reliability, ease of repair, small number of structural elements, the possibility of operation from an alternating current network, ease of maintenance. Various methods are used to solve the problems that appear during the uncontrolled start of an asynchronous motor, which to one degree or another ensure the acceleration of the asynchronous motor with a given value of current, which is significantly lower than with a direct (uncontrolled) start [1]. This makes it possible to prevent the premature failure of the asynchronous motor (AD) and driven mechanisms, to increase the resource of the switching equipment, to ensure the possibility of controlling the electric drive using modern automation tools. In addition, the use of modern controlled start-up allows you to reduce the active power consumption, significantly reduce the reactive power consumption, reduce the noise level, and reduce the vibration of the electric motor. The start of asynchronous short-circuited motors by direct connection to the network is usually accompanied by a large starting current, which exceeds the nominal value by several times.

Reversible time-step adaptation for the integration of few-body systems

ABSTRACT The time-step criterion plays a crucial role in direct N-body codes. If not chosen carefully, it will cause a secular drift in the energy error. Shared, adaptive time-step criteria commonly adopt the minimum pairwise time-step, which suffers from discontinuities in the time evolution of the time-step. This has a large impact on the functioning of time-step symmetrization algorithms. We provide new demonstrations of previous findings that a smooth and weighted average over all pairwise time-steps in the N-body system, improves the level of energy conservation. Furthermore, we compare the performance of 27 different time-step criteria, by considering three methods for weighting time-steps and nine symmetrization methods. We present performance tests for strongly chaotic few-body systems, including unstable triples, giant planets in a resonant chain, and the current Solar System. We find that the harmonic symmetrization methods (methods A3 and B3 in our notation) are the most robust, in the sense that the symmetrized time-step remains close to the time-step function. Furthermore, based on our Solar System experiment, we find that our new weighting method based on direct pair-wise averaging (method W2 in our notation), is slightly preferred over the other methods.

Energy Conservation and Firm Performance in Thailand: Comparison between Energy-Intensive and Non-Energy-Intensive Industries

This study investigated and compared energy conservation levels between listed companies in energy-intensive industries and non-energy-intensive industries in Thai capital markets. It also tested the impact of energy conservation on firm performance using companies in the two industries. The sample for the study was sourced from 552 companies in the Stock Exchange of Thailand (SET) and 169 companies in the Market for Alternative Investment (MAI). The data was collected from the companies' annual reports spanning the period from 2016 to 2020. Descriptive analysis, independent sample t-test, and unbalanced panel data analysis were used to analyze data. The findings revealed that energy conservation scores for Thai-listed companies were generally stable, averaging between 0.45 and 0.46. It was also revealed that the energy conservation of companies in energy-intensive industries was significantly greater than that of companies in non-energy-intensive industries, with average scores of 0.55 and 0.43, respectively. Additionally, the study found that energy conservation has a positive impact on the firm performance of energy-intensive industries, while no significant impact in energy-intensive industries was recorded. The findings demonstrate that stakeholder and legitimacy theories can help explain how energy conservation benefits companies in terms of increased firm performance.

Application of Passive Cooling Principles in Selected Hotel Buildings in Southwest Nigeria

This study was initiated in response to the high energy consumption connected with tourism-related activities. Air conditioning uses the majority of the energy required, typically exceeding 40%. Hotels in the tropics have higher average annual energy use intensity (avg. EUI) rates than those in the temperate zones; Regardless of the climate zone, the highest category hotels (i.e., five-star hotels) have a higher energy use index. When their efficiency is assessed and understood to ensure continuous improvement in their energy conservation, hotel buildings will make a much greater contribution to energy management. The objective of this paper is to investigate the extent to which Passive Cooling Principles were applied in hotel buildings in Nigeria, and the impact of these principles on the selected hotels; towards assessing the achieved level of energy conservation. The study is limited to selected hotel buildings in Nigeria; and they were studied in-depth to determine their compliance levels to passive cooling principles. Non-participant observation was carried out to obtain are objective data. As Lagos State houses a larger number of the five-star hotels in the study population, two of the selected case studies were from this location; and the last was from Abuja, which represented the North and Central Region of the country. The sampling technique used for this research is purposive sampling. The Five-Star hotels were selected based on their star rating according to set standards that have been identified in Literature; and they include prominent hotels in both Lagos and Abuja. The application rate of 64% also creates a basis for determining the minimum application rate targeted for the five-star hotel design carried out along-side this paper; which is 75%. This relays the extent to which Passive Cooling Principles are applied in hotel buildings in Nigeria; and also provides a benchmark for future researches and designers that intend to implement or study Passive Cooling Principles.

Performance Indicators for Energi Management of Tourism in The Pangururan District Kabupaten Samosir

. The Lake Toba area is a national tourist area visited by various tourists both from within and outside the country, and is included in the 88 national tours which are the parent of tourism development in Indonesia. One of the infrastructures that must be considered is the availability of electrical energy sources in the tourist area of ​​Lake Toba. Pangururan District as one of the tourism and administrative areas in the Lake Toba area must have sufficient electrical energy needs and become sustainable tourism. The purpose of this study was to examine the Performance of Tourism Energy Management in Pangururan District, Samosir Regency with an approach to analyzing the level of energy use and conservation, energy management programs, and utilization of renewable energy sources. The research method used is direct field observation and literature study, both theory and supporting documents in the research, which is then analyzed by interpreting the data obtained based on the theory and applicable policies. The results of this study are to identify that the need for electrical energy in the tourist area in the Pangururan sub-district is quite evenly distributed and the need for electrical energy is also met, but in the tourist area in the Pangururan sub-district conservation activities and the use of sustainable energy sources carried out by the government and the tourism business unit are still very low. a little. In addition, this research is expected to be a source of knowledge about Energy Management in the Tourism Sector.

Coupling Coordination Degree Measurement and Forecast of Poverty Alleviation, Energy Conservation, and Ecological Protection: Evidence from 30 Provinces and Cities in China

As China experiences rapid economic development, tasks involving poverty alleviation, energy conservation and ecological protection need to be addressed. Whether poverty alleviation, energy conservation and ecological protection in China have coordinated development has become a question worth studying. Based on the coupling coordination degree model and the GM (1, 1) model, this paper calculates and forecasts the development level of poverty alleviation, energy conservation and ecological protection of 30 provinces (cities) in China and analyses the synergy of the three systems spatially and temporally. The results show that first, from 2010 to 2019, the development level of China’s poverty alleviation system, energy conservation system and ecological protection system presented increasing trends, but regional differences could be seen in development trends. Second, the coupling coordination degree of the three systems in China showed an upwards trend. The average coupling coordination degree of 30 provinces (cities) rose from slight coordination in 2010 to moderate coordination in 2019. Third, in the following years, development level will still be on an upwards trend in the four regions of China from 2020 to 2025. The development level of the ecological protection system will be the highest in China, and poverty alleviation and energy conservation will rank second and third. Fourth, the coupling coordination degree of the three systems of 30 provinces (cities) in China will rise significantly, indicating that the development of the three systems in China will be more coordinated in the following years.

On the Basis of Computer Analysis of the Current Situation of Energy Conservation and Consumption Reduction in China’s Iron and Steel Industry and Research Measures

Adhering to the strategy of energy conservation and emission reduction is one of the important principles of China’s industrial development. As one of the indispensable pillar industries of the national economy with high energy consumption and emissions. at the same time because of the restriction of the natural environment conditions, the high-speed development of behind to face the problem of the shortage of resources, ecological destruction, in order to improve people’s quality of life and life experience, improve the level of energy conservation and emissions reduction iron and steel industry is imperative. Steel smelting industry, comprehensive considering the steel utilization, energy conservation and emissions reduction targets, etc., have noticed that the costs in smelting system energy-saving, the importance of the question is, society for steel utilization, can’t bring enough money for the iron and steel smelting industry benefit, and hindered the development of new energy saving technology, increased the energy saving of iron and steel smelting system pressure. Thus it can be seen that cost capital is the main problem of energy saving in modern iron and steel smelting system. Only with financial support can the level of energy saving be improved.

Impacts of home energy management systems on electricity consumption

Home energy management systems (HEMS) connect homes to a smart grid and may increase the overall use of renewable energy by directing energy demand to off-peak hours and increasing energy conservation. However, the promised changes in electricity consumption have yet to be proven in real-life experiments. We therefore analysed the changes in electricity consumption, daily consumption profiles, and number of low and high consumption hours after installing HEMS in 10 Finnish households. These changes were examined in the context of the values related to energy use in each household, which were derived from semi-structured interviews. In the real-life experiment, we showed that the HEMS reduced the total consumption of electricity in the winter months by up to 30%, shifted the consumption to off-peak hours and decreased the number of high consumption hours. These changes occurred even in the homes that valued comfort over savings or ecological sustainability. Nevertheless, the levels of energy conservation varied greatly between the households and between months in the same homes.

The Climate Change Dilemma: How Cooperation Beliefs Influence Energy Conservation Behavior

Despite widespread belief in anthropogenic climate change and high levels of concern about its consequences, behavioral changes necessary to adequately address climate change appear difficult to achieve. This concern–behavior gap is often explained by the public goods character of climate change mitigation, which is associated with a high individual incentive to take a free ride when possible. This paper examines cooperation beliefs and their impact on individuals’ energy conservation behavior. Analyzing data from the European Social Survey, it appears that cooperation beliefs are rather low in Europe and that most people do not expect others to limit their energy use to help mitigate climate change. This low trust contrasts with individuals’ reported level of energy conservation behavior and the general high level of energy conservation in most European countries. This trust gap has important implications for pro-environmental behavior as high trust in others’ pro-environmental behavior fosters individuals’ attempts to save energy.

The motivation and development impact of energy saving to sustainability in the construction of green campus: a case study of the Zhejiang University, China

The construction of green campus is related to the global sustainable development. Under the guidance of campus energy-saving policy, China’s green campus mainly focuses on campus’ energy saving. In contrast, the green campus in the USA pays more attention to environmental problems. This study focuses on the impact of “energy saving” on the sustainable development of green campus. On the one hand, it puts forward targeted optimization suggestions for the Chinese universities. On the other hand, it provides the experience reference and new development ideas for the global campus sustainability. Based on the characteristics of the development mode of green campus in China and the USA, this paper studies the motivation of “energy saving” to “sustainability” in the construction of green campus in China. In terms of research methods, this paper selects Zhejiang University a typical representative of China’s green campus that combined with the comparative group of four American universities and conducts a quantitative analysis of G-value and S-value that represented energy consumption and sustainability, respectively. Zhejiang University’s G-value (0.019) in 2016 is one-sixth of that of the comparative group in the same period, indicating that the implementation effect of the energy-saving monitoring platform is remarkable. From 2014 to 2017, the G-values are basically stable at 0.02, indicating that its future development potential is insufficient. Zhejiang University’s scores in the four categories of S-value are significantly lower than those in the comparative group, showing that there are great differences in the construction achievements of the five universities. According to the score rate of 17 sub-items of S-value, the five universities have different advantages and disadvantages. Therefore, the green campus construction of China’s case university is too one-sided and only stays at the level of energy conservation. The diversification of construction and the balanced development of all aspects should be paid more attention in the future.

Research on the Relationship between Economic Growth, Environmental Governance Investment and Carbon Emission--Based on the Time Series Data from 2000 to 2019

The study on the relationship between investment in environmental governance, carbon emission and economic growth is helpful for the relevant government departments to coordinate the influence among them when formulating the policies of reducing emission and conserving energy, so as to take the comparative advantages of various factors and promote the benign interaction between economic development and environmental governance. In this paper, the data of Per capita GDP, per capita investment in environmental governance and per capita CARBON dioxide emissions in China from 2000 to 2019 are selected as the research basis, and variables are studied by means of Granger causality and impulse response function. As shown in the results, there is a single Granger relationship between investment in environmental governance and carbon emissions, that is, the increase of investment in environmental governance leads to the reduction of carbon emissions. The influence of economic growth on environmental governance investment is small, but in the long term, it can restrain the growth of carbon emissions. Investment in environmental governance can promote economic growth and stimulate a reduction in the emissions in the short term; Economic growth was hindered by the emissions in the long term and fail to stimulate increased investment in environmental governance. Based on these findings, this paper proposes policy Suggestions for optimizing the structure of environmental governance investment, improving the carbon emission monitoring and response mechanism, and strengthening the technological level of energy conservation and emission reduction.

DEVELOPMENT OF MODERN STANDARDS FOR ENERGY EFFICIENCY OF INDUSTRIAL ENTERPRISES WITHIN THE EUROPEAN UNION POLICY

This study is aimed at identifying the weaknesses and strengths of the mechanism for managing industrial energy efficiency (EE) under the EU policy. It is of interest not only for countries consuming energy raw materials but also for its suppliers, since they are to predict the situation on the markets and follow global trends in energy saving and environmental protection. Within the framework of the research, the methods of analogies and comparisons are used to determine the costs of switching industrial enterprises to the EE principles. The modeling method is applied to five companies in the EU, the USA, Russia, and China. By comparing the existing mechanism for EE regulating, excellent results for the EU industrial companies can be observed. They are characterized by the achievement of a high level of energy saving (10-12%) at low costs. For most US companies, an adequate level of potential energy conservation can be noticed. Russian industrial enterprises are characterized by low energy saving at a huge investment cost. For companies in China, favorable conditions are created to achieve efficient energy conservation, however, the cost for EE remains high.

Cleaner production of Pakistan’s chemical industry: Perspectives of energy conservation and emissions reduction

The chemical industry is one of the highest energy-consuming and CO2 (carbon dioxide) emitting sectors in Pakistan. It is important to understand and identify ways to improve the sustainability features of the input factors. This research has attempted to examine the potential of input factors (capital, labor and energy consumption), output elasticities, and substitution elasticities in Pakistan’s chemical sector by using a translog production function. The ridge regression technique was applied to investigate the parameters of the function during 1980–2018. The results show that the output elasticities between capital, labor and energy consumption are positive; the elasticities of substitution between capital-energy, capital-labor and labor-energy consumption are close to 1, stable, and positive, which shows that these indicators are substitutes for one another. Moreover, based on the analyzed methodology, we estimate the level of energy conservation and CO2 emission reduction in 2018. Policy suggestions related to the given outcomes are presented below.