Effective Use Of Energy Research Articles

Implementation of Green Hospital Concept in Solid Medical Waste Management

Hospitals are one of the institutions that use considerable energy and contribute the largest amount of waste. To reduce the impact, initiatives have emerged in the form of greening hospitals for effective use of resources. Green Hospital is a hospital concept that is designed by empowering the potential of nature as the main resource so that it is friendly to the environment and saves energy expenditure. The existence of Green Hospital is needed to overcome climate change that can cause human health problems and the environment, because hospitals are one of the contributors to pollution. In Indonesia, Green Hospital is still a concept that emphasizes effective and efficient use of water and electrical energy, as well as environmentally sound waste management. The purpose of this study is to analyze solid medical waste management in Saraswati Dental and Oral Hospital Denpasar in realizing the Green Hospital concept. This research is qualitative. Data were collected by in-depth interviews with1 staff at the Environmental Health Installation and 3 staff of cleaning service, observation, and document review. Data were analyzed by data reduction, data presentation, and conclusion. Data validity used source triangulation and method triangulation. Medical waste management in Saraswati Dental & Oral Hospital Denpasar is generally in has been accordance with the Indonesian health regulation No. 1204/2004, but does not yet have a policy or direction to realise Green Hospital. To achieve Green Hospital, hospitals can start by making policies to implement non-medical waste minimization and increasing the number of personnel in the field of medical and non-medical waste management.

Effect of hydrogen on oxidative dissolution of epsilon particles-doped UO2 pellets under carbonate condition with hydrogen peroxide

The epsilon particles that result from nuclear fission of UO2 fuel possess both advantages and disadvantages from a spent nuclear fuel (SNF) management perspective. In this study, the effect of epsilon particles, namely Ru, Mo, and Pd, inherent in simulated UO2 pellets is examined. Various analytical methods have been used to explore the changes in the structural, surface, and electrochemical properties of which contain epsilon particles. A notable finding is that the epsilon particles are not evenly distributed and tend to clump together, transforming into a metallic state after sintering, as detailed in the X-ray diffraction analyses. Energy-dispersive X-ray spectroscopy analyses highlight interesting aspects of the distribution of elements, especially the disappearance of Pd during sintering, which is likely due to its high vapor pressure. Although the lattice structure of UO2 remains unchanged, the sizes of the grains and pores visibly change, which may influence the tendency of UO2 pellet-cracking. Despite the addition of the epsilon particles, the electrical conductivity analyses show no significant changes, suggesting that they act as minor impurities without affecting the structural lattice. However, their possible role as catalysts in electrochemical reactions opens new and interesting areas that require thorough investigation. Moreover, examining the anodic dissolution under various conditions provides detailed insights into UO2 dissolution and oxidation, revealing how epsilon particles subtly influence the oxidative dissolution process. This study clarifies the basic interactions and effects of epsilon particles in UO2 pellets and broadens the path for a deeper understanding and improvement of nuclear fuel matrices and steering advancements in the safe and effective use of nuclear energy.

Application of thermal energy efficiency utilization based on computer technology in green manufacturing blockchain production traceability

With the global emphasis on sustainable development, green manufacturing has become a key strategy to enhance economic efficiency and environmental friendliness. In the manufacturing process, the effective use and management of heat energy directly affect the consumption of resources and the protection of the environment. Blockchain technology, with its transparency and immutability, has gradually been introduced into the production process, helping to achieve traceability and optimization of thermal energy utilization. This study aims to explore how to combine computer technology with blockchain to establish a heat energy monitoring and management system based on computer technology, and collect real-time heat energy data through sensors. It then uses blockchain technology to create a transparent production traceability platform, store and manage thermal data, and ensure the security and reliability of the data. The research shows that the system combining computer technology and blockchain significantly improves the utilization efficiency of heat energy, greatly reduces the heat loss in the production process, and significantly improves the reuse rate of resources. The traceability function of the system effectively improves the transparency of the production process and enables enterprises to adjust their production strategies in time. Therefore, the combination of computer-based thermal efficiency utilization with blockchain production traceability offers a new solution for green manufacturing.

Enhancing PI controller performance in grid-connected hybrid power systems

The optimal operation of a microgrid was buildup of both uncontrollable (solar, wind) and controllable (batteries, diesel generators) electrical energy sources are enclosed in this paper. By replacing controllers, the variations in wavering power supply caused by load fluctuations are managed. The objective of the research paper is to optimize these controller gain settings for effective use of electrical energy. In this paper integral time square error principle is combined along with the Cuckoo search algorithm (CSA) and particle swarm algorithm (PSA) to obtain the accurate, precise and appropriate results. It enhances the microgrid's steady-state sensitive responsiveness in comparison to trial-and-error techniques, assuring a stable supply of electricity to the load.

Supply chain network design concerning economy and environmental sustainability: Crisis perspective

This paper proposes a GSCND that combines environmental, energy, and economic sustainability aspects of the crisis. Global SCs have been disrupted by the epidemic, underlining the need for a GSCND. Environmental and energy sustainability issues are closely linked to SC and economic systems. By examining available energy and total costs, integrated SC models aim to ensure the profitability of investments and the effective use of energy in economic systems. An example quantitatively illustrates the ability of the proposed model to reduce total costs and public energy consumption. The model enables several improvements in reducing the total cost and energy variables during a crisis. The weighted Tchebycheff method is used to optimize mathematical modeling. This network allows maximizing energy consumption while reducing the total economic cost. The special thing about this research paper is that it analyzes the COVID-19 epidemic simultaneously from an energy and financial perspective.

Assessment of health consequences of fossil fuel energy use in Osun state, Nigeria: burden and implications

The use of fossil fuel energy persists in all the continents of the world, especially in Africa. This study examined fossil fuel energy usage and its health implications in residents of Osun State, Nigeria. This was a cross-sectional study done across Osun State Nigeria. The study took place between January and June 2020. 1044 participants were recruited by multi-stage random sampling. Structured questionnaires were used to obtain necessary information from the study participants. The study data shows there were 534 females (51.1%). 601 (57.6%) relied solely on fossil fuel energy compared to 443 (42.4%) who use non-traditional energy sources. The proportion of people whose annual income is less than 56.6 USD (fifty thousand Naira based on the current official exchange rate as of Jan 2024) is far higher among those who use fossil fuel energy (88.0%) compared to those who use modern energy (59.1%). Electricity consumption accessibility was also more likely among those who used modern energy (91.9%) compared to 52.4% of those who use fossil fuel energy for daily energy needs. Reports of ill-health were significantly commoner among those who used fossil fuel than modern energy in the population including asthma illness (15.3% vs. 11.3%), cough (21.1% vs. 16.7%), catarrh (19.3% vs. 10.8%) and difficulty in breathing (9.3% vs. 6.3%) respectively. This study showed that fossil fuel energy use is very prevalent among residents of Osun State, Nigeria. And may be linked with many indices of poverty. It is associated with significant health impacts including respiratory diseases and poor quality of life. There is a need to encourage and implement policies toward effective and efficient energy use among residents in Osun State to reduce the associated long-term health impact.

Planting and Harvesting Mechanization on Productivity, Energy Efficacy and Profitability of Potato Production

Potato occupied the first position among all the vegetables in respect of area and total production in Bangladesh. Effective and efficient use of energy are necessary for an improved agricultural production. Therefore, this research was undertaken for potato production to assess productivity, quantify energy flow and financial profitability of different production systems. The experimented four systems were manual planting and manual harvesting, machine planting and manual harvesting, manual planting and machine harvesting and machine planting and machine harvesting, respectively. The experiment was conducted at Farm Machinery and Postharvest Process (FMP) Engineering Division of Bangladesh Agricultural Research Institute (BARI) during 2017-18. Yield of potato including yield contributing characters for different treatments was not significantly varied. Direct energy was the highest in mechanical planting and harvesting system (25%) and the lower manual planting and harvesting system (18%). Indirect energy shared 82% in manual planting and harvesting system, 78% in machine planting and manual harvesting system, 80% in manual planting and mechanical harvesting system, and 75% in machine planting and machine harvesting system, respectively. The largest source of indirect energy consumption was from fertilizer (22-27% of the total energy). The higher specific energy of 1.93 MJ/kg was found in manually planted and mechanized harvesting system. The higher product value was from manual planting and mechanical harvesting system. The highest BCR (2.25) was found from machine planted and machine harvested followed by manually planted and mechanically harvested plot (2.16), machine planted and manually harvested plot (1.93) and manual planting and harvesting plot (1.91). Thus, mechanically planted and harvested system can be recommended for potato production since it can reduce 52% labour requirement than manual method and can give higher BCR among the tested production methods.

Evaluation of solar and biomass perspectives using geographic information system - The case of Iraq regions

The study provides a comprehensive assessment of strategic zoning for biomass energy development across various regions in Iraq through GIS-based analysis. It delves into the energy surplus factor a pivotal metric indicating a region capacity to produce energy beyond its consumption needs. Results indicate a significant disparity in energy production-consumption balance across the regions, impacting local and national energy sustainability initiatives. A notable proportion of the study areas exceed a surplus factor of 3.5, showcasing the possibility of regions to not only meet their own energy needs but to also contribute to a surplus, thanks to effective renewable energy use and other energy-efficient practices. Conversely, a considerable number of cities have surplus factors below 1, signaling energy deficits and a dependence on external energy sources due to high consumption, underdeveloped local energy infrastructure, or other inefficiencies. Meanwhile, other regions achieve a balance, with surplus factors ranging from 1.5 to 4, indicating a more sustainable alignment of energy production with consumption. The study segments regions into tiers based on their surplus factors, suggesting that those with higher factors have greater CO2 reduction potential, thereby offering a nuanced strategy for resource management and environmental policy-making. These insights establish a nuanced framework for optimizing energy production, managing consumption, and reducing emissions, tailored to the diverse energy landscapes of Iraq regions.

Exergy and entropy analysis of metal foams based on 2nd law of thermodynamics

The available (exergy) and effective use (entropy generation) of energy at the end of thermodynamic processes are significantly important parameters in the design of optimum thermal system. Entropy analysis based on 2nd law of thermodynamics through various pore density metal foams placed in an asymmetrical heated horizontal channel is presented in the current work. Water flows through the channel at different flow rates (inlet velocity varies from 0.02 to 0.3 m/s). Highly porous and different pore density aluminum metal foams such as 10 (0.95), 20 (0.90), 30 (0.92) and 45 (0.90) are inserted into the channel to boost the heat transfer. Darcy Extended Forchheimer (DEF) and local thermal equilibrium (LTE) models are used for the calculation of flow and thermal variables respectively. The numerical outcomes of the examination are first confirmed by comparing with existing experimental literature results. The mean exergy Nusselt number results presented shows that the 10PPI metal foam stretches 35.41 % and 12.20 % higher thermal presentation with respect to 20PPI and 30PPI metal foam. The entropy examination showed that the 20PPI metal foam produces minimum entropy generation at a Reynolds number of 3464.32 and 10PPI metal foam shows highest presentation based on Bejan and entropy generation number.

Applications of Fractional Order Logistic Grey Models for Carbon Emission Forecasting

In recent years, global attention to carbon emissions has increased, becoming one of the main drivers of global climate change. Accurate prediction of carbon emission trends in small and medium-sized countries and scientific regulation of carbon emissions can provide theoretical support and policy references for the effective and rational use of energy and the promotion of the coordinated development of energy, environment, and economy. This paper establishes a grey prediction model using the classical Logistic mathematical model in a determined environment to investigate the carbon emission system. At the same time, we use the basic principle of fractional-order accumulation to establish a grey prediction model with fractional-order Logistic and obtain the parameter estimation and time-response equation of the new model by solving the model through the theory related to fractional-order operators. The particle swarm optimization algorithm is used to complete the optimization process of the order of the fractional order grey prediction model and obtain the optimal model order. Then, the new model is applied to predict carbon emissions in five medium-emission countries: Ethiopia, Djibouti, Ghana, Belgium, and Austria. The new model shows better advantages in the validity analysis process, and the simulation results indicate that the new model proposed in this paper has stronger stability and better simulation and prediction accuracy than other comparative models, proving the model’s validity. Finally, the model is used to forecast the carbon emissions of these five countries for the five years of 2021–2025, and the results are analyzed, and relevant policy recommendations are made.

Innovative twist design for solar water heaters: Experimental findings and implications

More effective use of solar energy in hot water systems is made possible by optimising heat transfer and flow resistance. In light of this, Research has been conducted to enhance convective heat transfer while analysing flow friction characteristics for best performance, resulting in the design of novel inserts known as customised twists, which increase the efficiency of the solar hot water system. A conventional, plain tube heater is used as a baseline for the study on thermal characteristics, heat transportation and flow friction attributes. A thorough analysis and comparison of the thermal behaviour of the system with customised twist inserts that have been modified using rods and spacers of different lengths is performed. As a result of the induced disturbance in the fluid particle flow pattern throughout the length of risers, a significant improvement in the coefficient of convective heat transfer is observed. The study validated the correlations for the convective heat transfer coefficient and the resistance coefficient against previous research findings. The findings indicated that the thermal efficiency of the full-length twist-inserted system is almost three times greater than that of a plain collector while doubling its pressure drop. The findings of this research could be useful in designing low-cost, compact solar water heaters.

Water transportation using a low-height overhang structure along with an expansion pressure of bubbles in a nucleate boiling region

Effective use of low-grade energy is a vital issue for a more sustainable society. Here, we propose a water pump using a low-height overhang structure that effectively uses an expansion pressure of bubbles in a nucleate boiling region. Specifically, by fabricating a periodic overhang structure on a brass surface, we show that a ∼20 mm/s net flow can be generated in a nucleate boiling regime. In addition, by observing bubbles with a high-speed camera of 960 fps, we find that bubbles are generated selectively in the overhang structure and grow to push out water in a lateral direction. Furthermore, by proposing a simple model that considers the expansion pressure of bubbles, we succeed in explaining the experimental results to some extent. Our findings should contribute to the effective use of low-grade energy in a nucleate boiling regime.

Yenilenebilir Enerji Tüketimi ve Piyasa Kapitalizasyonu ile Karbon Emisyonu Arasındaki İlişki: G20 Ülkeleri Örneği”

The research question of whether carbon emissions affect the economic growth and financial development of countries is discussed in the literature. Based on this, this study examines the relationship between carbon emissions (CO2) market capitalisation and renewable energy consumption, which are financial development indicators. The model established with the carbon emissions, renewable energy consumption, market value, fixed capital investments and gross domestic product indicators of the G20 countries between 1992 and 2018 was tested with panel data cointegration analysis and panel causality analysis. As a result of the empirical analysis, it has been found that there is a statistically significant and negative relationship between renewable energy consumption, market capitalisation and carbon emissions, and there is a bidirectional causality relationship between market capitalisation and carbon emissions. The results are that the effective use of energy and the developments in the financial system will contribute to sustainable development policies.

Annual performance analysis of solar-assisted raw-water source heat pumps at low water temperatures

With the increase in energy consumption for building heating and cooling, raw-water source heat pumps (RWSHPs) have garnered strong attention because of their advantages of high efficiency and utilization of a clean heat source. However, RWSHPs exhibit poor performance at low water source temperatures. Thus, this study proposes a solar-assisted raw-water source heat pump (SA-RWSHP) to solve the performance degradation of RWSHPs. The SA-RWSHP can improve performance during the heating period by elevating the entering water temperature (EWT) using solar collectors. During the cooling period, a solar heat source can be used to produce domestic hot water. Optimal design parameters are determined by analyzing the performance of SA-RWSHP using the TRNSYS. Additionally, the performance of SA-RWSHP is compared with that of RWSHP. During the heating period, the unit COP (COPhp) of SA-RWSHP was 12.7% higher than that of RWSHP on average, owing to the increase in the EWT. Furthermore, the annual total system COP of SA-RWSHP was approximately 18% higher than that of RWSHP owing to the high COPhp and effective use of solar energy. Overall, the SA-RWSHP exhibited superior performance throughout the year, resulting in a substantial reduction in building energy consumption.

The optimal dispatching strategy of cogeneration based on Deep Q-Network (DQN) algorithm

This work expands on previous research to offer a state-of-the-art approach for optimizing the dispatching of cogeneration systems, given the limitations faced by conventional coal-fired cogeneration units and the increasing environmental standards. Acknowledging the constraints of flexibility in winter heating, the study aims to improve unit coal use optimization and lower emissions. The paper presents a novel optimization approach for distributing electricity and heat in cogeneration units, utilizing the Deep Q-Network (DQN) algorithm. The suggested approach reduces operating expenses and improves system dependability using a sixth-order function fitting and fuzzy set space division. The study’s results indicate a significant 8.96% increase in performance, demonstrating the effectiveness of the DQN-based strategy in enabling cost-effective scheduling in cogeneration systems. This research offers a road towards sustainable and effective energy use and contributes to the development of cogeneration technology. It also has potential applications in natural energy systems.

Nanocosmos of catalysis: a voyage through synthesis, properties, and enhanced photocatalytic degradation in nickel sulfide nanocomposites.

Nanomaterials play a decisive role in environmental applications such as water purification, pollutant monitoring, and advanced oxidation-based remediation processes, particularly in semiconductor and metal sulfide-based photocatalysis. Metal sulfides are ideal for photocatalysis because of their unique optical, structural, and electronic characteristics. These properties enable the effective use of solar energy to drive various catalytic reactions with potential uses in environmental remediation with sustainable energy production. Among them, nickel sulfides (NiS) stand out for their narrow band gaps, high stability, and cost-effectiveness. This review thoroughly analyzes recent advancements in employing nickel-sulfide-based nanostructures for water decontamination. It begins by addressing environmental material needs and emphasizing the properties of nickel sulfide. To improve photocatalytic performance, controlled processes that affect the active structure, shape, composition, and size of nickel sulfide photocatalysts are examined, along with their synthesis methods. The heart of the review article is a detailed analysis of the modification of NiS through metal and non-metal doping, heterojunction, and nanocomposite formation for enhanced photocatalytic performance. The discussion also includes metal-modified nanostructures, metal oxides, and carbon-hybridized nanocomposites. This study underscores notable advancements in the degradation efficiency of NiS photocatalysts, rivaling their costly noble-metal counterparts. The analysis concludes with potential future directions for nickel sulfide-based photocatalysts in sustainable environmental remediation.

Machine Learning-Driven Wind Energy Forecasting for Sustainable Development

The growing need for energy, in addition to the depletion of fossil fuel supply, has underlined the importance of renewable energy for long-term growth. Renewable energy stands out among these, but its broad usage is hampered by the inherent uncertainty of wind power generation. This study uses machine learning to predict wind energy yield. Several regression models were used, including decision tree regression, linear regression, and random forest regression. The results emphasize the random forest regression, which has a high R-squared score, suggesting strong predictive ability. The paper also contains wind power output projections, which provide insights for optimal wind energy planning and usage. Overall, this attempt gives vital insights to improving the effective use of renewable energy, advancing the cause of sustainable development.

Green Economic Policies, Strategies & Initiatives of India

Sustainable economic development is crucial to secure human welfare and eliminate social inequality. Global leaders have recently made progress towards reaching an agreement on how to convert the current unsustainable economic trends into sustainable green economic growth. The viability of the green economy depends on several variables, including governmental policy, the business climate, and environmental concerns. The presented paper examines the implementation of green economic policies and analyses government strategies and initiatives taken by the government at the national level. The study uses a descriptive-analytical approach. The study finds India is putting many regulations and initiatives into place to encourage the effective use of energy in a variety of economic areas, including green building, equipment, farming, mobility, and fuels. These green growth initiatives lower the economy's carbon intensity and provide a sizable number of green jobs.

Usable thermal energy stored in the district heating system for peak shaving: A dynamic simulation study

The operational efficiency of district heating system (DHS) relies on the effective use of stored thermal energy, which spans from heating sources to heat users. Enhancing the operational flexibility of the combined heat and power (CHP) unit necessitates a quantitative evaluation of DHS’s usable thermal energy storage to optimize its utilization over time. This evaluation is subject to variability due to the scale, topological structure, and dynamic behaviors of the DHS, presenting a complex challenge. Therefore, the maximum maintenance time and room temperature recovery time were defined as indicators to estimate the usable thermal energy of the DHS for peak shaving in this study, and the dynamic DHS models were constructed for this purpose. Simulations reveal that upon cessation of heating steam flow, standard indoor temperature requirements can be preserved for approximately 2 h. These models facilitate the determination of the optimal maximum maintenance time for various scenarios, thereby maximizing thermal energy utilization within the DHS. Additionally, an analytical derivation of a simplified model for maximum maintenance time calculation, suitable for integration with control systems, is presented. The deviation of this model from actual values is below 10%.

Assessment of Batteries’ Contribution for Optimal Self-Sufficiency in Large Building Complexes

The EU has set ambitious targets to combat climate change. Incorporating renewable energy technologies to reduce greenhouse gas emissions is a critical aspect of achieving the European Union’s (EU) 2030 climate goals. Similarly to all member countries of the EU, Greece shares the same climate goals. In order to achieve these goals, ensuring a consistent supply and the effective use of clean energy is pursued, as it has a significant impact on the sustainable development and growth of the country. As the Greek tourism sector is one of the most energy-consuming of the national economy and a major contributor to the country’s GDP, opportunities are presented for innovation and investment in sustainable practices. Such investments must focus on buildings and facilities, where the energy consumption is concentrated. One of the most popular holiday destinations in Greece is the island of Crete. Visitation patterns are seasonal, which means during the summer months, Crete is exceptionally popular and more demanding energy-wise. One of the highest energy-demanding types of tourism-based businesses is the hospitality industry. Energy demands in hotels are driven by factors such as heating, cooling, lighting, and hot water. Thus, such activities require thermal and electrical energy to function. Electrical energy is one of the most essential forms of energy for hotels, as it powers a wide range of critical systems and services throughout the establishment. Therefore, the hotels are highly susceptible to fluctuations in energy prices which can significantly impact the operational costs of hotels. This paper presents an analysis of the annual consumption for the year of 2022 of five hotels located in Crete. An algorithm is also implemented which strives to minimize the capital expenditure (CAPEX), while ensuring a sufficient percentage of self-sufficiency.