Search Results (2,462)

The escalating utilisation of second homes has led to an extension in heating periods and, to a certain degree, renovations to elevate the standard, resulting in augmented energy and resource consumption. A comprehensive survey was conducted in Sweden, examining user patterns across different seasons, heating systems, and implemented energy efficiency measures. The results indicate that second homes are occupied for extended periods during the summer season and intermittently throughout the year. Over half of the second homes are heated even when unoccupied, with 12% maintaining a temperature above 16 °C. The predominant heating method is direct electricity (32.2%), followed by heat pumps (29.5%) and stoves (17.5%). A variety of renovations are undertaken, primarily to enhance the standard and technical performance, but also to implement energy efficiency measures such as window replacement, additional insulation, or heat pump installation. Based on the reported user and heating patterns, and the energy renovations carried out, the potential energy savings with different energy renovation strategies were estimated for the Swedish second home stock. The results show that though lowering the temperature when a second home is unoccupied emerges as the most efficient measure, both in terms of cost-effectiveness and climate impact, it needs to be complemented with intermittent heating or dehumidification to ensure that the relative humidity is below critical levels, to avoid the risk of damages caused by, for example, mould growth. Installing a heat pump is the second most energy- and cost-effective measure and has the advantage that the indoor temperature can be maintained at rather high levels. Full article

The thermal performance of windows is an important area of research to reduce the energy consumption of buildings and improve indoor comfort. The application of innovative glazing technologies can improve the energy performance of windows and transparent facades, resulting in significant energy savings. This paper presents research results on the energy performance of electrically heated windows. A comprehensive СFD and experimental analysis of the heat transfer processes in a window space depending on the size, power, and location of an electric heater was performed. The convective gas flows in the gas gaps and in the boundary layer were also analysed, and it is shown that a window with an electric heater can reduce the energy consumption of a room by 10–12%. This study is a pilot study to assess the feasibility and cost-effectiveness of electric local heating of a window or facade to minimise heat loss before full-scale implementation. The results of numerical modelling and experimental studies confirm the potential of the new technologies. Full article

Microgrid (MG) control is crucial for efficient, reliable, and sustainable energy management in distributed energy systems. Genetic Algorithm-based energy management systems (GA-EMS) can optimally control MGs by solving complex, non-linear, and non-convex problems but may struggle with real-time application due to their computational demands. Model Predictive Control (MPC)-based EMS, which predicts future behaviour to ensure optimal performance, usually depends on linear models. This paper introduces a novel Genetic Predictive Control (GPC) method that combines a GA and MPC to enhance resource allocation, balance multiple objectives, and adapt dynamically to changing conditions. Integrating GAs with MPC improves the handling of non-linearities and non-convexity, resulting in more accurate and effective control. Comparative analysis reveals that GPC significantly reduces excess power production, improves resource allocation, and balances cost, emissions, and power efficiency. For example, in the Mutation–Random Selection scenario, GPC reduced excess power to 76.0 W compared to 87.0 W with GA; in the Crossover-Elitism scenario, GPC achieved a lower daily cost of USD 113.94 versus the GA’s USD 127.80 and reduced carbon emissions to 52.83 kg CO2e compared to the GA’s 69.71 kg CO2e. While MPC optimises a weighted sum of objectives, setting appropriate weights can be difficult and may lead to non-convex problems. GAs offer multi-objective optimisation, providing Pareto-optimal solutions. GPC maintains optimal performance by forecasting future load demands and adjusting control actions dynamically. Although GPC can sometimes result in higher costs, such as USD 113.94 compared to USD 131.90 in the Crossover–Random Selection scenario, it achieves a better balance among various metrics, proving cost-effective in the long term. By reducing excess power and emissions, GPC promotes economic savings and sustainability. These findings highlight GPC’s potential as a versatile, efficient, and environmentally beneficial tool for power generation systems. Full article

This study presents an advanced co-optimization model for water–energy nexus systems (WENSs), illustrating considerable benefits in both energy conservation and cost reduction through synergistic operations. Case studies compare the co-optimized operations of a 33-bus power distribution network (PDN) coupled with a commercial-scale 15-node water distribution network (WDN) via water pumps and a standalone operations of a PDN and WDN, revealing that co-optimization notably decreases the operational costs for both networks by 23% and 49%, respectively, leading to substantial daily savings. In addition, this paper summarizes the current problems based on previous research, delineating the challenges in the co-optimization and management of WENSs, such as modeling inaccuracies, uncertainty management, and multi-stakeholder governance, providing meaningful insights and potential directions for future research. Full article

Limited material options and economic conditions significantly restrict the potential for energy efficiency improvements in rural houses in China’s cold regions. It is worth exploring how to propose suitable energy-saving renovation plans for rural houses in cold regions under practical constraints. By using Grasshopper within Rhinoceros 8 software, an algorithm integrates material selection, energy consumption calculations, and economic analysis. The method efficiently generates thermal optimization schemes, providing insights into energy use, costs, and payback periods. In a case study of a typical rural house in Daqing City, the optimized scheme achieved over 70% energy savings compared to traditional homes, with renovation costs amounting to less than 40% of residents’ annual income and a 2-year payback period. This significant improvement highlights the potential of the proposed method in enhancing the energy efficiency and economic viability of rural house renovations. Full article

The realm of green energy is in constant flux, drawing considerable attention from stakeholders dedicated to minimizing environmental impact, reducing costs, and developing structures that align with stringent standards. This study introduces an innovative approach aimed at improving onshore wind tower foundation systems, emphasizing both engineering and financial feasibility. The approach involves a comprehensive analysis of design load cases, particularly emphasizing resistance against overturn, while ensuring compliance with Eurocode guidelines. The foundation system is conceptualized as a beam slab with voids filled by soil material. High reduction in concrete quantity is achieved by reaching 30%, while the steel reduction reaches 90%. It is worth mentioning that the total cost is reduced by up to 70%. Furthermore, as a future trend, this study aims to integrate the new foundation system with steel 3D printing technology in the manufacturing process of the wind tower’s structural elements. This integration is expected to enhance the precision and customization of the superstructure-foundation system, thereby improving overall performance and efficiency. The optimized design not only significantly reduces construction costs but also streamlines installation, saving time. Simultaneously, this study enhances the structural behavior of the wind tower foundation by focusing on elements crucial to its efficiency. Full article

A multi-objective energy management and scheduling strategy for a microgrid comprising wind turbines, solar cells, fuel cells, microturbines, batteries, and loads is proposed in this work. The plan uses a fuzzy decision-making technique to reduce pollution emissions, battery storage aging costs, and operating expenses. To be more precise, we applied an improved honey badger algorithm (IHBA) to find the best choice variables, such as the size of energy resources and storage, by combining fuzzy decision-making with the Pareto solution set and a chaotic sequence. We used the IHBA to perform single- and multi-objective optimization simulations for the microgrid’s energy management, and we compared the results with those of the conventional HBA and particle swarm optimization (PSO). The results showed that the multi-objective method improved both goals by resulting in a compromise between them. On the other hand, the single-objective strategy makes one goal stronger and the other weaker. Apart from that, the IHBA performed better than the conventional HBA and PSO, which also lowers the cost. The suggested approach beat the alternative tactics in terms of savings and effectively reached the ideal solution based on the Pareto set by utilizing fuzzy decision-making and the IHBA. Furthermore, compared with the scenario without this cost, the results indicated that integrating battery aging costs resulted in an increase of 7.44% in operational expenses and 3.57% in pollution emissions costs. Full article

The application of fixed activated sludge with an attached growth process (FASAG) with optimal operating conditions (hydraulic retention time (HRT) of 7 h, dissolved oxygen (DO) of 6 mg/L, and alkalinity dosage of 7.14 mgCaCO₃/mgN-NH₄⁺) treats wastewater generated from office buildings to meet discharge requirements (as per the regulation in the nation where the study was conducted) with typical parameters such as pH of 6.87–7.56, chemical oxygen demand (COD) of 32–64 mg/L, suspended solids (SS) of 8–11 mg/L, N-NH₄⁺ of 1–7 mg/L, and denitrification efficiency reaches 53%. In addition, the FASAG is an outstanding integration that makes both economic and environmental sense when applied in local wastewater treatment systems. In particular, this process combines aerobic and anoxic processes in a creation tank. This explains why this approach can save investment and operating costs, energy, and land funds. In office building regions, where land area is frequently limited, saving land funds presents numerous options to enhance the density of green cover. Furthermore, as a new aspect, investing in reusing wastewater after treatment to irrigate plants or flush toilets in office buildings contributes to a decrease in the quantity of wastewater released into the environment, saving water resources and supporting sustainable development. Full article

Agriculture in controlled environments has gained popularity over time. Compared to traditional agriculture, controlled environments emerge as an alternative to mitigate the negative impacts of conventional farming methods. However, controlled environment agriculture, particularly plant factories with artificial lighting, incurs higher electricity costs, primarily for supplemental lighting and dehumidification of the cultivation area. Given these high costs, it is crucial to understand how efficiently plants utilize available light to convert it into biomass. This understanding can be used to design lighting strategies to reduce electricity usage. In this study, we cultivated ‘Rex’ lettuce (Lactuca sativa) plants on a soilless substrate and used an ebb-and-flow system for irrigation and fertilization. Plants grew in varying photosynthetic photon flux density (PPFD) levels ranging from 125 to 375 µmol·m⁻²·s⁻¹ and were assessed for various physiological responses. Our findings revealed that plants exposed to higher light levels exhibited greater final dry weight, increased photosynthetic activity, higher water use efficiency, and accelerated growth compared to those under lower light conditions. Notably, plants subjected to higher light intensities did not show a significant increase in transpiration, suggesting a potential trade-off between energy expenditure on supplemental lighting and dehumidification. This finding opens the possibility of reducing energy consumption for dehumidification and achieving economic savings by subjecting plants to optimal growing conditions for shorter durations. This depends on whether higher savings on dehumidification are achieved compared to the energy required to maintain high PPFD levels. Full article

Electric vehicle systems and smart grid systems are setting stringent development targets to respond to global trends in energy saving, carbon reduction, and sustainable environmental development. In the field of batteries, there has been extensive discussion on the estimation of battery charge. In battery management systems (BMSs) and charging/discharging systems, the accuracy of the measurement of battery physical parameters is critical, as it directly affects the system, alongside the algorithm’s estimation and error correction. Therefore, this paper proposes incorporating a low-power continuous-time delta-sigma analogue-to-digital converter into a battery measurement system to support deep learning algorithms for battery state estimation. This approach aims to maintain the accuracy of battery state estimation while reducing latency and overall system power consumption. Implemented using the UMC 0.18 μm CMOS 1P6M process, the proposed design achieves a measured signal-to-noise distortion ratio (SNDR) of 78.42 dB, an effective number of bits (ENOB) of 12.73 bits, and a power consumption of approximately 15.97 μW. The chip layout area is 0.67 mm × 0.56 mm. By applying delta-sigma modulators to energy management systems, this solution aims to increase the total number of battery monitoring units while reducing overall power consumption and construction costs. Full article

(1) Background: LCA is an established method for the systematic analysis of the environmental impact of products throughout their life cycle. (2) Methods: The LCA on fresh (un)packed and frozen carrots, with system boundaries from the cradle to supermarket gate and the functional unit of 1 kg of carrots, is applied using openLCA 1.11, Agribalyse v 3.1 and is calculated with EF 3.0. A sensitivity analysis of transport and carrot loss was made. To consider economic sustainability, a cost calculation for transportation and cooled storage is conducted. (3) Results: The impact category of climate change for fresh carrots results in 0.186 kg CO₂ eq for unpacked carrots, 0.200 kg CO₂ eq for LDPE-packed carrots, and 0.195 kg CO₂ eq for PLA-packed carrots. Transportation accounts for the largest impact, with up to 50% resulting from the transportation distance and the use of cooled lorries, followed by post-harvest handling (15–21%) and cultivation (21–22%). PLA-packed carrots save 2.4% of CO₂ and 6.0% of fossil energy compared to LDPE-packed carrots. Regional carrots with short transportation distances require only 57% of CO₂. Frozen carrots have a threefold higher result of 0.614 kg CO₂ eq, resulting mostly from the high amounts of energy required for production and frozen storage. Post-harvest handling contributes to 43% of CO₂, followed by supermarket storage (27%) and transport (22%). The transportation costs for frozen carrots are 24% higher than for fresh carrots, and their storage costs are 3.8 times higher at 0.181 EUR/kg. (4) Conclusion: Frozen carrots are more expensive and have a greater environmental impact. Nevertheless, they are relevant for the preservation of agricultural products and year-round availability. Full article

The European Union is increasingly directing efforts and resources toward promoting the adoption of energy saving measures among citizens, but the effectiveness of these efforts cannot be ensured if the heterogeneity of citizens is neglected. This paper assesses whether Greek citizens present heterogeneity in terms of their energy behavior and investigates whether they can be classified based on the practices they apply to reduce energy costs and their environmental attitudes. To that end, the study collected a representative citizen sample, and k-means cluster analysis was performed. Results indicated significant heterogeneity and four clusters were identified: ‘Extreme heat savers and pro-environmental food consumers’ saved on heating but neglected practices regarding lighting, hot water use, and transport; ‘Heat savers and environmentally unaware’ applied energy saving measures only to lower heating costs; ‘Environmentally aware energy savers’ were the most engaged segment in the application of energy saving measures driven by pro-environmental attitudes; and ‘Mindful resources and transport users’ did not apply any measures for heating despite having positive attitudes in terms of electricity, water and transport use. Therefore, it is necessary to train citizens on pro-environmental practices, and in doing so, the recorded heterogeneity can guide the design of differentiated and effective approaches. Full article

The mining industry is a basic sector of the Russian economy. Sustainable Development Goals appear in the strategies of mining companies and are ensured, inter alia, by increasing the energy efficiency of enterprises and plants within their structure through the implementation of projects. The lack of generally accepted criteria for assessing energy efficiency determines the need to develop a methodology that would allow taking into account the contribution of the results of projects of different scales and levels of implementation to improve the energy efficiency of the mining enterprise and the company as a whole. The purpose of the study is to develop a methodology for the comprehensive assessment of projects aimed at improving the energy efficiency of mining enterprises in the context of sustainable development. The research method is based on establishing a logical relationship between the goals of sustainable development, the principles of the “energy trilemma”, criteria and results of the implementation of projects aimed at improving the energy efficiency of the mining enterprise, taking into account the systematization of these projects. The authors develop a methodology for assessing projects related to the energy efficiency of mining enterprises. The methodology is based on a two-level system of criteria: the first-level criteria characterize the degree of realization of project objectives in accordance with the goals of sustainable development and the principles of the “energy trilemma”. The first-level criteria consist of the following: economic efficiency, ecological performance, reliability and safety, and flexibility. The second-level criteria characterize the economic results of the project based on the assessment of its economic efficiency. In order to provide a comprehensive economic assessment of various project outcomes, a set of indicators is proposed. The assessment of this methodology has been tested using the example of projects implemented at the mining enterprise “Albazinsky GOK” (mining and processing complex). Implementation of a comprehensive project, including the transition to a centralized power supply source, installation of a wind generator, photovoltaic installation, and energy storage system, will allow the enterprise to reduce CO₂ emissions by 100% and increase the flexibility of the enterprise’s power system by 33%. The economic effect will amount to RUB 1252.5 mln (due to savings on electricity costs). The obtained results can be used by managers of mining companies to select and assess projects aimed at improving energy efficiency. Full article

Water pumping is highlighted as the major energy consumer in the water cycle. Solar energy has emerged as a promising alternative to traditional electric networks, particularly in areas lacking an electrical infrastructure. Solar-powered pumping stations are categorized as connected and isolated, with the latter adapting the pump operation based on available solar energy. This article proposes a scheme to adjust the pump operation according to natural factors, like irradiance and temperature, aiming to optimize energy use and minimize investment costs in solar panels. An application of this method in Valencia, Spain, demonstrates significant savings. Full article

In a conventional automotive manufacturing plant, the paint shop alone can represent 36% of the total energy consumption, making it the most demanding area in terms of electricity and fossil fuel energy consumption. This study explores the possibility of decentralizing the production of electrical power and heat simultaneously, using an Organic Rankine Cycle (ORC) system integrated with a Parabolic Trough Collector (PTC) in a paint shop. To date, no similar system has been explored or implemented by the automotive industry. To increase the efficiency of the integrated system, wasted heat generated during the paint manufacturing process is recovered and used to pre-heat the organic fluid in the ORC system. A 4E analysis (Energy, Exergy, Economic, and Environmental) is conducted to determine the practical viability of the proposed system. When applied to the southern region of the USA, this system’s installed capacity is projected to be 11 times higher than the two unique SORC pieces of equipment currently running in Louisiana and Florida. The goals are to reduce the reliance on external primary energy sources and decrease the carbon emission footprint from production activity. The system is evaluated for a location in Alabama, USA. The designed SORC, using toluene, can produce 712.2 kW_el net and 13,132 kg/h of hot water, with an overall energy efficiency of 31.02%; exergy efficiency of 34.23; and ORC efficiency of 27.70%. This leads to an electrical energy saving of 5.9% for the manufacturing plant. The regenerative thermal oxidizer (RTO) heat exchanger, the secondary heat source of the system, has the highest exergy destruction—3583 kW. The system avoids the emission of 4521 tCO₂ per year. A payback period of 10.16 years for the proposed system is estimated. Considering a planning horizon of 10 years, the investment in the system is also justified by a benefit–cost analysis. Full article