Energy savings techniques in ventilation processes with fans operating at variable load

Energy saving in manufacturing is the key to reduce energy consumption of unit GDP. Forming equipments are one of the biggest energy consumers. The basic reason of high energy consumption and low efficiency for current forming equipments is the mismatch between uncontrollable driving characteristics and the variable loads in forming processes. Complex transmission and control mechanisms are needed, wasting a lot of energy. The basic principles of driving were put forward to realize energy saving for forming equipments: faster in virtual strokes, slower in working strokes, stop when idling and recycling excessive energy. The servo driving based on large AC servo motors can make the driving and forming loads match each other well, realizing not only high automation and intelligence, but energy saving greatly as well. Theoretical analysis and experiments showed that by adopting AC servo driving the crank presses, hydraulic presses and screw presses could get the energy saving results of 25-70%.

Energy Conservation Potential in SMEs of Thailand

This paper describes the results of enhancing energy effi ciency of hydro turbines by implementing the energy conservation measures for hydro turbine generators. The procedure for evaluating the on-line performance of generators is discussed. The energy saving in generators by maintaining optimum generator terminal voltage, by reducing the stator winding temperature, by improving the performance of coolers and reducing the excitation loss by appropriate tuning of excitation system are enumerated in detail with case studies. The implementation of energy conservation measures has a techno-economic feasibility with a payback period of 1–5 years.

Accurate estimation of energy savings is crucial for the effective implementation of energy conservation measures (ECMs). Simultaneously, the integration of Artificial Intelligence (AI) has revolutionized software engineering by imbuing software with intelligent capabilities and autonomy. In this paper, we propose an ensemble model for precisely estimating baseline energy consumption within the realm of AI-empowered autonomous software. The ensemble model combines predictions from three tree-based Machine Learning models, namely Random Forest, XGBoost, and LightGBM. Notably, our model emphasizes the provision of explainability, granting transparency and insights into the key factors influencing baseline energy consumption. To validate its effectiveness, we conduct experimental evaluations on a diverse cluster of real-world buildings in Latvia. The results demonstrate the superiority of our proposed ensemble model over individual models and even a deep learning network tailored for energy consumption estimation. These findings underscore the efficacy of AI-empowered models in the energy sector, offering a robust and interpretable solution for estimating energy savings.

STUDENT-PERFORMED ENERGY AUDITS: THREE CASE STUDIES

Introduction: South Africa is ranked among the 20 highest greenhouse gas (GHG) emitters worldwide, mainly due to its heavy reliance on coal for energy. The residential building industry can play a significant role towards the minimization of both GHG emissions and energy consumption. This research assesses the beneficial impacts of utilizing wall envelope insulation measures using five insulation materials, for a detached residential building, within the seven energy zones of South Africa in accordance with the South African National code for Building energy efficiency (SANS10400-XA).Methods: Lifecycle analysis (for 50 years), regression methods and sequential search techniques of building energy modelling were used to determine both the energy saving implications of adopting the insulation materials (at various levels of thickness), and their corresponding energy payback periods. The study area consisted of eight selected locations representing all the seven energy zones in South Africa (Welkom, Witbank, Thohoyandou, Cape Town, Pretoria, Ixopo, Sutherland, and Fraserburg).Results: Sutherland (zone 6), Cape Town (zone 4) and Fraserburg (zone 7) benefitted most from energy savings due to application of insulation measures. Witbank (Zone 2), Thohoyandou (zone 3) and Pretoria (zone 5) never benefitted from application of wall envelope insulation (in terms of energy savings). Cellulose and straw yielded the lowest payback periods. Generally, polyurethane yielded the highest net energy savings at lower insulation thickness levels, while cellulose was preferable at higher insulation thickness levels in Welkom (zone1) Cape Town (zone 4), Ixopo (zone 5H), Sutherland (zone 6) and Fraserburg (zone 7).Discussion: Lower optimal wall envelope insulation thicknesses (that maximized energy savings) appeared to correspond to locations with higher annual temperature ranges. Higher temperature ranges (hence, higher degree days) would ensure that more energy is saved in order to keep the indoor temperatures within the acceptable comfort limits, due to application of insulation. However, the selection of insulation material is also influenced by other factors such as resistance to insect and mould attack (which easily affect bio-insulation materials), fire retardancy, durability (which affects cellulose), sound proofing, structural strength, and resistance to water vapour.

The study aims to address advanced approaches to the optimal settings of heating structures and panels to improve thermal comfort and energy efficiency in buildings. The study analysed various materials for thermal insulation, different heating systems and energy-efficient windows, using common formulas to calculate their thermal performance and efficiency. The study analysed various modern methods of optimising heating systems to improve thermal comfort and energy efficiency in buildings. As such, the study determined that the use of intelligent heating control systems, such as smart thermostats and sensors, can significantly reduce energy consumption. The study also determined that heat pumps, especially geothermal and air source heat pumps, are effective solutions for sustainable heating. The study results confirmed that three-chamber windows with a third gap between the glass panes can maximise energy savings by significantly reducing heat loss and providing high thermal insulation. The study also determined that condensing gas boilers and heat pumps are optimal for efficient energy savings. Low-temperature heating systems, such as underfloor heating and efficient radiators, contribute to even heat distribution and energy savings. The use of renewable energy sources, such as solar collectors and wind turbines, was also determined to be an effective means of reducing dependence on traditional energy resources. The study also showed that the integration of various technologies and systems into a single climate control system allows for maximum efficiency and comfort. As a result, the combined use of innovative methods and materials not only significantly reduces energy consumption but also improves living conditions in modern buildings.

Ensuring a comfortable indoor air quality requires a minimum fresh air supply by ventilation. Moreover, the improvement of the air tightness in new and refurbished high performance buildings enhances the role of mechanical ventilation and its importance in further increasing the energy efficiency. Indeed, a reduction of the ventilation load can be achieved by installing air-to-air heat recovery devices, whose potential energy savings can be easily assessed by means of their nominal effectiveness. However, this estimation does not consider the impact on the overall performance of the system, in particular when humidity control is needed. Proper control strategies can be defined on the basis of the indoor latent load to prevent preheating or avoid moisture recovery when dehumidification by cooling is then required. In this work, the energy saving potential of heat recovery systems has been analyzed, considering the impact of different control strategies on both energy and cost savings. The calculations have been generalized using the specific latent load, which allows for the analysis of strategies and savings based on typical utilization categories, without considering in detail all the building characteristics. Representative hourly weather data for 66 European cities have been used to evaluate sensible and total heat recovery devices. The energy and the cost saving results have been mapped per each European Köppen-Geiger climate class and each country, respectively. The proposed strategies based on humidity control can strongly reduce the attractiveness of total heat recovery with respect to sensible heat recovery in terms of energy and cost savings, especially when high specific latent loads are considered.

Networking infrastructure consumes a sizable fraction of the electricity supply. A network design model aimed at maximizing energy savings by aggregating traffic demand at a small set of resources, to put under-utilized resources to sleep, is offset by legacy models aimed at maximizing the network throughput by spreading the load across network resources. Traffic fluctuations and sudden spikes further complicate the problem. In this paper, we show that the problem is NP-hard, and propose a heuristic which targets optimal power usage for common traffic demand, while accommodating traffic fluctuations. The efficacy of our design is tested on two published backbone networks: NLR and NSFNET. Simulation results reveal that the proposed heuristic closely matches the results of the optimal algorithm in both energy savings and network utilization, while enjoying polynomial time complexity.

This study summarizes the results from a simulation study for a typical villa in Muscat, a hot humid city in Oman. A housing model was generated in the DesignBuilder software. The model was compared against real utility readings before it was further taken for the energy calculations. Different thermal characteristics of building envelope including the heat transmission, thermal mass, solar heat gain through windows and air infiltration were evaluated. Many energy-efficient envelope design options were generated. Sensitivity analysis was then performed to narrow down the design parameters to the most significant parameters. From the sensitivity analysis, it was found that no significant energy savings are achieved beyond 15 cm of thermal insulation for both walls and roof. The solar heat gain coefficient (SHGC) was found more significant than the U-values of the glazing. It was also found that the house should be air tight as the air infiltration was significant. External shading was advantageous too in hot climates. A brute force optimization approach was then carried out using unsubsidized and subsidized energy cost scenarios. A maximum energy savings of 26.7% and a minimum energy savings of 18.4% were achieved for both energy cost scenarios. For maximum energy savings, 15 cm insulation for walls and roof, a double low-e selective tinted glazing, 100 cm of overhang shading were found to be the optimal design. The optimal designs for minimum life cycle cost were, however, different for the two energy cost scenarios. For unsubsidized energy cost, 10 cm insulation for walls and roof, a single green tinted glazing, and 100 cm of overhang shading were found to be the optimal design. For subsidized energy cost, a 7.5 cm for wall and roof are the optimal while other parameters are similar to the unsubsidized case. The results from the study will help both the policy makers, designers, and owners to select their optimal designs based on different cost functions.

Hybrid-type magnetic bearings using both permanent magnets and electromagnets have been used for rotating machinery. In the case of conventional thrust hybrid magnetic bearings supporting axial loads, radially magnetized permanent ring magnets, which have several demerits such as difficult magnetization and assembly, have been used to generate bias flux. In this study, a novel thrust hybrid magnetic bearing using an axially magnetized permanent ring magnet is presented. Because it is easy to magnetize a ring magnet in the axial direction, the segmentation of the ring magnet for magnetization is not required and the assembly process can be simplified. For verifying the performance of the proposed method, a test rig that consists of a proposed thrust magnetic bearing and variable loads is constructed. This paper presents the detailed design procedures and the obtained experimental results. The results show that the developed thrust magnetic bearing has the potential to replace conventional thrust magnetic bearings.

A SOGI-based adaptive controller design for second-harmonic currents suppression of variable frequency loads in DC buildings

Exceeding Pinch limits by process configuration of an existing modern crude oil distillation unit – A case study from refining industry

This paper details a study performed by the Irrigation Training and Research Center to determine motor performances under varying speeds [induced by a variable frequency drives (VFD) controller] and loads. A further goal of the study was to provide sufficient information to designers so that they could estimate total pumping plant power usage with a VFD-controlled installation. Motors were tested with a VFD as well as across-the-line. On average, the relative efficiency of the electrical system with a VFD may be approximately 8% lower than the relative efficiency of a properly designed, full-load across-the-line system. If one considers actual field operating conditions this 8% is misleading because overall energy savings can be obtained with VFDs due to their ability to properly adjust speeds to meet actual field conditions.

Motivation: MRI significantly contributes to healthcare-related greenhouse gas emissions; therefore, reducing MRI energy use through accelerated imaging and deep-learning reconstruction (DLR) is essential. Goal(s): To quantify the energy savings and emissions reductions achievable using accelerated MRI combined with DLR, while ensuring minimal compromise in image quality. Approach: Energy consumption was measured on three 3T MRI scanners during standard and accelerated imaging with DLR, validated using ACR phantom tests and human subject imaging. Results: Accelerated MRI with DLR reduced scan times and energy consumption by 3-5 times without compromising diagnostic image quality, yielding potential institutional savings of 74.1 metric tons of CO₂eq emissions annually. Impact: Accelerated MRI with DLR enables significant clinical efficiency and sustainability improvements, facilitating rapid, high-quality imaging. Future studies can explore enhanced DLR algorithms, optimizing diagnostic performance while maximizing energy savings and emissions reductions across healthcare settings.