Reduce Electricity Consumption Research Articles

Membrane-Free Water Electrolysis for Hydrogen Generation with Low Cost.

Conventional water electrolysis relies on expensive membrane-electrode assemblies and sluggish oxygen evolution reaction (OER) at the anode, which makes the cost of green hydrogen (H2) generation much higher than that of grey H2. Here, we develop an innovative and efficient membrane-free water electrolysis system to overcome these two obstacles simultaneously. This system utilizes the thermodynamically more favorable urea oxidation reaction (UOR) to generate clean N2 over a new class of Cu-based catalyst (CuXO) for replacing OER, fundamentally eliminating the explosion risk of H2 and O2 mixing while removing the need for membranes. Notably, this membrane-free electrolysis system exhibits the highest H2 Faradaic efficiency among reported membrane-free electrolysis work. In situ spectroscopic studies reveal that the new N2Hy intermediate-mediated UOR mechanism on the CuXO catalyst ensures its unique N2 selectivity and OER inertness. More importantly, an industrial-type membrane-free water electrolyser (MFE) based on this system successfully reduces electricity consumption to only 3.78 kWh Nm-3, significantly lower than the 5.17 kWh Nm-3 of commercial alkaline water electrolyzers (AWE). Comprehensive techno-economic analysis (TEA) suggests that the membrane-free design and reduced electricity input of the MFE plants reduce the green H2 production cost to US$1.81 kg-1, which is lower than those of grey H2 while meeting the technical target (US$2.00-2.50 kg-1) set by European Commission and United States Department of Energy.

Membrane‐Free Water Electrolysis for Hydrogen Generation with Low Cost

AbstractConventional water electrolysis relies on expensive membrane‐electrode assemblies and sluggish oxygen evolution reaction (OER) at the anode, which makes the cost of green hydrogen (H2) generation much higher than that of grey H2. Here, we develop an innovative and efficient membrane‐free water electrolysis system to overcome these two obstacles simultaneously. This system utilizes the thermodynamically more favorable urea oxidation reaction (UOR) to generate clean N2 over a new class of Cu‐based catalyst (CuXO) for replacing OER, fundamentally eliminating the explosion risk of H2 and O2 mixing while removing the need for membranes. Notably, this membrane‐free electrolysis system exhibits the highest H2 Faradaic efficiency among reported membrane‐free electrolysis work. In situ spectroscopic studies reveal that the new N2Hy intermediate‐mediated UOR mechanism on the CuXO catalyst ensures its unique N2 selectivity and OER inertness. More importantly, an industrial‐type membrane‐free water electrolyser (MFE) based on this system successfully reduces electricity consumption to only 3.78 kWh Nm−3, significantly lower than the 5.17 kWh Nm−3 of commercial alkaline water electrolyzers (AWE). Comprehensive techno‐economic analysis (TEA) suggests that the membrane‐free design and reduced electricity input of the MFE plants reduce the green H2 production cost to US$1.81 kg−1, which is lower than those of grey H2 while meeting the technical target (US$2.00–2.50 kg−1) set by European Commission and United States Department of Energy.

A non-intrusive fine-grained load identification method based on three-dimensional voltage–current trajectories

Addressing issues such as high hardware costs, low recognition accuracy, and the inability to achieve fine-grained equipment classification, a non-invasive load fine-grained recognition system based on FPGA was developed and tested on a Linux system for online training. A three-dimensional (3D) image construction method based on color coding of voltage–current (V-I) trajectories is proposed to preprocess the collected voltage and current data, allowing for the distinction of features of various electrical equipment in multiple dimensions. First, high-frequency sampling data is preprocessed to extract the V-I trajectory and higher harmonic characteristics of the load. Then, the V-I trajectory is processed using RGB color coding and fused with higher-order harmonic features to construct a 3D image. This results in a 3D color V-I trajectory image that incorporates both color and harmonic features. Finally, the improved ResNet50 network is employed to identify the load characteristics, and the method is validated using the PLAID dataset and measured data. The load identification method achieves an accuracy rate of over 98%, enhancing the information conveyed by the V-I trajectory and improving the uniqueness of load characteristics, thereby enabling fine-grained equipment identification. This advancement holds significant implications for energy conservation and emission reduction in household electricity consumption, as well as for eliminating potential safety hazards associated with electrical equipment.

Circulation process of methyl ester production from pretreated sludge palm oil using CaO/ABS catalytic static mixer coupled with an ultrasonic clamp

This study investigates the potential of fused deposition modeling (FDM) three-dimensional (3D) printing techniques for manufacturing catalytic static mixers during biodiesel synthesis. The printed catalytic mixing elements comprises acrylonitrile butadiene styrene (ABS) plastic with 15 wt% calcium oxide (CaO) as a solid catalyst. When the reactants flowed through the CaO/ABS mixing device, the blending and acceleration processes were both significantly impacted. Moreover, their characteristics, performance in biodiesel production, reusability, and economy were analyzed. The effects of methanol to oil (M:O) molar ratio, circulation time, and sonication time on methyl ester (ME) purity were also examined. The results showed that CaO crystals were distributed on the CaO/ABS mixer’s surface, which is crucial for catalytic purposes. During circulation process of ME from pretreated sludge palm oil (PSPO), catalytic static mixer (CSM) and CSM coupled with ultrasound (CSM/US) reactors were employed. The full ultrasonic power of CSM/US reactor of 16 × 400 W (total 6400 W) was operated at 20 kHz frequency. Moreover, the continuous and pulse ultrasonic modes of CSM/US reactor were compared to determine the ME purity and electricity consumption for ME production. For the CSM reactor, 12:1 M:O molar ratio and 8.5 h circulation time were recommended to realize 94.2 wt% ME purity. For the CSM/US reactor, 12:1 M:O molar ratio and 2.25 h circulation time were recommended to achieve 96.5 wt% ME purity. Under the pulsed mode operation, ME purity of 95.09 wt% was achieved, with a reduction in electricity consumption by approximately 37.6 % compared to continuous mode operation. Furthermore, the CaO/ABS catalytic static mixer was determined to be reusable for up to three cycles in both CSM and CSM/US reactors. Thus, CaO/ABS catalytic static mixers assure high purity ME production through FDM 3D printing technology with a CaO solid catalyst.

Technical and economic analysis of digitally controlled substations in local district heating networks

Since the 1990s, there has been a noticeable increase in the establishment of local district heating networks in Germany, coinciding with the use of thermal energy from biogas and biomass facilities. Historically, the prioritization of economically efficient heat utilization was subdued due to favorable electricity feed-in tariffs. However, with the expiration of Renewable Energy Sources Act subsidies, operators shifted focus to the operational costs of district heating networks. This study aims to examine the effects of optimizing controllers and valves at district heating substations in single-family homes, utilizing two local district heating networks. The emphasis is on evaluating impacts on operating costs and determining whether the economic and energetic benefits justify implementation. Simulation studies in MATLAB/Simulink Simscape depict both consumers and district heating networks individually, without aggregation. In the most favorable scenario, investing in enhancing substation controllers in single-family homes is projected to yield returns after 13 years. Comprehensive optimization of all substation controls in single-family homes can potentially result in up to 9 % savings in thermal energy demand due to reduced heat losses and a corresponding 9 % reduction in electrical power consumption for the main pump.

Application of Non-Parametric and Forecasting Models for the Sustainable Development of Energy Resources in Brazil

To achieve Sustainable Development Goal 7 (SDG7) and improve energy management efficiency, it is essential to develop models and methods to forecast and enhance the process accurately. These tools are crucial in shaping the national policymakers’ strategies and planning decisions. This study utilizes data envelopment analysis (DEA) and bootstrap computational methods to evaluate Brazil’s energy efficiency from 2004 to 2023. Additionally, it compares seasonal autoregressive integrated moving average (SARIMA) models and autoregressive integrated moving average (ARIMA) forecasting models to predict the variables’ trends for 2030. One significant contribution of this study is the development of a methodology to assess Brazil’s energy efficiency, considering environmental and economic factors to formulate results. These results can help create policies to make SDG7 a reality and advance Brazil’s energy strategies. According to the study results, the annual energy consumption rate is projected to increase by an average of 2.1% by 2030, which is accompanied by a trend of GDP growth. By utilizing existing technologies in the country, it is possible to reduce electricity consumption costs by an average of 30.58% while still maintaining the same GDP value. This demonstrates that sustainable development and adopting alternatives to minimize the increase in energy consumption can substantially impact Brazil’s energy sector, improving process efficiency and the profitability of the Brazilian industry.

Research on the Driving Factors and Policy Guidance for a Reduction in Electricity Consumption by Urban Residents

The urgency of mitigating climate change and the challenges it poses to ecosystems and human systems are highlighted in the Intergovernmental Panel on Climate Change’s (IPCC) Sixth Assessment Report (AR6). In order to achieve sustainable development, it is imperative to adopt a series of adaptive measures to enhance the resilience of various sectors to climate change and reduce greenhouse gas emissions. This article analyzes the driving mechanism behind the reduction in electricity consumption by urban residents based on 302 valid questionnaires from 18 communities in nine districts in B City. Using a method that combines qualitative and empirical research, the study proposes policy recommendations aimed at guiding urban residents toward reducing their electricity consumption. These recommendations serve as a policy reference for cities striving to achieve sustainability and low-carbon targets. The primary innovations and conclusions of the study are as follows: (1) this study summarizes the primary factors and processes influencing the reduction in electricity consumption among urban residents, examined from the following three perspectives: residents’ characteristics, psychological understanding, and external environment. (2) On the basis of the research data, empirical analysis and hypothesis testing are conducted using a variety of mathematical and statistical methods. The results indicate significant differences in the electricity consumption reduction behavior of heterogeneous urban residents in both public and private areas. Subjective norms, perceived behavioral control, and knowledge of electricity conservation have significant direct influences on residents’ willingness to reduce their electricity consumption. Among these factors, subjective norms have the most significant impact, while the impact of attitude is negligible. Economic incentive policies have a significant positive regulatory effect on the relationship between “willingness (intention)” and “private area electricity consumption reduction behavior”.

An evaluation and innovative coupling of seawater heat pumps in district heating networks

Seawater heat pumps present promising solutions for the decarbonization of the heating sector by utilising seawater as a renewable heat source. This study explores their integration into district heating networks in cold climate regions, focusing on case studies in Estonia, and Norway. A main challenge lies in the freezing threat of seawater during winter, prompting investigations into innovative solutions. This research evaluates two proposed strategies: coupling seawater heat pumps with an additional heat source and locating them far off the shore where water temperatures are more stable. The study employs a multifaceted approach, considering technical, economic, and environmental factors. The research assesses and models seawater heat pumps in two case studies, exploring 10 MW heat supply scenarios. Performance indicators include Coefficient of Performance (COP), Electricity consumption, CO2 emissions, and Levelized Cost of Heat (LCOH). Results highlight the feasibility and advantages of coupling free heat sources with seawater heat pumps in district heating networks. In the Norwegian case, coupling waste heat and seawater heat pumps significantly reduces electricity consumption, CO2 emissions, and LCOH by 88 %, 65 %, and 76 %, respectively. In Tallinn, where seawater freezing is a concern, installing far-off the shore seawater heat pumps maintain year-round operation with a seasonal COP of 3.5 and a 34 % reduction in CO2 emissions compared to electric boiler coupling. Economic assessments suggest the feasibility of integrating far-off the shore seawater heat pumps in low-power price scenarios.

On ways to reduce the energy supply costs in Russia

Purpose: is to research of ways to reduce the energy supply costs for Russian consumers.Methods: the analysis of the transformation of the electric power industry was carried out using the tools of tectology and system economic theory.Results: the key reason for the constant increase in the cost of energy supply has been identified, which is the transition from a systematic approach to energy development aimed at increasing general economic efficiency to maximizing the economic performance of independent energy companies. The need to adjust the basic principles laid down in the concept of electric power industry development is substantiated.Conclusions and Relevance: the result of the successful completion of the reform of the Russian electric power industry is a steady influx of significant investments into the industry over the course of decades. But despite the increase in power system capacity, which is outstripping the dynamics of electricity demand, the need for the most expensive peak power sources and energy storage systems is growing, which leads to an increase in electricity prices in addition to the investment component. A positive feedback has been identified that reduces the structural stability of the energy sector, namely: between rising electricity prices; reduction of electricity consumption from the network as a result of the installation of their own generation by some consumers; increasing costs of generating and network companies; more intensive growth in electricity prices and increased motivation to install their own generation for that part of consumers who continue to use grid electricity. The ways are proposed and the solutions are considered aimed at forming new connections between participants in the single technological process of production, transmission and consumption of energy resources, with the aim of reducing the energy supply costs and improving the specific performance indicators of the energy system, and in the future reducing the costs of integrating renewable energy sources into it.

Ultra-low temperature heating system based on dual-source solar assisted heat pump using compound parabolic concentrator-capillary tube solar collector

The fifth-generation heating – ultra-low temperature heating benefits to reduce electricity consumption and achieve the net zero goal. The dual-source solar assisted heat pump based heating system has been demonstrated to be an attractive green heating technology for the domestic sector. However, the slower response speed of the low temperature heating to the variation of heating load in responding to the variations of weather conditions limits its thermal comfort performance. The enhancement in solar collector performance brings valuable improvements in response speed of the heating system. In the present work, a heating system based on solar assisted air source heat pump using a compound parabolic concentrator-capillary tube solar collector (CPC-CSC) is investigated with the set heating temperatures of 40, 45, 50, and 55 °C. This heating system works for both space heating and hot water under the weather conditions in London. The results suggest that using a concentrated solar collector improves the response speed of the heating system at low set heating temperatures. For such a heating system, the ultra-low heating temperature increases the application of renewable energy and passive heating (by 6.4%). Compared with the dual-source indirect expansion solar assisted heat pump using flat plate collector, the heating system using CPC-CSC can reduce TEWI by 4.6% with a slightly longer (1.9%) payback period. As the set heating temperature decreases from 55 to 40 °C, the seasonal and yearly system seasonal performance factors significantly increase by 17.1% and 20.5%, respectively.

Estimation of Domestic Load Profile for Effective Demand-Side Management

In this article domestic base and shift based load profile are estimated for effective Demand Side Management (DSM). Domestic electricity consumption in Pakistan accounts for approximately 40% of total electricity sales. Effective DSM can reduce electricity consumption. Power generation companies are increasingly recognising the importance of analysing their customers' consumption patterns. This article proposes an agent-based modelling approach for forecasting household electricity consumption profile. AnyLogic software is used for establishing the model that uses variables and functions to estimate base and shiftable load of three hundred households. This article also estimates the weekly and 24- hour load profile for effective DSM operations by smart grid infrastructure. The results show that the agent-based simulation closely approximates real-time data, with a difference of only 2.4%.

Association between public and private greenspace availability and electricity consumption

Natural environment including greenspace has been suggested to be beneficial for health and well-being of urban residents. Several mechanisms have been proposed, including mitigation of environmental stressors, such as air pollution, and thermal stress. However, the role of greenspace on reducing electricity consumption in the urban environments has not yet been reported using these mechanisms. The present study used the annual electricity consumption of Yazd city dwellers in the period (2016–2019) and examined its association with different greenspace indicators at their residential addresses. Different private and public greenspace indicators were defined, including private garden access and area, distance to the nearest park (regional and local), percentage of land covered with urban greenspace and residential surrounding greenness (by normalized difference vegetation index [NDVI]) at different buffer size around residential addresses. Different demographic, urban design and contextual variables were included as the covariates in the models. An inverse association was found between the increase of greenspace in a private garden and the amount of electricity consumption in all the included buildings. One-unit increase in NDVI was significantly associated with 2046.5 kWh/y lower electricity consumption (95 % CI: 1151.79: 2941.21). An increase of 1 m2 in the area of a private garden was associated to 1.2 kWh/y lower energy consumption. A stronger association was also found between the private garden area and lower electricity consumption in contemporary urban texture compared to two other urban texture (contemporary urban texture: β: −1.97, 95 % CI: −2.39 to −1.54, old urban texture: β: −1.21, 95 % CI: −1.97 to −0.46, and historical urban texture: β: −0.25, 95 % CI: −1 to 0.49). The results of this study can strengthen previous theories about eco-friendly cities and sustainable cities. Promoting availability and access to greenspace can help urban sustainability through lower energy consumption.

Energy efficient design of buildings in hot climates through cooling of the envelope

The building envelope can afford many enhancements for lowering the cooling load in hot regions. In this paper, an active upgraded model utilizing an evaporative system to cool the envelope will be tested in the relatively humid climate of the coastal area of the Arabian Gulf. A couple of buildings were erected for this purpose. One was fully enclosed by a secondary structure around it, and the gap between the two was cooled using an evaporative cooler. This was compared to the second, which was insulated according to Dubai Municipality standards. A third comparison was also performed, which concerned the standalone secondary envelope with no evaporative cooling. The interior of all three cases was cooled using DX window-type air conditioners, and the power consumption measured. Thermal simulations were performed on similarly designed models using Ecotect 5.5 to see how each system would perform in full-scale functioning buildings. The measured tests on the building models showed a reduction of electrical consumption in both upgrades compared to the regulation insulated reference. The secondary envelope provided savings of 40 % and 47.3 % in the hot months of June and July, while the evaporative solution saved 52.1 % and 53.7 %, respectively. The simulation of a full-size building over the entire year showed the secondary envelope saving 48.9 % and the evaporative assisted 57.15 %.

Energy and Exergy Performance Analysis of Solar-Assisted Thermo-Mechanical Vapor Compression Cooling System

Air conditioning is vital for indoor comfort but traditionally relies on vapor compression systems, which raise electricity demand and carbon emissions. This study presents a novel thermo-mechanical vapor compression system that integrates an ejector with a conventional vapor compression cycle, incorporating a thermally driven second-stage compressor powered by solar energy. The goal is to reduce electricity consumption and enhance sustainability by leveraging renewable energy. A MATLAB® model was developed to analyze the energy and exergy performance using R1234yf refrigerant under steady-state conditions. This study compares four solar collectors—evacuated flat plate (EFPC), evacuated tube (ETC), basic flat plate (FPC), and compound parabolic (CPC) collectors—to identify the optimal configuration based on the collector area and costs. The results show a 31% reduction in mechanical compressor energy use and up to a 44% improvement in the coefficient of performance (COP) compared to conventional systems, with a condenser temperature of 65 °C, a thermal compression ratio of 0.8, and a heat source temperature of 150 °C. The evacuated flat plate collectors performed best, requiring 2 m2/kW of cooling capacity with a maximum exergy efficiency of 15% at 170 °C, while compound parabolic collectors offered the lowest initial costs. Overall, the proposed system shows significant potential for reducing energy costs and carbon emissions, particularly in hot climates.

Environmental performance of a multi-energy liquid air energy storage (LAES) system in cogeneration asset – A life cycle assessment-based comparison with lithium ion (Li-ion) battery

Increase in energy demand is shaping both developed and developing countries globally. As a result, the endeavour to reduce carbon emissions also encompasses electrical energy storage systems to ensure environmentally friendly power production and distribution. Currently, the scientific community is actively exploring and developing new storage technologies for this purpose. The focus of this work is to compare the eco-friendliness of a relatively novel technology such as liquid air energy storage (LAES) with an established storage solution such as Li-Ion battery (Li-ion). The comparison is carried out through Life Cycle Assessment (LCA) methodology which aims to assess the environmental impacts from each life stage, according to different impact categories. In particular, the study refers to the unitary storage and the delivery of electricity as well as cooling energy, considering all the inefficiencies and limits of each technology. The results show that in the full electric case study Li-ion battery environmentally outperform LAES due to (1) the higher round trip efficiency and (2) the significantly high environmental impact of the diathermic oil utilized by LAES, accounting for 92 % of the manufacture and disposal phase. Conversely, the cogeneration case study highlights that the “flexibility” and “dualism” of LAES, capable to efficiently deliver both electricity and cooling, offset the impact related to the higher electricity consumption during the use phase. Notably in energy mix frameworks with high share of primary energy source from fossil fuels, cogenerative LAES demonstrates superior environmental performance compared to Li-ion battery (i.e. 1302 kgCO2eq/MWhe vs 1140 kgCO2eq/MWhe for Singapore energy mix), attributable to its reduced electricity consumption.

Awareness of Campus Building Users to Achieve Energy Efficiency in Facing the Implementation of Green Buildings (Case Study: Politeknik Negeri Pontianak Integrated Lecture Building)

Abstract Building users’ awareness is a very crucial factor in efforts to achieve efficient energy use in buildings, especially in the green building concept. However, research that examines the awareness of building users specifically in the campus environment is still very rarely conducted, especially in Indonesia. This research, which uses a case study at Politeknik Negeri Pontianak integrated lecture building, investigates the criteria for awareness of building users and their behavior in using energy in the building. This research tries to identify social parameters in achieving building energy efficiency using a quantitative approach. The series of statistical tools used includes ranking of average values. The results of this research show that the focus of improvement can be done by increasing awareness of several things, namely recognizing the problem of decreasing electrical resources, dividing resource use in order to reduce electricity consumption, and understanding efforts and making preparations in the face of reduced electrical energy sources.

Empowering energy conservation: A prototype of household energy consumption monitoring based on Internet of Things

Abstract One of the obstacles to control household energy consumption is unavailability electricity instruments/tools to monitor electricity energy consumed by appliances causing a lack of awareness of household energy saving. Energy meter installed on buildings only show electricity consumption in total. This study aims to design and create a prototype system that can monitor and control the electrical appliances usage utilizing the Internet of Things (IoT)-based electronic devices where electricity usage data is stored in Firebase real-time database. The methods carried out are arranged in several stages, starting from data collection, design, configuration, and implementation. The tools used in this research will utilize the ESP8266 as the microcontroller, the PZEM-004T as current sensor and the Blynk as the web server. The tool will send current voltage (Volt (V)) and capacity (Watt (W)) data and then converted to energy and also the costs incurred from electricity usage based on the basic electricity tariff of National Electricity Company (PLN) and the results can be seen directly through IoT (i.e. smartphone, PC, laptop). The accuracy of power measurement by the system is 97.4% compared to measurement used by watt-checker. The results of this study show that an electrical power monitoring system makes people easier to monitor electrical power consumption by appliances used. The pilot measurement shows that a unit system can monitor electricity usage for four units of electronic equipment i.e. water pump, Television, fridge, electrical iron, rice cooker, etc. precisely and succeeded to control and increase energy saving awareness to reduce electricity consumption at the end.

Effects of occupant thermostat preferences and override behavior on residential demand response in CityLearn

As space heating accounts for 54% of annual residential electricity consumption in Quebec, demand response programs specifically target load shifting through the automated control of thermostat setpoints during peak hours. On a district scale, varied thermostat preferences and setpoint override behaviors can have an impact on the success of the demand response program. This study examines two unique occupant types (Average, Tolerant) in terms of thermostat setpoint preferences as well as three different occupant Levels-of-Detail (LoDs) and analyzes their effects on the energy flexibility provided during demand response periods. For our baseline scenario, LoD 1, a static setpoint schedule is used and there is no control of the heat pump, while LoD 2 and LoD 3 incorporate thermostat setbacks during demand response events. LoD 2 assumes the occupant is comfortable within 2°C from the setpoint while LoD 3 allows the occupant to override the DR setbacks. We estimate the flexibility services provided by a ten-house residential community through the automated control of heat pumps during a three-month winter period, and we implement and simulate our study in CityLearn using reinforcement learning-based control for district-level energy management. When comparing LoD 3 to LoD 1, electricity cost was reduced by approximately 12% and net electricity consumption was reduced by approximately 17% during demand response periods. Likewise, we find that LoD 2 could overestimate savings in net electricity consumption, cost, and peak demand by 5% compared to LoD 3. The number of hours where the indoor temperature deviated more than ▪ from the setpoint occurred for less than 5% of the timesteps on average for the 10 buildings for LoD 3 while still achieving significant net electricity consumption reductions, thus highlighting that we can provide energy flexibility services to the grid while balancing occupant thermal comfort. Finally, the agents learned optimal decision-making that reduced the number of overrides across the training episodes for both Average and Tolerant occupants. We thus present a multi-agent framework as a means for addressing various occupant setpoint preferences and override behaviors for the control of heat pump systems at the neighborhood level.

Biogas Heat Pump Power Supply Based on Smart Grid Functioning Solar Electric System Network

A comprehensive integrated solar power plant system has been developed to support the operation of a biogas plant based on a heat pump, for which fermented wort is a low-potential energy source. The change in the power factor of the solar power system connected to the grid and the temperature of the coolant entering the heat exchanger built into the methane tank are predicted. Promising solutions include changing the power of the heat pump compressor to maintain biogas production, unloading fermented wort and loading fresh material while maintaining the power factor of the grid solar system and changing the level of electricity transmission to the grid. The voltage at the input of the hybrid inverter, the voltage at the output of the frequency converter to assess their ratio and the voltage frequency are constantly measured. When changing the voltage at the input of the hybrid inverter from 240 V to 600 V, promising solutions were adopted to reduce the power of the heat pump from 3.14 kW to 1.58 kW in the production of biogas 352.5 m3/day to maintain the temperature of the heating coolant entering the heat exchanger built into the methane tank at 55° C - 45 °C in order to obtain biogas, unload fermented wort and load fresh raw materials. There is an increase in the power of electricity transmission to the grid from 0.27 to 1 and an increase in the power factor by 40% from 0.58 to 0.98. The use of the developed Smart Grid technology allows preventing peak loads of the power system, reducing electricity consumption from the grid by up to 30%.

Mechanochemistry-mediated colloidal liquid metals for electronic device cooling at kilowatt levels.

Electronic systems and devices operating at significant power levels demand sophisticated solutions for heat dissipation. Although materials with high thermal conductivity hold promise for exceptional thermal transport across nano- and microscale interfaces under ideal conditions, their performance often falls short by several orders of magnitude in the complex thermal interfaces typical of real-world applications. This study introduces mechanochemistry-mediated colloidal liquid metals composed of Galinstan and aluminium nitride to bridge the practice-theory disparity. These colloids demonstrate thermal resistances of between 0.42 and 0.86 mm2 K W-1 within actual thermal interfaces, outperforming leading thermal conductors by over an order of magnitude. This superior performance is attributed to the gradient heterointerface with efficient thermal transport across liquid-solid interfaces and the notable colloidal thixotropy. In practical devices, experimental results demonstrate their capacity to extract 2,760 W of heat from a 16 cm2 thermal source when coupled with microchannel cooling, and can facilitate a 65% reduction in pump electricity consumption. This advancement in thermal interface technology offers a promising solution for efficient and sustainable cooling of devices operating at kilowatt levels.