Energy-efficient Strategy Research Articles

Advancements in the energy-efficient brine mining technologies as a new frontier for renewable energy

The scientific community has profoundly relied on the recovery of various elements with special inference on the renewable energy-powered desalination of wastewater. Advanced developments in modern science and technology allow them to accomplish the aforesaid target using the various desalination approaches including zero discharge technology, multi-stage flash, multi-effect distillation, vapor compression, electrodialysis and membrane distillation. The recent advancements in the distribution of novel concepts over the treatment strategies allow the research community to integrate the green energy-based approaches with solar energy-efficient strategies as a renewable energy-powered desalination approach. There have been a number of advantages and disadvantages are concerned with the all the discussed approaches. However, the green-based technologies have well proven to be more preferred technology than the conventional approaches since the energy consumption, production cost and efficiency are noted to be reliable for these green-based approaches.

Surface reconstruction and charge distribution enabling Ni/W5N4 Mott-Schottky heterojunction bifunctional electrocatalyst for efficient urea-assisted water electrolysis at a large current density

Urea-assisted water electrolysis is regarded as an energy-efficient strategy for hydrogen production, but its potential use is still limited by sluggish kinetics in both anodic urea oxidation reaction (UOR) and cathodic hydrogen evolution reaction (HER). Herein, we report the facile synthesis of nickel foam (NF) supported Ni/W5N4 Mott-Schottky heterojunction nano-microspheres as a highly active catalyst for both UOR and HER using a hydrothermal method followed by nitridation treatment. The as-prepared Ni/W5N4/NF catalyst with high electrochemically active surface area would reconstruct under oxidizing condition to form nickel tungsten oxyhydroxides to efficiently drive UOR, with a potential of only 1.34 V (versus reversible hydrogen electrode) at 10 mA cm−2. Impressively, thus-prepared catalyst benefited from charge redistribution only required an overpotential of 25 mV at 10 mA cm−2 for HER. In particular, the Ni/W5N4/NF catalyst couple used for urea-assisted water electrolysis just needed a cell voltage of 1.77 V at 1000 mA cm−2.

Mott-Schottky heterojunction of Se/NiSe2 as bifunctional electrocatalyst for energy efficient hydrogen production via urea assisted seawater electrolysis

Seawater electrolysis is considered to be very challenging owing to competitive reaction kinetics in between oxygen evolution reaction and corrosive chlorine evolution reaction mechanism at anode, especially towards higher current density. The present work, proposes a promising and energy efficient strategy by coupling seawater splitting with urea decomposition lowering oxidation potential and thereby avoiding hypochlorite formation even at high current density. The rational design of Mott-Schottky heterojunction of Se/NiSe2 as electrocatalyst is considered to be highly effective in this regard. The developed Se/NiSe2 exhibits extraordinary energy saving for alkaline seawater splitting in presence of urea. The Se/NiSe2/NF || Se/NiSe2/NF electrolyser configuration achieved 10 and 50 mAcm−2 current densities with cell voltage of 1.59 and 1.70 V along with outstanding operational durability over 50 h. The large number of carrier density generates by synergistic self-driven electron transfer from Se to NiSe2 at the heterojunction, unique metallic properties of selenium (Se), and also abundance accessible reactive edges on the porous channel of Ni foam are believed to be the reason behind such enhanced electrocatalytic activities towards urea oxidation reaction and hydrogen evolution reaction offering unique and much energy saving approach for alkaline-urea-seawater electrolysis avoiding hypochlorite formation.

Application of blanching pretreatment in herbaceous peony (Paeonia lactiflora Pall.) flower processing: Improved drying efficiency, enriched volatile profile and increased phytochemical content

Although various techniques have been developed to dry herbaceous peony (Paeonia lactiflora Pall.) flowers, the dried products usually have a low retention level of bioactive compounds, which limits the valorization of peony-derived products. This work is the first to employ steam blanching (SB), high-humidity hot air impingement blanching (HHAIB), and vacuum-steam pulsed blanching (VSPB) before drying to improve the drying efficiency and quality of dried peony flowers. Results showed blanching pretreatment led to significant (p < 0.05) reductions in drying time by 7.02–40.35% and energy consumption by 6.86–39.96%, respectively. The final dried samples also exhibited reductions in browning degree by 30.93–62.89% and shrinkage ratio by 30.05–68.83%, respectively. Based on blanching pretreatment, the retention levels of bioactive compounds in dried samples were significantly (p < 0.05) improved. The dried samples blanched with VSPB possessed the highest contents of gallic acid (76.76 ± 1.75 mg/100 g DW), catechins (0.327 ± 0.010 mg/100 g DW), paeoniflorin (51.00 ± 1.41 mg/100 g DW), total phenolic (85.41 ± 1.81 mg GAE/100 g DW), flavonoid (11.00 ± 0.26 mg RE/100 g DW), and sugar (22.86 ± 0.13 g/100 g DW), thus causing superior antioxidant capacity. Furthermore, a total of 28 volatiles were identified, with alcohols (8.58–166.10 μg/g), alkanes (11.69–70.01 μg/g), and terpenes (5.89–47.93 μg/g) being the dominant contributors to the flavor of dried samples. This work provides insight for researchers to develop dried peony flowers with high added value using an energy-efficient strategy in the future.

A green energy circular system with carbon capturing and waste minimization in a smart grid power management

Sustainable electricity production is an energy-efficient strategy aimed at both economic progress and environmental conservation. The power generation sector is the major contributor to global emissions and waste. The scope of circular economy in the power production sector with investments in waste minimization and emission reduction was not discussed in previous studies. In this context, a circular sustainable smart electric supply chain system is introduced in this paper with an aim of maximizing the profit with the minimum amount of emissions and waste generated from the power generation units. The power plant in this system consists of four power generation units that generate electricity from coal, waste, wind, and solar plants. A smart grid management system is used in this system for an efficient power supply according to the demands of the customer, and it enhances the system to distribute the power from renewable energies. In this system, the carbon dioxide from the thermal plants is captured and converted to natural gas to reduce emissions. Municipal and industrial waste is transformed into composite fuel to generate electricity. The profit for each unit and the customer’s demand for electricity depends on the circularity index. Linear demand versus linear and logistical cases of unit profit was considered. This study theoretically and numerically maximizes the profit of the system with optimal power consumption, circularity index of electricity, and green and waste minimization investment as per the carbon cap policy. To find the optimal strategies for maximum profit, an algorithm was developed. Sensitivity analysis is done to determine the fluctuations in the profit, emission cost, waste cost, circularity index, and power consumption due to the variations in parameters. The wise allocation of power generation from each unit and reduce energy loss by installing efficient storage devices will result in a higher profit. A system with the high efficacy of green techniques to reduce emissions, a smart grid to minimize waste, higher taxes to regulate emissions, and a rise in the amount of production of electricity from renewable sources will result in a greener power system that gains more profit than conventional systems. The key findings state that electric supply chain systems can obtain a good profit in a more sustainable manner than conventional systems.

Enhancing Financial Security and Energy Efficiency: Integrating Biometric Payments with Power System Engineering in India

This research explores the integration of biometric payment systems with power system engineering within the Indian financial sector. It aims to understand and optimize this convergence by examining the current state, assessing power consumption patterns, evaluating regulatory compliance, and providing holistic insights. Utilizing a mixed-method approach including qualitative interviews, focus group discussions, and quantitative surveys, the study uncovers variations in biometric adoption rates among financial institutions, highlighting the correlation with power consumption and the necessity for standardized frameworks. The findings underscore the importance of balancing technology adoption, energy efficiency, and data protection. Practical implications include informed decision-making for financial institutions and refined policies for regulatory authorities to foster a secure, efficient, and sustainable payment ecosystem. This research contributes to existing knowledge by offering comprehensive insights and emphasizes the need for energy-efficient strategies and robust regulatory standards. Overall, it advances our understanding of this convergence, paving the way for a more secure and sustainable financial technology landscape in India.

A Sustainable Opportunity to Re-Inhabit Traditional Buildings in Italy: Energy Efficiency Actions End Fiscal Incentives

In recent decades, the Italian building trade has recorded an increasing interest in the renovation and improvement of both listed and unlisted existing buildings by the Ministry of Culture, growing the debate on adapting historical buildings to current sustainability needs. The Italian National Institute of Statistics (ISTAT) observed the increase in family commuting and the attractiveness of marginal territories. Despite the scarcity of services, one-fifth of Italian small municipalities are attractive according to some indicators, primarily the demographic growth in the last three years. The COVID-19 pandemic has contributed to the re-evaluation of inland areas. Remote working and the new need for open spaces could increase the return to small villages and be further boosted by the fiscal incentives. This paper considers the evolution of last year’s real estate market, evaluating whether the regulatory tools for energy retrofit and tax relief meet the trade crisis with a possible benefit of preserving historical buildings. This research cannot ignore the European background; therefore, this paper offers an overview of EU regulatory strategies for energy efficiency recently issued to increase sustainability, focusing on tax credits for improving existing buildings. In conclusion, some considerations are proposed for future in-depth research.

Model predictive control and deep reinforcement learning based energy efficient eco-driving for battery electric vehicles

Automated self-driving vehicles not only allow of improved energy saving but also better traffic flow. In particular, with the rapid technological advance of autonomous self-driving, technical development of efficient energy consumption for fully electric vehicles (EVs) is becoming progressively important for due to the limited battery capacity and power of EVs. This article proposes a hybrid approach using Deep Reinforcement Learning (DRL) and Model Predictive Control (MPC) for improving the energy economy of the EVs . In this study, the MPC algorithm is used to solve the optimization problem for the speed control of the EVs for minimization of energy consumption in a receding horizon, where the cost value of the horizon is fed into the DRL networks as observed state. Thus, the terminal cost of a state is learned by nearest neighbors and the terminal condition is constrained in a state observed before. The proposed scheme was tested virtually with the high fidelity car simulator (CarSim) and the remaining power of the battery source was sensed during tracing the given track in real-time. Two algorithms for performance evaluation are quantitatively explored and compared in terms of battery energy-saving. The simulation results show that the eco-driving strategy for energy saving of the EVs can be established on road driving in real-time. The performance of energy-saving about average 1% and 17% under simple uphill climbing and multiple ascents and descents, respectively. The results, as an energy efficient planning strategy of the future autonomous and intelligent eco-driving for the EVs, might be possible for guiding and significant practice.

A Novel Machine Language-Driven Data Aggregation Approach to Predict Data Redundancy in IoT-Connected Wireless Sensor Networks

Real world data aggregation and delivery in Internet of Things (IoT) technology are essential to predict and retrieve target data in short time so that the end user feels no delay but ensures a high quality of information. In addition to habitat monitoring and disaster management, these networks have a wide range of other uses, including security and military operations. The processing capabilities of sensor nodes are restricted due to the fact that they have a limited battery life and hence a modest size and processing capacity. WSNs are also susceptible to failure as a result of the limited battery power available. In WSNs, data aggregation is practiced as an energy efficient strategy to reduce computing and transmission latency. It is because of sensor node distribution density that shares the same data at a time data redundancy comes to exist. It is possible to reduce redundancy by adopting a suitable machine learning algorithm while executing the data aggregation process. Researchers are still chasing behind algorithms and modeling strategies effectively to ease the process of developing an effective and acceptable data aggregation strategy from existing wireless sensor network (WSN) models. A three stage framework is proposed for an efficient data aggregation mechanism, and the stages are Modified LEACH, extreme learning machines (ELM), adaptive Kalman filter, and Bi-LSTM. This experiment result shows better performance than the existing methods.

Reinforcement learning based energy efficient resource allocation strategy of MapReduce jobs with deadline constraint

Reinforcement learning based energy efficient resource allocation strategy of MapReduce jobs with deadline constraint

Strategic energy and climate policy planning: Lessons learned from European energy efficiency policies

Strategic policy planning has gained increasing importance in international energy and climate policy. This paper aims to contribute to the debate on stringent policy planning by drawing lessons learned from two decades of strategy development in the field of European energy efficiency policy. Since the inception of the first national energy efficiency action plans under the Energy Services Directive (2006/32/EC), the European Commission and the Member States have had a long experience in planning national strategies. This paper analyses the lessons learned in setting up national energy efficiency strategies and traces the progress made in 2007–2020. Our findings show that major improvements are attained in the latest national energy and climate plans through the adoption of harmonised reporting approaches, evidence-based target setting methods, establishment of better monitoring systems and broader consideration of policy packages. Various areas with a significant potential for further improvements are also identified, ranging from more coherent reporting framework for policies and measures to the need of setting up systems that encourage the adoption of targets in line with a country's cost-effective energy efficiency potential. Embedding energy efficiency in the larger climate policy framework, considering how it can support pressing socioeconomic challenges, is also of pivotal importance.

Energy Efficient Routing Protocol in Novel Schemes for Performance Evaluation

Wireless sensor networks (WSNs) are a comparatively new revolutionary technology that has the potential to revolutionize how we live together with the present system. To enhance data archiving, WSNs are frequently used in scientific studies. Many applications have proved the value of wired sensors; however, they are prone to wire cutting or damage. While preventing wire tangles and damage, wireless sensor networks provide autonomous monitoring. The WS network suffers from a number of fundamental restrictions, including insufficient processing power, storage space, available bandwidth, and information exchange. Consequently, energy-efficient strategies are necessary for maximizing the performance and lifespan of WSNs. As a result, the special cluster head relay node and energy balancing techniques will be applied to deal with WSN energy consumptions. This extends the life of the network. In wireless sensor networks, clustering is a smart approach to reduce energy consumption. Energy scarcity and consumption are serious issues that must be addressed with effective and dependable solutions. The proposed MGSA considers the distance between each node and its corresponding CHs, as well as the residual energy and delay, as important factors in the relay node selection. The proposed approach outperforms the current methods, such as low-energy adaptive clustering hierarchy, LEACH (in terms of data delivery rate), energy efficiency, and network longevity. The next level, which will boost the efficiency of wireless sensor networks, with two fitness functions, is proposed. The cluster head (CH) is in charge of collecting and transmitting data from all other cluster nodes. The flow of the consistency of the cluster head selection process will beat the improved data delivery rate, energy efficiency, recommended fuzzy clustering performance experiments, and assessments. As a result, energy-efficient operations are necessary to maximize the WSN performance and lifespan.

Incorporation of Energy Efficient Computational Strategies for Clustering and Routing in Heterogeneous Networks of Smart City

For decision-making and governance, smart cities depend on tracking data collected via a substantial percentage of wireless sensing nodes. However, several limitations affect Wireless Sensor Network (WSN)-based Internet of Things (IoT) services, such as low battery life, recurrent connectivity problems due to multi-hop connections, and a limited channel capacity. Furthermore, in many systems, clustering and routing are handled independently, which prevents the adaptation of effective strategies for optimal energy usage and prolonged network lifespan. This research gathers data from heterogeneous IoT nodes linked via WSN and distributed across a smart infrastructure. There are two interrelated problems to be addressed with respect to energy efficiency computations: clustering and routing. We provide a new clustering strategy through which efficient routing of critical and regular data is handled. As a result, both clustering and routing have been significantly strengthened, which balances the communication load across different sectors of the smart infrastructure network. Minkowski distance and ranking strategy are used for routing and selecting cluster heads, respectively. Deterministic distributed–time division multiple access (DD-TDMA) scheduling is employed to balance the communication load across the network. The experimental results show that the proposed work outperforms some of the popular cluster-based routing strategies.

Electrochemical Desalination Using a Hybrid Redox-Flow Cell with a Ceramic Ion Conductor

Electrochemical desalination is a potentially energy-efficient strategy for distributed, small-scale purification of brackish sources, especially as compared to conventional processes that are reliant on heat or reverse osmosis. One promising subcategory of electrochemical desalination systems features a combination of sodium-intercalating electrodes and polymer-based anion-exchange membranes. Although desalination is technically feasible with this design, polymer-based ion-exchange membranes tend to have imperfect permselectivities and to be susceptible to water crossover between diluate and concentrate streams. These issues result in parasitic losses that increase the energetic cost of desalination.We propose a hybrid flow cell design that features a redox-active electrolyte separated from a solid, anion-converting or anion-intercalating electrode with a solid ceramic ion-exchange membrane. By making use of a dense, ceramic membrane with a far greater selectivity for sodium ion conduction than analogous polymeric ion-exchange membranes, the parasitic issues described above are avoided. We discuss considerations that will impact the relationship among electrode and electrolyte properties, operational parameters (e.g. current density, concentration factor and water recovery percentage) and the energetic cost of desalination.

Frontal polymerization-triggered simultaneous ring-opening metathesis polymerization and cross metathesis affords anisotropic macroporous dicyclopentadiene cellulose nanocrystal foam

Multifunctionality and effectiveness of macroporous solid foams in extreme environments have captivated the attention of both academia and industries. The most recent rapid, energy-efficient strategy to manufacture solid foams with directionality is the frontal polymerization (FP) of dicyclopentadiene (DCPD). However, there still remains the need for a time efficient one-pot approach to induce anisotropic macroporosity in DCPD foams. Here we show a rapid production of cellular solids by frontally polymerizing a mixture of DCPD monomer and allyl-functionalized cellulose nanocrystals (ACs). Our results demonstrate a clear correlation between increasing % allylation and AC wt%, and the formed pore architectures. Especially, we show enhanced front velocity (vf) and reduced reaction initiation time (tinit) by introducing an optimal amount of 2 wt% AC. Conclusively, the small- and wide-angle X-ray scattering (SAXS, WAXS) analyses reveal that the incorporation of 2 wt% AC affects the crystal structure of FP-mediated DCPD/AC foams and enhances their oxidation resistance.

Energy Efficient and Delay Aware Optimization Reverse Routing Strategy for Forecasting Link Quality in Wireless Sensor Networks

Energy Efficient and Delay Aware Optimization Reverse Routing Strategy for Forecasting Link Quality in Wireless Sensor Networks

Energy Efficient Pneumatics: Aspects of Control and Systems Theory

As the public call for increasing efforts in achieving the global climate protection goals intensifies, discussions about the efficient use of resources and energy are on the daily agenda. As many other areas, the industry has seen itself facing growing concerns about the long neglected environmental aspects. Since a large proportion of the energy in production is used by pneumatic drives, this survey paper exclusively focuses on pneumatics in handling and automation technology and presents the most common components, followed by multiple model-based strategies to increase energy efficiency in modern production plants. First, single units are studied extensively and methods for design and energy efficient control are presented. Since in production lines pneumatic drives are generally operated in large networks, the second part focuses on energy efficient strategies at plant level. These include an optimized adjustment of the supply pressure, a cascaded air usage, and an automated adaptive control pattern. Care is taken to ensure that the considered approaches are applicable in today’s industrial plants, which is demonstrated by experiments in a production line. The experimental findings show the immense potential of the discussed measures in the form of compressed air savings of more than 60% compared to the industry standard.

Energy Efficiency in High-rise Office Buildings: An Appraisal of its Adoption in Lagos, Nigeria

High-rise office buildings are naturally energy-intensive as energy is required in large quantities to run modern building services and to power equipment needed for a hitch-free operation of the buildings. It was found in studied literature that maintaining good indoor environmental quality through air-conditioning, lighting and powering of office equipment contribute the most to an office building’s total energy consumption. Hence, over time, various strategies have been employed to reduce the intense energy demand in high-rise office buildings. This paper adopted the use of both literature review and case study methods. The paper identifies the key energy efficiency strategies that have been successfully deployed in high-rise office buildings using the literature review approach. Also, case studies were conducted on three relatively new high-rise office buildings in Lagos, Nigeria by evaluating them against the background of the best practices in energy efficiency. The study found that deployment of energy efficiency strategies in high-rise office buildings in the study area is still very low especially in the areas of building orientation, building envelope design and the use of renewable energy. However, the use of day-lighting techniques and sustainable lighting systems are quite prominent in the office buildings studied. The study underscores the need to make high-rise office buildings more sustainable through energy efficiency strategies across the whole building life cycle of design, construction, use and end of life.

Impact of Energy Efficient Design Strategies on Users Comfort in Selected Mixed-Use Buildings in Lagos State, Nigeria

Human comfort is a major criterion for mixed-use buildings to be habitable, leading to the usage of technologies such as HVAC and artificial lighting. These devices demand high electricity, causing a 25% rise in building greenhouse gas emissions. It is important for architects to develop energy efficient design strategies in order to maintain and improve user comfort in mixed-use buildings. This study investigated the impact of energy efficiency design strategies on users’ comfort in selected mixed-used building in Lagos State, Nigeria, with a view to identify areas for further improvements. The research adopted a quantitative approach. A structured questionnaire was used to obtain data. The Statistical Product & Service Solutions software was used to analyse the data. The result was presented with the aid of texts, tables and graphs. The findings indicated that building orientation was one of the most important techniques, affecting each dimension of human comfort. This revelation suggests that when adopting energy efficiency measures, a building’s early design stage should focus on enhancing human comfort. The study recommended that professionals conduct critical analysis on buildings in the design stage to guarantee energy-efficient approaches used throughout the planning, design, and construction stages of mixed-use buildings. In order to create sustainable future designs, it is therefore necessary to recognise the significance of energy efficient design techniques on users’ comfort.

Investigating passive strategies in a cold climate – teaching EDDA in architectural education

This paper describes the results of an architectural teaching module investigating passive building strategies in cold climatic conditions on the case study of Iceland. Focusing on thermal comfort in buildings, usual case study tasks are located in cooling-dominated climates - as vernacular design for hot climate zones offers more passive strategies than for cold climates. As part of the architectural education programme at Jade University of Applied Sciences, students investigated the impact of passive strategies in a building design concept for a hotel in Iceland by applying numerical simulation within the initial design phase. The aim was to develop a holistic energy efficiency strategy and to optimize their initial design propositions exploiting its full potential for high thermal comfort in the guest rooms. Although each student started with an individual research question for a specific passive strategy, i.e., investigating varying construction materials, buffer zones, window-wall-ratio, Trombe walls, etc., all design concepts finally included multi-storey glazed buffer zones contributing to comfortable room temperatures by high solar gains from April to September resulting in a significantly reduced heating load. Furthermore, the study identified several design metrics for passive solar buffer zones to ensure the positive impact throughout the months with varying solar intensity. The teaching module called EDDA (Environmental Digital Design Analysis) is based on simplified 3D models in McNeels Rhinoceros 3D undergoing thermal simulation with a Grasshopper–Ladybug-Honeybee workflow. This allowed the students to iterate their building designs for maximum thermal comfort before adding HVAC systems. Ultimately, EDDA fostered to design climate-sensitive buildings by identifying a suitable set of passive strategies for the predominant climatic conditions as a first – but essential - step towards climate-neutral buildings. At the same time, prospective architects are empowered leading the building sectors towards a carbon-neutral future.