Leftover Energy Research Articles

Enhanced electrochemical discharge of Li-ion batteries for safe recycling.

The recycling of spent lithium-ion batteries (LIBs) is crucial to sustainably manage resources and protect the environment as the use of portable electronics and electric vehicles (EVs) increases. However, the safe recycling of spent LIBs is challenging, as they often contain residual energy. Left untreated, this can trigger a thermal runaway and result in disasters during the recycling process. For efficient recycling, it is important to withdraw any leftover energy from LIBs, regardless of the processing method that follows the discharge. The electrochemical discharge method is a quick and inexpensive method to eliminate this hazard. This method works by immersing batteries in an aqueous inorganic salt solution to discharge LIBs completely and efficiently. Previously, research focus has been on different inorganic salt solutions that release toxic or flammable gaseous products during discharge. In contrast, we present an entirely new approach for electrochemical discharge - the utilization of an Fe(ii)-Fe(iii) redox couple electrolyte. We show that this medium can be used for efficient LIB deep discharge to a voltage of 2.0 V after rebound, a level that is low enough for safe discharge. To accomplish this, periodic discharge methods were used. In addition, no corrosion on the battery casing was observed. The pH behavior at the poles was also investigated, and it was found that without convection, gas evolution during discharge cannot be avoided. Finally, it was discovered that the battery casing material plays a vital role in electrochemical discharge, and its industrial standardization would facilitate efficient recycling.

Effects of inherent components and disposal temperature on the melting behavior of petrochemical sludge char during CO2 gasification

Pyrolysis-coupled gasification-melting is a promising technology as it can dispose of the petrochemical sludge (PS) and recover the leftover energy. Unfortunately, there has been little research investigating the effects of pyrolysis degree on melting characteristics of the pyrolysis residue (PR) and the transformation properties of the heavy metal (HM). In this study, the function of inherent components and disposal temperature were elucidated. The results show that the moisture and light volatile could disperse the melting residue (MR) during gasification-melting treatment, causing different morphology and color of the MR. In addition, as pyrolysis temperature increased, the HMs speciation (e.g. Zn, Cu, and Cr) in the PR was transformed from bioavailable to a stable state, and the yield of PR decreased from 66.8% to 36.5%. The PR produced at 800 °C could decrease about 0.9 ∼ 1.9 potential ecological risk of releasing substances during the subsequent high-temperature gasification-melting owing to its stable HMs state and less char composition. Moreover, the gasification at 1250 °C could realize the safe disposal of the PR. Further increasing the gasification temperature to 1450 °C could not improve the acid-leaching resistance of the HMs, although the apparent concentration of C and the acid dissolution proportion of slag decreased by 6.3% and 1.7%, respectively.

A novel approach based on bio‐inspired efficient clustering algorithm for large‐scale heterogeneous wireless sensor networks

SummaryIn large‐scale heterogeneous wireless sensor networks (WSNs), clustering is particularly significant for lowering sensor nodes (SNs) energy consumption and creating algorithm more energy efficient. The selection of cluster heads (CHs) is a crucial task in the clustering method. In this paper, optimised K‐means clustering algorithm and optimised K‐means based modified intelligent CH selection based on BFOA for large‐scale network (lar‐OK‐MICHB) is hybridised for CH selection process. Here, we utilised the extended capabilities of OK‐MICHB algorithm for large‐scale network. Furthermore, in many applications where energy is a primary constraint, such as military surveillance and natural disaster prediction, the stability region is also a significant factor, with a longer network lifespan being a primary requirement. In the proposed approach, only the CH selection is made after every round in place of cluster and CH change as done in conventional hierarchical algorithm. The simulation results reveal that, while keeping the distributive structure of WSNs, suggested lar‐OKMIDEEC can locate real greater leftover energy nodes for selection of CH without utilising randomise or estimated procedures. Furthermore, as compared with the multi‐level MIDEEC protocol, this offers a larger stability region with 68.96% increment, more consistent selection of CH in every round, and greater packets (i.e., in numbers) received at the base station (BS) with a longer network lifetime with 327% increment.

Cooperative Channel and Optimized Route Selection in Adhoc Network

Over the last decade, mobile Adhoc networks have expanded dramatically in popularity, and their impact on the communication sector on a variety of levels is enormous. Its uses have expanded in lockstep with its growth. Due to its instability in usage and the fact that numerous nodes communicate data concurrently, adequate channel and forwarder selection is essential. In this proposed design for a Cognitive Radio Cognitive Network (CRCN), we gain the confidence of each forwarding node by contacting one-hop and second level nodes, obtaining reports from them, and selecting the forwarder appropriately with the use of an optimization technique. At that point, we concentrate our efforts on their channel, selection, and lastly, the transmission of data packets via the designated forwarder. The simulation work is validated in this section using the MATLAB program. Additionally, steps show how the node acts as a confident forwarder and shares the channel in a compatible method to communicate, allowing for more packet bits to be transmitted by conveniently picking the channel between them. We calculate the confidence of the node at the start of the network by combining the reliability report for the first hop and the reliability report for the secondary hop. We then refer to the same node as the confident node in order to operate as a forwarder. As a result, we witness an increase in the leftover energy in the output. The percentage of data packets delivered has also increased.

Evolutionary Optimization of Drone-Swarm Deployment for Wireless Coverage

The need for longer lasting and wider wireless coverage has driven the transition from a single drone to drone swarms. Unlike the single drone, drone swarms can collaboratively achieve full coverage over a target area. However, the existing literature on the drones’ wireless coverage has largely overlooked one important fact: that the network lifetime is determined by the minimum leftover energy among all drones. Hence, the maximum energy consumption is minimized in our drone-swarms deployment problem (DSDP), which aims to balance the energy consumption of all drones and maximize the full-coverage network lifetime. We present a genetic algorithm that encodes the solutions as chromosomes and simulates the biological evolution process in search of a favorable solution. Specifically, an integer code scheme is adopted to encode the sequence of the drones’ deployment. With the order of the drones’ sequence determined by the coding process, we introduce a feasibility checking operator with binary search to improve the performance. By relaxing the constraint of full coverage as an objective of coverage rate, we study the tradeoffs between energy consumption, number of drones, and coverage rate of the target area. By taking advantage of the MOEA/D framework with neighboring subproblems searching, we present a drone-swarms deployment algorithm based on MOEA/D (DSDA-MOEA/D) to find the best tradeoff between these objectives. Extensive simulations were conducted to evaluate the performance of the proposed algorithms.

Drone Deployment Algorithms for Effective Communication Establishment in Disaster Affected Areas

Communication establishment is crucial for rescue operations in disaster affected areas. A standard tool for communication is the use of cell phones. However, they can be useless in situations where the cellular network’s base stations are damaged in a disaster. A contemporary approach to re-establishing a communication network is by hosting base stations in drones. However, low battery life and difficulty in calculating the number of drones needed in different terrains are limitations of the above approach. This paper introduces a novel terrain-aware algorithm that calculates the minimum number of drones needed to cover an area with no voids in the network coverage. Our method ensures that the drones are deployed at optimal heights to maximize the average leftover energy in the network. We apply the algorithm for an actual location in Pettimudi, India and find the optimal number and positions of the drones to cover the area effectively without voids. In addition, we provide a simulation of the the communication establishment using above drones, and our experiments yield an average network efficiency of 98%, showing the effectiveness of our method.

TECHNO-ECONOMIC ANALYSIS OF EXCESS WIND ENERGY UTILITZATION IN THE ENERGY SUPPLY OF RESIDENTIAL QUARTERS

In this study we have examined the potential of excess wind use in Germany. Excess wind constitutes roughly 40% of unused capacities of installed wind power in Germany. Using LP modelling and representative annual load profiles on an hourly resolution, we investigate the impact of the price level for wind peak power supply of residential quarters with heat, cold and electricity in Germany in combination with different power ratios of wind supply and demand. As we show, an application of wind peak tariff is technically and economically feasible and allows using green leftover energy without going in competition with e.g., green fuels or green H2 production.

Optimized Energy Conservation Procedure for Heterogeneous Wireless Sensor Network

A WSN is composed of device with dissimilar energy levels. For saving energy, a grouping algorithm is obligatory and it also intensification the epoch time of the network and the firmness epoch of the network. For securing the energy conservation of the network, energy-efficient grouping etiquettes are designed for the HWSN. We projected the protocol for the energy-efficient grouping scheme which is an enhanced version of the protocols such as EDEEC, SEP, DEEC, and DDEEC. Simulation outcomes demonstrate that the proposed mechanism is well recovering than the SEP (A Stable Election Protocol), DEEC (Distributed Energy Efficient Grouping Protocol), EDEEC (Enhanced Distributed Energy-Efficient Protocol), DDEEC (Developed DEEC) in standings of the network duration, number of packets delivered to the BS, amount of CH selected and number of nodes alive per smoothed. The CH will be selected founded on the original energy and the left-over energy of the device.

Trust Based Approach to Counter Attacks on WSN

Wireless sensor networks (WSN) have a developing future due to their minimal expense, power-efficiency, and simple to-carry out attributes. Be that as it may, its security issues have become an interesting issue of exploration these days. This article inspects the headway of system of countering assaults where the responsibility, leftover energy of hub and examination of effective and fruitless occasions are consider while registering the trust level. Unlike existing work, this paper talk about the technique in which the trust esteem per layer of a sensor hub is assessed by the deviations of key boundaries at every convention layer considering the attacks. The execution of the proposed counter measure is then investigated utilizing the t-conveyance. Reproduction of WSN has been done to approve the outcomes. With the assistance of reenactment results, it has been seen that the proposed trust-based methodology for interruption location beats existing plans to the extent of revealing safety breaks in WSN.

Implementation of Hybrid Algorithm in Cluster Head using Neural Networks

A Neural Network is a data processing system consisting of large number of simple, highly interconnected processing elements. In this paper a graphical convention is utilized where hubs are orchestrated in the form of cluster. An epic methodology is presented for choice of group head by the utilization of fake neural organization to expand organization's lifetime in WSN and calculation of steering convention dependent on neural organizations (NNs). In the proposed work, a standard burned-through energy is used for the choice of bunch head and and steering convention LEACH is used. The leftover energy is utilized for making group head and for the determination of bunch head using Neural Network. In the proposed system Using LEACHNN algorithm Throughput, packet delivery ratio ,energy is improved by 20%.

Energy Efficient of IDS Using Fuzzy Logic for Lifetime Improvement in Wireless Sensor Network

The Wireless Sensor Network (W.S.N.) comprises little batteries fueled sensor gadgets with restricted energy assets. The Sensor hubs used to monitor the physical screen or conditionsbased on normal, theinformation must be private organization to primary area. The Most significant obstacles in a sensing the remote in the particular network which used to make an efficient energy framework. Clustering is the one of the major process in the sensor network based on wireless which used to drag out the life time of an organization lifetime which in turn reduce the energy utilization of the network. It includes gathering hubs into groups and choosing bunch heads (CH) for all the groups. CH gather information from separate group hubs and forward the collected data to the fundamental corner. This paper proposes novel fluffy various dynamic methodology measures: “Energy Efficient Optimal Cluster Head Selection utilizing Fuzzy Logic (EEOCH-FL)” for Wireless Sensor Network. Fluffy different boundary dynamic methodology is used to choose C.H.s utilizing three standards: leftover energy, fixation, the right ways from the principle hubs, and base station. The life cycle of Clustering hub and Clustering Head are grouped, clustering hub which transmitted all data to the Cluster Header Leader (CHL). The bunch head pioneers sent collected information to the Base Station (B.S.) from that point forward. The determination of bunch heads, group head pioneers is controlled and monitored by utilizing a fluffy rationale. The information transmission measure is per-shaped by the briefest energy way chosen to apply Dijkstra Algorithm. The reenactment results show that this methodology is more potent in boosting the availability inside each bunch. Furthermore, the reproduction aftereffects of this examination are contrasted and different conventions LEACH and CEELRP to assess the proposed steering convention's presence. The assessment reasons that convention of steering of this proposed work proved to be an effective in utilization of an energy.

SmartDR:A device-to-device communication for post-disaster recovery

Natural disasters, such as earthquakes, can cause severe destruction and create havoc in the society. Buildings and other structures may collapse during disaster incidents causing injuries and deaths to victims trapped under debris and rubble. Immediately after a natural disaster incident, it becomes extremely difficult for first responders and rescuers to find and save trapped victims. Often searches are carried out blindly in random locations, which delay the rescue of the victims. This paper introduces a Smartphone Assisted Disaster Recovery (SmartDR) method for post-disaster communication using Smartphones. SmartDR utilizes the device-to-device (D2D) communication technology in Fifth Generation (5G) networks, which enables direct communication between proximate devices without the need of relaying through a network infrastructure, such as mobile access points or mobile base stations. We examine a scenario of multi-hop D2D communication where smartphones carried by trapped victims and other people in disaster affected areas can self-detect the occurrence of a disaster incident by monitoring the radio environment and then can self-switch to a disaster mode to transmit emergency help messages with their location coordinates to other nearby smartphones. To locate other nearby smartphones also operating in the disaster mode and in the same channel, each smartphone runs a rendezvous process. The emergency messages are thus relayed to the functional base station or rescue centre. To facilitate routing of the emergency messages, we propose a path selection algorithm, which considers both delay and the leftover energy of a device (a smartphone in this case). Thus, the SmartDR method includes: (i) a multi-channel channel hopping rendezvous protocol to improve the victim localization or neighbour discovery, and (ii) an energy-aware multi-path routing (Energy-aware ad-hoc on-demand distance vector or E-AODV) protocol to overcome the higher energy depletion rate at devices associated with single shortest path routing. The SmartDR method can guide search and rescue operations and increase the possibility of saving lives immediately aftermath a disaster incident. A simulation-based performance study is conducted to evaluate the protocol performance in post-disaster scenario. Simulation results show that a significant performance gain is achievable when a device utilizes the channel information for the rendezvous process and the leftover energy for routing path selection. Our results show that peer discovery in multi-channel D2D environment can be significantly improved when channel quality information is considered in CH sequence design. Moreover, selecting a routing path based on LoE of a device and the standard deviation of residual energy of a path, can not only enhance the network lifetime, but also reduce the chance of network being partitioned.

Energy-Saving Deployment Algorithms of UAV Swarm for Sustainable Wireless Coverage

Recent years have witnessed increasingly more uses of Unmanned Aerial Vehicle (UAV) swarms for rapidly providing wireless coverage to ground users. Each UAV is constrained in its energy storage and wireless coverage, and it consumes most energy on flying to the top of the target area, thus leaving limited leftover energy for hovering at its deployed position and keeping wireless coverage. The literature largely overlooks the sustainability issues of deploying UAV swarm and the UAV-to-UAV cooperation, and we aim to maximize the minimum leftover energy storage among all the UAVs after their deployment. Our new energy-saving deployment problem captures that each UAV's wireless coverage is adjustable by its service altitude, and also takes the no-fly-zone (NFZ) constraint into account. We show that a UAV with larger initial energy storage in the UAV swarm should be deployed further away from the UAV station, and we propose an optimal energysaving deployment algorithm by jointly balancing heterogeneous UAVs' flying distances on the ground and final service altitudes in the sky. When n UAVs with different initial energy storages are dispatched from different initial locations, we prove this problem is NP-hard in general by reduction from partition problem. Despite of this, we propose to preserve the UAVs' location order and successfully design an approximation algorithm of complexity n log1/g to arbitrarily approach the optimum with error e. Inspiring by this proposed (1 - ε)-approximation algorithm, we present a heuristic algorithm to solve the general case by balancing the efficiency and computation complexity well.

A Fuzzy Based Techniques For Energy Efficient Cluster Head Selection For Wireless Sensor Network

WSN is split into various clustering nodes in order to obtain proper arrangement and network stability and thus drags the system's lifetime. Each detector node transmits the necessary data to cluster head of each cluster in each cluster-based WSN. Cluster head is liable for collecting the data gathered and forwarding it to sink of network deployed. This manuscript suggests an enhanced Fuzzy-based CH selection algorithm that observes the leftover energy, node compactness and sink distance as input to the Fuzzy inference system. For each node, the eligibility index is calculated to select the head of the cluster. By taking in account the probability assigned to , this algorithm chooses the best candidate for place of the cluster advisor. To each sensor node and helps to increase the energy efficient of network.

Influence of diameter and quality of beech logs on the potential energy of sawmill residues

The influence of log diameter and log quality were studied relative to the potential heat energy produced from wood residue. Research was conducted on beech sawmill logs (30 cm to 49 cm in diameter and 4 m in length) of different qualities. Logs with greater diameters and of better quality increased the amount of products and decreased the amount of residue. A decrease in the diameter and quality of beech logs increased the total energy capacity, ranging between 840 kWh/m3 (highest quality logs, 40 cm to 49 cm in diameter) and 1,350 kWh/m3 (lower quality logs, 30 cm to 34 cm in diameter). Drying the lumber produced from logs of small diameters used less than 10% of the potential heating energy. However, logs of 40 cm to 49 cm in diameter increased this usage to 33%. When burner losses and drying energy losses were calculated, there was approximately 430 kWh/m3 to 960 kWh/m3 of leftover energy. This could be used for various purposes or it could be sold. The amount of obtained energy was influenced more by log diameter than by the log quality.

A Novel Redundant Hole Identification and Healing Algorithm for a Homogeneous Distributed Wireless Sensor Network

The Quality of Service of a Wireless Sensor Network depends mainly on how perfectly the required area is covered. The work aims at identifying the coverage hole in the region of interest using the advanced Delaunay technique. Secondly, the healing process is initiated through the identification of the redundant node. Unlike the basic distance and energy parameter, the number of occurrences of the redundant node in the redundancy map is also taken into consideration which helps to choose the best redundant node. The third objective of the work is to devise a cooperative incomplete game for the process of healing to have a better coverage based on the average leftover energy and distance of the run. The sizing of the coverage hole after each run of the algorithm helps to check if the required threshold level of coverage is reached. To reduce the number of healer node participating in the healing process the redundancy in the hole point is identified so as to heal more than one hole at a time. It is shown that if we adopt a variable sensing range along with the random mobility pattern in healing the best coverage can be achieved. The coverage improvement with the sensing radius of 15 m is about 14% better than the conventional technique with the hole area being 89.59% lesser after healing. The total distance moved to heal is 59.7% lesser with the average residual energy being 20.87% more in the proposed technique.

Energy efficient channel aware multipath routing protocol for mobile ad‐hoc network

SummaryMobile ad‐hoc network (MANET) is a gathering of portable nodes that works without foundation or central administration. Because of the accessibility of little and cheap remote conveying nodes, MANETs can be utilized as a part of different applications, for example, front line correspondence and debacle alleviation applications. Energy consumption is an important issues in MANET because the mobile nodes are battery powered, hence diminishing system lifetime as batteries get depleted rapidly as nodes move and change their positions quickly crosswise over MANET. We propose an energy efficient channel aware routing algorithm for mobile ad‐hoc networks, called energy efficient channel aware ad‐hoc on‐demand multipath distance vector routing (EECA‐AOMDV). EECA‐AOMDV addresses three vital prerequisites of mobile ad‐hoc networks: energy effectiveness, unwavering quality and dragging out system lifetime. The proposed energy efficient channel mindful AOMDV (EECA‐AOMDV) utilizes the channel normal nonfading span and nodal residual energy as directing metric to choose the stable route for way revelation. The key thought of the convention is to discover average channel nonfading duration and maximum nodal residual energy as routing metrics of each course during the time spent choosing way and sort the multi course by slipping channel nonfading duration and nodal leftover energy.

Optimal Hour-Ahead Bidding in the Real-Time Electricity Market with Battery Storage Using Approximate Dynamic Programming

There is growing interest in the use of grid-level storage to smooth variations in supply that are likely to arise with an increased use of wind and solar energy. Energy arbitrage, the process of buying, storing, and selling electricity to exploit variations in electricity spot prices, is becoming an important way of paying for expensive investments into grid-level storage. Independent system operators such as the New York Independent System Operator (NYISO) require that battery storage operators place bids into an hour-ahead market (although settlements may occur in increments as small as five minutes, which is considered near “real-time”). The operator has to place these bids without knowing the energy level in the battery at the beginning of the hour and simultaneously accounting for the value of leftover energy at the end of the hour. The problem is formulated as a dynamic program. We describe and employ a convergent approximate dynamic programming (ADP) algorithm that exploits monotonicity of the value function to find a revenue-generating bidding policy; using optimal benchmarks, we empirically show the computational benefits of the algorithm. Furthermore, we propose a distribution-free variant of the ADP algorithm that does not require any knowledge of the distribution of the price process (and makes no assumptions regarding a specific real-time price model). We demonstrate that a policy trained on historical real-time price data from the NYISO using this distribution-free approach is indeed effective.

Two-dimensional numerical simulation of a decaying laser spark in air with radiation loss

Results are presented on two-dimensional numerical simulation of a decaying laser spark after the air breakdown. Radiation loss is modeled in a finite volume framework for a finite wavelength range of the emitted rays. The redistribution of assumed absorbed energy among different parts, namely the blast wave energy, the radiative heat energy and the left-over energy is quantified. About 5% of the absorbed energy is found to be trapped around the breakdown region after the blast wave moves away. A prediction is made about the actual available energy for ignition of a combustible mixture. A distinct rollup motion around the breakdown region is demonstrated from the simulation, which is in accordance with other numerical and experimental observations. Finally, the evolution of the blast wave radius with time is validated against in-house experimental data.

Ecology on the Web

Ecology on the Web