Effective Power Utilization Research Articles

High-Precision Low-Cost Mid-Infrared Photoacoustic Gas Sensor Using Aspherical Beam Shaping for Rapidly Measuring Greenhouse Gases

A high-precision low-cost mid-infrared photoacoustic sensor for greenhouse composite gases based on aspherical beam shaping is proposed and demonstrated. The assembled optical source module and luminous characteristics of infrared source are innovatively investigated and analyzed with aspherical beam shaping. The proposed aspherical-beam-shaping-technique could effectively reduce optical loss and enhance system sensitivity, achieving an effective power utilization ratio of a radiation source of 91% and sidewall noise ratio of 8.9%. Experiments verify the 1.7 times improvement in responsivity and 50% enhancement in minimum detection limit (MDL) on average. In terms of comprehensive greenhouse gas composites and with short integration time of 1 s, MDLs of CO2, CH4, N2O, NF3, SF6, PFC-14, and HFC-134a are 73 ppb, 267 ppb, 72 ppb, 81 ppb, 14 ppb, 9 ppb and 115 ppb, respectively. Furthermore, a 48 h continuous monitoring of H2O, CO2 and CH4 in the atmosphere is conducted and verifies the performance of the gas sensor. The developed sensor allows for the rapid route of low-cost and high-precision detection of multiple greenhouse gases.

Locational marginal price based scheduling strategy for effective utilization of battery energy storage in PV integrated distribution system

Integration of renewable energy resources (RERs) and complexities associated with varying load patterns urge the demand for energy storage systems (ESS) to ensure real power balancing of distribution system. Among various ESS, battery energy storage system (BESS) guarantees the reliable operation of microgrids in terms of economic and technical functionalities. The scheduling of microgrids becomes essential for the economic and optimal performance of both generating sources and loads. In this work, the load-shifting capability of BESS is utilized for the optimal scheduling of grid-connected microgrids. BESS has a significant role in the effective utilization of power from RERs during grid balancing. This paper discusses the scheduling of grid-connected microgrid with two scheduling strategies, which differ in the charging behaviour of BESS. Scheduling decisions are based on the value of locational marginal price (LMP) of distribution system. In scheduling strategy-I, BESS charges at off-peak hours, either from the PV system or from the grid. Meanwhile, in scheduling strategy- II, BESS charges from the PV system at peak or off-peak hours. These two scheduling methods are also compared with the scheduling of the distribution system without integrating the microgrid. The cost of power generation, power from the main grid, and active power losses of the distribution system are calculated by performing optimal power flow (OPF). The effectiveness of the proposed scheduling strategies are validated on the IEEE-69 bus system for 24 h time duration by using MATPOWER simulation tool. The results obtained after OPF establishes the requirement of effective utilization of BESS in PV integrated distribution system.

Design and Implementation of IoT based PV Integrated Power Monitoring System

The awareness of usage of power and effective utilization of power is based on intelligent decision, which can help the user as well as supplier. In this paper the design and implementation of IOT based PV integrated system is presented. A hardware prototype is developed with PV module connected to boost converter, Arduino Uno controller, ESP 8266 Wi-Fi module, and Thing speak to monitor a real-time power. The Arduino Uno serves as the central controller, gathering data from smart power meters and PV modules for solar energy generation. The collected data is wirelessly delivered to the ThingSpeak, which provides cloud-based storage, data analysis, and visualization. With these users may remotely monitor usage of power, track solar energy generation, and get notifications for energy utilization.

Aspects relating to the development of motor skills, strength, and balance in U16 football

Regarding the process of development of young athletes, our primary focus is their health. It is widely recognized that a significant injury can slow down the process of development in the best-case scenario, or prematurely end an athlete’s career, in the worst-case scenario. The nature of football introduces a heightened risk of injuries due to its dynamic and unpredictable characteristics. In order to optimize our efforts in the process of preventing these injuries, we believe that the best practice is to understand the pillars on which performance in football is based, and adapt our training plans and sessions to address particular weaknesses. The two pillars that need our full attention are strength and balance. To pinpoint the vulnerabilities of young athletes, we employed two devices to measure both balance and strength in each athlete. A total of two tests were conducted for each athlete, measuring maximal power in the lower body, dynamic balance from one foot to the other, limb asymmetry in terms of muscle strength, and dynamic balance. The study confirmed that neuromuscular control has a key role in the effective utilization of power by the athlete, as in the dynamic balance test, football team B used less power and recorded (at the same time) a lower limb asymmetry score than team A.

Enhancing the network lifetime of a wireless sensor network using modified k-means Firefly Optimization

Developing technology including the Internet of Things, digital services, smart microgrids, and machine-to-machine systems encourage the implementation of self-configuring, automated systems in massive wireless sensor networks (WSNs). Effective Power utilization is critical in order to keep a network operational for the maximum possible time. Sensor nodes, which are small, battery-powered devices, are used in WSNs. As a result, one of the significant research issues in improving the lifespan of a WSN is resource management. A modified k-means (Mk-means) algorithm for clustering has been proposed to select Cluster Head (CH) to minimize energy usage of the nodes. Several optimization methods have been suggested in this area to extend the WSN lifetime. Following that, the Firefly Algorithm (FFA) is employed to generate the optimal routing through the CHs to a Base Station (BS), where multiple fitness functions such as residual energy, distance, and routing traffic are taken into account to optimize the FFA. As a result, information transmission among intermediate CHs in a hierarchy cluster-based design aids in lowering node energy usage. The proposed MKMFA (modified k-means Firefly Algorithm) technique’s performance is evaluated with K-means AODV (Ad-hoc On-demand Distance Vector) and IPC-KMAN(Improved Performance Clustering Using Modified K-Means Algorithm in Mobile Adhoc Networks) using network lifetime, throughput, Load Balancing Factor (LBF), and Packet Delivery Ratio (PDR). This work is based on recent advances in WSNs, which include application fields, design parameters, and lifetime prediction designs.

Cross layer design with weighted sum approach for extending device sustainability in smart cities

IoT associates with MEMS technology and various other technologies to connect smart devices globally. Providing reliable interaction between the smart devices and maintaining the battery sustainability of smart devices are the major demand since most of the IoT devices are run by a battery source. Device sustainability is the prime concern in most the IoT applications such as smart cities, e-health, smart grid, etc. Thus, we have come up with a cross layer design that improves the device sustainability and lifetime of the IoT networks in smart cities. In the proposed design, physical layer and data link layer information is utilized by the network layer to explore the energy efficient communication among the IoT devices, since 70% - 80% of device energy is utilized for its communication. Cross-layer design can be an optimal solution to enhance the modalities of the wireless network. The Weighted sum approach is used in the proposed model which is an effective computation method to analyze and identify the routing metrics that are associated with energy efficiency. Based on the routing metric analysis (Table 2) it is found that a particular combination of routing metrics performs effective power utilization (by attaining optimal transmission power) and achieves sustained device lifetime. From the obtained results, it is noticed that the MTPM + ETP + ND routing metric combination outperforms all the other combinations, and designing the cross-layer mechanism with the weighted sum approach computation gives better network performance without compromising the device lifetime. In smart cities applications, the device scalability is huge, since frequent battery replacement is a very difficult task. Therefore, we come up with an efficient network model that is more suitable to maintain device sustainability in smart cities.

An Isolated Dual-Input Half-Bridge DC–DC Boost Converter With Reduced Circulating Power Between Input Ports

This article addresses a dual-input half-bridge DC–DC converter for proper utilization of renewable energy sources (RESs). The proposed system includes two different variable sources to examine the power distribution in each module, two high-frequency transformers (HFTs), and a three-leg converter (TLC) at secondary. The TLC is connected in parallel structure to gain reduced circulating power between input modules. This results in obtaining a compact design with a minimum number of switches. Complete steady-state analysis and control strategy of the proposed system have been analyzed. Digital closed-loop control has been implemented using the field programmable gate array (FPGA) controller to minimize the complexity of the control strategy. A laboratory prototype has been developed to justify the feasible operation of the proposed converter. Extensive tests result demonstrates the enhanced performance of the proposed system in effective utilization of power from different sources to feed the telecom load.

Power Distribution Strategy for an Electric Bus with a Hybrid Energy Storage System

To address the power distribution problem that occurs in hybrid energy storage systems (HESSs) in electric vehicles, a fuzzy control distribution method is proposed in this paper, taking the vehicle demand power; supercapacitor power, PSC;; and lithium battery power, Pbat, as the inputs and the power distribution factor of the supercapacitor as the output to control the power distribution of the composite energy storage system, in addition to dividing the whole working condition into three time scales, namely, long, medium and short. In this study, we conducted a comprehensive analysis and comparison with typical control methods regarding the energy storage element output power, battery state of charge (SOC) change, energy flow diagram and power frequency. The simulation experiment results show that the proposed strategy is more effective in reducing the peak output power of the power battery, improving the effective power utilization rate of HESS and the effective energy utilization rate. In order to further verify the effectiveness of the control strategy, a pure electric bus power system test bench was built based on similar principles, and a representative time period under the driving conditions of the China city bus (CHTC-B) was selected, involving an acceleration process from 30 to 48 s (process 1), a uniform speed process from 636 to 671 s (process 2) and a regenerative braking process from 1290 to 1304 s (process 3), further verifying the effectiveness and feasibility of the proposed control strategy.

Investigation on Maximum Power Point Tracking Algorithm (INC and FLC) for Effective Utilization of Power Under Partial Shaded Photovoltaic System

Aim: This paper makes a comparative analysis on two types of maximum power point tracking algorithm to trace the global peak power efficiently with minimum oscillation and less tracking time under partial shaded photovoltaic green energy systems. Materials & Methods: Incremental conductance (INC) and fuzzy logic (FLC) MPPT algorithm are implemented to analyze the tracking efficiency under varying insolation conditions. Results: FLC MPP algorithm extracts peak power of 97.6 W with tracking time of 0.003s while INC extracts 94 W with tracking time of 0.004s. Conclusion: FLC MPPT algorithm provides better efficiency compared to INC algorithm for the selected data set.

Pre-eminent Strategy for Effective Utilization of Power in Data Center

Cloud computing is generating billions of dollars in revenue annually with very minor indication of slowing down. Today, most innovative technology is cloud-centric by retrofitting the technology to on-premises. Every IT business is also rushing from cloud-first to cloud-only concept. Data center are accounting for billions of kilowatt hours of electricity consumption every year. Huge costs spend for energy consumption than establishing the data center Infrastructure. In this paper we discuss some of the best practices to decrease energy consumption in data center .We can better control the things when we can measure it. So we also focus on seizing and measuring the energy needed for a typical data center. There is also environmental concern to be taken care with respect to data center because of CO2 Emission in cooling system.

Research on Short-Term Load Prediction Based on Seq2seq Model

Electricity load prediction is the primary basis on which power-related departments to make logical and effective generation plans and scientific scheduling plans for the most effective power utilization. The perpetual evolution of deep learning has recommended advanced and innovative concepts for short-term load prediction. Taking into consideration the time and nonlinear characteristics of power system load data and further considering the impact of historical and future information on the current state, this paper proposes a Seq2seq short-term load prediction model based on a long short-term memory network (LSTM). Firstly, the periodic fluctuation characteristics of users’ load data are analyzed, establishing a correlation of the load data so as to determine the model’s order in the time series. Secondly, the specifications of the Seq2seq model are given preference and a coalescence of the Residual mechanism (Residual) and the two Attention mechanisms (Attention) is developed. Then, comparing the predictive performance of the model under different types of Attention mechanism, this paper finally adopts the Seq2seq short-term load prediction model of Residual LSTM and the Bahdanau Attention mechanism. Eventually, the prediction model obtains better results when merging the actual power system load data of a certain place. In order to validate the developed model, the Seq2seq was compared with recurrent neural network (RNN), LSTM, and gated recurrent unit (GRU) algorithms. Last but not least, the performance indices were calculated. when training and testing the model with power system load data, it was noted that the root mean square error (RMSE) of Seq2seq was decreased by 6.61%, 16.95%, and 7.80% compared with RNN, LSTM, and GRU, respectively. In addition, a supplementary case study was carried out using data for a small power system considering different weather conditions and user behaviors in order to confirm the applicability and stability of the proposed model. The Seq2seq model for short-term load prediction can be reported to demonstrate superiority in all areas, exhibiting better prediction and stable performance.

Hybrid Photovoltaic and Wind Power System with Battery Management System using Fuzzy Logic Controller

<span lang="EN-US">In recent year, the development of hybrid renewable energy sources has the important role of power generation. This paper focused on design of hybrid PV / Wind power system and its battery management system. The fuzzy logic control based battery management system has been designed for effective power utilization. The proposed control to operate the battery charging and discharging mode during non-linear power generation. The battery will charge whenever the renewable energy power is greater than to consumer load power as well as the battery will discharge whenever the renewable energy power is lesser than to consumer load power. The proposed model will be simulated using Matlab environment and analysis the proposed system results. Finally, simulation results are evaluated and validating the effectiveness of the proposed controller.</span>

Hybrid Photovoltaic and Wind Power System with Battery Management System Using Fuzzy Logic Controller

In recent year, the development of hybrid renewable energy sources has the important role of power generation. This paper focused on design of hybrid PV / Wind power system and its battery management system. The fuzzy logic control based battery management system has been designed for effective power utilization. The proposed control to operate the battery charging and discharging mode during non-linear power generation. The battery will charge whenever the renewable energy power is greater than to consumer load power as well as the battery will discharge whenever the renewable energy power is lesser than to consumer load power. The proposed model will be simulated using Matlab environment and analysis the proposed system results. Finally, simulation results are evaluated and validating the effectiveness of the proposed controller.

Experimental investigation of energy balance in plasma arc cutting process

The present paper describes the power balance of the arc cutting process provided by a plasma torch with steam working medium. The work was concentrated on definition of different power terms including power input as well as effective power utilization and losses as a function of plasma gas flow rate. The work was mostly experimental. The results have shown around 20% of total available power is utilized for material cutting and removing for the studied conditions.

Discrete model-based operation of cooling tower based on statistical analysis

This study is aimed to utilize the operation data to build a physical-meaningful and precise-enough model to assist the operation of a cooling tower. To do so, this work introduces a dimensionless index, which can describe the cooling capability of a cooling tower in terms of effective power utilization. In the first phase of this study, principal component analysis, one of factor analysis methods, is used to investigate effects of ambient air temperature and relative humidity on the cooling capability of a cooling tower. Based on the proposed cooling capability index, the operation data are partitioned into different groups by the fuzzy c-mean clustering algorithm. The resulted groups are distinctly categorized by the conditions of ambient air temperature and relative humidity. In the second phase of the study, data within the same mode of a set of fans are partitioned by the fuzzy c-mean clustering algorithm. The resulted groups of data are then modeled by linear regression. The acquired multiple models are highly accurate in predicting the output temperature of cooling water from the cooling tower. The acquired models assist the operator to accurately select the proper fan mode when process conditions, e.g., cooling loading, or environment conditions, e.g., ambient air temperature, change. It results in electricity saving. This study is concluded by the presentation of a discrete model-based approach to determine the fan mode. The application to a real cooling tower in an iron and steel plant is promising in saving electricity consumed by the fan set.

Green Computing: Issues on the Primary Memory of Personal Computers

Green computing is now a days becoming a research problem and many scientists are focusing their attention to do research on various issues related to this discipline. The topic addresses issues such as , effective power utilization, maximizing efficiency, maximizing efficiency of utilization, correct disposal of electronic gadgets, reliable and cost effectiveness etc. One of the most used components by ICT group are personal computers and hence considered for our analysis under green computing. Any personal computer has major functional components such as CPU, memory , monitors and peripheral devices etc. Each components have certain contribution towards green computing. The main focus of attention of this paper is to study how the power consumed by each functional units are effectively minimized so as to perform the job without any deviation while using the personal computer. Power thus saving is equivalent to power generation or optimal usage. Since there are many functional units present in a personal computer, in this paper, we discuss how memory is contributing to the green computing by conducting various studies on SDRAMs. Results and discussions are presented. The work related to the monitor and the processors are in progress.

Improved Control Strategies for Electric Space Heating Processes

This paper describes three new control strategies for the discontinuous control of electric space heating processes. Discontinuous controllers are invariably used for such processes in order to reduce the cost of control. The disadvantages of such systems are the large overshoots and undershoots, large periods of oscillation, and offset errors. The first strategy utilizing an ON-OFF controller with derivative feedback is shown to minimize the magnitude of oscillations, the period of oscillation, and offset errors. The second strategy utilizes a three-position controller with derivative feedback. Besides eliminating oscillations and offset errors, the controller enables a time optimal start-up of the process. By minimizing the deadzone in the controller, sensitivity to disturbances is increased. A simple method of designing such a controller is also indicated. The third strategy utilizes a pulsewidth modulated (PWM) controller for processes where power is available either at its maximum rating or no power at all. By a proper choice of the parameters, it is shown that the magnitude of oscillations and the period of oscillation can be controlled by the designer. Offset error is completely eliminated, indicating a more effective utilization of power. All the three strategies described require only a minor modification of the existing controllers; the resulting improvement in performance is expected to compensate the slight increase in cost of control. The mathematical derivations involved in the design and analysis of such controllers have deliberately avoided, since the presentation is specifically intended for practicing engineers.