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Summary: The solution of resource allocation is based on NOMA and OMA structures that are suboptimal to satisfy the demanding QoS and higher data rate requirements compared to EE requirements in 5G cellular networks. In this work, the resource allocation problem in the hybrid MC‐NOMA system is solved. The system achieves the trade‐off between spectral and energy efficiency (EE) with the lowest rate of user requirements. The system's resource allocation, including power allocation, is considered the crucial factor and is identified as a single‐objective problem. The suggested work focuses on user pairing and allocation on paired users following processing. The user grouping is designed to connect near‐ and far‐users with high C3 to increase the fairness of NOMA. As a result, this work considers multiple goals, such as C3 maximization, spectrum efficiency, and energy efficiency. This paper aims to present a novel hybrid optimization model with the combination of coati and bald eagle optimization algorithms, to solve the defined optimization problem. The experimental results show that the suggested system outperforms the conventional algorithms by evaluating different performance measures such as channel correlation, spectrum efficiency, energy efficiency, and power allocation. [ABSTRACT FROM AUTHOR]

At present, in order to conduct non‐destructive testing on the grounding grid of substations under the condition of continuous power supply and no excavation, researchers have applied wireless technology based on electrochemical methods to remotely monitor the corrosion state of grounding conductors online. Nevertheless, wireless signals are affected by the environment when they are transmitted underground. In the field of grounding gird wireless monitoring, how to plan the information transmission path of wireless sensor network (WSN) with high accuracy of data transfer and low energy consumption earns growing research attention. To address the problem of WSN path planning in grounding grid area, a path planning method for WSN based on the hybrid algorithm of map‐matching algorithm and double‐pole search algorithm (MM‐DPS) is proposed in this paper. The map‐matching algorithm is employed to calculate the optimal sampling node number of the data transmission path. On the basis of the optimal sampling node number, the double‐pole search algorithm is employed in seeking out each sensor node of the path, and two groups of path plans are obtained. In the simulation experiment, compared with the A‐star algorithm, the MM‐DPS algorithm shortens the data transmission path length by about 39% and reduces the energy consumption by about 57%. The research work brings a method to alleviate the problem of data transmission underground of WSN in grounding grid area. The method not only ensures the accuracy of data transmission, but also shorts the transmission distance and reduces energy consumption. [ABSTRACT FROM AUTHOR]

Conservation voltage reduction (CVR) is a strategy that tries to save energy consumption by managing consumers' voltage. On the other hand, enhancing reactive power compensation in the power system gives rise to CVR implementation more effectively. This paper addresses how the power system planner could encourage investment to establish the above‐mentioned topics. Here, a model for encouraging industrial loads to dynamically invest in implementing the CVR strategy over the planning horizon is presented. To make CVR implementation more efficient, investment in upgrading plug‐in electric vehicles (PEVs) chargers to be utilized as reactive power compensators is also considered. Industrial loads benefit from saving in their electricity bills and incentive payments that might be paid by utilities (if necessary). The objective function of the proposed planning model is to maximize the energy‐saving of industrial loads and to minimize incentive payment by electric utilities over the planning horizon. This objective is achieved subject to that the investment plan is economically feasible. Moreover, power system operation constraints in the planning horizon based on AC power flow equations and voltage‐dependent load models are considered. The proposed planning problem is modelled as a non‐linear optimization problem that can be solved by off‐the‐shelf software, for example, GAMS. The proposed model is applied to the Ontario transmission system. The numerical results show the proposed model's effectiveness in designing an investment plan for industrial loads to implement the CVR strategy and upgrade PEVs' chargers. Here, a model for encouraging industrial loads to dynamically invest in implementing the conservation voltage reduction (CVR) strategy over the planning horizon is presented. To make CVR implementation more efficient, investment in upgrading plug‐in electric vehicles (PEVs) chargers to be utilized as reactive power compensators is also considered. The objective function of the proposed planning model is to maximize the energy‐saving of industrial loads and to minimize incentive payment by electric utilities over the planning horizon. This objective is achieved subject to the fact that the investment plan is economically feasible. Moreover, power system operation constraints in the planning horizon based on AC power flow equations and voltage‐dependent load models are considered. [ABSTRACT FROM AUTHOR]

Conventional energy resource problems made power system planners apply more renewable energy sources (RESs) in the power system. RESs have a significant impact on fulfilling the world's energy demand, protecting the environment at least in the exploration phase, and providing energy reliability as well as security for the new generation of power grids. In this regard, wind power generation is considered a promising solution. However, by increasing the share of wind power generation units in the power sector, some challenges, such as voltage problems, transient stability, increasing system losses, and line congestions can occur. Consequently, an alternative solution is required to accelerate wind power units' connections to the grid by preventing the problems caused by the penetration of wind power. In this regard, Flexible Alternating Current Transmission Systems (FACTS) devices can play an important role while they can improve power grid dynamic performance. This paper presents a review of the optimization techniques applied to accelerate the penetration of wind energy by exploiting FACTS devices. The topic identifies the objectives and optimization formulations, as well as schemes and models available in the published literature. This survey gives noteworthy insights to the researchers to cover available solutions in these regards. The literature in the field is summarized in different aspects, such as FACTS technology, objective functions, constraints, optimization methods, planning or operation purposes, and load flow types. At each aspect, a comparison is derived to recognize the most important issues. The result of the review is the finding of future work and contributions which can be done in the field of wind energy integration acceleration using FACTS devices and the output of the paper can be used as a guide for researchers to find a new path for research in this area. [ABSTRACT FROM AUTHOR]

The energy consumption of a battery‐powered train in an interstation depends on the running time and state of energy (SOE) at departure. In this paper, we develop an optimization method of train timetables to minimize energy consumption in line with several stations. The variables in this proposed optimization model are running, dwell, and charging times as real numbers and places of charging facilities as binaries. Additionally, we conducted a case study using the real‐world light rail transit (LRT) route, vehicle, and onboard battery model to confirm the effectiveness. In the case study, the proposed method can optimize the timetable and placement of charging facilities by considering the track gradient and battery SOE. [ABSTRACT FROM AUTHOR]

This paper focuses on enhancing the energy collection efficiency of an integrated collector storage solar water heater (ICS SWH) by vee‐corrugating the absorber and optimizing the design for the vee‐included angle through simulation and experimental study. This paper presents an efficient algorithm for analyzing a vee‐corrugated absorber ICS SWH using Engineering Equation Solver Software. For validating this algorithm, two models of ICS SWH systems have been fabricated: one with a flat absorber and the other with a 60° vee‐included angle corrugated absorber with eight corrugations. The basic purpose of the fabrication of the flat absorber ICS SWH system was to approximate the absorptivity of the absorber. A typical value of 0.68 was estimated for the absorptivity of the aluminum absorber coated with nonselective black paint. After the experimental investigation of the 60° vee‐included angle ICS SWH system, it was found that the real‐time readings were in close agreement with the numerical model readings. For comparison with the previous work, a five‐corrugation system with an approximate 90° vee‐included angle with the same projected dimensions was modeled and the efficiencies of both the models for the time from 7 a.m. to 3 p.m. were calculated. The efficiency of the eight‐corrugation model was 42.56%, which was better than the previous work of the five‐corrugation model, with a 38.86% efficiency for the same ambient conditions. Also, it was theoretically deduced that we had an optimized system at 18 corrugations and a vee‐included angle of 28.78°. [ABSTRACT FROM AUTHOR]

Summary: Multiple‐input multiple‐output (MIMO) systems perform well from the energy efficiency (EE) and the spectral efficiency (SE) points of view in fifth generation (5G) communication systems. This paper considers the operation of a MIMO system with a relay. The optimization problem relates to the EE maximization. This problem has two types of limitations, which provide a maximum transmission power and a minimum data rate for users. The encountered objective function is in a fractional form and thus it is a non‐convex function. Besides, the problem is constrained. We utilize a lower bound analysis for the data rates, some properties of the linear programming, and the maximum ratio transmission (MRT) precoding scheme to obtain a convex objective function. Using the Lagrange dual function, we obliterate the constraints of the problem and then it is easy to solve. To improve system performance, users are divided into two groups based on their channel gains, and the maximum transmission power is reasonably divided between them. Two iterative algorithms are proposed to solve the optimization problem numerically, and finally we investigate performance of the proposed method. [ABSTRACT FROM AUTHOR]

Summary: Wireless sensor network (WSN) is a well‐developed domain suitable in the optimal collection and processing of information needed for the present world. For processing and transmitting the correct data by the network, it is affected by many disrupting factors like interference, battery life, distance between the nodes, and redundant data. There have been many methods proposed in the past. Among all the disrupting factors, routing has been the most studied problem in the WSN literature, whereas packet length sizing has been the most untouched topic compared to routing. Sizing the packet lengths to transmit it through the network is important to get error‐free data and run an energy‐efficient network. In this paper, we propose a sling‐shot spider optimization (S2SO) algorithm for packet length optimization in WSN and Internet of Things (IoT)‐based networks. The S2SO algorithm is developed based on the spider's unique behavior of catching prey. The proposed algorithm is implemented in three types of networks: 1‐hop, 2‐hop, and multi‐hop networks. A mathematical model for the communication channel, energy efficiency, and energy consumption is developed for all three types of networks. The proposed packet length optimization model is simulated in MATLAB software and compared with conventional bio‐inspired algorithms. The results show that the proposed algorithm is very fast in finding the optimal results and transmits optimal packet size with low error rate of 0.2 p.u. and a high efficiency of 98%. [ABSTRACT FROM AUTHOR]

Energy‐efficient train operation (EETO) in high‐speed railways (HSRs) is an extra cost‐effective and flexible means to promote energy‐saving. This paper first examines the energy consumption sources and energy‐saving measures of high‐speed trains (HSTs). Then presents the EETO in HSRs, including three categories: energy‐efficient train control, energy‐efficient train timetabling, and EETO considering train timetabling and driving strategy. Next, the current research status and progress on three aspects of EETO in HSRs, namely optimization algorithm, constraint condition, and oriented scenario, are sorted out. Finally, the research on EETO in HSRs has prospected and proposed directions that can study in depth in the future. By summarizing and reviewing the research on EETO in HSRs, it is hoped to furnish a reference for the railway sector to enhance quality, efficiency, and green, low‐carbon development. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

The paper considers the problem of maximum efficiency for the system of distillation columns. Columns in such systems are connected in parallel or sequential way. The mixture being separated is assumed to be close to ideal one. Authors parameterize the relationship between feed flow rate and heat duties of a steady‐state binary distillation column using two parameters: the reversible efficiency and the irreversibility coefficient. This relationship is later being used to solve the problems of optimal distribution of heat and feed flows within the system. The results obtained allow one to estimate minimum heat energy demand for distillation of the given feed flow, maximum performance, and efficiency of the system. [ABSTRACT FROM AUTHOR]

A highly efficient psi‐shaped solar energy absorber in the paper is developed. This structure is designed using titanium‐based psi shaped resonator, SiO2 based substrate, and Tungsten metal‐based base layer to achieve a near‐perfect ultrawideband absorption spectrum under solar radiation. The average absorption of 97.04% is achieved in the observed range including the ultraviolet to mid‐infrared regimes and the ultrawideband characteristics are also achieved. It is also noted that for the bandwidth of 3730 and 2500 nm, above 90% and 95% absorption rate are achieved, respectively. The effect of several design parameters on the spectrum of absorption is explored and accordingly, optimized design is identified. Furthermore, the absorption response of the developed solar energy absorber is polarization‐insensitive and wide‐angle from 0° to 50°. Experiments are meant to identify the optimal parameter values for solar absorber design by employing a random restart hill climbing optimization approach. According to the experimental data, this strategy can reduce the computing power and time requirements of the simulation process by 97.57%. [ABSTRACT FROM AUTHOR]

Electricity access is a critical factor for social and economic development. Microgrid becomes cost‐effective means to provide access to electricity for the rural community. Rural electrification demands high investment due to its low energy demand and population. Planning of rural electrification is a technical and financial challenge for policymakers. This paper proposes the grid‐connected electrification of the rural community of Uttarakhand (India). An integrated model formed with the solar photovoltaic system, wind energy, and battery. This research aims to provide the optimal cost‐effective solution for the electrification of the rural community. The suggested model is optimized using Differential Algorithm to determine the optimal system configuration, cost of energy, and net present cost. The effectiveness of the proposed DE algorithm is compared with genetic algorithm and particle swarm optimization. The results confirm that the proposed renewable energy‐based microgrid has a total production cost of $5 185 367.04, with a per‐unit cost of energy is $0.20/kWh. The proposed microgrid is a more suitable option for electrification in rural communities with less dependence on the grid and conventional sources. [ABSTRACT FROM AUTHOR]

Summary: Wireless sensor networks (WSNs) consist of nodes. Issues involved with the use of a sensor network are energy‐saving and the effective use of energy. Clustering in WSNs is a proven technique for energy optimization. The relationship between sensor nodes and cluster heads (CHs) has only been considered prior to cluster‐based routing protocols. However, most clustering algorithms have failed to address the routing overhead and the energy consumption rate between CH nodes and SINK. In this paper, a new framework named as EEC‐MA‐PSOGA ‐ an energy‐efficient (EE) intra‐cluster mobile agent (INC‐MA)‐based particle swarm optimization–genetic algorithm (PSO‐GA), has been presented to initiate the distance communication and place the SINK optimally in WSNs. The cluster members send the collected data towards their respective CHs for aggregation. To find the sink's best position, the PSO‐GA‐based location estimation algorithm is initiated based on the network structure. The limited capability of WSNs makes them more vulnerable to attackers. The prevention mechanism must be less complex to ensure the fair operations in the network. Here, the attack detection ability of the proposed solution has been tested against clone attack. With varied communication range, simulation time, and sensor nodes, the tests are conducted extensively on various scenarios of WSNs. When compared with the prior mechanisms, the framework provides better results and better prevention with less overhead by analyzing the experimental results such as energy consumption, network lifetime, and throughput. [ABSTRACT FROM AUTHOR]

Prominent equipment with a very high demand for fuels in refineries is the fired preheater of crude oil. There are two main reasons to investigate the energy usage of such fired heaters. First, this is essential to the economic value of the refinery process unit and second, this is located at the beginning of the process line, which causes inefficient performance or damage in downstream equipment if it is not tuned properly. This paper concentrates on the thermal modeling of a fired heater of crude oil to evaluate the effect of influential parameters on fuel consumption. As the number of variables is markedly high, and considering the complexity of thermal modeling, all equations in a code yield predefined heater efficiency. Results from the model show that the increase in heater size yields a decrease in efficiency. It was also found that with a constant dimension of the fired heater, change in the number of pipes is much less influential rather than more inexpensive ideas like increasing speed of the burning gas on reduction of the fuel consumption. In other words, it was found that a distance of 500–650 mm from the center to the center distance of the pipes is the optimal distance to reduce fuel consumption. [ABSTRACT FROM AUTHOR]

Summary: A wireless sensor network (WSN) is a prominent technology that could assist in the fourth industrial revolution. Sensor nodes present in the WSNs are functioned by a battery. It is impossible to recharge or replace the battery, hence energy is the most important resource of WSNs. Many techniques have been devised and used over the years to conserve this scarce resource of WSNs. Clustering has turned out to be one of the most efficient methods for this purpose. This paper intends to propose an efficient technique for election of cluster heads in WSNs to increase the network lifespan. For the achievement of this task, grey wolf optimizer (GWO) has been employed. In this paper, the general GWO has been modified to cater to the specific purpose of cluster head selection in WSNs. The objective function for the proposed formulation considers average intra‐cluster distance, sink distance, residual energy, and CH balancing factor. The simulations are carried out in diverse conditions. On comparison of the proposed protocol, ie, GWO‐C protocol with some well‐known clustering protocols, the obtained results prove that the proposed protocol outperforms with respect to the consumption of the energy, throughput, and the lifespan of the network. The proposed protocol forms energy‐efficient and scalable clusters. [ABSTRACT FROM AUTHOR]

In this paper, a novel liquefied air energy storage (LAES) system driven by wind energy and natural gas, integrated with a two‐stage supercritical carbon dioxide cycle is proposed and investigated. Three different sensible thermal energy storage (TES) systems are considered in this study to store the heat produced in the compressions stage and use it later to improve the performance. The proposed system is analyzed in terms of energy, exergy, exergo‐economic, and environmental impacts. A detailed economical and technical investigation is carried out to determine system hotspots, exergy destruction rates, and the performance of the system and subsystems. Finally, by considering ten design variables, the nondominated sorting genetic algorithm‐II (NSGA‐II) is employed to evaluate the optimal design solutions for double objective functions, including cost per unit of exergy and overall system exergy efficiency. Results indicate that for a 50 MW of discharging power, 80.75 MW of charging electricity and 1.22 kg/s of fuel are required. Additionally, the product cost per unit of exergy and the levelized costs are calculated as 32.02 $/GJ and 0.133 $/kWh, respectively. The results of the optimization study also show that for the optimal Pareto solution, the energy efficiency would be 52.2% while the exergy efficiency is 45.26%. [ABSTRACT FROM AUTHOR]

Summary: Wireless sensor networks (WSN) encompasses millions of nodes that work jointly, senses environmental information, and transmits to the Base Station (BS). "Energy hole" or "hot‐spot" is a problem in which sensor nodes near to the BS deceasetoo early which creates the partitioning of the network. This is due to the reason of the difference in the consumption of energy by the nodes in WSN which reduces the lifespan of the sensor network. The distribution of the cluster heads and the load balancing are the major pitfalls. In this paper to deal with the statedpitfalls, a hybrid of fuzzy logic technique and harmony search algorithm is proposed to lengthen the lifetime of the network. Unequal clustering is a technique proposed by the researchers to handle the hot‐spot issue, hence it is also included. The proposed algorithm forms unequal clusters. To prove the efficiency of the proposed algorithm, some well‐known unequal clustering algorithms and harmony search based algorithmare used to compare the proposed algorithm under different network settings. In all the settings, better performance is achieved by the proposed protocol. It prolongs the lifespan of the network as compared to the different algorithms proposed so far. [ABSTRACT FROM AUTHOR]

Summary: This paper discusses the use of logic minimization techniques and wide fan‐in primitives and how the design and evaluation of combinational blocks for full‐custom dual‐precharge‐logic‐based cryptocircuits affect security, power consumption, and hardware resources. Generalized procedures for obtaining optimized solutions were developed and applied to the gate‐level design of substitution boxes, widely used in block ciphers, using sense‐amplifier–based logic in a 90‐nm technology. The security of several proposals was evaluated with simulation‐based correlation power analysis attacks, using the secret key measurements to disclosure metric. The simulation results showed increased security‐power‐delay figures for our proposals and, surprisingly, indicated that those solutions which minimized area occupation were both the most secure and the most power‐efficient. This paper discusses the use of logic minimization techniques and wide fan‐in primitives and how the design of full‐custom dual precharge logic‐based cryptocircuits affect security, power consumption, and hardware resources. Generalized procedures for obtaining optimized solutions were developed to the gate‐level design using sense‐amplifier–based logic in a 90‐nm technology. The correlation power analysis attacks results showed increased security‐power‐delay figures for our proposals and indicated that those solutions which minimized area occupation were both the most secure and the most power‐efficient. [ABSTRACT FROM AUTHOR]

Most of the crude oil produced in China is highly viscous and easy to condense, and the pipeline transportation method is mostly heated. At present, frequency conversion technology is gradually applied to oil pump units. In order to find the best pipeline operation scheme, this paper is based on MATLAB programming software and established a corresponding mathematical model of oil pipeline energy consumption. This model innovatively takes the rotational speed of the variable frequency pump as one of the model optimization variables, calculating the pressure change and temperature change between stations of the pipeline, predicting the energy consumption of the pipeline and can guide the optimized operation of the pipeline, which has a high popularization and application value. An example of Qingtie Fourth‐line crude oil pipeline shows that among the genetic algorithm, particle swarm optimization, and simulated annealing algorithms for solving the optimization model, the particle swarm optimization algorithm has fast convergence speed, short optimization time, obtains the most optimal scheme, and can reduce energy consumption by 7.84%, which proves the practicability and creativity of the optimization model. [ABSTRACT FROM AUTHOR]

Summary: Recently, academic and industrial research communities are paying more explicit attention to the 5G multiple radio access technology ultra‐dense networks (5G multi‐RAT UDNs) for boosting network capacity, especially in UD urban zones. To this aim, in this paper, we intend to tackle the user association problem in 5G multi‐RAT UDNs. By considering the decoupled uplink/downlink access (DUDA), we divide our user association problem into two distinct subproblems representing, respectively, the uplink and the downlink channels. Next, we formulated each one as a nonlinear optimization problem with binary variables. Then, to solve them, we were restricted by the hard complexity, as well as the hard feasibility of centralized user association schemes. Thus, to resolve our user association problem in a reasonable time and distributed manner, we formulated each subproblem as a many‐to‐one matching game based on matching theory. Next, we provide two fully distributed association algorithms to compute the uplink and downlink stable matching among user equipments (UEs) and base stations (BSs). Simulation results corroborate our theoretical model and show the effectiveness and improvement of our achieved results in terms of the overall network performance, quality of service (QoS), and energy efficiency (EE) of UEs. [ABSTRACT FROM AUTHOR]

One of the most commonly used processes for the removal of acid gases from natural gas is absorption in alkanolamine-based solvents. Operating cost and energy consumption beside environmental cares are the main limiting factors, which lead process designers to select optimum values of sensitive parameters in sweetening plants. This paper summarizes a study that determines values of optimum operating parameters for sweetening a sour gas stream with 5 mol% of CO2 and 0.39 mol% of H2S considering optimum cost and energy consumption. A typical amine sweetening process plant is used to accomplish a steady-state simulation by HYSYS process simulator v8.4 using different amine solutions, i.e. single, mixed, and also activated amines. It also examined some of the important amine process parameters for each amine type such as amine circulation rate, lean amine temperature, corrosion and amine loss considerations. Finally, an economic evaluation is performed by Aspen process economic analyzer to compare operational and total capital costs of processes. It has been revealed that mixture of methyldiethanolamine and dieathanolamine is more applicable due to its higher absorption capacity, lower capital and operational expenditure, and lower costs related to corrosion and amine losses. © 2015 Curtin University of Technology and John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In order to carry out energy saving service, it is indispensable to calculate the energy saving effect quantitatively by presuming the energy cost at the time of not executing the energy saving measure. However, it is difficult because the energy cost changes when environment (energy demand, unit prices of fuel or electric power, and so on) changes even if an energy saving measure is not executed. Although the effect has been conventionally evaluated by the difference between the energy costs before and after the energy saving measure, the effect cannot be calculated correctly when there is environmental change. In this paper, we propose the method of estimating the energy saving effect by presuming the energy cost after an energy saving measure, assuming that the measure is not executed, and show the results of its application to the practical power plants. © 2009 Wiley Periodicals, Inc. Electr Eng Jpn, 168(4): 14–20, 2009; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.20880 [ABSTRACT FROM AUTHOR]

Iron ore sintering is an important and large energy‐consumption segment in the iron and steel industry. It is thus essential to save energy in the sintering process considering both quality and quantity. This paper takes exergy loss minimization as an optimization objective, and a sintering optimization model is established based on material balance and exergy balance. Optimized results are obtained by solving constrained multidimensional nonlinear programming problems. Two types of sintering processes, in which solid fuels consist of coke and coke/coal powder, are calculated and analyzed. The effects of fuel ratio, fuel preheat temperature, and sinter basicity on exergy losses are also studied. The results show that the exergy losses obtained from optimizations for two types of solid fuels decrease by 5.0% and 8.1%, respectively. Exergy loss has a negative correlation with the coal ratio and fuel preheat temperature and a positive correlation with the coke ratio and sinter basicity. Exergy efficiencies increase from 29.7% to 35.0% and 35.5%, for each optimization. The research in this paper is highly significant to exploring of the sintering process, guiding steel production, and reducing energy consumption. A sintering optimization model is established taking exergy loss minimization as an optimization objective. Optimized results are obtained by solving constrained multidimensional nonlinear programming problems. Exergy losses obtained from optimizations for two types of sintering processes, in which solid fuels consist of coke and coke/coal, decrease by 5.0% and 8.1%, respectively. [ABSTRACT FROM AUTHOR]

Nowadays, due to the increasing electrical demand, optimal operation of distribution network has taken much attention. To reach this goal, 1 of the useful methods is the implementation of custom power devices. This paper tries to investigate the unified power quality conditioner (UPQC) placement and sizing along with distribution network reconfiguration for the reactive power compensation in the radial distribution system. This approach finds the optimal sizing and location of UPQC and the optimal changing of the switches status between feeders. Real power loss reduction is the chief function of this work. The proposed method is applied on the 69‐bus radial distribution test system. To check the feasibility and effectiveness of the proposed methodology, various scenarios of reconfiguration and UPQC placement are taken into account at different load conditions. Results show that the network reconfiguration with the placement of UPQC provides lower energy losses compared with other methods. [ABSTRACT FROM AUTHOR]

SUMMARY In this paper, we study a wireless access network based on the Institute of Electrical and Electronics Engineers 802.11 standard and enriched with features such as caching and mesh networking. This system is analysed in terms of energy efficiency and traffic offloading, two objectives that are somewhat in contrast but both relevant to network and service providers as they directly impact the operational cost. In addition, QoS is also accounted for in the form of guaranteed bandwidth and bounded delay. To this aim, we developed a mathematical model of the system and solved it to optimality by means of integer linear programming. We can thus show how much can be saved both in terms of energy and traffic, also considering various tradeoff points among the two contrasting objectives. As a last step, we provide an investigation on the benefits of adding traffic aggregation features to the mathematical model. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Because the energy consumption is growing rapidly, green radio, which lays emphasis on the energy efficiency (EE) in wireless networks, is becoming increasingly important. As potential paradigms for future wireless network design, cognitive radio (CR) is a promising technology to solve the spectrum shortage and inefficiency issues, while cooperative relay is capable of improving spectral efficiency by combating severe fading in wireless environment. In this paper, we investigate the energy-efficient power allocation problem in orthogonal frequency division multiplexing (OFDM)-based relaying CR networks. We develop a general framework to maximize the overall EE of the CR system, under the constraints of transmission power budget, traffic demands, and the interference constraints of the primary users. Our problem formulation is a nonconvex optimization task, and it is hard to obtain the optimal solution. We first convert our formulated problem into a convex optimization problem via its hypograph form, which can be solved by the barrier method. Then we further speed up the computation of Newton step during the barrier method, significantly reducing the complexity of the algorithm by exploiting its special structure. Numerical results validate that our method can exploit the overall EE of CR systems, while the algorithm converges efficiently and stably. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

SUMMARY This paper investigates the impact of an extensive introduction of electric vehicles ( EV) and plug-in hybrid vehicles ( PHEV) into the global energy system by 2050. The significant growth of automobile ownership in emerging countries is likely to increase world oil demand and the associated carbon dioxide emissions. In order to address these energy, security, and environmental concerns, the deployment of clean energy vehicles, such as EV and PHEV, is expected to play a crucial role due to their high fuel efficiency. Consequently, we develop both a global energy system model and a world vehicle penetration model, which can explicitly analyze the impact of EV introduction into the seasonal daily electric load curve, with consideration of the specific electricity charging profile through 2050. The simulation results confirm that EV deployment contributes to energy conservation, because oil demand reduction outstrips the growth in electricity demand and the associated fuel input into the power generation mix. Concerning carbon dioxide abatement, the magnitude of the impact relies on the carbon intensity of the power generation mix. If the intensity is low enough to guarantee a carbon mitigation effect due to EV fuel saving, emissions reduction is well assured. It should be noted, however, that in regions with high carbon intensity in the power generation mix, carbon emissions per mileage of EVs is almost equivalent to that of efficient gasoline vehicles such as hybrid vehicles, and the figure for PHEV is slightly higher than for hybrid vehicles. © 2013 Wiley Periodicals, Inc. Electr Eng Jpn, 186(4): 20-36, 2014; Published online in Wiley Online Library (wileyonlinelibrary.com). DOI 10.1002/eej.22373 [ABSTRACT FROM AUTHOR]