Application of MPSO technique to find optimal location and parameter setting of TCSC

A new mothod was presented to find the optimal location and parameter setting of Thyristor Controlled Series Compensator (TCSC) to maxmize the transfer capability.Firstly the sensitivity of the transfer capability with respect was described to the line's reactance was described to find the more sensitive lines for installing TCSC,however,the line which has the most sesitivity value is always not the best line for installing TCSC.For solving this problem,the more sensitive m lines were selected as the alternative line group of installing TCSC,and then modified particle swarm optimization (MPSO) was used to find out the optimal location and the optimal parameter settings of TCSC.Particle swarm optimization (PSO) algorithm can results premature convergence.For solving this problem,population entropy and cellular automata were introduced to it.Simulation results of IEEE 30-bus system proved the effectiveness of the method and its application values.

Improving Voltage Stability of Power System by Optimal Location of FACTS Devices Using Bio-Inspired Algorithms

Power system operations can be optimized using power electronics based FACTS devices. The location of these devices at appropriate transmission line plays a major role in their performance. In this paper, two bio-inspired algorithms are used to optimally locate two FACTS devices: UPFC and STATCOM, so as to reduce the voltage collapse and real power losses. Particle swarm optimization and BAT algorithms are chosen as their behaviour is similar. VCPI index is used as a metric to calculate the voltage collapse scenario of the power system. The algorithm is tested on two benchmark power systems: IEEE 118 and the Indian UPSEB 75 bus system. Performance metrics are compared with the system without FACTS devices. Application of PSO and BAT algorithms to optimally locate the FACTS devices reduces the VCPI index and real power losses in the system.

Optimal location query based on k nearest neighbours

Optimal location query in road networks is a basic operation in the location intelligence applications.Given a set of clients and servers on a road network,the purpose of optimal location query is to obtain a location for a new server,so that a certain objective function calculated based on the locations of clients and servers is optimal.Existing works assume no labels for servers and that a client only visits the nearest server.These assumptions are not realistic and it renders the existing work not useful in many cases.In this paper,we relax these assumptions and consider the k nearest neighbours(KNN)of clients.We introduce the problem of KNN-based optimal location query(KOLQ)which considers the k nearest servers of clients and labeled servers.We also introduce a variant problem called relocation KOLQ(RKOLQ)which aims at relocating an existing server to an optimal location.Two main analysis algorithms are proposed for these problems.Extensive experiments on the real road networks illustrate the efficiency of our proposed solutions.

Optimal location of a particulate matter sampling head outside an unmanned aerial vehicle

Particulate matter （PM） has received considerable attention from scientists because of its adverse effects on human health. Unmanned aerial vehicles （UAVs） offer a new approach for monitoring PM in inaccessi- ble or dangerous locations. Computational fluid dynamics software and a wind-tunnel experiment were used to evaluate the flow field at 20, 30, and 40m/s, as well as the trajectories of PM1, PM2.5, and PMlo. The numerical simulation results show that the PM sampling head can be installed 440-680 mm from the UAV nose, and at least 130, 135, and 145 mm below the horizontal axis for free stream velocities of 20, 30, and 40 m/s, respectively. Wind-tunnel experiment results confirmed and improved on those numer- ical results, and showed that the PM sampling head can be 500-600 mm aft the UAV nose, at vertical distances below the horizontal axis of at least 138 mm for 500-550 mm, and 157 mm for 550-600 mm. In addition, sampling points can be located at either side of the optimal ranges, not only on the center line or the UAV.

A Cooperative Security Monitoring Mechanism Aided by Optimal Multiple Slave Cluster Heads for UASNs

As each cluster head(CH)sensor node is used to aggregate,fuse,and forward data from different sensor nodes in an underwater acoustic sensor network(UASN),guaranteeing the data security in a CH is very critical.In this paper,a cooperative security monitoring mechanism aided by multiple slave cluster heads(SCHs)is proposed to keep track of the data security of a CH.By designing a low complexity“equilateral triangle algorithm(ETA)”,the optimal SCHs(named as ETA-based multiple SCHs)are selected from the candidate SCHs so as to improve the dispersion and coverage of SCHs and achieve largescale data security monitoring.In addition,by analyzing the entire monitoring process,the close form expression of the probability of the failure attack identification for the SCHs with respect to the probability of attack launched by ordinary nodes is deduced.The simulation results show that the proposed optimal ETA-based multiple SCH cooperation scheme has lower probability of the failure attack identification than that of the existing schemes.In addition,the numerical simulation results are consistent with the theoretical analysis results,thus verifying the effectiveness of the proposed scheme.

PLC-Oriented Access Point Location Planning Algorithm in Smart-Grid Communication Networks

In this study, we investigate the optimal location of access points （APs） to connect end nodes with a service provider through power-line communication in smartgrid communication networks. APs are the gateways of power-distribution communication networks, connecting users to control centers. Hence, they are vital for the reliable, safe, and economical operation of a power system. This paper proposes a planning method for AP allocation that takes into consideration economics, reliability, network delay, and （n-l） resilience. First, an optimization model for the AP location is established, which minimizes the cost of installing APs, while satisfying the reliability, network delay, and （n-1） resilience constraints. Then, an improved genetic algorithm is proposed to solve the optimization problem. The simulation results indicate that the proposed planning method can deal with diverse network conditions satisfactorily. Furthermore, it can be applied effectively with high flexibility and scalability.

The coalbed methane production potential method for optimization of wells location selection

A gas production potential method for optimization of gas wellsite locations selection is proposed in terms of the coalbed gas resources volume and the recoverability. The method uses the actual data about reservoirs in a coalbed gas field in central China to optimize wellsite locations in the studied area in combination with the dynamic data about actual production in the coalbed gas field, selects a favorable subarea for gas wells deployment. The method is established based on the basic properties of coal reservoirs, in combination with the coalbed thickness and the gas content to make an analysis of the gas storage potential of a coal reservoir, as well as resources volume and the permeability of a coal reservoir. This method can be popularized for optimization of wellsite locations in other methane gas development areas or blocks.

Optimal placement of two soil soundings for rectangular footings

This study uses a recently proposed algorithm for consideration of soil sounding locations in the bearing capacity estimations of spatially variable soil for rectangular footings.The objective of the study is to assess the possibility of indicating general guidelines for optimal soil sounding locations in the case of two soundings and rectangular footings.The possibility of proposing such general guidelines would be extremely valuable from the engineering practice point of view.Moreover,it would be promising for future studies concerning more complex foundation arrangements.For this reason,numerous scenarios are analyzed for a variety of vertical and horizontal fluctuation scales and a variety of rectangular foundation lengths.For generality of the results,two correlation structures are considered,i.e.the Gaussian and the Markovian ones.The optimal sounding location results are discussed.The observations indicate that,for a specified vertical fluctuation scale,all optimal borehole locations in dimensionless coordinates form a curve.This phenomenon can be utilized in practical applications.The potential applications of the obtained results and the directions for future studies in this area are also discussed.

Location optimization for the tuned mass damper system on a long-span floor

The L4 roof of Beijing Olympic International Conference Center is a long-span floor with a tuned mass damper system. The locations of dampers in the layout are not optimal theoretically. This paper is about the location optimization of the 74 sets of dampers on the floor. The main content includes the establishment of a 2D dot-matrix model for the structure, the optimal location combination searched by a genetic algorithm, and the optimal results for five working conditions by calculating the total weight.

The Integrated System of Aerial Photogrammetry and Tower Locations Optimization for Transmission Lines

This paper describes the functions and the features of the integrated system of aerial survey and tower locations optimization for transmission lines, which includes all stages from data acquisition, data transmission and data processing to automatic optimization of the tower locations and drawing. The paper also briefly describes the economic benefit gained from this system, and finally proposes the directions of the future development for this system.

A Novel Location Method for Interline Power Flow Controllers Based on Entropy Theory

As one of the new generation flexible AC transmission systems(FACTS)devices,the interline power flow controller(IPFC)has the significant advantage of simultaneously regulating the power flow of multiple lines.Nevertheless,how to choose the appropriate location for the IPFC converters has not been discussed thoroughly.To solve this problem,this paper proposes a novel location method for IPFC using entropy theory.To clarify IPFC’s impact on system power flow,its operation mechanism and control strategies of different types of serial converters are discussed.Subsequently,to clarify the system power flow characteristic suitable for device location analysis,the entropy concept is introduced.In this process,the power flow distribution entropy index is used as an optimization index.Using this index as a foundation,the power flow transfer entropy index is also generated and proposed for the IPFC location determination study.Finally,electromechanical electromagnetic hybrid simulations based on ADPSS are implemented for validation.These are tested in a practical power grid with over 800 nodes.A modular multilevel converter(MMC)-based IPFC electromagnetic model is also established for precise verification.The results show that the proposed method can quickly and efficiently complete optimized IPFC location and support IPFC to determine an optimal adjustment in the N-1 fault cases.

Strategic Planning for Equitable RWIS Implementation:A Comprehensive Study Incorporating a Multi-variable Semivariogram Model

This paper extends the previously developed method of optimizing Road Weather Information Systems(RWIS)station placement by unveiling a sophisticated multi-variable semivariogram model that concurrently considers multiple vital road weather variables.Previous research primarily centered on single-variable analysis focusing on road surface temperature(RST).The study bridges this oversight by introducing a framework that integrates multiple critical weather variables into the RWIS location allocation framework.This novel approach ensures balanced and equitable RWIS distribution across zones and aligns the network with areas both prone to traffic accidents and areas of high uncertainty.To demonstrate the effectiveness of this refinement,the authors applied the framework to Maine’s existing RWIS network,conducted a gap analysis through varying planning scenarios and generated optimal solutions using a heuristic optimization algorithm.The analysis identified areas that would benefit most from additional RWIS stations and guided optimal resource utilization across different road types and priority locations.A sensitivity analysis was also performed to evaluate the effect of different weightings for weather and traffic factors on the selection of optimal locations.The location solutions generated have been adopted by MaineDOT for future implementations,attesting to the model’s practicality and signifying an important advancement for more effective management of road weather conditions.

Eco-economic Background of Hilly-Gullied Loess Region and Optimized Eco-productive Paradigm of Small Watersheds

A thorough analysis on its natural environment as well as social economic status of the hilly-gullied loess region is presented. A small watershed, the dominant landscape unit of the region, has been singled out for further and specific study on landscape pattern and function, its social and economic distinctions. The authors proposed several principles based on its eco-economic background study, which includes water balance and efficient use principle, co-development of grass and agro-forestry principle, location optimization principle. Integrated with detailed analysis of a small watershed, an eco-productive paradigm for the loess land's development based on a small watershed scale was worked out. It consists of circle pattern with villages at core for high efficient agriculture production, hierarchical pattern along the slope for eco-economic development, point-axis pattern for commodity production and circulation in small watersheds and core-margin pattern for exchanges among watersheds.

A Convergent Algorithm for Continuously Optimal Location Problem

In this paper, the continuously optimal location problem is considered. The strong convexity of the objective function, the Lipschitz continuity of the gradient of the objective function are proved. Furthermore, a variant of conjugate gradient method for continuously optimal location problem is presented and its global convergence is analyzed.

Evaluation of the Behavior of Evacuees on Dynamic Floor Condition by Using Multi-agent Simulation

The prediction of the behavior of people in a disaster has a useful role to play in the design of urban structures such as department stores, schools, and office buildings. We focus on using emergency exit signs to effectively guide the evacuation of people on a floor with a dynamically changing layout. A multi-agent simulation is developed to simulate the behavior of evacuees on a floor. A mathematical model is constructed to obtain optimal sign locations to efficiently assist evacuation under the condition that obstacles are dynamically generated on the floor. The optimal sign locations are calculated by the mathematical model. Then, the developed simulation is performed to evaluate the effectiveness of the emergency exit signs and the behavior of evacuees on simple layout models using the calculated optimal sign locations.

Station-and-network–coordinated planning of integrated energy system considering integrated demand response

The integrated energy system(IES)is an important energy supply method for mitigating the energy crisis.A station-and-network–coordinated planning method for the IES,which considers the integrated demand responses(IDRs)of flexible loads,electric vehicles,and energy storage is proposed in this work.First,based on load substitution at the user side,an energy-station model considering the IDR is established.Then,based on the characteristics of the energy network,a collaborative planning model is established for the energy station and energy network of the IES,considering the comprehensive system investment,operation and maintenance,and clean energy shortage penalty costs,to minimize the total cost.This can help optimize the locations of the power lines and natural gas pipelines and the capacities of the equipment in an energy station.Finally,simulations are performed to demonstrate that the proposed planning method can help delay or reduce the construction of new lines and energy-station equipment,thereby reducing the investment required and improving the planning economics of the IES.

Energy-efficient relay selection and optimal relay location in cooperative cellular networks with asymmetric traffic

Energy-efficient communication is an important requirement for mobile relay networks due to the limited battery power of user terminals. This paper considers energy-efficient relaying schemes through selection of mobile relays in cooperative cellular systems with asymmetric traffic. The total energy consumption per information bit of the battery-powered terminals,i.e.,the mobile station （MS） and the relay,is derived in theory. In the joint uplink and downlink relay selection （JUDRS） scheme we proposed,the relay which minimizes the total energy consumption is selected. Additionally,the energy-efficient cooperation regions are investigated,and the optimal relay location is found for cooperative cellular systems with asymmetric traffic. The results reveal that the MS-relay and the relay-base station （BS） channels have different influence over relay selection decisions for optimal energy-efficiency. Information theoretic analysis of the diversity-multiplexing tradeoff （DMT） demonstrates that the proposed scheme achieves full spatial diversity in the quantity of cooperating terminals in this network. Finally,numerical results further confirm a significant energy efficiency gain of the proposed algorithm comparing to the previous best worse channel selection and best harmonic mean selection algorithms.

An effective digital audio watermarking using a deep convolutional neural network with a search location optimization algorithm for improvement in Robustness and Imperceptibility

Watermarking is the advanced technology utilized to secure digital data by integrating ownership or copyright protection.Most of the traditional extracting processes in audio watermarking have some restrictions due to low reliability to various attacks.Hence,a deep learning-based audio watermarking system is proposed in this research to overcome the restriction in the traditional methods.The implication of the research relies on enhancing the performance of the watermarking system using the Discrete Wavelet Transform(DWT)and the optimized deep learning technique.The selection of optimal embedding location is the research contribution that is carried out by the deep convolutional neural network(DCNN).The hyperparameter tuning is performed by the so-called search location optimization,which minimizes the errors in the classifier.The experimental result reveals that the proposed digital audio watermarking system provides better robustness and performance in terms of Bit Error Rate(BER),Mean Square Error(MSE),and Signal-to-noise ratio.The BER,MSE,and SNR of the proposed audio watermarking model without the noise are 0.082,0.099,and 45.363 respectively,which is found to be better performance than the existing watermarking models.

Investigation of Connecting Wind Turbine to Radial Distribution System on Voltage Stability Using SI Index and λ - V Curves

The growth of wind energy penetration level in distribution system raises the concern about its impact on the operation of the power system, especially voltage stability and power loss. Among the major concerns, this paper studied the impact of connecting wind Turbine (WT) in radial distribution system with different penetration levels and different power factor (lead and lag) on power system voltage stability and power loss reduction. Load flow calculation was carried out using forward-backward sweep method. The analysis proceeds on 9- and 33-bus radial distribution systems. Results show that voltage stability enhancement and power loss reduction should be considered as WT installation objective.

AN ANT COLONY ALGORITHM FOR YARD TRUCK SCHEDULING AND YARD LOCATION ASSIGNMENT PROBLEMS WITH PRECEDENCE CONSTRAINTS

This paper examines the yard truck scheduling,the yard location assignment for discharging containers,and the quay crane scheduling in container terminals.Taking into account the practical situation,we paid special attention to the loading and discharging precedence relationships between containers in the quay crane operations.A Mixed Integer Program（MIP） model is constructed,and a two-stage heuristic algorithm is proposed.In the first stage an Ant Colony Optimization（ACO） algorithm is employed to generate the yard location assignment for discharging containers.In the second stage,the integration of the yard truck scheduling and the quay crane scheduling is a flexible job shop problem,and an efficient greedy algorithm and a local search algorithm are proposed. Extensive numerical experiments are conducted to test the performance of the proposed algorithms.