Optimal Placement and Sizing of Distributed Generations for Power Losses Minimization Using PSO-Based Deep Learning Techniques

The integration of distributed generations (DGs) into distribution systems (DSs) is increasingly becoming a solution for compensating for isolated local energy systems (ILESs). Additionally, distributed generations are used for self-consumption with excess energy injected into centralized grids (CGs). However, the improper sizing of renewable energy systems (RESs) exposes the entire system to power losses. This work presents an optimization of a system consisting of distributed generations. Firstly, PSO algorithms evaluate the size of the entire system on the IEEE bus 14 test standard. Secondly, the size of the system is allocated using improved Particles Swarm Optimization (IPSO). The convergence speed of the objective function enables a conjecture to be made about the robustness of the proposed system. The power and voltage profile on the IEEE 14-bus standard displays a decrease in power losses and an appropriate response to energy demands (EDs), validating the proposed method.

Optimal Placement of Active Members in Truss Adaptive Structures

The mathematical model of optimal placement of active members in truss adaptive structures is essentially a nonlinear multi-objective optimization problem with mixed variables. It is usually much difficult and costly to be solved. In this paper, the optimal location of active members is treated in terms of （0, 1） discrete variables. Structural member sizes, control gains, and （0, 1） placement variables are treated simultaneously as design variables. Then, a succinct and reasonable compromise scalar model, which is transformed from original multi-objective optimization, is established, in which the （0, 1） discrete variables are converted into an equality constraint. Secondly, by penalty function approach, the subsequent scalar mixed variable compromise model can be formulated equivalently as a sequence of continuous variable problems. Thirdly, for each continuous problem in the sequence, by choosing intermediate design variables and temporary critical constraints, the approximation concept is carried out to generate a sequence of explicit approximate problems which enhance the quality of the approximate design problems. Considering the proposed method, a FORTRAN program OPAMTAS2.0 for optimal placement of active members in truss adaptive structures is developed, which is used by the constrained variable metric method with the watchdog technique （CVMW method）. Finally, a typical 18 bar truss adaptive structure as test numerical examples is presented to illustrate that the design methodology set forth is simple, feasible, efficient and stable. The established scalar mixed variable compromise model that can avoid the ill-conditioned possibility caused by the different orders of magnitude of various objective functions in optimization process, therefore, it enables the optimization algorithm to have a good stability. On the other hand, the proposed novel optimization technique can make both discrete and continuous variables be optimized simultaneously.

Optimal placement of dampers and actuators based on stochastic approach

A general method is developed for optimal application of dampers and actuators by installing them at optimal location on seismic-resistant structures.The study includes development of a statistical criterion,formulation of a general optimization problem and establishment of a solution procedure.Numerical analysis of the seismic response in time-history of controlled structures is used to verify the proposed method for optimal device application and to demonstrate the effectiveness of seismic response control with optimal device location.This study shows that the proposed method for the optimal device application is simple and general,and that the optimally applied dampers and actuators are very efficient for seismic response reduction.

Optimal Placement and Sizing of Distributed Generation Using Metaheuristic Algorithm

Power loss and voltage uncertainty are the major issues prevalently faced in the design of distribution systems.But such issues can be resolved through effective usage of networking reconfiguration that has a combination of Distributed Generation(DG)units from distribution networks.In this point of view,optimal placement and sizing of DGs are effective ways to boost the performance of power systems.The optimum allocation of DGs resolves various problems namely,power loss,voltage profile improvement,enhanced reliability,system stability,and performance.Several research works have been conducted to address the distribution system problems in terms of power loss,energy loss,voltage profile,and voltage stability depending upon optimal DG distribution.With this motivation,the current study designs a Chaotic Artificial Flora Optimization based on Optimal Placement and Sizing of DGs(CAFO-OPSDG)to enhance the voltage profiles and mitigate the power loss.Besides,the CAFO algorithm is derived from the incorporation of chaos theory concept into conventional artificial flora optimization AFO algorithm with an aim to enhance the global optimization abilities.The fitness function of CAFO-OPSDG algorithm involves voltage regulation,power loss minimization,and penalty cost.To consider the actual power system scenario,the penalty factor acts as an important element not only to minimize the total power loss but to increase the voltage profiles as well.The experimental validation of the CAFO-OPSDG algorithm was conducted against IEEE 33 Bus system and IEEE 69 Bus system.The outcomes were examined under various test scenarios.The results of the experiment established that the presented CAFO-OPSDG model is effective in terms of reducing the power loss and voltage deviation and boost-up the voltage profile for the specified system.

Optimal Placement of Phasor Measurement Unit in Smart Grids Considering Multiple Constraints

The distribution of measurement noise is usually assumed to be Gaussian in the optimal phasor measurement unit(PMU)placement(OPP)problem.However,this is not always accurate in practice.This paper proposes a new OPP method for smart grids in which the effects of conventional measurements,limited channels of PMUs,zero-injection buses(ZIBs),single PMU loss contingency,state estimation error(SEE),and the maximum SEE variance(MSEEV)are considered.The SEE and MSEEV are both obtained using a robust t-distribution maximum likelihood estimator(MLE)because t-distribution is more flexible for modeling both Gaussian and non-Gaussian noises.The A-and G-optimal experimental criteria are utilized to form the SEE and MSEEV constraints.This allows the optimization problem to be converted into a linear objective function subject to linear matrix inequality observability constraints.The performance of the proposed OPP method is verified by the simulations of the IEEE 14-bus,30-bus,and 118-bus systems as well as the 211-bus practical distribution system in China.

Ruppert's Delaunay Triangulation Refinement Scheme for Optimal RSUs Placement in Vehicle to Infrastructure Communication Network

Road Side Units(RSUs)are the essential component of vehicular communication for the objective of improving safety and mobility in the road transportation.RSUs are generally deployed at the roadside and more specifically at the intersections in order to collect traffic information from the vehicles and disseminate alarms and messages in emergency situations to the neighborhood vehicles cooperating with the network.However,the development of a predominant RSUs placement algorithm for ensuring competent communication in VANETs is a challenging issue due to the hindrance of obstacles like water bodies,trees and buildings.In this paper,Ruppert’s Delaunay Triangulation Refinement Scheme(RDTRS)for optimal RSUs placement is proposed for accurately estimating the optimal number of RSUs that has the possibility of enhancing the area of coverage during data communication.This RDTRS is proposed by considering the maximum number of factors such as global coverage,intersection popularity,vehicle density and obstacles present in the map for optimal RSUs placement,which is considered as the core improvement over the existing RSUs optimal placement strategies.It is contributed for deploying requisite RSUs with essential transmission range for maximal coverage in the convex map such that each position of the map could be effectively covered by at least one RSU in the presence of obstacles.The simulation experiments of the proposed RDTRS are conducted with complex road traffic environments.The results of this proposed RDTRS confirmed its predominance in reducing the end-to-end delay by 21.32%,packet loss by 9.38%with improved packet delivery rate of 10.68%,compared to the benchmarked schemes.

Optimal placement of distributed generation units in distribution systems via an enhanced multi-objective particle swarm optimization algorithm

This paper deals with the optimal placement of distributed generation(DG) units in distribution systems via an enhanced multi-objective particle swarm optimization(EMOPSO) algorithm. To pursue a better simulation of the reality and provide the designer with diverse alternative options, a multi-objective optimization model with technical and operational constraints is constructed to minimize the total power loss and the voltage fluctuation of the power system simultaneously. To enhance the convergence of MOPSO, special techniques including a dynamic inertia weight and acceleration coefficients have been integrated as well as a mutation operator. Besides, to promote the diversity of Pareto-optimal solutions, an improved non-dominated crowding distance sorting technique has been introduced and applied to the selection of particles for the next iteration. After verifying its effectiveness and competitiveness with a set of well-known benchmark functions, the EMOPSO algorithm is employed to achieve the optimal placement of DG units in the IEEE 33-bus system. Simulation results indicate that the EMOPSO algorithm enables the identification of a set of Pareto-optimal solutions with good tradeoff between power loss and voltage stability. Compared with other representative methods, the present results reveal the advantages of optimizing capacities and locations of DG units simultaneously, and exemplify the validity of the EMOPSO algorithm applied for optimally placing DG units.

Optimal sensor placement in hydropower house based on improved triaxial effective independence method

The capacity and size of hydro-generator units are increasing with the rapid development of hydroelectric enterprises, and the vibration of the powerhouse structure has increasingly become a major problem. Field testing is an important method for research on dynamic identification and vibration mechanisms. Research on optimal sensor placement has become a very important topic due to the need to obtain effective testing information from limited test resources. To overcome inadequacies of the present methods, this paper puts forward the triaxial effective independence driving-point residue （EfI3-DPR3） method for optimal sensor placement. The Efl3-DPR3 method can incorporate both the maximum triaxial modal kinetic energy and linear independence of the triaxial target modes at the selected nodes. It was applied to the optimal placement oftriaxial sensors for vibration testing in a hydropower house, and satisfactory results were obtained. This method can provide some guidance for optimal placement of triaxial sensors of underground powerhouses.

Optimal Placement and Sizing of Renewable Distributed Generation Using Hybrid Metaheuristic Algorithm

The problem of optimal placement and sizing(OPS) of renewable distributed generation(RDG) is followed by numerous technical, economical, geographical, and ecological constraints. In this paper, it is investigated from two viewpoints, namely the simultaneous minimization of total energy loss of a distribution network and the maximization of profit for RDG owner. The stochastic nature of RDG such as the wind turbine and photovoltaic generation is accounted using suitable probabilistic models. To solve this problem, a hybrid metaheuristic algorithm is proposed, which is a combination of the phasor particle swarm optimization and the gravitational search algorithm. The proposed algorithm is tested on an IEEE69-bus system for several cases in two scenarios. The results obtained by the hybrid algorithm shows that it provides high-quality solution for all cases considered and has better performances for solving the OPS problem compared to other metaheuristic population-based techniques.

Repulsive firefly algorithm-based optimal switching device placement in power distribution systems

To achieve optimal configuration of switching devices in a power distribution system,this paper proposes a repulsive firefly algorithm-based optimal switching device placement method.In this method,the influence of territorial repulsion during firefly courtship is considered.The algorithm is practically applied to optimize the position and quantity of switching devices,while avoiding its convergence to the local optimal solution.The experimental simulation results have showed that the proposed repulsive firefly algorithm is feasible and effective,with satisfying global search capability and convergence speed,holding potential applications in setting value calculation of relay protection and distribution network automation control.

Optimal placement of wind turbines within a wind farm considering multi-directional wind speed using two-stage genetic algorithm

Most wind turbines within wind farms are set up to face a pre-determined wind direction.However,wind directions are intermittent in nature,leading to less electricity production capacity.This paper proposes an algorithm to solve the wind farm layout optimization problem considering multi-angular(MA)wind direction with the aim of maximizing the total power generated on wind farms and minimizing the cost of installation.A twostage genetic algorithm(GA)equipped with complementary sampling and uniform crossover is used to evolve a MA layout that will yield optimal output regardless of the wind direction.In the first stage,the optimal wind turbine layouts for 8 different major wind directions were determined while the second stage allows each of the previously determined layouts to compete and inter-breed so as to evolve an optimal MA wind farm layout.The proposed MA wind farm layout is thereafter compared to other layouts whose turbines have focused site specific wind turbine orientation.The results reveal that the proposed wind farm layout improves wind power production capacity with minimum cost of installation compared to the layouts with site specific wind turbine layouts.This paper will find application at the planning stage of wind farm.

Multi-objective Optimal Trajectory and Placement of a Robot for Cotton Yarns Handling

This study deals with a robot manipulator for yarn bobbin handling in the cotton yarns lattice distortion modification system.The aim is to achieve an operation of yarn bobbin handling with minimal execution time,energy consumption and jerk in motion together.The placement of the robot,in relation to the yarn bobbin stations,is also optimized in conjunction of trajectory optimization.Three possible techniques for building the handling traj'ectory were considered:the quaternion spherical linear interpolation in Cartesian space,the quintic polynomial spline and quintic B-spline in joint space.The genetic algorithm(GA) was used to optimize the trajectories of the robot,with a penalty function to handle nonlinear constraints associated in the robot motion.Two simulations of the optimal trajectory in joint space and the placement of robot were carried out and the results obtained were presented and discussed.It is concluded that the quintic polynomial spline constructs a better trajectory in joint space and the proper placement of robot makes better performance.

Optimal sensor placement for structural response estimation

A methodology, termed estimation error minimization(EEM) method, was proposed to determine the optimal number and locations of sensors so as to better estimate the vibration response of the entire structure. Utilizing the limited sensor measurements, the entire structure response can be estimated based on the system equivalent reduction-expansion process(SEREP) method. In order to compare the capability of capturing the structural vibration response with other optimal sensor placement(OSP) methods, the effective independence(EI) method, modal kinetic energy(MKE) method and modal assurance criterion(MAC) method, were also investigated. A statistical criterion, root mean square error(RMSE), was employed to assess the magnitude of the estimation error between the real response and the estimated response. For investigating the effectiveness and accuracy of the above OSP methods, a 31-bar truss structure is introduced as a simulation example. The analysis results show that both the maximum and mean of the RMSE value obtained from the EEM method are smaller than those from other OSP methods, which indicates that the optimal sensor configuration obtained from the EEM method can provide a more accurate estimation of the entire structure response compared with the EI, MKE and MAC methods.

Achieving Effective Power System Observability in Optimal PMUs Placement Using GA-EHBSA

Normally, the power system observation is carried out for the optimal PMUs placement with minimum use of unit in the region of the Smart power grid system. By advanced tool, the process of protection and management of the power system is considered with the measurement of time-synchronized of the voltage and current. In order to have an efficient placement solution for the issue, a novel method is needed with the optimal approach. For complete power network observability of PMU optimal placement a new method is implemented. However, the process of placement and connection of the buses is considered at various places with the same cost of installation. GA based Enhanced Harmony and Binary Search Algorithm (GA-EHBSA) is proposed and utilized with the improvement to have least PMU placement and better optimization approach for finding the optimal location. To evaluate the optimal placement of PMUs the proposed approach is implemented in the standard test systems of IEEE 14-bus, IEEE 24-bus, IEEE 30-bus, IEEE 39-bus and IEEE 57-bus. The simulation results are evaluated and compared with existing algorithm to show the efficient process of optimal PMUs placement with better optimization, minimum cost and redundancy than the existing.

Novel Method for Optimal Location of STATCOM in Distribution Systems Using Sensitivity Analysis by DIgSILENT Software

In this paper a new method has been proposed to decide optimal placement and best sizing of STATCOM （static synchronous compensator）. The best place of STATCOM is found using the sensitivity analysis and optimum sizing of STATCOM is managed using the genetic algorithm. The average model can account for the high-frequency effects and power electronic losses, and more accurately predict the active and reactive power outputs of the STATCOM. This paper employs the DIgSILENT simulator and DPL （DIgSILENT programming language） as a programming tool of the DIgSILENT to show the validity of the proposed method. The effectiveness of suggested approach has been tested on part of the distribution network of Iran, Khoramdarreh city in Zanjan province.

Placement Optimization of Caching UAV-Assisted Mobile Relay Maritime Communication

Recently, due to the deployment flexibility of unmanned aerial vehicles(UAVs), UAV-assisted mobile relay communication system has been widely used in the maritime communication. However, the performance of UAV-assisted mobile relay communication system is limited by the capacity of wireless backhaul link between base station and UAV. In this paper, we consider a caching UAV-assisted decode-and-forward relay communication system in a downlink maritime communication. For the general case with multiple users, the optimal placement of UAV is obtained by solving the average achievable rate maximization problem through the one-dimensional linear search. For a special case with single user, we derive a semi closedform expression of the optimal placement of UAV. Simulation results confirm the accuracy of analytical results and show that the optimal placement of UAV and the average achievable rate significantly depend on the cache capacity at UAV. We also show the difference between the performances of the air-to-ground model and the air-to-sea model.

A global harmony search algorithm for finding optimal capacitor location and size in distribution networks

Shunt capacitors are broadly applied in distribution systems to scale down power losses, improve voltage profile and boost system capacity. The amount of capacitors added and location of deployment in the system highly determine the advantage of compensation. A novel global harmony search(GHS) algorithm in parallel with the backward/ forward sweep power flow technique and radial harmonic power flow was used to investigate the optimal placement and sizing of capacitors in radial distribution networks for minimizing power loss and total cost by taking account load unbalancing, mutual coupling and harmonics. The optimal capacitor placement outcomes show that the GHS algorithm can reduce total power losses up to 60 k W and leads to more than 18% of cost saving. The results also demonstrate that the GHS algorithm is more effective in minimization of power loss and total costs compared with genetic algorithm(GA), particle swarm optimization(PSO) and harmony search(HS) algorithm. Moreover, the proposed algorithm converges within 800 iterations and is faster in terms of computational time and gives better performance in finding optimal capacitor location and size compared with other optimization techniques.

Multi-type sensor placement and response reconstruction for building structures: Experimental investigations

Estimation of lateral displacement and acceleration responses is essential to assess safety and serviceability of high-rise buildings under dynamic loadings including earthquake excitations. However, the measurement information from the limited number of sensors installed in a building structure is often insufficient for the complete structural performance assessment. An integrated multi-type sensor placement and response reconstruction method has thus been proposed by the authors to tackle this problem. To validate the feasibility and effectiveness of the proposed method, an experimental investigation using a cantilever beam with multi-type sensors is performed and reported in this paper. The experimental setup is first introduced. The finite element modelling and model updating of the cantilever beam are then performed. The optimal sensor placement for the best response reconstruction is determined by the proposed method based on the updated FE model of the beam. After the sensors are installed on the physical cantilever beam, a number of experiments are carried out. The responses at key locations are reconstructed and compared with the measured ones. The reconstructed responses achieve a good match with the measured ones, manifesting the feasibility and effectiveness of the proposed method. Besides, the proposed method is also examined for the cases of different excitations and unknown excitation, and the results prove the proposed method to be robust and effective. The superiority of the optimized sensor placement scheme is finally demonstrated through comparison with two other different sensor placement schemes： the accelerometer-only scheme and non-optimal sensor placement scheme. The proposed method can be applied to high-rise buildings for seismic performance assessment.

Joint Placement and Resource Allocation for UAV?Assisted Mobile Edge Computing Networks with URLLC

This paper investigates an unmanned aerial vehicle (UAV) assisted mobile edge computing (MEC) network with ultra-reliable and low-latency communications (URLLC), in which a UAV acts as an aerial edge server to collect information from a set of sensors and send the processed data (e.g., command signals) to the corresponding actuators. In particu?lar, we focus on the round-trip URLLC from the sensors to the UAV and to the actuators in the network. By considering the finite block-length codes, our objective is to minimize the maximum end-to-end packet error rate (PER) of these sensor-actuator pairs, by jointly opti?mizing the UAV's placement location and transmitting power allocation, as well as the us?ers'block-length allocation, subject to the UAV's sum transmitting power constraint and the total block-length constraint. Although the maximum-PER minimization problem is non-convex and difficult to be optimally solved, we obtain a high-quality solution to this problem by using the technique of alternating optimization. Numerical results show that our proposed design achieves significant performance gains over other benchmark schemes without the joint optimization.

Ideal Drift Response Curve for Robust Optimal Damper Design for Elastic-Plastic MDOF Structures under Multi-Level Earthquakes Dedicated to Professor Karl S.Pister for his 95th birthday

A new method of robust damper design is presented for elastic-plastic multi-degree-of-freedom(MDOF)building structures under multi-level ground motions(GMs).This method realizes a design that is effective for various levels of GMs.The robustness of a design is measured by an incremental dynamic analysis(IDA)curve and an ideal drift response curve(IDRC).The IDRC is a plot of the optimized maximum deformation under a constraint on the total damper quantity vs.the design level of the GMs.The total damper quantity corresponds to the total cost of the added dampers.First,a problem of generation of IDRCs is stated.Then,its solution algorithm,which consists of the sensitivity-based algorithm(SBA)and a local search method,is proposed.In the application of the SBA,the passive added dampers are removed sequentially under the specified-level GMs.On the other hand,the proposed local search method can search the optimal solutions for a constant total damper quantity under GMs’increased levels.In this way,combining these two algorithms enables the comprehensive search of the optimal solutions for various conditions of the status of the GMs and the total damper quantity.The influence of selecting the type of added dampers(oil,hysteretic,and so on)and the selection of the input GMs on the IDRCs are investigated.Finally,a robust optimal design problem is formulated,and a simple local search-based algorithm is proposed.A simple index using the IDRC and the IDA curve of the model is used as the objective function.It is demonstrated that the proposed algorithm works well in spite of its simplicity.