Distributed collaborative complete coverage path planning based on hybrid strategy

Collaborative coverage path planning(CCPP) refers to obtaining the shortest paths passing over all places except obstacles in a certain area or space. A multi-unmanned aerial vehicle(UAV) collaborative CCPP algorithm is proposed for the urban rescue search or military search in outdoor environment.Due to flexible control of small UAVs, it can be considered that all UAVs fly at the same altitude, that is, they perform search tasks on a two-dimensional plane. Based on the agents’ motion characteristics and environmental information, a mathematical model of CCPP problem is established. The minimum time for UAVs to complete the CCPP is the objective function, and complete coverage constraint, no-fly constraint, collision avoidance constraint, and communication constraint are considered. Four motion strategies and two communication strategies are designed. Then a distributed CCPP algorithm is designed based on hybrid strategies. Simulation results compared with patternbased genetic algorithm(PBGA) and random search method show that the proposed method has stronger real-time performance and better scalability and can complete the complete CCPP task more efficiently and stably.

Correlation knowledge extraction based on data mining for distribution network planning

Traditional distribution network planning relies on the professional knowledge of planners,especially when analyzing the correlations between the problems existing in the network and the crucial influencing factors.The inherent laws reflected by the historical data of the distribution network are ignored,which affects the objectivity of the planning scheme.In this study,to improve the efficiency and accuracy of distribution network planning,the characteristics of distribution network data were extracted using a data-mining technique,and correlation knowledge of existing problems in the network was obtained.A data-mining model based on correlation rules was established.The inputs of the model were the electrical characteristic indices screened using the gray correlation method.The Apriori algorithm was used to extract correlation knowledge from the operational data of the distribution network and obtain strong correlation rules.Degree of promotion and chi-square tests were used to verify the rationality of the strong correlation rules of the model output.In this study,the correlation relationship between heavy load or overload problems of distribution network feeders in different regions and related characteristic indices was determined,and the confidence of the correlation rules was obtained.These results can provide an effective basis for the formulation of a distribution network planning scheme.

Research on Grid Planning of Dual Power Distribution Network Based on Parallel Ant Colony Optimization Algorithm

A distribution network plays an extremely important role in the safe and efficient operation of a power grid.As the core part of a power grid’s operation,a distribution network will have a significant impact on the safety and reliability of residential electricity consumption.it is necessary to actively plan and modify the distribution network’s structure in the power grid,improve the quality of the distribution network,and optimize the planning of the distribution network,so that the network can be fully utilized to meet the needs of electricity consumption.In this paper,a distribution network grid planning algorithm based on the reliability of electricity consumption was completed using ant colony algorithm.For the distribution network structure planning of dual power sources,the parallel ant colony algorithm was used to prove that the premise of parallelism is the interactive process of ant colonies,and the dual power distribution network structure model is established based on the principle of the lowest cost.The artificial ants in the algorithm were compared with real ants in nature,and the basic steps and working principle of the ant colony optimization algorithm was studied with the help of the travelling salesman problem(TSP).Then,the limitations of the ant colony algorithm were analyzed,and an improvement strategy was proposed by using python for digital simulation.The results demonstrated the reliability of model-building and algorithm improvement.

Distribution network planning based on shortest path

In order to form an algorithm for distribution network routing,an automatic routing method of distribution network planning was proposed based on the shortest path.The problem of automatic routing was divided into two steps in the method:the first step was that the shortest paths along streets between substation and load points were found by the basic ant colony algorithm to form a preliminary radial distribution network,and the second step was that the result of the shortest path was used to initialize pheromone concentration and pheromone updating rules to generate globally optimal distribution network.Cases studies show that the proposed method is effective and can meet the planning requirements.It is verified that the proposed method has better solution and utility than planning method based on the ant colony algorithm.

A Novel Model Calculated Distribution Systems Planning Intergrated Distribution Generators for Competitive Electricity Markets

Recently, the distributed generator (DG) has been successfully studied and applied in distribution system at many countries around the world. Many planning models of the DG integrated distribution system have been proposed. These models can choose the optimization locations, capacities and technologies of DG with the objective function minimizing power loss, investment costs or total life cycle costs of the investment project. However, capacity of DG that uses renewable energy resources is natural variability according to primary energy. This study proposed a planning model of optimized distribution system that integrates DG in the competitive electricity market. Model can determine equipment sizing and timeframe requiring for upgrading equipment of distribution system as well as select DG technologies with power variable constraints of DG. The objective function is minimizing total life cycle cost of the investment project. The proposed model is calculated and tested for a 48-bus radial distribution system in the GAMS programming language.

Models and Methods for Urban Power Distribution Network Planning

The models, methods and their application experiences of a practical GIS(geographic information system)-based computer decision-making support system of urban power distribution network planning with seven subsystems,termed CNP,are described.In each subsystem there is at least one or one set of practical mathematical methobs.Some new models and mathematical methods have been introduced.In the development of CNP the idea of cognitive system engineering has been insisted on,which claims that human and computer intelligence should be combined together to solve the complex engineering problems cooperatively.Practical applications have shown that not only the optimal plan can be automatically reached with many complicated factors considered, but also the computation,analysis and graphic drawing burden can be released considerably.

Power Inverted Topp–Leone Distribution in Acceptance Sampling Plans

We introduce a new two-parameter model related to the inverted Topp–Leone distribution called the power inverted Topp–Leone(PITL)distribution.Major properties of the PITL distribution are stated;including;quantile measures,moments,moment generating function,probability weighted moments,Bonferroni and Lorenz curve,stochastic ordering,incomplete moments,residual life function,and entropy measure.Acceptance sampling plans are developed for the PITL distribution,when the life test is truncated at a pre-specified time.The truncation time is assumed to be the median lifetime of the PITL distribution with pre-specified factors.The minimum sample size necessary to ensure the specified life test is obtained under a given consumer’s risk.Numerical results for given consumer’s risk,parameters of the PITL distribution and the truncation time are obtained.The estimation of the model parameters is argued using maximum likelihood,least squares,weighted least squares,maximum product of spacing and Bayesian methods.A simulation study is confirmed to evaluate and compare the behavior of different estimates.Two real data applications are afforded in order to examine the flexibility of the proposed model compared with some others distributions.The results show that the power inverted Topp–Leone distribution is the best according to the model selection criteria than other competitive models.

Acceptance Sampling Plans with Truncated Life Tests for the Length-Biased Weighted Lomax Distribution

In this paper,we considered the Length-biased weighted Lomax distribution and constructed new acceptance sampling plans(ASPs)where the life test is assumed to be truncated at a pre-assigned time.For the new suggested ASPs,the tables of the minimum samples sizes needed to assert a specific mean life of the test units are obtained.In addition,the values of the corresponding operating characteristic function and the associated producer’s risks are calculated.Analyses of two real data sets are presented to investigate the applicability of the proposed acceptance sampling plans;one data set contains the first failure of 20 small electric carts,and the other data set contains the failure times of the air conditioning system of an airplane.Comparisons are made between the proposed acceptance sampling plans and some existing acceptance sampling plans considered in this study based on the minimum sample sizes.It is observed that the samples sizes based on the proposed acceptance sampling plans are less than their competitors considered in this study.The suggested acceptance sampling plans are recommended for practitioners in the field.

Improved Attribute Chain Sampling Plan for Darna Distribution

Recently,the Darna distribution has been introduced as a new lifetime distribution.The two-parameter Darna distribution represents is a mixture of two well-known gamma and exponential distributions.A manufacturer or an engineer of products conducts life testing to examine whether the quality level of products meets the customer’s requirements,such as reliability or the minimum lifetime.In this article,an attribute modified chain sampling inspection plan based on the time truncated life test is proposed for items whose lifetime follows the Darna distribution.The plan parameters,including the sample size,the acceptance number,and the past lot result of the proposed sampling plan,are determined with the help of the two-point approach considering the acceptable quality level(AQL)and the limiting quality level(LQL).The plan parameters and the corresponding operating characteristic functions of a new plan are provided in tabular form for various Darna distribution parameters.Also,a few illustrated examples are presented for various distribution parameters.The usefulness of the proposed attribute modified chain sampling plan is investigated using two real failure time datasets.The results indicate that the proposed sampling plan can reduce the sample size when the termination ratio increases for fixed values of the producer’s risk and acceptance number.Hence,the proposed attribute modified chain sampling inspection plan is recommended to practitioners in the field.

Enhancing Autonomy Capability in Regional Power Grids:A Strategic Planning Approach with Multiple Autonomous Evaluation Indexes

After the integration of large-scale DistributedGeneration(DG)into the distribution network,the randomness and volatility of its output result in a reduction of spatiotemporal alignment between power generation and demand in the distribution network,exacerbating the phenomenon of wind and solar power wastage.As a novel power system model,the fundamental concept of Regional Autonomous Power Grids(RAPGs)is to achieve localized management and energy autonomy,thereby facilitating the effective consumption of DGs.Therefore,this paper proposes a distributed resource planning strategy that enhances the autonomy capabilities of regional power grids by considering multiple evaluation indexes for autonomy.First,a regional Energy Storage(ES)configuration strategy is proposed.This strategy can select a suitable reference value for the upper limit of ES configuration based on the regional load andDGoutput to maximize the elimination of source load deviations in the region as the upper limit constraint of ES capacity.Then,a control strategy for regional ES is proposed,the charging and discharging reference line of ES is set,and multiple autonomy and economic indexes are used as objective functions to select different proportions of ES to control the distributed resources of the regional power grid and establish evaluation indexes of the internal regional generation and load power ratio,the proportion of power supply matching hours,new energy consumption rate and tie line power imbalance outside the region to evaluate changes in the regional autonomy capabilities.The final simulation results showthat in the real regional grid example,the planning method in the planning year in the region of the overall power supply matching hour ratio and new energy consumption rate increased by 3.9%and 4.8%on average,and the power imbalance of the tie line decreased by 7.8%on average.The proposed planning approach enables the maximization of regional autonomy while effectively smoothing the fluctuation of power exchange between the regional grid and the higher-level grid.This presents a rational and effective planning solution for the regional grid,facilitating the coordinated development between the region and the distribution network.

Modeling Simulation Technology Research for Distribution Network Planning

This paper proposes to use the power system simulation software CYME to plan, model and simulate for an actual distribution network for improving the reliability and efficiency, enhancing the efficiency and capacity, simulating the abnormal condition of distribution network, and presenting operation program of safe, reliable and having simulation record statements. The modeling simulation results show that the software module has lots of advantages including high accuracy, ideal reliability, powerful practicality in simulation and analysis of distribution network, it only need to create once model, the model can sufficiently satisfy multifarious types of simulation analysis required for the distribution network planning.

Firepower distribution method of anti-ship missile based on coupled path planning

Anti-ship missile coordinated attack mission planning is a complex multi-objective optimization problem with multiple combinations of platforms, strong decision-making constraints,and tightly coupled links. To avoid the coupling disorder between path planning and firepower distribution and improve the efficiency of coordinated attack mission planning, a firepower distribution model under the conditions of path planning is established from the perspective of decoupling optimization and the algorithm is implemented. First, we establish reference coordinate system of firepower distribution to clarify the reference direction of firepower distribution and divide the area of firepower distribution;then, we construct an index table of membership of firepower distribution to obtain alternative firepower distribution plans;finally, the fitness function of firepower distribution is established based on damage income, missile loss,ratio of efficiency and cost of firepower distribution, and the mean square deviation of the number of missiles used, and the alternatives are sorted to obtain the optimal firepower distribution plan. According to two simulation experiments, the method in this paper can effectively solve the many-to-many firepower distribution problem of coupled path planning. Under the premise of ensuring that no path crossing occurs, the optimal global solution can be obtained, and the operability and timeliness are good.

Distribution network planning algorithm based on Hopfield neural network

This paper presents a new algorithm based on Hopfield neural network to find the optimal solution for an electric distribution network. This algorithm transforms the distribution power network-planning problem into a directed graph-planning problem. The Hopfield neural network is designed to decide the in-degree of each node and is in combined application with an energy function. The new algorithm doesn’t need to code city streets and normalize data, so the program is easier to be realized. A case study applying the method to a district of 29 street proved that an optimal solution for the planning of such a power system could be obtained by only 26 iterations. The energy function and algorithm developed in this work have the following advantages over many existing algorithms for electric distribution network planning: fast convergence and unnecessary to code all possible lines.

Overall Framework and Module of Distribution Network Coordinated Planning Considering Distributed Generation

Combining with the characteristics of China's energy and the strategy of sustainable development, analyzing the pros and cons which caused by the appearance of DG and their operation connecting to grid, this paper points out that the two sides can achieve win-win under a reasonable combination between DG and distribution system, so as to optimize the allocation of resources, improve the utilization ratio of resource, and obtain maximum social benefit, harmoniously promote the development of power industry, economy and environment. As a word, this paper puts forward a new model of distribution network planning including DG and brings in penalty factorto guide the investment and construction of DG. Last of all, this paper presents the adoption of the coordination development coefficients which is to evaluate the power planning.

Distribution Network Equipment Location and Capacity Planning Method Considering Energy Internet Attribute from the Perspective of Life Cycle Cost

For facing the challenges brought by large-scale renewable energy having access to the system and considering the key technologies of energy Internet,it is very necessary to put forward the location method of distribution network equipment and capacity from the perspective of life cycle cost.Compared with the traditional energy network,the equipment capacity problem of energy interconnected distribution network which involves in electricity network,thermal energy network and natural gas network is comprehensively considered in this paper.On this basis,firstly,the operation architecture of energy interconnected distribution network is designed.Secondly,taking the grid connection location and configuration capacity of key equipment in the system as the control variables and the operation cost of system comprehensive planning in the whole life cycle as the goal,the equipment location and capacity optimization model of energy interconnected distribution network is established.Finally,an IEEE 33 bus energy mutual distribution grid system is taken for example analysis,and the improved chaotic particle swarmoptimization algorithm is used to solve it.The simulation results show that the method proposed in this paper is suitable for the equipment location and capacity planning of energy interconnected distribution network,and it can effectively improve the social and economic benefits of system operation.

Research on Distribution Network Automation and Distribution Network Planning Mode

Based on the research of distribution network automation and distribution network planning mode, the analysis of the significance of urban distribution network automation must be performed at the first place. Combined with the problems existing in China’s current distribution network, it is concluded that, establish effective hardware support system, data sharing and feeder automation to ensure automation safety;strengthen power distribution and power line material testing to improve distribution automation system and distribution network planning;research methods of improving the professional skills and comprehensive quality of professionals.

Distribution Network Expansion Planning Based on Multi-objective PSO Algorithm

This paper presents a novel approach for electrical distribution network expansion planning using multi-objective particle swarm optimization (PSO). The optimization objectives are: investment and operation cost, energy losses cost, and power congestion cost. A two-phase multi-objective PSO algorithm is employed to solve this optimization problem, which can accelerate the convergence and guarantee the diversity of Pareto-optimal front set as well. The feasibility and effectiveness of both the proposed multi-objective planning approach and the improved multi-objective PSO have been verified by the 18-node typical system.

Parallel Computing Based Solution for Reliability-constrained Distribution Network Planning

The main goal of distribution network(DN)expansion planning is essentially to achieve minimal investment con-strained by specified reliability requirements.The reliability-constrained distribution network planning(RcDNP)problem can be cast as an instance of mixed-integer linear programming(MILP)which involves ultra-heavy computation burden especially for large-scale DNs.In this paper,we propose a parallel computing based solution method for the RcDNP problem.The RcDNP is decomposed into a backbone grid and several lateral grid problems with coordination.Then,a parallelizable augmented Lagrangian algorithm with acceleration method is developed to solve the coordination planning problems.The lateral grid problems are solved in parallel through coordinating with the backbone grid planning problem.Gauss-Seidel iteration is adopted on the subset of the convex hull of the feasible region constructed by decomposition.Under mild conditions,the optimality and convergence of the proposed method are verified.Numerical tests show that the proposed method can significantly reduce the solution time and make the RcDNP applicable for real-worldproblems.

Cyber-physical Integrated Planning of Distribution Networks Considering Spatial-temporal Flexible Resources

The rapid development of cyber technology and the increase of flexible resources have transformed the distribution network into a cyber-physical distribution system,while the accompanying multidimensional uncertainties have brought new planning challenges.In this paper,an innovative approach is proposed to effectively leverage distributed resources while considering the impact of cyber-physical coupling in distribution network planning.A cyber-physical integrated planning model of the distribution network is proposed,considering the effects of spatial-temporal flexible resources and multi-network coupling.Specifically,a three-layer optimization model is established and analyzed by the simulate anneal-particle swarm optimization algorithm.The upper layer achieves the optimization of the location and configuration of energy storage systems and smart terminal units.The middle layer optimizes the data load migration strategy using spatial-temporal flexible resources to solve the voltage exceeding problem caused by high penetration of distributed power access,while the lower layer optimizes the cyber side communication topology,improving the convergence speed and control performance of the distribution network.Then,the optimization model is analyzed iteratively with objective functions including total planning cost,operation excess loss and distributed control performance.Finally,the effectiveness and economy of the proposed planning scheme is verified and compared to traditional methods.

Optimal Planning of Hybrid AC/DC Low-voltage Distribution Networks Considering DC Conversion of Three-phase Four-wire Low-voltage AC Systems

The increasing integration of distributed household photovoltaics(PVs)and electric vehicles(EVs)may further ag gravate voltage violations and unbalance of low-voltage distribu tion networks(LVDNs).DC distribution networks can increase the accommodation of PVs and EVs and mitigate mutilple pow er quality problems by the flexible power regulation capability of voltage source converters.This paper proposes schemes to es tablish hybrid AC/DC LVDNs considering the conversion of the existing three-phase four-wire low-voltage AC systems to DC op eration.The characteristics and DC conversion constraints of typical LVDNs are analyzed.In addition,converter configura tions for typical LVDNs are proposed based on the three-phase four-wire characteristics and quantitative analysis of various DC configurations.Moreover,an optimal planning method of hybrid AC/DC LVDNs is proposed,which is modeled as a bi-level programming model considering the annual investments and three-phase unbalance.Simulations are conducted to verify the effectiveness of the proposed optimal planning method.Sim ulation results show that the proposed optimal planning method can increase the integration of PVs while simultaneously reduc ing issues related to voltage violation and unbalance.