Location and Capacity Determination Method of Electric Vehicle Charging Station Based on Simulated Annealing Immune Particle Swarm Optimization

As the number of electric vehicles(EVs)continues to grow and the demand for charging infrastructure is also increasing,how to improve the charging infrastructure has become a bottleneck restricting the development of EVs.In other words,reasonably planning the location and capacity of charging stations is important for development of the EV industry and the safe and stable operation of the power system.Considering the construction and maintenance of the charging station,the distribution network loss of the charging station,and the economic loss on the user side of the EV,this paper takes the node and capacity of charging station planning as control variables and the minimum cost of system comprehensive planning as objective function,and thus proposes a location and capacity planning model for the EV charging station.Based on the problems of low efficiency and insufficient global optimization ability of the current algorithm,the simulated annealing immune particle swarm optimization algorithm(SA-IPSO)is adopted in this paper.The simulated annealing algorithm is used in the global update of the particle swarm optimization(PSO),and the immune mechanism is introduced to participate in the iterative update of the particles,so as to improve the speed and efficiency of PSO.Voronoi diagram is used to divide service area of the charging station,and a joint solution process of Voronoi diagram and SA-IPSO is proposed.By example analysis,the results show that the optimal solution corresponding to the optimisation method proposed in this paper has a low overall cost,while the average charging waiting time is only 1.8 min and the charging pile utilisation rate is 75.5%.The simulation comparison verifies that the improved algorithm improves the operational efficiency by 18.1%and basically does not fall into local convergence.

Determining effective criteria for the selection of MDF industry locations in Mazandaran Province: Application of AHP

Selecting the optimum location with attention to conditions and restrictions is one of the most importantfactors in establishing a manufacturing plant. Identification of effective criteria is an important stage in the selection for the location of industrial units. In this study, an analytic hierarchy process （AHP） was applied to select the most effective criteria for the location of MDF （medium density fiberboard） industry in Mazandaran Province, Iran. A consideration in ttaining this goal is that Mazandaran is favored over other provinces because of its resources of raw lignocellulosic ma- erial required for wood and paper industries. The results indicate that the criterion of ＂materials and products＂ and the ub-criterion of ＂reliability of supply of raw material＂ are the most important factors.

Evaluation of alternative criteria for determining the optimal location of RWIS stations

This article presents a comprehensive framework for determining the location of road weather information system （RWIS） stations over a regional road network. In the proposed methodology, the region is divided into a grid of equal-sized zones which are considered as the minimum spatial unit for allocating a candidate set of RWIS stations. These zones are ranked according to a set of pre-specified criteria that reflect the needs for, and potential benefits from, real-time RWIS, including road surface temperature variability, precipitation, network traffic, and collision patterns. A case study based on the existing RWIS network in the province of Ontario was conducted to illustrate the major features of the proposed method and evaluate the implications of alternative loca- tion selection criteria. The findings of the study suggest that it is feasible to develop a systematic process for locating RWIS stations using an integrated location criterion to capture multiple factors being considered in prac- tice. The study has also revealed the need to establish quantitative models for estimating the benefit of real-time information from RWIS stations, which is the foundation of a cost-benefit-based RWIS location optimization model.

Classification and Location Scheme Selection of Coupling Components in Integrated Electrical and Heating Systems with Renewable Energy

Integrated energy systems(IES)are under development to accommodate the widespread penetration of renewable energy into power systems.The universal utilization of coupling components makes the connection between power grids and heat grids even closer.This paper applies energy flow calculations to planning problems and explores a method for selecting coupling components in the integrated electrical and heating systems.This process is based on the analysis of energy flow distribution and the comprehensive indexes,which include operation cost and the penalty cost of wind curtailment and solar energy curtailment.Besides,a selection method of coupling components installation locations based on energy flow calculations is provided.At last,an IES with 5 electrical buses and 5 heating nodes,and a 9-bus electrical power system with a 31-node heating transmission system are chosen to study the specific application problems in detail as well as to elucidate the effectiveness of the proposed method.It turned out that the relevant coupling components and their positions can be selected according to the indexes obtained by integrated electrical-hydraulic-thermal calculation.This proposed method is conducive to the planning of integrated energy systems.

Selection of PCEs' location in multi-domain optical networks

Path computation elements （PCEs） are employed to compute end-to-end paths across multi-domain optical networks due to the advantages of powerful computation capability. However, PCEs＇ location selection is still an open problem which is closely related to the communication overhead. This paper mainly focuses on the problem of PCEs＇ location selection to minimize the overall communication overhead in the control plane. The problem is formulated as a quadratic integer programming （QIP） model, and an optimal decision rule is gained from the solution of the QIP model. Then based on the decision rule, a distributed heuristic algorithm is proposed for dynamic network scenario. Simulation results demonstrate the benefit and the effectiveness of our proposed approach by comparing it with random selection policy.

Combining data envelopment analysis and Random Forest for selectingoptimal locations of solar PV plants

Solar photovoltaic (PV) energy has emerged as a potential alternative to carbon-based energies to meet theParis agreement commitment. This study investigates the effect of environmental variables on the efficiencyof solar PV panels. Data Envelopment Analysis (DEA) is used to estimate efficiencies of 91 solar PV panelslocated in Australia during the time period 2010–2020. The effects of environmental variables on the estimatedefficiencies are quantified using the truncated regression model. Random forest is then used to predict efficiencyof solar PV panel in every city of Australia. The results allow to determine the most suitable location and regions for solar PV energy production in Australia. This study provides an interesting and easily interpretabletool for policy decision makers.

Location optimization of multiple distribution centers under fuzzy environment

Locating distribution centers optimally is a crucial and systematic task for decision-makers.Optimally located distribution centers can significantly improve the logistics system's efficiency and reduce its operational costs.However,it is not an easy task to optimize distribution center locations and previous studies focused primarily on location optimization of a single distribution center.With growing logistics demands,multiple distribution centers become necessary to meet customers' requirements,but few studies have tackled the multiple distribution center locations(MDCLs) problem.This paper presents a comprehensive algorithm to address the MDCLs problem.Fuzzy integration and clustering approach using the improved axiomatic fuzzy set(AFS) theory is developed for location clustering based on multiple hierarchical evaluation criteria.Then,technique for order preference by similarity to ideal solution(TOPSIS) is applied for evaluating and selecting the best candidate for each cluster.Sensitivity analysis is also conducted to assess the influence of each criterion in the location planning decision procedure.Results from a case study in Guiyang,China,reveals that the proposed approach developed in this study outperforms other similar algorithms for MDCLs selection.This new method may easily be extended to address location planning of other types of facilities,including hospitals,fire stations and schools.

Research on reference nodes placement and selection of ubiquitous computing locating service

Obtaining the location of an unknown node accurately is a key problem of a locating service under a ubiquitous computing environment.The paper proposes and proves three theorems of location reference node placement according to the analysis of the location error produced during location using a polygon location method and three important characteristics of chaos dynamics.Based on the three theorems,the location reference node selection(LRNS)algorithm is proposed by improving on the traditional polygon location algorithm.The simulation results indicate that the reference node placement theorems and the LRNS algo-rithm can meet the requirements of a ubiquitous terminal’s real-time location and possess a preferable precision in location.

PREPARATION OF COMPOSITE MAGNETIC MICROSPHERES BY REACTIVE BLENDING

A novel method for preparation of polymer-based magnetic microspheres was proposed by utilizing melt reactive blending, which was based on selective location of Fe3O4 nanoparticles in PA6 domains of polystyrene （PS）/polyamide 6 （PA6） immiscible blends. The morphology of PA6/Fe3O4 composite magnetic mierospheres was studied by scanning electronic microscopy （SEM）. The composite magnetic mierospheres were spherical with a diameter range of 0.5-8 μm; the diameter was sharply decreased with a very narrow distribution by adding terminal maleic anhydride fimctionalized polystyrenes （FPS） for reactive blending. Transmission electron microscopy （TEM） and thermogravimetry analysis （TGA） results showed that most of Fe3O4 was located in the PA6 microspheres. Magnetization data revealed the magnetite content of PA6/Fe3O4 microspheres was about 32 wt% and the saturation magnetization could be up to 17.2 AmE/kg.