The path planning scheme for joint charging and data collection in WRSNs: A multi-objective optimization method

Wei, Zhenchun; Xia, Chengkai; Yuan, Xiaohui; Sun, Renhao; Lyu, Zengwei; Shi, Lei; Ji, Jianjun

doi:10.1016/j.jnca.2020.102565

Title: The path planning scheme for joint charging and data collection in WRSNs: A multi-objective optimization method

Full Record
Other Related Research

Authors:: Wei, Zhenchun; Xia, Chengkai; Yuan, Xiaohui; Sun, Renhao; Lyu, Zengwei; Shi, Lei; Ji, Jianjun

Publication Date:: 2020-04-01

Sponsoring Org.:: USDOE Office of Electricity (OE), Advanced Grid Research & Development. Power Systems Engineering Research

OSTI Identifier:: 1698149

Grant/Contract Number:: 201904a07020030

Resource Type:: Publisher's Accepted Manuscript

Journal Name:: Journal of Network and Computer Applications

Additional Journal Information:: Journal Name: Journal of Network and Computer Applications Journal Volume: 156 Journal Issue: C; Journal ID: ISSN 1084-8045

Publisher:: Elsevier

Country of Publication:: United States

Language:: English

Citation Formats


                    Wei, Zhenchun, Xia, Chengkai, Yuan, Xiaohui, Sun, Renhao, Lyu, Zengwei, Shi, Lei, and Ji, Jianjun. The path planning scheme for joint charging and data collection in WRSNs: A multi-objective optimization method.  United States: N. p., 2020. 
Web.  doi:10.1016/j.jnca.2020.102565.

Copy to clipboard


                    Wei, Zhenchun, Xia, Chengkai, Yuan, Xiaohui, Sun, Renhao, Lyu, Zengwei, Shi, Lei, & Ji, Jianjun. The path planning scheme for joint charging and data collection in WRSNs: A multi-objective optimization method.  United States.  https://doi.org/10.1016/j.jnca.2020.102565

Copy to clipboard


                    Wei, Zhenchun, Xia, Chengkai, Yuan, Xiaohui, Sun, Renhao, Lyu, Zengwei, Shi, Lei, and Ji, Jianjun. Wed .  
"The path planning scheme for joint charging and data collection in WRSNs: A multi-objective optimization method".  United States.  https://doi.org/10.1016/j.jnca.2020.102565.

Copy to clipboard


                    
@article{osti_1698149,

  title        = {The path planning scheme for joint charging and data collection in WRSNs: A multi-objective optimization method},

  author       = {Wei, Zhenchun and Xia, Chengkai and Yuan, Xiaohui and Sun, Renhao and Lyu, Zengwei and Shi, Lei and Ji, Jianjun},

  abstractNote = {},

  doi          = {10.1016/j.jnca.2020.102565},

  journal      = {Journal of Network and Computer Applications},

  number       = C,

  volume       = 156,

  place        = {United States},

  year         = {2020},

  month        = {4}

}

Copy to clipboard

Journal Article:

Free Publicly Available Full Text

Accepted Manuscript (Publisher)

Publisher's Version of Record
https://doi.org/10.1016/j.jnca.2020.102565

Other availability

Search WorldCat to find libraries that may hold this journal

Save / Share:

Export Metadata

Save to My Library

Similar Records in DOE PAGES and OSTI.GOV collections:

Optimal multi-objective VAR planning using an interactive satisfying method

Journal Article Chen, Y L ; Liu, C C - IEEE Transactions on Power Systems

In this paper, an interactive satisfying method, a two-level structure, is presented for solving a multi-objective VAR planning problem. In this structure, the analysis level is concerned with the calculation of a possible or a set of possible solutions to the multi-objective problem, and the decision level s concentrated on the task of inducing the analysis level to generate noninferior solutions that meet the decision makers` preferences. On the analysis level, the {epsilon}-constraint method based on the Simulated Annealing (SA) approach is developed to find a global noninferior solution. Through interaction with the decisionmaker (DM), the proposed method guarantees themore »« less
https://doi.org/10.1109/59.387901
Joint Optimization Scheme for the Planning and Operations of Shared Autonomous Electric Vehicle Fleets Serving Mobility on Demand

Journal Article Sheppard, Colin J. R. ; Bauer, Gordon S. ; Gerke, Brian F. ; ... - Transportation Research Record

As the transportation sector undergoes three major transformations—electrification, shared/on-demand mobility, and automation—there are new challenges to analyzing the impacts of these trends on both the transportation system and the power sector. Most models that analyze the requirements of fleets of shared autonomous electric vehicles (SAEVs) operate at the scale of an urban region, or smaller. A quadratically constrained, quadratic programming problem is formulated, designed to model the requirements of SAEVs at a national scale. The size of the SAEV fleet, the necessary charging infrastructure, the fleet charging schedule, and the dispatch required to serve demand for trips in a region are treated as decision variables. By minimizing both the amortized cost of the fleet and chargers as well as the operational costs of charging, it is possible to explore the coupled interactions between system design and operation. To apply the model at a national scale, key complications about fleet operations are simplified; but a detailed agent-based regional simulation model to parameterize those simplifications is leveraged. Preliminary results are presented, finding that all mobility in the United States (U.S.) currently served by 276 million personally owned vehicles could be served by 12.5 million SAEVs at a cost ofmore »« less
Cited by 1
https://doi.org/10.1177/0361198119838270

Full Text Available
A computer package for optimal multi-objective VAR planning in large scale power systems

Journal Article Chiang, H D ; Liu, C C ; Chen, Y L ; ... - IEEE Transactions on Power Systems (Institute of Electrical and Electronics Engineers); (United States)

This paper presents a simulated annealing based computer package for multi-objective, VAR planning in large scale power systems - SAMVAR. This computer package has three distinct features. First, the optimal VAR planning is reformulated as a constrained, multi-objective, non-differentiable optimization problem. The new formulation considers four different objective functions related to system investment, system operational efficiency, system security and system service quality. The new formulation also takes into consideration load, operation and contingency constraints. Second, it allows both the objective functions and equality and inequality constraints to be non-differentiable; making the problem formulation more realistic. Third, the package employs amore »« less
Weak bus-oriented optimal multi-objective VAR planning

Journal Article Chen, Y L - IEEE Transactions on Power Systems

This paper presents a weak bus-oriented criterion to determine the candidate buses for installing new VAR sources in the VAR planning problem. First, an efficient method, using a voltage collapse proximity indicator, is described for identifying weak buses. Then appropriate VAR planning in those weak buses can enhance the system security margin, in particular, to prevent voltage collapse. Next, the goal attainment (GA) method based on the Simulated Annealing (SA) approach is applied to solving general multi-objective VAR planning problems by assuming that the decisionmaker (DM) has goals for each of the objective functions. The presented method can both obtainmore »« less
https://doi.org/10.1109/59.544659
Multi-Objective Optimization Technique for the Operation of Grid tied PV Powered EV Charging Station

Journal Article Eldeeb, Hassan H. ; Faddel, Samy ; Mohammed, Osama A. - Electric Power Systems Research
https://doi.org/10.1016/j.epsr.2018.08.004

Similar Records