Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

A Distributed Power Planning Method Based on Improved Orthogonal Optimization Swarm Intelligence Algorithm

A technology of distributed power supply and swarm intelligence algorithm, applied in the direction of AC network circuits, electrical components, circuit devices, etc., can solve the problem of not fully utilizing the orthogonal design search function, etc., to reduce the amount of optimization search calculation, improve efficiency and usability , The effect of reducing the system voltage offset

Active Publication Date: 2020-04-24
CHINA THREE GORGES UNIV
View PDF3 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Scholars have proposed many improved heuristic intelligent algorithms, and the search for the optimal solution interval is realized by designing orthogonal experiments, such as the orthogonal genetic algorithm, the cellular differential evolution algorithm of the orthogonal crossover operator, and the orthogonal immune cloning particle swarm optimization algorithm. etc., but these algorithms only design orthogonal experiments in the population initialization process, and do not fully utilize the search function of orthogonal design

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • A Distributed Power Planning Method Based on Improved Orthogonal Optimization Swarm Intelligence Algorithm
  • A Distributed Power Planning Method Based on Improved Orthogonal Optimization Swarm Intelligence Algorithm
  • A Distributed Power Planning Method Based on Improved Orthogonal Optimization Swarm Intelligence Algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0094] Take the IEEE14 node network system as an example:

[0095] According to the distributed power planning mathematical model proposed by the present invention and the improved orthogonal optimization group intelligence algorithm, the IEEE14 node power distribution system is simulated by MATLAB, and its power distribution network structure is as follows figure 1 As shown, the value per unit is 100MVA, the voltage of each node is 0.97~1.1 times the reference voltage, and the total load of the system is 259.9MW+73.5Mvar. Treat the distributed power supply as an ordinary PQ point, and set node 1 as a balance node. In the fuzzy comprehensive evaluation of the multi-objective model, the weights of active network loss, voltage offset, investment and operating costs are 1 / 2, 3 / 8, and 1 / 8, respectively. The planning of distributed power generation is shown in Table 2.

[0096] Table 2 Distributed power supply installation location and installation capacity

[0097]

[0098] ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

A distributed power supply planning method based on an improved orthogonal optimization swarm intelligence algorithm comprises the steps of building a multi-target optimization model by taking active power loss, investment running cost and load point voltage deviation quantity of a system as optimization indexes; initializing original data of an input node network; building an initial orthogonal table L(b<c>), and calculating a local optimal value of the orthogonal table; and calculating a variance proportion Rho of each variable in variance analysis of the orthogonal table, building a new orthogonal table according to the variance proportion, and repeatedly performing iterative optimization until an optimal solution is found. The distributed power supply planning method based on the improved orthogonal optimization swarm intelligence algorithm have obvious effects of reducing active power loss and system voltage deviation quantity during distributed power supply planning, a search direction and a search range of further orthogonal optimization are provided according to the variance proportion analysis, so that the search optimization calculation quantity and the search time are reduced, and the efficiency and the availability of a configuration optimization algorithm of a microgrid are improved.

Description

technical field [0001] The invention relates to a distributed power supply planning method based on an improved orthogonal optimization group intelligent algorithm, and relates to the field of micro-grid planning. Background technique [0002] With the accelerated development of the global economy, energy shortages and environmental pollution have become huge challenges facing society today. Due to the continuous growth of power load, the aging of the power system structure, the bottleneck of energy utilization efficiency, the user's requirements for high-standard power quality, and environmental protection issues, it is urgent to develop clean and non-polluting renewable energy power generation methods as an effective alternative to traditional centralized power generation. Supplementary, distributed power generation technology came into being. Distributed power generation refers to a system in which the power generation system is arranged in a small-scale (small-scale mod...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Patents(China)
IPC IPC(8): H02J3/38
CPCH02J3/381H02J2203/20
Inventor 黄雄峰张宇娇郭梽炜普子恒姜岚苏攀智李
Owner CHINA THREE GORGES UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products