Multi-target moth algorithm-based small hydropower station optimal scheduling method

A technology for optimal dispatching and hydropower stations, applied in computing, instruments, data processing applications, etc., can solve problems such as incomplete consideration and difficult solutions, and achieve uniform distribution of individuals, good diversity, and accelerated global convergence.

Inactive Publication Date: 2016-11-16
ZHEJIANG UNIV OF TECH
View PDF0 Cites 4 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In recent years, although many gratifying research results have been obtained in the research and practice of reservoir optimal scheduling at home and abroad, the research target has developed from a single reservoir to cascade and cross-basin reservoir groups, and the runoff description has developed from a deterministic description to a random description. This optimization theory, algorithm and optimal dispatching model are also constantly developing, and some aspects are also applied in practice—but as far as the optimal dispatching of rural small hydropower is concerned, since rural small hydropower has different characteristics from those of large rivers and large river basins, whether it is The coverage area of ​​the watershed or the characteristics of hydrology and water conser

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
  • Multi-target moth algorithm-based small hydropower station optimal scheduling method
  • Multi-target moth algorithm-based small hydropower station optimal scheduling method
  • Multi-target moth algorithm-based small hydropower station optimal scheduling method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0038] Example: such as figure 1 , figure 2 As shown, the present invention aims at defects such as the traditional method is easily trapped in a local optimal solution and the convergence speed is slow, and in order to avoid the influence of the poor initial population distribution on the optimization process, a small hydropower station based on the multi-objective moth algorithm is provided. Optimal scheduling method, which adopts the external storage of the dynamic update mechanism and introduces the moth directional spiral search process to realize the ability of global optimization of the algorithm, and uses multi-objective decision-making theory to independently select the optimal scheduling scheme on the basis of non-dominated solution sets , to realize the multi-objective optimal dispatching of small hydropower stations, the specific steps include:

[0039] Step (1), establishing the power generation benefit model of the small hydropower station:

[0040] S=∑c i N ...

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

The invention relates to a multi-target moth algorithm-based small hydropower station optimal scheduling method. The method comprises the following steps of: firstly collecting target small hydropower station, and combining a storage capacity, a water yield, power generation scheduling, water supply and a boundary condition constraint to establish a mathematic model with targets of maximum power generation capacity and minimum ecological water deficit; and secondly taking the established model as a target function and substituting the target function into a multi-target moth algorithm to carry out optimal computation, and after carrying out the optimal computation through the algorithm, finally returning a set with optimal scheduling schemes so that decision makers can finally make a scheduling scheme through referencing the given optimal scheduling scheme set. The method provided by the invention emphasizes on improving the correctness and high efficiency of optimal scheduling of small hydropower stations and solving the problems existing on models and methods in the prior art, and has significance for pushing the development of the optimal scheduling of the small hydropower stations and improving the economic benefit.

Description

technical field [0001] The invention relates to the field of operation and optimal scheduling of small-scale water conservancy and hydropower projects, in particular to an optimal scheduling method for small-scale hydropower stations based on a multi-objective moth algorithm. Background technique [0002] With the continuous development of my country's economy, people's living standards are gradually improving, and the demand for electricity is also increasing, which also drives the rapid development of various power industries, such as hydropower, thermal power, nuclear power, photovoltaic industry, wind power and even tidal power. All have made great progress and achieved world-renowned achievements. By the end of 2010, the national hydropower installed capacity reached 210 million kW, ranking first in the world, and the annual power generation reached 563.3 billion kW·h, accounting for 21.6% and 16.4% of the national power installed capacity and annual power generation res...

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
IPC IPC(8): G06Q10/04G06Q10/06G06Q50/06
CPCG06Q10/04G06Q10/0631G06Q50/06Y02E40/70Y04S10/50
Inventor 王万良李伟琨任沁李笠陈超应森亮
Owner ZHEJIANG UNIV OF TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products