A regional energy system optimization method based on type II fuzzy chance constraint

An energy system, type-two fuzzy technology, applied in the direction of instruments, data processing applications, forecasting, etc., can solve the constraints of regional energy system optimization research, the lack of methods to characterize the complexity and multiple uncertainties of regional energy systems, and the inability to time and Spatially fully consider the uncertainties of regional energy systems and other issues

Active Publication Date: 2018-12-14
BEIJING NORMAL UNIVERSITY
View PDF4 Cites 3 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

For example, there is a lack of research and development of methods to characterize the complexity and multiple uncertainties of regional energy systems, and the uncertainty factors of regional energy systems cannot be effe

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 regional energy system optimization method based on type II fuzzy chance constraint
  • A regional energy system optimization method based on type II fuzzy chance constraint
  • A regional energy system optimization method based on type II fuzzy chance constraint

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0096] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments. In order to illustrate the technical scheme of the specific embodiment of the present invention, at first briefly explain the basic principle of the present invention as follows:

[0097] Consider the type 2 fuzzy parameters:

[0098] The first step is to fuzzify the parameters into traditional fuzzy parameters. Suppose h 1 , h 2 , h 3 , ..., are the fuzzy parameters c ij The value of , and there exists at least one pair of i≠j such that h i ≠ h j . fuzzy parameter c ij The fuzzification process of is as follows:

[0099] 1) Calculate the relative distance matrix D=|d ij | t×t , where d ij =|h i -h j |;

[0100] 2) Calculate the average value of the relative distance

[0101] 3) Introduce pairwise comparison number p ij , Pair matrix P=[p ij ] t×t ;

[0102] 4) Calculate h j real weight w j ,

[0103] 5) Calculate the...

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 discloses a regional energy system optimization method based on type II fuzzy chance constraint, belonging to the field of energy system optimization dispatching. The method comprises the steps of: A, building an optimization model with the minimum regional energy system cost as the objective and with various kinds of constrains as constraint conditions; B, constructing type II fuzzyparameters according to the method for determining weights and the parameter possibility distribution, constructing random parameter according to the parameter probability distribution, and converting the type II fuzzy parameters and the random parameters into deterministic parameters through a type II fuzzy reduction method based on critical values and an opportunity constraint method, and solving the model; C, choosing different default probabilities of the energy system and substituting the probabilities into the model for solving, and obtaining the relationship between system default probability and system cost, energy purchase, energy supply and pollutant emission. The invention can optimize the regional energy system under the condition of multiple uncertainties, and provides an optimal energy purchase, energy supply and pollutant emission scheme.

Description

technical field [0001] The invention belongs to the field of optimal scheduling of energy systems, and in particular relates to a method for optimizing regional energy systems based on Type II fuzzy chance constraints. Background technique [0002] Energy is the material basis for the survival and development of human beings. Every progress of human civilization is accompanied by the improvement and replacement of energy. The rational development and utilization of energy is of great significance to the development of the world economy and human society. However, with economic development, population increase, and accelerated industrialization, global energy consumption and demand are showing a sharp upward trend, and fossil fuels dominate. At present, my country has become the world's largest energy consumer and coal consumer. Its oil consumption is second only to the United States, and it is the second largest oil consumer in the world. Zhong Ziran, chief engineer of the ...

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): G06Q10/04G06Q50/02
CPCG06Q10/04G06Q50/02
Inventor 李永平索彩李延峰孙杰
Owner BEIJING NORMAL UNIVERSITY
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

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap