Source network load storage multi-element ubiquitous optimization scheduling method for clean energy consumption

A technology of clean energy and optimal scheduling, applied in design optimization/simulation, resources, electrical components, etc., can solve problems such as huge number of constraints, non-convergence, and long time-consuming, so as to improve the ability to resist risks, low energy consumption, The effect of reducing carbon emissions

Pending Publication Date: 2022-04-29
STATE GRID ZHEJIANG ELECTRIC POWER CO LTD HANGZHOU POWER SUPPLY CO
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The thermal power and new energy unit game and the day-ahead optimal dispatching model considering carbon emission reduction constraints are a mixed integer quadratic programming problem with complex calculations, a large number of constraints, and strong nonlinearity. It is not only difficult to solve d

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
  • Source network load storage multi-element ubiquitous optimization scheduling method for clean energy consumption
  • Source network load storage multi-element ubiquitous optimization scheduling method for clean energy consumption
  • Source network load storage multi-element ubiquitous optimization scheduling method for clean energy consumption

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0082] Example: such as figure 1 As shown in Fig. 1, the multiple ubiquitous optimal scheduling method of source, network, load and storage for clean energy consumption includes the following steps:

[0083] S1. Taking the lowest power consumption and carbon emissions as the optimization goals, determine the objective function of the day-ahead low-carbon power generation dispatching model;

[0084] The objective function of the day-ahead low-carbon generation scheduling model is as follows:

[0085]

[0086] In the formula, F 1 is the total power consumption of the system; F 2 is the total carbon emission of system power generation; T is the number of time periods; N is the total number of thermal power units in the system; U i,t is the variable of the operating state of unit i in period t, when U i,t = 1 when the unit is running, U i,t =Stop when 0; S i is the start-up energy consumption of unit i; SC i is the CO when unit i starts up 2 Emissions; f i (P i,t ) is...

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 source network load storage multivariate ubiquitous optimization scheduling method for clean energy consumption. The method comprises the following steps: S1, determining a target function of a day-ahead low-carbon power generation scheduling model; s2, setting constraint conditions of the day-ahead low-carbon power generation dispatching model; s3, converting the low-carbon power generation dispatching optimization model into a single-target optimization model; s4, establishing a quantitative model of the carbon emission external cost; s5, establishing a risk assessment model, determining the operation risk indexes of the power system, calculating the weight omega E of each index by using an entropy method, calculating the weight omega A by combining an analytic hierarchy process, obtaining the final weight omega, and solving the safety comprehensive risk value of the power system in each time period; and S6, calculating a weight coefficient in the objective function based on a linear weighting method of a zero-sum game, and substituting the weight coefficient back into the original dual-objective optimization model to obtain an optimal power generation plan. According to the scheme, the carbon emission can be greatly reduced, and the method has guiding significance for establishing a lower-energy-consumption strong smart power grid.

Description

technical field [0001] The invention belongs to the field of optimal dispatching of electric power systems, and relates to a multiple ubiquitous optimal dispatching method of source, network, load and storage for clean energy consumption. Background technique [0002] Facing the increasingly severe pressure of abnormal climate change, human beings need to slow down the occurrence of extreme weather phenomena by controlling greenhouse gas emissions. Facing the prospect of future fossil energy depletion, it is necessary to vigorously develop renewable energy and increase Utilization efficiency, reducing human consumption and dependence on fossil energy, these two factors require the existing scheduling model to fully consider the issue of carbon emissions. At the same time, power generation scheduling must meet the basic requirements for safe operation of the power system, and at the same time reduce economic costs as much as possible to achieve low-carbon, safe, and economica...

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): G06Q10/06G06F30/20H02J3/00H02J3/28H02J3/46G06F111/04G06F113/04
CPCG06Q10/0635G06Q10/0631G06F30/20H02J3/466H02J3/28H02J3/008G06Q10/06315H02J2203/10H02J2203/20H02J2300/24H02J2300/28G06F2111/04G06F2113/04Y02E40/70Y04S10/50
Inventor 黄天恩吴振杰莫雅俊唐剑周志全王源涛李祥徐双蝶许鹏周依希王艳李城达应燕陈煜张超廖培夏衍董航孙思聪张洁陈嘉宁苏熀兴杨兴超李跃华祝文澜向新宇
Owner STATE GRID ZHEJIANG ELECTRIC POWER CO LTD HANGZHOU POWER SUPPLY CO
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