Completely distributed collaborative optimization method for multi-source energy storage type micro-grid

A collaborative optimization and distributed technology, applied in the fields of simulation, analysis and scheduling, and power system operation, can solve the problems of insufficiently exploiting the elastic adjustability of the demand-side load, not considering the profit risk, and increasing the scheduling cost, so as to achieve the priority of guarantee. Output and utilization, balance between benefits and risks, and the effect of improving the power load curve

Pending Publication Date: 2021-12-17
SOUTH CHINA UNIV OF TECH
View PDF0 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] However, from these research results, 1) the "elasticity" and "adjustability" of the demand side load are not fully explored, and the power load is simply divided into interrupted load and non-interruptible load
In fact, demand-side loads can be divided into important loads and flexible loads. Flexible loads are a type of "virtual energy storage" with elasticity and adjustability. The optimized operation of the microgrid will promote the friendly interaction between the load side and the source side, and improve the level of wind and wind consumption; 2) The above-mentioned distributed optimization method can be seen, ignoring the influence of uncertain factors on new energy output, and not considering The profit and risk problems brought about by scheduling decisions under certain conditions will lead to a certain degree of waste of resources and increase scheduling costs

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
  • Completely distributed collaborative optimization method for multi-source energy storage type micro-grid
  • Completely distributed collaborative optimization method for multi-source energy storage type micro-grid
  • Completely distributed collaborative optimization method for multi-source energy storage type micro-grid

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0062] The present invention will be further described in detail below in conjunction with the embodiments and the accompanying drawings, but the embodiments of the present invention are not limited thereto.

[0063] see figure 1 and figure 2 As shown, the fully distributed collaborative optimization method of the multi-source energy storage microgrid provided in this embodiment uses the YALMIP toolbox to establish a game optimization model in the MATLAB programming environment. The specific implementation steps are as follows:

[0064] 1) Obtaining data, including relevant parameters of microgrid equipment and collecting new energy and load data; wherein, relevant parameters of said microgrid equipment include the capacity of diesel units, minimum and maximum mechanical output, fuel consumption rate coefficient, energy storage equipment capacity, initial state of charge and charge and discharge efficiency, maintenance cost coefficients of new energy units, diesel units and ...

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 completely distributed collaborative optimization method for a multi-source energy storage type micro-grid. The method comprises the steps of 1) obtaining data, including related parameters of micro-grid equipment, and collecting new energy and load data; 2) in combination with the acquired data, establishing a game mapping model of micro-grid individuals, namely players; and 3) on the basis of micro-grid individual modeling, establishing an interactive game model among micro-grid individuals by adopting a potential game method to realize local and overall economic optimization of the micro-grid. According to the method, a completely distributed multi-subject decision optimization mode is adopted, and the conditional value-at-risk model and the generalized energy storage model are combined, so that local decision and management of micro-grid individuals are realized, income fluctuation caused by wind and light output uncertainty is effectively avoided, the consumption level of new energy is improved, and meanwhile, the individual benefits of the micro-grid can be ensured and the overall benefits of the micro-grid can be maximized by adopting a potential game mode.

Description

technical field [0001] The invention relates to the technical field of power system operation, simulation, analysis and scheduling, in particular to a fully distributed collaborative optimization method for a multi-source energy storage microgrid. Background technique [0002] The core feature of the new power system in the future is that new energy will occupy a dominant position and accelerate the replacement of fossil energy. Connecting new energy to the power grid in the form of distributed power generation is an important measure for large-scale grid integration of renewable energy, and a micro-grid with autonomy and autonomy is the best bridge between distributed power and the large power grid. [0003] The optimal operation of the microgrid is the core of the energy management system. The optimization operation of the microgrid is divided into centralized optimization and distributed optimization. From the perspective of centralized optimization, a mixed integer pro...

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 Applications(China)
IPC IPC(8): G06Q10/04G06Q10/06G06Q50/06H02J3/00
CPCG06Q10/04G06Q10/0637G06Q50/06H02J3/00H02J2203/20
Inventor 刘俊峰罗燕曾君符致敏
Owner SOUTH CHINA 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