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Dynamic economic dispatch distributed optimization method and system for smart power grid

A smart grid and economic dispatching technology, applied in power network operating system integration, system integration technology, AC network voltage adjustment, etc., can solve problems such as poor robustness of centralized optimization strategy, large computational burden, and no consideration of dynamic constraints, etc. Achieving the effect of solving poor robustness

Active Publication Date: 2021-04-09
SHANDONG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In order to overcome the deficiencies of the above-mentioned existing technologies, the present disclosure provides a distributed optimization method for dynamic economic dispatching of smart grids, which solves the shortcomings of centralized optimization strategies such as poor robustness and large computational burden, and makes up for the fact that static optimization methods do not consider dynamic constraints. insufficient

Method used

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  • Dynamic economic dispatch distributed optimization method and system for smart power grid
  • Dynamic economic dispatch distributed optimization method and system for smart power grid
  • Dynamic economic dispatch distributed optimization method and system for smart power grid

Examples

Experimental program
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Embodiment 1

[0033] This embodiment discloses a distributed optimization method for dynamic economic scheduling of smart grids, including:

[0034] figure 1 is the system structure diagram, the solid line represents the energy transmission line, and the dotted line represents the communication topology of the system. figure 2 It is a flowchart of the optimization method, and the specific steps are as follows:

[0035] Step 1: Set the initial parameters: the number of traditional generator nodes, the number of wind turbine nodes, and the number of battery energy storage system nodes are n respectively g , n w , n s , and the correlation coefficients of each unit are shown in Table 1-Table 3. The total scheduling time τ=12, the penalty factor ρ=0.8.

[0036] Initialization time t=0, scheduling time τ∈R, original residual r, dual residual d, alternating direction multiplier method optimization iteration number k=0 and maximum iteration number k max ∈R, X update iteration number κ and m...

Embodiment 2

[0121] The purpose of this embodiment is to provide a computing device, including a memory, a processor, and a computer program stored in the memory and operable on the processor. When the processor executes the program, the method in the first embodiment above is implemented. A step of.

Embodiment 3

[0123] The purpose of this embodiment is to provide a computer-readable storage medium.

[0124] A computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the steps of implementing the method in Example 1 are executed.

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Abstract

The invention provides a dynamic economic dispatch distributed optimization method and system for a smart power grid, and the method comprises the steps: measuring the frequency of each node, and calculating the Lagrange multiplier deviation; updating the Lagrange multiplier at the current moment based on the consistency algorithm and the Lagrange multiplier deviation corresponding to the generating capacity at the previous moment; and updating the generating capacity and the charging and discharging power in the X update and performing judging, and if the conditions are met, performing Y updating on all nodes. On the basis of a neural network controller, the variable quantity of a Lagrange multiplier is calculated through frequency deviation, so that power balance in a power grid is realized, and a novel thought is provided for realizing power balance constraint in an economic dispatching problem.

Description

technical field [0001] The disclosure belongs to the technical field of smart grid energy scheduling, and in particular relates to a distributed optimization method and system for dynamic economic scheduling of smart grids. Background technique [0002] The statements in this section merely provide background information related to the present disclosure and do not necessarily constitute prior art. [0003] With the development of society and the progress of science and technology, the power generation and operation mode of the traditional power grid can no longer meet people's various needs for electricity and the requirements for energy conservation, emission reduction, and environmental protection. Therefore, the research on the smart grid combined with renewable energy has become a major trend in the development of the grid. Wind energy is one of the renewable energy sources with relatively mature technology for power generation and great development value. However, du...

Claims

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Application Information

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IPC IPC(8): H02J3/00H02J3/38H02J3/32H02J3/46H02J3/14G06Q50/06G06Q10/06G06F17/10
CPCH02J3/008H02J3/381H02J3/388H02J3/32H02J3/466H02J3/144G06Q10/06315G06Q50/06G06F17/10H02J2203/20H02J2300/28H02J2300/40Y04S20/222Y02B70/3225
Inventor 刘帅王祎帆宇文成杨伟明
Owner SHANDONG UNIV
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