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An optimization method for combined wind, water and fire scheduling considering the elastic space of power generation operation

An elastic space, power generation operation technology, applied in wind power generation, electrical components, circuit devices, etc., can solve problems such as high efficiency of commercial solvers, short-term stability characteristics of limited operating areas, and rough modeling.

Active Publication Date: 2020-11-24
CHONGQING UNIV
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  • Application Information

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Problems solved by technology

Among them, in terms of deep peak regulation of thermal power, there are currently literatures that have qualitatively and quantitatively discussed the economic cost of deep peak regulation of thermal power units and fuel combustion, and analyzed the value of unit peak regulation to the economic operation of the system. Most of the literature considers the operation optimization model of deep peak regulation of units to be established as a non-convex mixed integer nonlinear programming problem, which cannot be solved efficiently and robustly by commercial solvers; in terms of hydropower restricted operation areas, the existing methods are relatively rough in modeling , did not consider the short-term stability characteristics of the restricted operation area; moreover, the existing methods did not fully consider the elastic space of power generation operation, such as the deep peak shaving of thermal power and the short-term stability characteristics of the hydropower restricted operation area, to analyze its economic benefits and impact on new energy consumption. Nano's influence

Method used

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  • An optimization method for combined wind, water and fire scheduling considering the elastic space of power generation operation
  • An optimization method for combined wind, water and fire scheduling considering the elastic space of power generation operation
  • An optimization method for combined wind, water and fire scheduling considering the elastic space of power generation operation

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Embodiment 1

[0098] see Figure 1 to Figure 6 , considering the flexible space of power generation operation, the wind-water-fire joint scheduling optimization method mainly includes the following steps:

[0099] 1) Obtain the basic data of the power network, and establish an operational elasticity model for thermal power deep peak regulation.

[0100] The main steps to establish the operating elasticity model for thermal power deep peak regulation are as follows:

[0101] 1.1) The cost function C of deep peak regulation of thermal power units h (P h )As follows:

[0102]

[0103] In the formula, w n Indicates the cost function of the normal operation of the thermal power unit; w d1 Indicates the operating cost function of the thermal power unit under the condition of no oil input when the thermal power unit equipment is aging and the coal consumption increases; w d2Indicates the operating cost function of the thermal power unit under the state of fuel input when the thermal power...

Embodiment 2

[0183] The main steps of a verification method for wind-water-fire joint scheduling optimization considering the flexible space of power generation operation are as follows:

[0184] 1) Establish IEEE30 node standard test system.

[0185] 2) Compare with the model

[0186] In order to verify the effectiveness of the wind-water-fire joint scheduling optimization method that considers the flexible operation space of power generation proposed by the present invention, evaluate the economic benefits of scheduling after considering the flexible operation space of power generation and the situation of wind power consumption, the following four models are used for comparison:

[0187] M1: Conventional wind, water and fire joint dispatching scheme, without considering the deep peak shaving of thermal power and the operating flexibility of hydropower restricted operation areas;

[0188] M2: A wind-water-fire joint scheduling scheme that only considers the flexibility of deep peak-shav...

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Abstract

The invention discloses an optimization method for wind, water and thermal joint scheduling considering the elastic space of power generation operation. The main steps are: 1) establishing an operating elastic space model for deep peak regulation of thermal power; 2) establishing an operating elastic space model for a limited operating area of ​​a hydroelectric unit; 3) Establish an optimization model of combined wind, water, and thermal scheduling considering the flexible space of power generation operation; 4) Based on the optimized model of combined scheduling of wind, water, and thermal power considering the elastic space of power generation operation, complete the combined scheduling of wind, water, and thermal power in the power network. The invention expands the feasible range of unit output, expands the safe operation range of the power grid, and improves the ability of the power grid to accept hydropower and wind power.

Description

technical field [0001] The invention relates to the field of economic dispatching of electric power systems, in particular to an optimization method for joint dispatching of wind, water and fire considering the elastic space of power generation operation. Background technique [0002] With the rapid development of my country's economy, the power load continues to increase; at the same time, the national energy is transforming to clean and low-carbon, and the installed capacity of new energy units such as wind and light is also increasing year by year. The increase of uncertainty in power load and grid injection has brought new challenges to the safe and economical operation of the grid. At present, the establishment of a power grid optimization model that considers uncertainty, investment in energy storage equipment, and the use of multi-energy complementarity and demand-side response to improve the security and economy of the power grid can alleviate the increase in grid lo...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H02J3/46
CPCH02J3/46H02J2203/20Y02E10/76
Inventor 代伟余娟杨知方刘林虎谢开贵
Owner CHONGQING UNIV
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