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A Fractal Steepest Descent Method for Power Grid Economic Dispatch Considering Valve Point Effect

A technology of economic scheduling and valve point effect, applied in the direction of electrical digital data processing, special data processing applications, instruments, etc., can solve problems such as large amount of calculation and low solution efficiency

Active Publication Date: 2017-01-11
SOUTH CHINA UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0003] The purpose of the present invention is to overcome the shortcomings and deficiencies of the prior art, and provide a fractal steepest descent solution method considering the valve point effect power grid economic dispatching problem, to solve the problem of low solution efficiency and huge amount of calculation

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  • A Fractal Steepest Descent Method for Power Grid Economic Dispatch Considering Valve Point Effect
  • A Fractal Steepest Descent Method for Power Grid Economic Dispatch Considering Valve Point Effect
  • A Fractal Steepest Descent Method for Power Grid Economic Dispatch Considering Valve Point Effect

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Embodiment 1

[0044] The present invention considers the fractal dimension steepest descent solution method of the grid economic dispatching problem considering the valve point effect, such as figure 1 shown, proceed as follows:

[0045] Step (1), obtain the output upper and lower limit data of each unit in the power system with N generator sets Coefficient data a of output-fuel cost function g ,b g ,c g ,e g , f g and system load data P d .

[0046] Step (2), establishing a mathematical optimization model of the power grid economic dispatching problem considering the unit valve point effect.

[0047] In the traditional economic dispatching problem, the unit output-fuel cost curve is approximated as a smooth quadratic polynomial. It should be noted that the output-fuel cost curve of the unit is obtained by multiplying the inherent output-fuel consumption curve of the unit by the fuel cost coefficient. However, the wire-drawing effect when the intake valve of the turbine is suddenl...

Embodiment 2

[0086] In order to make step (3) in the specific implementation of the present invention clearer, taking a 3-unit system with a total load of 850MW as an example, Table 1 gives the solution obtained in the whole process of solving step (3). From Table 1, it can be seen that the fuel cost unit decrease value D of unit 3 in the first iteration g is the largest, so its singular point position changes from 4 minus 1 to 3 in the second iteration, and the fuel cost unit of unit 1 decreases by D in the second iteration g is the largest, so its singular point position changes from 6 minus 1 to 5 in the third iteration, and so on. After 8 iterations, the total output of N units is closest to and greater than the system load. After 16 iterations All units are at the lower limit of output. It can be seen from Table 1 that the calculation of step (3) is very simple and intuitive. In the 13-machine system with a system load of 1800MW, step (3) stops after 47 iterations. In the 40-machine...

Embodiment 3

[0092] Taking a standard test system of 3 units, 13 units and 40 units as examples respectively, the problems are solved respectively by adopting the steepest descent method of the present invention. Among them, the total load of the 3-unit system is 850MW, the total load of the 13-unit system is 1800MW, and the total load of the 40-unit system is 10500MW. In step (4), the optimization method is implemented using the YALMIP toolbox in MATLAB. Since the goal of the 0-1 variable quadratic optimization problem shown in formula (7) is mainly to minimize the load imbalance, its solution is relatively simple. Therefore, the following settings are used in the solution of the optimization problem shown in step (4) and formula (7) of the three standard test systems: YALMIP adopts the branch and bound method solver, and the maximum number of iterations of the branch and bound solution method is set to 20. The continuous variable optimization subproblem in the branch and bound method ado...

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Abstract

The invention discloses a fractal dimension steepest descent calculation method for a valve point effect power grid economic dispatch problem. According to the method, characteristics of units disposed at singular points mostly are calculated by fully using the local minimum of the problem. The method is composed of three stages: 1) selecting a unit with the largest fuel cost unit decrease value every time, and making the singular point position of the unit minus 1 till each unit is below the power output lower limit; 2) selecting one solution of the power output sum of N units, which is closest to and larger than or equal to the system load, from all solutions produced in 1), as the initial solution, and optimizing the initial solution to enable the load unbalance amount to be minimum; 3) selecting a load balance unit from each solution of two solutions before and after the optimization of the initial solution, and adjusting the power output to enable the load to be balanced. The total fuel cost minimal solution obtained in the step 3) serves as the final solution. The method is simple and easy to implement, quite small in calculation amount, high in convergence precision and capable of greatly improving generation economy and efficiency of power systems.

Description

technical field [0001] The invention relates to the technical field of operation, analysis and dispatching of electric power systems, in particular to a method for solving the economical dispatching problem of a power grid considering the valve point effect of units. Background technique [0002] Considering the valve point effect, the economic dispatching problem of power grid is a non-convex, non-differentiable optimization problem with multiple local minimum solutions. The traditional gradient method and Newton method cannot solve the problem. In order to solve the problem better, scholars proposed an evolutionary programming algorithm (Q.H.Wu, and J.T.Ma. Power system optimal reactive power dispatching using evolutionary programming[J]. IEEE Transactions on Power Systems, 1995, 10(3): 1243-1249. Wu Qinghua, J.T.Ma. Optimal Reactive Power Economic Dispatch of Power System Using Evolutionary Programming [J]. IEEE Transactions on Power Systems, 1995 , 10(3):1243-1249.), ge...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F19/00
Inventor 吴青华詹俊鹏
Owner SOUTH CHINA UNIV OF TECH