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Genetic algorithm-based power supply enterprise cost optimization method taking into account electricity benefits

A technology of cost optimization and genetic algorithm, which is applied in the field of cost optimization of power supply enterprises based on genetic algorithms and electricity efficiency, can solve problems such as difficulty in realizing the optimal distribution of operating costs of power supply enterprises and inability to adapt to the development of power supply enterprises, so as to ensure long-term overall management Efficient development, optimization of operating costs, and improvement of comprehensive benefits

Inactive Publication Date: 2016-06-01
SOUTH CHINA UNIV OF TECH
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Problems solved by technology

With limited annual available resources, if we continue to allocate resources according to the traditional benefit accounting mechanism, it will be difficult to achieve the optimal allocation of operating costs for power supply enterprises
[0003] The traditional optimization and allocation of operating costs can no longer adapt to the future development of power supply enterprises. It is of great significance to further break the traditional rigid resource allocation model and explore more reasonable and effective methods of operating cost optimization

Method used

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  • Genetic algorithm-based power supply enterprise cost optimization method taking into account electricity benefits
  • Genetic algorithm-based power supply enterprise cost optimization method taking into account electricity benefits
  • Genetic algorithm-based power supply enterprise cost optimization method taking into account electricity benefits

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Embodiment 1

[0035] This embodiment is based on the cost optimization method of the power supply enterprise based on the genetic algorithm and taking into account the power efficiency. The process is as follows figure 1 shown, including the following steps:

[0036] Step S1, obtain the industry types in the power supply area to be optimized, and obtain the historical data of electricity consumption and GDP output value corresponding to each industry type; specifically, assuming that there are n types of industries in the power supply area to be optimized, industry type Refers to the currently defined industry type; get the electricity consumption P of the industry type i in the past t years ik and GDP output value G ik ; Among them, i=(1,2,...,n); k is the number of past years, k=(1,2,...,t); figure 2 As shown, for each historical year, each industry type has a corresponding power consumption P ik and GDP output value G ik , so the electricity consumption and GDP output value of indus...

Embodiment 2

[0053] This embodiment takes a certain district of Guangzhou as an example of a power supply area to be optimized to illustrate the cost optimization method for power supply enterprises based on genetic algorithms and taking into account power efficiency; it includes the following steps:

[0054] Step S1, obtain the industry type of the power supply area to be optimized, and obtain the industry types of the power supply area to be optimized, including bulk industry, general industry and commerce; collect the historical data of electricity consumption corresponding to each industry type in the power supply area to be optimized from 2009 to 2012 and the historical data of GDP output value, as shown in Table 1;

[0055] Table 1 historical data

[0056]

[0057] Step S2, calculate the historical value of the unit electricity benefit of each industry type, the unit is 10,000 yuan / MWh, as shown in Table 2;

[0058] Table 2 Unit electricity benefit

[0059] year

[006...

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Abstract

The invention provides a genetic algorithm-based power supply enterprise cost optimization method taking into account electricity benefits. The method is characterized by comprising steps: industry types existing in a to-be-optimized power supply area, corresponding historical electricity consumption data and historical GDP output data are acquired; a unit electricity benefit historical value of each industry type is calculated respectively; a least square method is adopted for fitting to acquire the unit electricity predicted benefit of each industry type in a to-be-optimized year; a cost optimization model is built; a genetic algorithm is adopted to solve the cost optimization model to acquire the resource allocation ratio of each industry type by the power supply enterprise in the to-be-optimized year; and according to the resource allocation ratio of each industry type by the power supply enterprise in the to-be-optimized year, total annual input resources are allocated for each industry type. In a condition in which the total annual input resources of the power supply enterprise are determined, the resource allocation ratio solution is carried out when the unit electricity benefit is combined, scientific management on the operation cost is facilitated, the comprehensive benefits are greatly enhanced, and the resource allocation is optimized.

Description

technical field [0001] The present invention relates to the technical field of power supply enterprise operation cost optimization, and more specifically, relates to a cost optimization method for power supply enterprises based on genetic algorithm while taking electricity efficiency into consideration. Background technique [0002] In the context of power reform and energy conservation and emission reduction, power supply companies need to pay more attention to the economic benefits of marketization and realize the optimization of their own operating costs. At present, the method of calculating the benefits of power supply enterprises is mainly based on the classification of electricity prices related to the nature of users (such as bulk industry, non-industrial, general industry, commercial, residential, agricultural, etc.), combined with the electricity consumption of various industries for the supply and sale of electricity In terms of benefit accounting, this investment...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/06G06N3/12
CPCY02P80/10G06Q10/04G06N3/126G06Q50/06
Inventor 安晓华欧阳森郜幔幔
Owner SOUTH CHINA UNIV OF TECH
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