CN-122022401-A - Energy balance optimization scheduling method and device for provincial domain

CN122022401ACN 122022401 ACN122022401 ACN 122022401ACN-122022401-A

Abstract

The invention discloses a power saving domain energy balance optimizing and scheduling method and a device, belonging to the field of energy scheduling; the method comprises the steps of calculating energy consumption of each city area and each county area based on a local city structure and a county structure of energy consumption of each industry, predicting supply quantity based on energy supply weight, energy production quantity and energy dispatching quantity of each county area, predicting supply quantity based on heat supply standard coal consumption and power supply standard coal consumption, constructing a double-layer energy dispatching model according to the energy consumption of each city area and each county area and the energy supply quantity, solving the double-layer energy dispatching model by adopting a solver in a layering mode, generating a power-saving-area energy dispatching instruction, and controlling a power-saving-area energy network of a target province according to the power-saving-area energy dispatching instruction to conduct energy dispatching. Therefore, by implementing the invention, the accuracy and the scheduling efficiency of energy supply and demand balance can be obviously improved.

Inventors

CHEN ZHIHAO
LI XUEFENG
WANG XIRAN
QIAN JUNJIE
XIE JIAYE
ZHOU XIAOMING
LV JIANREN
AN YUNZHAN
ZHANG YONG
SHEN YIDI

Assignees

国网浙江省电力有限公司经济技术研究院

Dates

Publication Date: 20260512
Application Date: 20260413

Claims (10)

1. The energy balance optimizing and scheduling method for the provincial domain is characterized by comprising the following steps of: Carrying out electricity consumption prediction based on electricity consumption characteristics of each industry in a preset time period, obtaining energy consumption of a province area based on electricity consumption prediction results and energy structure conversion of each industry, and decomposing the energy consumption of the province area into energy consumption of each city area and energy consumption of each county area based on a local city structure and a county structure of energy consumption of each industry; performing preliminary prediction on the energy supply quantity of each city and each county based on the energy supply weight, the energy production quantity and the energy modulation quantity of each county, predicting the heat supply quantity and the power supply quantity based on the heat supply standard coal consumption and the power supply standard coal consumption, and adding the heat supply quantity and the power supply quantity with the preliminary prediction results to obtain the energy supply quantity of each city and the energy supply quantity of each county; Constructing a double-layer energy scheduling model according to the energy consumption of each city domain, the energy consumption of each county domain, the energy supply of each city domain and the energy supply of each county domain, wherein the double-layer energy scheduling model aims at minimizing the total flowing energy amount, and the constraint conditions are supply constraint and channel capacity constraint; And adopting a solver to solve the double-layer energy scheduling model in a layering manner, generating a provincial energy scheduling instruction, and controlling a provincial energy network with target provincial resources to perform energy scheduling according to the provincial energy scheduling instruction.
2. The method for optimizing and scheduling energy balance in a province according to claim 1, wherein the predicting electricity consumption based on electricity consumption characteristics of each industry in a preset time period, converting energy structures of each industry into energy consumption in the province based on electricity consumption prediction results and energy structures of each industry, and decomposing the energy consumption in the province into energy consumption in each city and energy consumption in each county based on a local city structure and a county structure of energy consumption in each industry, comprises: Clustering industries of a target province into a plurality of industry groups based on electricity utilization characteristics of each industry in a preset time period, and predicting electricity consumption of each industry group by adopting a gray prediction model based on ARIMA residual error correction to obtain first province energy consumption; And carrying out energy conversion based on the first provincial energy consumption and the energy structures of the industries to obtain provincial energy consumption, and respectively calculating the energy consumption of each provincial region and the energy consumption of each county region based on the local city structure and the county structure of the energy consumption of each industry.
3. The power saving energy balance optimizing and scheduling method according to claim 2, wherein the clustering the industries of the target province into a plurality of industry groups based on the power consumption characteristics of the industries of the preset time period, and performing power consumption prediction on each industry group by using a gray prediction model based on ARIMA residual error correction, to obtain the first power saving energy consumption, comprises: Collecting the first industry electricity consumption of each industry of the target province in the preset time period; extracting characteristics of the electricity consumption of each first industry respectively to correspondingly obtain industry electricity consumption characteristics of each industry, wherein the industry electricity consumption characteristics comprise industry electricity consumption composite growth rate, industry annual fluctuation range, industry electricity consumption contribution duty ratio and industry electricity consumption proportion trend characteristics; Based on the electricity utilization characteristics of each industry, adopting a K-Means algorithm to perform clustering division to obtain a plurality of industry groups, wherein the number of the industry groups is determined according to the contour coefficients of each industry; respectively predicting the electricity consumption of each industry group by adopting a gray prediction model to correspondingly obtain a plurality of first industry group electricity consumption, respectively carrying out residual correction on each first industry group electricity consumption by adopting an ARIMA model to correspondingly obtain a plurality of industry group electricity consumption; And calculating the industry electricity consumption of each industry based on the electricity consumption data of each industry group and the ratio of each industry in the corresponding industry group, and adding all the industry electricity consumption to obtain the first provincial energy consumption of the target provincial.
4. The energy balance optimizing and scheduling method of claim 3, wherein said energy conversion based on said first energy consumption of the province and the energy structure of each industry to obtain the energy consumption of the province comprises: performing trend fitting on the energy structures of the industries in the preset time period by adopting an ARIMA model to obtain a plurality of first energy conversion ratios of the industries, wherein the first energy conversion ratios correspond to one of four energy sources of coal, petroleum, natural gas and heat energy; respectively correcting each first energy conversion ratio based on the electric energy substitution quantity in the preset time period, and correspondingly obtaining a plurality of energy conversion ratios of each industry; And carrying out energy conversion based on the first provincial energy consumption and the energy conversion proportion to obtain a plurality of second provincial energy consumption, and adding the first provincial energy consumption and the second provincial energy consumption to obtain the provincial energy consumption of the target provincial.
5. The provincial and regional energy balance optimization scheduling method of claim 4, wherein the calculating the energy consumption of each city and each county based on the local and county structures of energy consumption of each industry comprises: performing weighted movement smoothing on a first city structure of energy consumption of each industry in the preset time period to obtain a city structure of energy consumption of each industry; decomposing the provincial energy consumption to each local city based on each local city structure to obtain each city energy consumption of the target provincial; Correcting a first county structure of energy consumption of each industry in the preset time period based on industry electricity consumption increasing trend to obtain a county structure of energy consumption of each industry; And correspondingly decomposing the energy consumption of each city domain into each county based on each county structure to obtain the energy consumption of each county domain of the target province.
6. The energy balance optimizing and scheduling method of claim 1, wherein the preliminary prediction of the energy supply amount of each city and the energy supply amount of each county based on the energy supply weight, the energy production amount and the energy input amount of each county, and the prediction of the heat supply amount and the energy supply amount based on the heat supply standard coal consumption and the power supply standard coal consumption and the addition of the preliminary prediction result to obtain the energy supply amount of each city and the energy supply amount of each county comprise: Carrying out layered weighting on the energy supply capacity index data to obtain a plurality of energy supply weights of each county, and carrying out supply quantity prediction based on the energy supply weights, the energy production quantities and the energy modulation quantities to obtain energy supply quantities of each first city and each first county; And respectively carrying out heat supply prediction and power supply prediction on each heat supply standard coal consumption and each power supply standard coal consumption based on unit aging rate correction, and correspondingly adding the prediction result with each first city energy supply amount and each first county energy supply amount to obtain each city energy supply amount and each county energy supply amount.
7. The power saving energy balance optimizing and scheduling method of claim 6, wherein the step of hierarchically weighting the energy supply capability index data to obtain a plurality of energy supply weights for each county, and performing supply prediction based on each of the energy supply weights, each of the energy production amounts, and each of the energy intake amounts to obtain each of the first city energy supply amounts and each of the first county energy supply amounts, comprises: Collecting energy supply capacity index data, first province energy modulation amount, first city energy production amount and first county energy production amount of each county of the target province in the preset time period, so as to respectively determine a plurality of energy supply weights of each county, the province energy modulation amount, the city energy production amount and predicted values of each county energy production amount; Decomposing the provincial energy supply amount into each local city and each county according to each energy supply weight, and adding the provincial energy supply amount and the county energy supply amount with the corresponding energy production amount of each city to obtain each second city energy supply amount and each second county energy supply amount; and correspondingly decomposing the energy supply quantity of each second city domain and the energy supply quantity of each second county domain into the energy processing conversion quantity of each city domain and the energy supply quantity of each first city domain, and the energy processing conversion quantity of each county domain and the energy supply quantity of each first county domain according to the plurality of first energy processing conversion ratios of the preset time period.
8. The power saving area energy balance optimizing and scheduling method according to claim 7, wherein the performing the heat supply prediction and the power supply prediction on each heat supply standard coal consumption and each power supply standard coal consumption based on the unit aging rate correction, and adding the prediction result to each of the first city area energy supply and each of the first county area energy supply to obtain each of the city area energy supply and each of the county area energy supply, respectively, includes: collecting the standard coal quantity, the heat supply quantity and the power supply quantity of each unit of the target province in the preset time period to calculate the first heat supply standard coal consumption and the first power supply standard coal consumption of each unit, and correcting the first heat supply standard coal consumption and the first power supply standard coal consumption according to the aging rate of each unit to obtain the heat supply standard coal consumption and the power supply standard coal consumption of each unit; Calculating by utilizing the heat supply standard coal consumption and the power supply standard coal consumption according to the energy processing conversion amounts of the municipal areas and the county areas to obtain energy supply amounts of the second municipal areas and the second county areas, and energy supply amounts of the third municipal areas and the third county areas; And correspondingly adding the energy supply quantity of each first city domain, the energy supply quantity of each second city domain and the energy supply quantity of each third city domain to obtain the energy supply quantity of each city domain, and correspondingly adding the energy supply quantity of each first county domain, the energy supply quantity of each second county domain and the energy supply quantity of each third county domain to obtain the energy supply quantity of each county domain.
9. The provincial energy balance optimizing dispatching method of claim 1, wherein the constructing a dual-layer energy dispatching model according to the city energy consumption and the county energy consumption and the city energy supply and the county energy supply comprises: Comparing the energy consumption of each county with the energy supply of each corresponding county to determine a first energy balance condition of the corresponding county, and comparing the energy consumption of each city with the energy supply of each corresponding city to determine a second energy balance condition of the corresponding city; Constructing a first energy scheduling model according to the first energy balance condition, constructing a second energy scheduling model according to the second energy balance condition, taking the first energy scheduling model as a first layer, taking the second energy scheduling model as a second layer, and constructing a double-layer energy scheduling model.
10. The energy balance optimizing and scheduling device for the province domain is characterized by comprising an energy consumption prediction module, an energy supply prediction module, a scheduling model construction module and an energy scheduling module; The energy consumption prediction module is used for predicting the electricity consumption based on the electricity consumption characteristics of each industry in a preset time period, obtaining the energy consumption of a province area based on the electricity consumption prediction result and the energy structure conversion of each industry, and decomposing the energy consumption of the province area into the energy consumption of each city area and the energy consumption of each county area based on the local city structure and the county structure of the energy consumption of each industry; The energy supply prediction module is used for performing preliminary prediction on the energy supply quantity of each city and the energy supply quantity of each county based on the energy supply weight, the energy production quantity and the energy adjustment quantity of each county, predicting the heat supply quantity and the power supply quantity based on the heat supply standard coal consumption and the power supply standard coal consumption, and adding the heat supply quantity and the power supply quantity with the preliminary prediction result to obtain the energy supply quantity of each city and the energy supply quantity of each county; The scheduling model construction module is used for constructing a double-layer energy scheduling model according to the energy consumption of each city domain, the energy consumption of each county domain, the energy supply of each city domain and the energy supply of each county domain, wherein the double-layer energy scheduling model aims at minimizing the total flowing energy amount, and constraint conditions are supply constraint and channel capacity constraint; the energy scheduling module is used for solving the double-layer energy scheduling model in a layering manner by adopting a solver, generating a provincial energy scheduling instruction, and controlling a provincial energy network of a target provincial according to the provincial energy scheduling instruction to perform energy scheduling.

Description

Energy balance optimization scheduling method and device for provincial domain Technical Field The invention relates to the field of energy scheduling, in particular to a power saving domain energy balance optimization scheduling method and device. Background The construction of the energy balance model is one of the main modes for realizing the rapid decomposition simulation and balance calculation of the regional energy system structure and the evolution path. However, the existing energy balance model has the following problems: first, the lack of adaptability to provincial applications, such as international mainstream models (e.g., MARKAL or LEAP, etc.), is mostly based on large-scale designs, with granularity up to industry or local market, and no support for county-level data input and result output. Secondly, the default accounting of the classified energy sources is unclear, the existing energy balance model is used for researching the total energy consumption and supply comprehensively, and the description of the supply and demand of the classified energy sources is ignored. Third, the energy transport flow direction is ambiguous, and there is a lack of efficient modeling of the energy flow path between counties and municipalities and optimizing the distribution mechanism. Disclosure of Invention The invention provides a province-area energy balance optimization scheduling method and device, which can realize the fine energy scheduling from province-area to county and remarkably improve the accuracy and scheduling efficiency of energy supply and demand balance. The embodiment of the invention provides a power saving domain energy balance optimizing and scheduling method, which comprises the following steps: Carrying out electricity consumption prediction based on electricity consumption characteristics of each industry in a preset time period, obtaining energy consumption of a province area based on electricity consumption prediction results and energy structure conversion of each industry, and decomposing the energy consumption of the province area into energy consumption of each city area and energy consumption of each county area based on a local city structure and a county structure of energy consumption of each industry; performing preliminary prediction on the energy supply quantity of each city and each county based on the energy supply weight, the energy production quantity and the energy modulation quantity of each county, predicting the heat supply quantity and the power supply quantity based on the heat supply standard coal consumption and the power supply standard coal consumption, and adding the heat supply quantity and the power supply quantity with the preliminary prediction results to obtain the energy supply quantity of each city and the energy supply quantity of each county; Constructing a double-layer energy scheduling model according to the energy consumption of each city domain, the energy consumption of each county domain, the energy supply of each city domain and the energy supply of each county domain, wherein the double-layer energy scheduling model aims at minimizing the total flowing energy amount, and the constraint conditions are supply constraint and channel capacity constraint; And adopting a solver to solve the double-layer energy scheduling model in a layering manner, generating a provincial energy scheduling instruction, and controlling a provincial energy network with target provincial resources to perform energy scheduling according to the provincial energy scheduling instruction. The method and the system can effectively improve the accuracy of electricity consumption prediction of each industry through carrying out industry clustering based on electricity utilization characteristics and adopting a combined prediction model of grey prediction and ARIMA residual correction, provide a reliable data basis for subsequent energy balance calculation, accurately predict the consumption structure of multiple energy varieties through adopting an energy conversion method combining trend fitting and electric energy replacement correction, enhance the comprehensiveness and foresight of energy demand prediction, realize reasonable space distribution of energy consumption through a district-city county structure decomposition method of weighted movement smoothing and increasing trend correction, improve the refinement level of regional energy management, scientifically predict the energy supply of each district county through layered weighted energy supply capacity evaluation and processing conversion proportion analysis, provide accurate supply side data support for energy scheduling, accurately reflect equipment efficiency attenuation through introducing heat supply standard coal consumption prediction of unit aging rate correction, improve the reliability of energy supply capacity prediction, realize layered dispatching and optimize energy transmission cost by constructin